Project

AMYPAD

Goal: AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) is a collaborative research initiative (IMI) aiming to improve the understanding, diagnosis and management of Alzheimer’s disease through the utilization of amyloid PET imaging.
For further details visit: https://amypad.eu/

Date: 5 October 2016

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Cindy Birck
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Emma S. Luckett, Yasmina Abakkouy, Mariska Reinartz, Katarzyna Adamczuk, Jolien Schaeverbeke, Sare Verstockt, Steffi De Meyer, Koen Van Laere, Patrick Dupont, Isabelle Cleynen & Rik Vandenberghe
Abstract:
Background: Early detection of individuals at risk for Alzheimer’s disease (AD) is highly important. Amyloid accumulation is an early pathological AD event, but the genetic association with known AD risk variants beyond the APOE4 effect is largely unknown. We investigated the association between different AD polygenic risk scores (PRS) and amyloid accumulation in the Flemish Prevent AD Cohort KU Leuven (F-PACK).
Methods: We calculated PRS with and without the APOE region in 90 cognitively healthy F-PACK participants (baseline age 67.8 (52–80) years, 41 APOE4 carriers), with baseline and follow-up amyloid-PET (time interval 6.1 (3.4–10.9) years). Individuals were genotyped using Illumina GSA and imputed. PRS were calculated using three p-value thresholds (pT) for variant inclusion: 5 × 10−8, 1 × 10−5, and 0.1, based on the stage 1 summary statistics from Kunkle et al. (Nat Genet 51:414–30, 2019). Linear regression models determined if these PRS predicted amyloid accumulation.
Results: A score based on PRS excluding the APOE region at pT = 5 × 10−8 plus the weighted sum of the two major APOE variants (rs429358 and rs7412) was significantly associated with amyloid accumulation (p = 0.0126). The two major APOE variants were also significantly associated with amyloid accumulation (p = 0.0496). The other PRS were not significant.
Conclusions: Specific PRS are associated with amyloid accumulation in the asymptomatic phase of AD.
Published: 23 September 2022
Alzheimer's Research & Therapy
 
Fiona Heeman
added a research item
Background Despite its widespread use, the semi-quantitative standardized uptake value ratio (SUVR) may be biased compared with the distribution volume ratio (DVR). This bias may be partially explained by changes in cerebral blood flow (CBF) and is likely to be also dependent on the extent of the underlying amyloid-β (Aβ) burden. This study aimed to compare SUVR with DVR and to evaluate the effects of underlying Aβ burden and CBF on bias in SUVR in mainly cognitively unimpaired participants. Participants were scanned according to a dual-time window protocol, with either [ ¹⁸ F]flutemetamol ( N = 90) or [ ¹⁸ F]florbetaben ( N = 31). The validated basisfunction-based implementation of the two-step simplified reference tissue model was used to derive DVR and R 1 parametric images, and SUVR was calculated from 90 to 110 min post-injection, all with the cerebellar grey matter as reference tissue. First, linear regression and Bland–Altman analyses were used to compare (regional) SUVR with DVR. Then, generalized linear models were applied to evaluate whether (bias in) SUVR relative to DVR could be explained by R 1 for the global cortical average (GCA), precuneus, posterior cingulate, and orbitofrontal region. Results Despite high correlations (GCA: R ² ≥ 0.85), large overestimation and proportional bias of SUVR relative to DVR was observed. Negative associations were observed between both SUVR or SUVR bias and R 1, albeit non-significant. Conclusion The present findings demonstrate that bias in SUVR relative to DVR is strongly related to underlying Aβ burden. Furthermore, in a cohort consisting mainly of cognitively unimpaired individuals, the effect of relative CBF on bias in SUVR appears limited. EudraCT Number: 2018-002277-22, registered on: 25-06-2018.
Cindy Birck
added an update
Luigi Lorenzini, Loes T Ansems, Isadora Lopes Alves, Silvia Ingala, David Vállez García, Jori Tomassen, Carole Sudre, Gemma Salvadó, Mhnaz Shekari, Gregory Operto, Anna Brugulat-Serrat, Gonzalo Sánchez-Benavides, Mara ten Kate, Betty Tijms, Alle Meije Wink, Henk J M M Mutsaerts, Anouk den Braber, Pieter Jelle Visser, Bart N M van Berckel, Juan Domingo Gispert, Frederik Barkhof, Lyduine E Collij, the AMYPAD consortium, the EPAD consortium, ALFA cohort
Abstract:
White matter hyperintensities (WMH) have a heterogeneous etiology, associated with both vascular risk factors and amyloidosis due to Alzheimer’s disease (AD). While spatial distribution of both amyloid and WM lesions carry important information for the underlying pathogenic mechanisms, the regional relationship between these two pathologies and their joint contribution to early cognitive deterioration remains largely unexplored.
We included 662 non-demented participants from three AMYPAD-affiliated cohorts: EPAD-LCS (N = 176), ALFA+ (N = 310), and EMIF-AD Twin60++ (N = 176). Using PET imaging, cortical amyloid burden was assessed regionally within early-accumulating regions (medial-orbitofrontal, precuneus, and cuneus) and globally, using the Centiloid method. Regional WMH volume was computed using Bayesian Model Selection (BaMoS). Global associations between WMH, amyloid, and cardiovascular risk-scores (Framingham and CAIDE) were assessed using linear models. Partial least square (PLS) regression was used to identify regional associations. Models were adjusted for age, sex, and APOE-e4 status. Individual PLS scores were then related to cognitive performance in 4 domains (attention, memory, executive functioning, and language).
While no significant global association was found, the PLS model yielded two components of interest. In the first PLS component, a fronto-parietal WMH pattern was associated with medial orbitofrontal-precuneal amyloid, vascular risk, and age. Component 2 showed a posterior WMH pattern associated with precuneus-cuneus amyloid, less related to age or vascular risk. Component 1 was associated with lower performance in all cognitive domains, while component 2 only with worse memory.
In a large pre-dementia population, we observed two distinct patterns of regional associations between WMH and amyloid burden, and demonstrated their joint influence on cognitive processes. These two components could reflect the existence of vascular-dependent and -independent manifestations of WMH-amyloid regional association that might be related to distinct primary pathophysiology.
Brain Communications
June, 2022
 
Cindy Birck
added an update
Daniele Altomare, Lyduine Collij, Camilla Caprioglio, Philip Scheltens, Bart N.M. van Berckel, Isadora Lopes Alves, Johannes Berkhof, Yvonne de Gier, Valentina Garibotto, Christian Moro, Léa Poitrine, Julien Delrieu, Pierre Payoux, Laure Saint-Aubert, José Luis Molinuevo, Oriol Grau-Rivera, Juan-Domingo Gispert, Carolina Minguillón, Karine Fauria, Marta Felez Sanchez, Andreea Rădoi, Alexander Drzezga, Frank Jessen, Claus Escher, Philip Zeyen, Agneta Nordberg, Irina Savitcheva, Vesna Jelic, Zuzana Walker, Ho-Yun Lee, Lean Lee, Jean-François Demonet, Sonia Plaza Wuthrich, Rossella Gismondi, Gill Farrar, Frederik Barkhof, Andrew W. Stephens, Giovanni B. Frisoni, the AMYPAD Consortium
Abstract: Introduction: AMYPAD Diagnostic and Patient Management Study (DPMS) aims to investigate the clinical utility and cost-effectiveness of amyloid-PET in Europe. Here we present participants’ baseline features and discuss the representativeness of the cohort.
Methods: Participants with subjective cognitive decline plus (SCD+), mild cognitive impairment (MCI), or dementia were recruited in eight European memory clinics from April 16, 2018, to October 30, 2020, and randomized into three arms: ARM1, early amyloid-PET; ARM2, late amyloid-PET; and ARM3, free-choice.
Results: A total of 840 participants (244 SCD+, 341 MCI, and 255 dementia) were enrolled. Sociodemographic/clinical features did not differ significantly among recruiting memory clinics or with previously reported cohorts. The randomization assigned 35% of participants to ARM1, 32% to ARM2, and 33% to ARM3; cognitive stages were distributed equally across the arms.
Discussion: The features of AMYPAD-DPMS participants are as expected for a memory clinic population. This ensures the generalizability of future study results.
Published online: 17 June 2022
Alzheimer’s & Dementia: the Journal of the Alzheimer’s Association
 
Cindy Birck
added an update
Fiona Heeman, Maqsood Yaqub, Janine Hendriks, Bart N. M. van Berckel, Lyduine E. Collij, Katherine R. Gray, Richard Manber, Robin Wolz, Valentina Garibotto, Catriona Wimberley, Craig Ritchie, Frederik Barkhof, Juan Domingo Gispert, David Vállez García, Isadora Lopes Alves & Adriaan A. Lammertsma on behalf of the AMYPAD Consortium
Abstract: Background: Despite its widespread use, the semi-quantitative standardized uptake value ratio (SUVR) may be biased compared with the distribution volume ratio (DVR). This bias may be partially explained by changes in cerebral blood flow (CBF) and is likely to be also dependent on the extent of the underlying amyloid-β (Aβ) burden. This study aimed to compare SUVR with DVR and to evaluate the effects of underlying Aβ burden and CBF on bias in SUVR in mainly cognitively unimpaired participants. Participants were scanned according to a dual-time window protocol, with either [18F]flutemetamol (N = 90) or [18F]florbetaben (N = 31). The validated basisfunction-based implementation of the two-step simplified reference tissue model was used to derive DVR and R1 parametric images, and SUVR was calculated from 90 to 110 min post-injection, all with the cerebellar grey matter as reference tissue. First, linear regression and Bland–Altman analyses were used to compare (regional) SUVR with DVR. Then, generalized linear models were applied to evaluate whether (bias in) SUVR relative to DVR could be explained by R1 for the global cortical average (GCA), precuneus, posterior cingulate, and orbitofrontal region.
Results: Despite high correlations (GCA: R2 ≥ 0.85), large overestimation and proportional bias of SUVR relative to DVR was observed. Negative associations were observed between both SUVR or SUVRbias and R1, albeit non-significant.
Conclusion: The present findings demonstrate that bias in SUVR relative to DVR is strongly related to underlying Aβ burden. Furthermore, in a cohort consisting mainly of cognitively unimpaired individuals, the effect of relative CBF on bias in SUVR appears limited.
Published: 12 May 2022
EJNMMI Research
 
Cindy Birck
added an update
Marthe Smedinga, Eline M. Bunnik, Edo Richard & Maartje H. N. Schermer
Abstract: An increasing number of people seek medical attention for mild cognitive symptoms at older age, worried that they might develop Alzheimer’s disease. Some clinical practice guidelines suggest offering biomarker testing in such cases, using a brain scan or a lumbar puncture, to improve diagnostic certainty about Alzheimer’s disease and enable an earlier diagnosis. Critics, on the other hand, point out that there is no effective Alzheimer treatment available and argue that biomarker tests lack clinical validity. The debate on the ethical desirability of biomarker testing is currently polarized; advocates and opponents tend to focus on their own line of arguments. In this paper, we show how the method of reflective equilibrium (RE) can be used to systematically weigh the relevant arguments on both sides of the debate to decide whether to offer Alzheimer biomarker testing. In the tradition of RE, we reflect upon these arguments in light of their coherence with other argumentative elements, including relevant facts (e.g. on the clinical validity of the test), ethical principles, and theories on societal ideals or relevant concepts, such as autonomy. Our stance in the debate therefore rests upon previously set out in-depth arguments and reflects a wide societal perspective.
Published 19 March 2022
Journal of Bioethical Inquiry
 
Cindy Birck
added an update
Hugh G. Pemberton, Lyduine E. Collij, Fiona Heeman, Ariane Bollack, Mahnaz Shekari, Gemma Salvadó, Isadora Lopes Alves, David Vallez Garcia, Mark Battle, Christopher Buckley, Andrew W. Stephens, Santiago Bullich, Valentina Garibotto, Frederik Barkhof, Juan Domingo Gispert & Gill Farrar on behalf of the AMYPAD consortium
Abstract: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
Published: 7 April 2022
European Journal of Nuclear Medicine and Molecular Imaging
 
Cindy Birck
added an update
Lyduine E. Collij, Gemma Salvadó, Viktor Wottschel, Sophie E Mastenbroek, Pierre Schoenmakers, Fiona Heeman, Leon Aksman, Alle Meije Wink, Bart N.M. Berckel, Wiesje M van de Flier, Philip Scheltens, Pieter Jelle Visser, Frederik Barkhof, Sven Haller, Juan Domingo Gispert, Isadora Lopes Alves, on behalf of for the Alzheimer’s Disease Neuroimaging Initiative; for the ALFA study
Abstract: Background and objectives: Currently, amyloid-β (Aβ) staging models assume a single spatial-temporal progression of amyloid accumulation. We assessed evidence for Aβ accumulation subtypes by applying the data-driven Subtype and Stage Inference (SuStaIn) model to amyloid-PET data.
Methods: Amyloid-PET data of 3010 subjects were pooled from 6 cohorts (ALFA+, EMIF-AD, ABIDE, OASIS, and ADNI). Standardized uptake value ratios (SUVr) were calculated for 17 regions. We applied the SuStaIn algorithm to identify consistent subtypes in the pooled dataset based on the cross-validation information criterion (CVIC) and the most probable subtype/stage classification per scan. The effect of demographics and risk factors on subtype assignment was assessed using multinomial logistic regression.
Results: Participants were mostly cognitively unimpaired (N=1890, 62.8%), had a mean age of 68.72 (SD=9.1), 42.1% was APOE-ε4 carrier, and 51.8% was female. While a one-subtype model recovered the traditional amyloid accumulation trajectory, SuStaIn identified an optimal of three subtypes, referred to as Frontal, Parietal, and Occipital based on the first regions to show abnormality. Of the 788 (26.2%) with strong subtype assignment (>50% probability), the majority was assigned to Frontal (N=415, 52.5%), followed by Parietal (N=199, 25.3%), and Occipital subtypes (N=175, 22.2%). Significant differences across subtypes included distinct proportions of APOE-ε4 carriers (Frontal:61.8%, Parietal:57.1%, Occipital:49.4%), subjects with dementia (Frontal:19.7%, Parietal:19.1%, Occipital:31.0%) and lower age for the Parietal subtype (Frontal/Occipital:72.1y, Parietal:69.3y). Higher amyloid (Centiloid) and CSF p-tau burden was observed for the Frontal subtype, while Parietal and Occipital did not differ. At follow-up, most subjects (81.1%) maintained baseline subtype assignment and 25.6% progressed to a later stage.
Discussion: While a one-trajectory model recovers the established pattern of amyloid accumulation, SuStaIn determined that three subtypes were optimal, showing distinct associations to AD risk factors. Nonetheless, further analyses to determine clinical utility is warranted.
Published: March 2022
Neurology
 
Cindy Birck
added an update
Emma M. Coomans, Jori Tomassen, Rik Ossenkoppele, Sandeep S. V. Golla, Marijke den Hollander, Lyduine E. Collij, Emma Weltings, Sophie van der Landen, Emma E. Wolters, Albert D. Windhorst, Frederik Barkhof, Eco J.C. de Geus, Philip Scheltens, Pieter Jelle Visser, Bart N. M. van Berckel, Anouk den Braber
Abstract: Tau accumulation starts during the preclinical phase of Alzheimer’s disease and is closely associated with cognitive decline. For preventive purposes, it is important to identify factors associated with tau accumulation and spread. Studying genetically identical twin-pairs may give insight into genetic and environmental contributions to tau pathology, as similarities in identical twin-pairs largely result from genetic factors, while differences in identical twin-pairs can largely be attributed to non-shared, environmental factors. This study aimed to examine similarities and dissimilarities in a cohort of genetically identical older twin-pairs in 1) tau load and 2) spatial distribution of tau, measured with [18F]flortaucipir PET.
We selected 78 genetically identical twins (39 pairs; average age 73 ± 6), enriched for amyloid-β pathology and APOE ε4 carriership, who underwent dynamic [18F]flortaucipir PET. We extracted binding potentials (BPND) in entorhinal, temporal, widespread neocortical and global regions, and examined within-pair similarities in BPND using age and sex corrected intra-class correlations. Furthermore, we tested whether twin-pairs showed a more similar spatial [18F]flortaucipir distribution compared to non-twin pairs, and whether the participant’s co-twin could be identified solely based on the spatial [18F]flortaucipir distribution. Last, we explored whether environmental (e.g. physical activity, obesity) factors could explain observed differences in twins of a pair in [18F]flortaucipir BPND.
On visual inspection, Alzheimer’s disease-like [18F]flortaucipir PET patterns were observed, and although we mainly identified similarities in twin-pairs, some pairs showed strong dissimilarities. [18F]flortaucipir BPND was correlated in twins in the entorhinal (r = 0.40; p = 0.01), neocortical (r = 0.59; p < 0.01) and global (r = 0.56; p < 0.01) regions, but not in the temporal region (r = 0.20; p = 0.10). The [18F]flortaucipir distribution pattern was significantly more similar between twins of the same pair (mean r = 0.27; SD = 0.09) than between non-twin pairings of participants (mean r = 0.01; SD = 0.10) (p < 0.01), also after correcting for proxies of off-target binding. Based on the spatial [18F]flortaucipir distribution, we could identify with an accuracy of 86% which twins belonged to the same pair. Finally, within-pair differences in [18F]flortaucipir BPND were associated with within-pair differences in depressive symptoms (0.37<β<0.56), physical activity (-0.41<β<-0.42) and social activity (-0.32<β<-0.36) (all p < 0.05).
Overall, identical twin-pairs were comparable in tau load and spatial distribution, highlighting the important role of genetic factors in the accumulation and spreading of tau pathology. Considering also the presence of dissimilarities in tau pathology in identical twin-pairs, our results additionally support a role for (potentially modifiable) environmental factors in the onset of Alzheimer’s disease pathological processes, which may be of interest for future prevention strategies.
Published: January 2022
Brain
 
Cindy Birck
added an update
Julia Pfeil, Merle C. Hoenig, Elena Doering, Thilo van Eimeren, Alexander Drzezga, Gérard N. Bischof, and for the Alzheimer's Disease Neuroimaging Initiative
Abstract: Although beta-amyloid (Aβ) positivity has shown to be associated with higher risk of progression to Alzheimer's disease (AD) in mild cognitive impairment (MCI), information on the time to conversion to manifest dementia cannot be readily deduced from this binary classification. Here, we assessed if regional patterns of Aβ deposition measured with 18F-florbetapir may serve as biomarker for progression risk in Aβ-positive cognitively normal (CN) and MCI patients, including clinical follow-up data and cerebrospinal fluid (CSF) biomarkers. Voxel-wise group comparisons between age and sex-matched Aβ-positive groups (i.e., CN-stables [n = 38] vs. CN-to-MCI/AD progressors [n = 38], MCI-stables [n = 104] versus MCI-to-AD progressors [n = 104]) revealed higher Aβ burden in precuneus, subcortical, and parietal regions in CN-to-MCI/AD progressors and cingulate, temporal, and frontal regions in MCI-to-AD progressors. Importantly, these regional patterns predicted progression to advanced stages on the AD spectrum in the short and the long-term beyond global Aβ burden and CSF biomarkers. These results suggest that distinct regional patterns of Aβ burden are a valuable biomarker for risk of disease progression in CN and MCI.
Published: October 2021
Neurobiology of Aging
 
Cindy Birck
added an update
Lyduine E. Collij, Sophie E. Mastenbroek, Gemma Salvadó, Alle Meije Wink, Pieter Jelle Visser, Frederik Barkhof, Bart. N.M. van Berckel, Isadora Lopes Alves
Abstract: Introduction: The value of quantitative longitudinal and regional amyloid beta (Aβ) measurements in predicting cognitive decline in initially cognitively unimpaired (CU) individuals remains to be determined.
Methods: We selected 133 CU individuals with two or more [11C]Pittsburgh compound B ([11C]PiB) scans and neuropsychological data from Open Access Series of Imaging Studies (OASIS-3). Baseline and annualized distribution volume ratios were computed for a global composite and four regional clusters. The predictive value of Aβ measurements (baseline, slope, and interaction) on longitudinal cognitive performance was examined.
Results: Global performance could only be predicted by Aβ burden in an early cluster (precuneus, lateral orbitofrontal, and insula) and the precuneus region of interest (ROI) by itself significantly improved the model. Precuneal Aβ burden was also predictive of immediate and delayed episodic memory performance. In Aβ subjects at baseline (N = 93), lateral orbitofrontal Aβ burden predicted working and semantic memory performance.
Discussion: Quantifying longitudinal and regional changes in Aβ can improve the prediction of cognitive functioning in initially CU individuals.
Published: 2 August 2021
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
 
Fiona Heeman
added 2 research items
Purpose: Moderate-to-high correlations have been reported between the [11C]PiB PET-derived relative tracer delivery rate R1 and relative CBF as measured using [15O]H2O PET, supporting its use as a proxy of relative CBF. As longitudinal PET studies become more common for measuring treatment efficacy or disease progression, it is important to know the intrinsic variability of R1. The purpose of the present study was to determine this through a retrospective data analysis. Procedures: Test-retest data belonging to twelve participants, who underwent two 90 min [11C]PiB PET scans, were retrospectively included. The voxel-based implementation of the two-step simplified reference tissue model with cerebellar grey matter as reference tissue was used to compute R1 images. Next, test-retest variability was calculated, and test and retest R1 measures were compared using linear mixed effect models and a Bland-Altman analysis. Results: Test-retest variability was low across regions (max. 5.8 %), and test and retest measures showed high, significant correlations (R2=0.92, slope=0.98) and a negligible bias (0.69±3.07 %). Conclusions: In conclusion, the high precision of [11C]PiB R1 suggests suitable applicability for cross-sectional and longitudinal studies.
Background: Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. Methods: Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. Results: Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). Conclusion: Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development.
Cindy Birck
added an update
Fiona Heeman; Janine Hendriks; Isadora Lopes Alves; Nelleke Tolboom; Bart N. M. van Berckel; Maqsood Yaqub; Adriaan A. Lammertsma
Abstract: Purpose: Moderate-to-high correlations have been reported between the [11C]PiB PET-derived relative tracer delivery rate R1 and relative CBF as measured using [15O]H2O PET, supporting its use as a proxy of relative CBF. As longitudinal PET studies become more common for measuring treatment efficacy or disease progression, it is important to know the intrinsic variability of R1. The purpose of the present study was to determine this through a retrospective data analysis.
Procedures: Test-retest data belonging to twelve participants, who underwent two 90 min [11C]PiB PET scans, were retrospectively included. The voxel-based implementation of the two-step simplified reference tissue model with cerebellar grey matter as reference tissue was used to compute R1 images. Next, test-retest variability was calculated, and test and retest R1 measures were compared using linear mixed effect models and a Bland-Altman analysis.
Results: Test-retest variability was low across regions (max. 5.8 %), and test and retest measures showed high, significant correlations (R2=0.92, slope=0.98) and a negligible bias (0.69±3.07 %).
Conclusions: In conclusion, the high precision of [11C]PiB R1 suggests suitable applicability for cross-sectional and longitudinal studies.
Published: 21 April 2021
Molecular Imaging and Biology
 
Cindy Birck
added an update
Isadora Lopes Alves, Fiona Heeman, Lyduine E. Collij, Gemma Salvadó, Nelleke Tolboom, Natàlia Vilor-Tejedor, Pawel Markiewicz, Maqsood Yaqub, David Cash, Elizabeth C. Mormino, Philip S. Insel, Ronald Boellaard, Bart N. M. van Berckel, Adriaan A. Lammertsma, Frederik Barkhof & Juan Domingo Gispert
Abstract: Background: Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer’s disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials.
Methods: Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database (www.oasis-brains.org). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only.
Results: Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR).
Conclusion: Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development.
Published online: 19 April 2021
Alzheimer's Research & Therapy
 
Daniele Altomare
added 2 research items
Purpose To review how outcomes of clinical utility are operationalized in current amyloid-PET validation studies, to prepare for formal assessment of clinical utility of amyloid-PET-based diagnosis. Methods Systematic review of amyloid-PET research studies published up to April 2020 that included outcomes of clinical utility. We extracted and analyzed (a) outcome categories, (b) their definition, and (c) their methods of assessment. Results Thirty-two studies were eligible. (a) Outcome categories were clinician-centered (found in 25/32 studies, 78%), patient-/caregiver-centered (in 9/32 studies, 28%), and health economics-centered (5/32, 16%). (b) Definition: Outcomes were mainly defined by clinical researchers; only the ABIDE study expressly included stakeholders in group discussions. Clinician-centered outcomes mainly consisted of incremental diagnostic value (25/32, 78%) and change in patient management (17/32, 53%); patient-/caregiver-centered outcomes considered distress after amyloid-pet-based diagnosis disclosure (8/32, 25%), including quantified burden of procedure for patients’ outcomes (n = 8) (1/8, 12.5%), impact of disclosure of results (6/8, 75%), and psychological implications of biomarker-based diagnosis (75%); and health economics outcomes focused on costs to achieve a high-confidence etiological diagnosis (5/32, 16%) and impact on quality of life (1/32, 3%). (c) Assessment: all outcome categories were operationalized inconsistently across studies, employing 26 different tools without formal rationale for selection. Conclusion Current studies validating amyloid-PET already assessed outcomes for clinical utility, although non-clinician-based outcomes were inconsistent. A wider participation of stakeholders may help produce a more thorough and systematic definition and assessment of outcomes of clinical utility and help collect evidence informing decisions on reimbursement of amyloid-PET.
Purpose Assess the individual and combined diagnostic value of amyloid-PET and tau-PET in a memory clinic population. Methods Clinical reports of 136 patients were randomly assigned to two diagnostic pathways: AMY-TAU, amyloid-PET is presented before tau-PET; and TAU-AMY, tau-PET is presented before amyloid-PET. Two neurologists independently assessed all reports with a balanced randomized design, and expressed etiological diagnosis and diagnostic confidence (50–100%) three times: (i) at baseline based on the routine diagnostic workup, (ii) after the first exam (amyloid-PET for the AMY-TAU pathway, and tau-PET for the TAU-AMY pathway), and (iii) after the remaining exam. The main outcomes were changes in diagnosis (from AD to non-AD or vice versa) and in diagnostic confidence. Results Amyloid-PET and tau-PET, when presented as the first exam, resulted in a change of etiological diagnosis in 28% (p = 0.006) and 28% (p < 0.001) of cases, and diagnostic confidence increased by 18% (p < 0.001) and 19% (p < 0.001) respectively, with no differences between exams (p > 0.05). We observed a stronger impact of a negative amyloid-PET versus a negative tau-PET (p = 0.014). When added as the second exam, amyloid-PET and tau-PET resulted in a further change in etiological diagnosis in 6% (p = 0.077) and 9% (p = 0.149) of cases, and diagnostic confidence increased by 4% (p < 0.001) and 5% (p < 0.001) respectively, with no differences between exams (p > 0.05). Conclusion Amyloid-PET and tau-PET significantly impacted diagnosis and diagnostic confidence in a similar way, although a negative amyloid-PET has a stronger impact on diagnosis than a negative tau-PET. Adding either of the two as second exam further improved diagnostic confidence. Trial number PB 2016-01346.
Silvia Ingala
added an update
We found an association between continuous regional amyloid burden (PET) and white matter microstructure (DTI) in preclinical AD. This relationship is non-linear and suggests very early effects of amyloid deposition.
 
Juan D Gispert
added a research item
Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated. For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.
Arianna Sala
added a research item
Mismatch between CSF and PET amyloid-β biomarkers occurs in up to ≈20% of preclinical/prodromal Alzheimer's disease individuals. Factors underlying mismatching results remain unclear. In this study we hypothesized that CSF/PET discordance provides unique biological/clinical information. To test this hypothesis, we investigated non-demented and demented participants with CSF amyloid-β 42 and [18F]Florbetapir PET assessments at baseline (n = 867) and at 2-year follow-up (n = 289). Longitudinal trajectories of amyloid-β positivity were tracked simultaneously for CSF and PET biomarkers. In the longitudinal cohort (n = 289), we found that participants with normal CSF/PET amyloid-β biomarkers progressed more frequently toward CSF/PET discordance than to full CSF/PET positivity (χ 2 (1) = 5.40; p < 0.05). Progression to CSF+/PET+ status was ten times more frequent in cases with discordant biomarkers, as compared to csf−/pet− cases (χ 2 (1) = 18.86; p < 0.001). Compared to the CSF+/pet− group, the csf−/PET+ group had lower APOE-ε4ε4 prevalence (χ 2 (6) = 197; p < 0.001; n = 867) and slower rate of brain amyloid-β accumulation (F (3,600) = 12.76; p < 0.001; n = 608). These results demonstrate that biomarker discordance is a typical stage in the natural history of amyloid-β accumulation, with CSF or PET becoming abnormal first and not concurrently. Therefore, biomarker discordance allows for identification of individuals with elevated risk of progression toward fully abnormal amyloid-β biomarkers, with subsequent risk of neurodegeneration and cognitive decline. Our results also suggest that there are two alternative pathways ("CSF-first" vs. "PET-first") toward established amyloid-β pathology, characterized by different genetic profiles and rates of amyloid-β accumulation. In conclusion, CSF and PET amyloid-β biomarkers provide distinct information, with potential implications for their use as biomarkers in clinical trials.
Fiona Heeman
added a research item
Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [¹⁸F]flutemetamol and [¹⁸F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [¹⁸F]flutemetamol and [¹⁸F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time-window protocol and either [¹⁸F]flutemetamol (N=24) or [¹⁸F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([¹⁸F]flutemetamol: range AUC=0.96-0.97 [¹⁸F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R²≥0.87), while lowest correlation were observed for MRTM2 (R²=0.71-0.80). Furthermore, bias was low (≤ 5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R1), which is useful for measuring disease progression.
Cindy Birck
added an update
Lyduine E. Collij, Silvia Ingala, Herwin Top, Viktor Wottschel, Kristine E. Stickney, Jori Tomasse,n Elles Konijnenberg, Mara ten Kate, Carole Sudre, Isadora Lopes Alves, Maqsood M. Yaqub, Alle Meije Wink, Dennis Van ‘t Ent, Philip Schelten,s Bart N.M. van Berckel, Pieter Jelle Visser, Frederik Barkhof, Anouk Den Braber
Abstract:
Introduction: Amyloid beta (Aβ) accumulation is the first pathological hallmark of Alzheimer's disease (AD), and it is associated with altered white matter (WM) microstructure. We aimed to investigate this relationship at a regional level in a cognitively unimpaired cohort.
Methods: We included 179 individuals from the European Medical Information Framework for AD (EMIF‐AD) preclinAD study, who underwent diffusion magnetic resonance (MR) to determine tract‐level fractional anisotropy (FA); mean, radial, and axial diffusivity (MD/RD/AxD); and dynamic [18F]flutemetamol) positron emission tomography (PET) imaging to assess amyloid burden.
Results: Regression analyses showed a non‐linear relationship between regional amyloid burden and WM microstructure. Low amyloid burden was associated with increased FA and decreased MD/RD/AxD, followed by decreased FA and increased MD/RD/AxD upon higher amyloid burden. The strongest association was observed between amyloid burden in the precuneus and body of the corpus callosum (CC) FA and diffusivity (MD/RD) measures. In addition, amyloid burden in the anterior cingulate cortex strongly related to AxD and RD measures in the genu CC.
Discussion: Early amyloid deposition is associated with changes in WM microstructure. The non‐linear relationship might reflect multiple stages of axonal damage.
Published: 1 April 2021
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
 
Cindy Birck
added an update
Santiago Bullich, Núria Roé-Vellvé, Marta Marquié, Susan M. Landau, Henryk Barthel, Victor L. Villemagne, Ángela Sanabria, Juan Pablo Tartari, Oscar Sotolongo-Grau, Vincent Doré, Norman Koglin, Andre Müller, Audrey Perrotin, Aleksandar Jovalekic, Susan De Santi, Lluís Tárraga, Andrew W. Stephens, Christopher C. Rowe, Osama Sabri, John P. Seibyl & Mercè Boada
Abstract:
Background: A low amount and extent of Aβ deposition at early stages of Alzheimer’s disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition.
Methods: The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition (“gray zone”), and subjects with established Aβ pathology.
Results: SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the “gray zone” or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology.
Conclusions: This study supports the utility of using two cutoffs for amyloid PET abnormality defining a “gray zone”: a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention.
Published: 27 March 2021
Alzheimer's Research & Therapy
 
Cindy Birck
added an update
Fiona Heeman, Maqsood Yaqub, Janine Hendriks, Ilona Bader, Frederik Barkhof, Juan Domingo Gispert, Bart N M van Berckel, Isadora Lopes Alves, Adriaan A Lammertsma
Abstract:
Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [18F]flutemetamol and [18F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [18F]flutemetamol and [18F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [18F]flutemetamol (N=24) or [18F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90–110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([18F]flutemetamol: range AUC=0.96–0.97 [18F]florbetaben: range AUC=0.83–0.85). Outcome parameters of most methods were highly correlated with the reference method (R2≥0.87), while lowest correlation were observed for MRTM2 (R2=0.71–0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R1), which is useful for measuring disease progression.
Published online: 21 March 2021
NeuroImage
 
Cindy Birck
added an update
Daniele Altomare, Camilla Caprioglio, Frédéric Assal, Gilles Allali, Aline Mendes, Federica Ribaldi, Kelly Ceyzeriat, Marta Martins, Szymon Tomczyk, Sara Stampacchia, Alessandra Dodich, Marina Boccardi, Christian Chicherio, Giovanni B. Frisoni & Valentina Garibotto
Abstract:
Purpose: Assess the individual and combined diagnostic value of amyloid-PET and tau-PET in a memory clinic population.
Methods: Clinical reports of 136 patients were randomly assigned to two diagnostic pathways: AMY-TAU, amyloid-PET is presented before tau-PET; and TAU-AMY, tau-PET is presented before amyloid-PET. Two neurologists independently assessed all reports with a balanced randomized design, and expressed etiological diagnosis and diagnostic confidence (50–100%) three times: (i) at baseline based on the routine diagnostic workup, (ii) after the first exam (amyloid-PET for the AMY-TAU pathway, and tau-PET for the TAU-AMY pathway), and (iii) after the remaining exam. The main outcomes were changes in diagnosis (from AD to non-AD or vice versa) and in diagnostic confidence.
Results” Amyloid-PET and tau-PET, when presented as the first exam, resulted in a change of etiological diagnosis in 28% (p = 0.006) and 28% (p < 0.001) of cases, and diagnostic confidence increased by 18% (p < 0.001) and 19% (p < 0.001) respectively, with no differences between exams (p > 0.05). We observed a stronger impact of a negative amyloid-PET versus a negative tau-PET (p = 0.014). When added as the second exam, amyloid-PET and tau-PET resulted in a further change in etiological diagnosis in 6% (p = 0.077) and 9% (p = 0.149) of cases, and diagnostic confidence increased by 4% (p < 0.001) and 5% (p < 0.001) respectively, with no differences between exams (p > 0.05).
Conclusion” Amyloid-PET and tau-PET significantly impacted diagnosis and diagnostic confidence in a similar way, although a negative amyloid-PET has a stronger impact on diagnosis than a negative tau-PET. Adding either of the two as second exam further improved diagnostic confidence.
Published: 27 February 2021
European Journal of Nuclear Medicine and Molecular Imaging
 
Cindy Birck
added an update
Matteo Cotta RamusinoGiulia PeriniDaniele AltomarePaola BarbarinoWendy WeidnerGabriella Salvini PorroFrederik BarkhofGil D RabinoviciWiesje M van der FlierGiovanni B Frisoni, Valentina GaribottoStefan TeipelMarina Boccardi
Abstract:
Purpose: To review how outcomes of clinical utility are operationalized in current amyloid-PET validation studies, to prepare for formal assessment of clinical utility of amyloid-PET-based diagnosis.
Methods: Systematic review of amyloid-PET research studies published up to April 2020 that included outcomes of clinical utility. We extracted and analyzed (a) outcome categories, (b) their definition, and (c) their methods of assessment.
Results: Thirty-two studies were eligible. (a) Outcome categories were clinician-centered (found in 25/32 studies, 78%), patient-/caregiver-centered (in 9/32 studies, 28%), and health economics-centered (5/32, 16%). (b) Definition: Outcomes were mainly defined by clinical researchers; only the ABIDE study expressly included stakeholders in group discussions. Clinician-centered outcomes mainly consisted of incremental diagnostic value (25/32, 78%) and change in patient management (17/32, 53%); patient-/caregiver-centered outcomes considered distress after amyloid-pet-based diagnosis disclosure (8/32, 25%), including quantified burden of procedure for patients' outcomes (n = 8) (1/8, 12.5%), impact of disclosure of results (6/8, 75%), and psychological implications of biomarker-based diagnosis (75%); and health economics outcomes focused on costs to achieve a high-confidence etiological diagnosis (5/32, 16%) and impact on quality of life (1/32, 3%). (c) Assessment: all outcome categories were operationalized inconsistently across studies, employing 26 different tools without formal rationale for selection.
Conclusion: Current studies validating amyloid-PET already assessed outcomes for clinical utility, although non-clinician-based outcomes were inconsistent. A wider participation of stakeholders may help produce a more thorough and systematic definition and assessment of outcomes of clinical utility and help collect evidence informing decisions on reimbursement of amyloid-PET.
Published: 17 February 2021
European Journal of Nuclear Medicine and Molecular Imaging
 
Cindy Birck
added an update
Lyduine E. Collij, Gemma Salvadó, Mahnaz Shekari, Isadora Lopes Alves, Juhan Reimand, Alle Meije Wink, Marissa Zwan, Aida Niñerola-Baizán, Andrés Perissinotti, Philip Scheltens, Milos D. Ikonomovic, Adrian P. L. Smith, Gill Farrar, José Luis Molinuevo, Frederik Barkhof, Christopher J. Buckley, Bart N. M. van Berckel & Juan Domingo Gispert.
Abstract:
Purpose: To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR.
Methods: [18F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [18F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density.
Results: VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERADSOT-based classification (i.e., any region mCERADSOT > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density.
Conclusion: VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value.
Published: 22 February 2021
European Journal of Nuclear Medicine and Molecular Imaging
 
Cindy Birck
added an update
Pawel J. Markiewicz; Julian C. Matthews; John Ashburner; David M. Cash; David L. Thomas; Enrico De Vita; Anna Barnes; M. Jorge Cardoso; Marc Modat; Richard Brown; Kris Thielemans; Casper da Costa-Luis; Isadora Lopes Alves; Juan Domingo Gispert Lopez; Mark Schmidt; Paul Marsden; Alexander Hammers; Sebastien Ourselin; Frederik Barkhof
Abstract:
Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated.
For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.
Published: 12 February 2021
NeuroImage
 
Cindy Birck
added an update
Victor L. Villemagne, Frederik Barkhof, Valentina Garibotto, Susan M. Landau, Agneta Nordberg, Bart N. M. van Berckel
Abstract: Not only can molecular imaging using PET help show the pathologic hallmarks of Alzheimer disease and assess loss of dopaminergic terminals in parkinsonian disorders, but the development of novel tracers for neuroinflammation and synaptic density further allows for elucidation of the molecular pathologic characteristics of dementia disorders.
The increasing prevalence of dementia worldwide places a high demand on healthcare providers to perform a diagnostic work-up in relatively early stages of the disease, given that the pathologic process usually begins decades before symptoms are evident. Structural imaging is recommended to rule out other disorders and can only provide diagnosis in a late stage with limited specificity. Where PET imaging previously focused on the spatial pattern of hypometabolism, the past decade has seen the development of novel tracers to demonstrate characteristic protein abnormalities. Molecular imaging using PET/SPECT is able to show amyloid and tau deposition in Alzheimer disease and dopamine depletion in parkinsonian disorders starting decades before symptom onset. Novel tracers for neuroinflammation and synaptic density are being developed to further unravel the molecular pathologic characteristics of dementia disorders. In this article, the authors review the current status of established and emerging PET tracers in a diagnostic setting and also their value as prognostic markers in research studies and outcome measures for clinical trials in Alzheimer disease.
Published: 19 January 2021
Radiology
 
Cindy Birck
added a project reference
Cindy Birck
added 9 research items
Traditional quantitative cut‐offs for amyloid PET positivity have been defined to discriminate Alzheimer’s dementia (AD) subjects from elderly Aβ‐negative non‐demented controls. Currently, observational and interventional studies focus on earlier stages of Aβ deposition, where established cut‐offs might not be appropriate. Here, we review recent developments on early pathology identification, and provide supporting evidence from three cohorts for the establishment of a “gray‐zone” of amyloid burden. Data from three cohorts of cognitively unimpaired individuals were included, namely ALFA+ (n=357), FACEHBI (n=228) and the AMYPAD Prognostic Study (n=122). PET scans ([18F]flutemetamol and [18F]florbetaben) were analyzed in Centiloid (CL) units. Gaussian Mixture Modelling was used to fit two/three Gaussians to the global CL values, and the cut‐off for early pathology detection was defined as two standard deviations above the mean of the left Gaussian. Then, the data was merged to derived a joint cut‐off. Finally, these data‐driven cut‐offs were compared to previously established thresholds in the context defining a range of CL values where pathology is emerging. GMM identified a cut‐off of CL=11 for FACEHBI, CL=14 for ALFA+, CL=17 for AMYPAD and CL=11 for the cohorts combined (Figure 1). Similarly, Salvadó et al identified two cut‐offs based on a direct comparison with established CSFAβ42 thresholds: CL=12 to rule out‐amyloid pathology and CL=29 to denote established pathology. With a different approach, the FACEHBI working group finds CL=13 as an early threshold defined based on young healthy controls, and CL=36 as an established cut‐off to separate healthy elderly from Aβ‐positive AD‐dementia subjects. In AMYPAD, where a more comprehensive sampling of the AD continuum is present, fitting 3 Gaussians through the data allows the identification of two data‐driven cut‐offs: CL=13 and CL=29. A number of recent and current reports converge to the utility of two cut‐offs for amyloid PET abnormality, an early cut‐off around CL=11‐17 where pathology may be emerging, and a second around CL=29‐36 where amyloid burden levels greatly correspond to neuropathology findings. Together, these create a gray‐zone of CL values pre‐AD dementia levels of amyloid burden, which can improve the detection of emerging pathology in observational and secondary prevention trials.
Amyloid‐PET is increasingly used for diagnostic purposes in patients with cognitive impairment due to suspected Alzheimer’s disease. However, cognitively unimpaired individuals are frequently included in research studies involving amyloid‐PET scan. Even if amyloid‐PET is not clinically recommended in these cases, these patients often want to know their amyloid status, a strong risk factor for incident dementia. Currently, evidence on the impact of the disclosure of amyloid‐PET results on patients’ psychological well‐being is scanty. The aim of this sub‐study is to assess how a positive amyloid‐PET result affects the psychological well‐being of patients with subjective cognitive decline plus (SCD+) enrolled in a prospective study on the diagnostic utility of amyloid PET (AMYPAD‐DPMS). The impact of the disclosure of amyloid‐PET results on patient’s psychological well‐being was investigated using the Impact of Event Scale–Revised (IES‐R). IES‐R is used to detect potential changes from the current time point and a previous time point preceding up to 7 days an event (the amyloid‐PET result disclosure in this case). IES‐R was administered 1‐3 days post‐disclosure, and consists of one total score (0‐88) and three sub‐scores (0‐4): avoidance (avoidance of thoughts, feelings, memories or situations), intrusions (intrusive memories, thoughts, or feelings causing distress), and hyperarousal (hypervigilance, feeling watchful and on guard, difficulty concentrating). IES‐R total score between 12‐32: symptoms of post‐traumatic stress, patient monitoring is required; ≥33: probable presence of a post‐traumatic stress disorder. So far, 36 SCD+ participants of AMYPAD‐DPMS, who received their amyloid‐PET results, have accepted to participate in this sub‐study. Amyloid‐positive patients (n=9) had higher IES‐R total score (median=10, lower‐upper quartiles=1‐14) than amyloid‐negatives (1, 0‐6), albeit at trend level (p=0.052). We also observed higher avoidance scores in amyloid‐positives compared to amyloid‐negatives (0, 0.00‐0.62 vs. 0, 0.00‐0.00, p=0.004), but no differences in the other two sub‐scores (p>0.05). These preliminary data on 36 participants suggests that the disclosure of positive amyloid scan to an SCD+ patient is associated with the avoidance of thoughts and memories of the news. Future analyses will address additional outcome measures (e.g. post‐disclosure anxiety and depression) and factors associated with a milder psychological impact in amyloid‐positive patients.
Detecting amyloid‐β plaque accumulation in individuals who are initially amyloid negative can help understand the earliest stages of Alzheimer’s disease (AD). This study aimed to determine sample sizes that would be needed to detect statistically significant longitudinal changes using semi‐ (standard uptake value ratios; SUVR) and quantitative (distribution volume ratios; DVR) PET measures at global and regional levels. [11C]PIB scans of 239 cognitively normal (CN) subjects (mean age 63.4 ± 9.3 years) in the OASIS‐3 data‐set, who underwent at least two PET scans, were included. Regional SUVR and DVR were extracted using a cortical composite as target, and cerebellar gray matter as reference region (PUP, https://github.com/ysu001/PUP). PET positivity was defined by Gaussian Mixture Modelling of the global SUVR (SUVR>1.16). Annual accumulation rates were calculated using linear regression, and sample sizes to detect a significant longitudinal change (alpha = 0.05; 1‐beta = 0.80) were determined with the sampsizepwr function in Matlab. The percentage of accumulators (rates of change >2SD of negative group) was also computed. As expected, rates of change were higher in subjects with positive PET at baseline, and APOE‐ε4 carriership increased accumulation rates in both negative and positive groups (Table 1). Using either metric, orbitofrontal and precuneus displayed the highest rates of change in the negative group. SUVR rendered higher accumulation rates than DVR, but also displayed higher variability. As a consequence, to detect 0.22% early accumulation (mean of negative group), global DVR required N = 584 compared with N = 917 for global SUVR (Figure 1). In addition, DVR classified 13% of subjects as accumulators compared with 9% for SUVR. Finally, precuneus and orbitofrontal regions classify more subjects as accumulators than global SUVR, i.e. 17 and 25%, respectively. As compared to SUVR, DVR can reduce the sample size needed to detect longitudinal amyloid changes by approximately 40% in amyloid negative populations. Additional improvements in statistical power can be achieved by focusing on precuneus and orbitofrontal regions.
Cindy Birck
added an update
Arianna Sala, Agneta Nordberg, Elena Rodriguez-Vieitez & for the Alzheimer’s Disease Neuroimaging Initiative
ABSTRACT
Mismatch between CSF and PET amyloid-β biomarkers occurs in up to ≈20% of preclinical/prodromal Alzheimer’s disease individuals. Factors underlying mismatching results remain unclear. In this study we hypothesized that CSF/PET discordance provides unique biological/clinical information. To test this hypothesis, we investigated non-demented and demented participants with CSF amyloid-β42 and [18F]Florbetapir PET assessments at baseline (n = 867) and at 2-year follow-up (n = 289). Longitudinal trajectories of amyloid-β positivity were tracked simultaneously for CSF and PET biomarkers. In the longitudinal cohort (n = 289), we found that participants with normal CSF/PET amyloid-β biomarkers progressed more frequently toward CSF/PET discordance than to full CSF/PET positivity (χ2(1) = 5.40; p < 0.05). Progression to CSF+/PET+ status was ten times more frequent in cases with discordant biomarkers, as compared to csf−/pet− cases (χ2(1) = 18.86; p < 0.001). Compared to the CSF+/pet− group, the csf−/PET+ group had lower APOE-ε4ε4 prevalence (χ2(6) = 197; p < 0.001; n = 867) and slower rate of brain amyloid-β accumulation (F(3,600) = 12.76; p < 0.001; n = 608). These results demonstrate that biomarker discordance is a typical stage in the natural history of amyloid-β accumulation, with CSF or PET becoming abnormal first and not concurrently. Therefore, biomarker discordance allows for identification of individuals with elevated risk of progression toward fully abnormal amyloid-β biomarkers, with subsequent risk of neurodegeneration and cognitive decline. Our results also suggest that there are two alternative pathways (“CSF-first” vs. “PET-first”) toward established amyloid-β pathology, characterized by different genetic profiles and rates of amyloid-β accumulation. In conclusion, CSF and PET amyloid-β biomarkers provide distinct information, with potential implications for their use as biomarkers in clinical trials.
Molecular Psychiatry (2020)
 
Cindy Birck
added an update
Giovanni B FrisoniJosé Luis MolinuevoDaniele AltomareEmmanuel CarreraFrederik BarkhofJohannes BerkhofJulien DelrieuBruno DuboisMiia KivipeltoAgneta NordbergJonathan M SchottWiesje M van der FlierBruno VellasFrank JessenPhilip ScheltensCraig Ritchie
ABSTRACT
Empirical evidence suggests that a fair proportion of dementia cases are preventable, that some preventive actions can be taken immediately, and others may soon be implemented. Primary prevention may target cognitively normal persons with modifiable risk factors through lifestyle and multiple domain interventions (including general cardiovascular health). While the effect on individuals may be modest, it might have a large societal impact by decreasing overall dementia incidence by up to 35%. Secondary prevention will target cognitively normal persons at high risk of dementia due to Alzheimer's disease pathology with future anti-amyloid, anti-tau, or other drugs. This approach is likely to have major benefits to both individuals and society. Memory clinics will need structural and functional changes to adapt to novel technologies and increased patients' demands, and brand-new services may need to be developed with specific skills on risk profiling, risk communication, and personalized risk reduction plans.
Alzheimers Dement. 2020 Oct;16(10):1457-1468.
 
Cindy Birck
added a research item
Empirical evidence suggests that a fair proportion of dementia cases are preventable, that some preventive actions can be taken immediately, and others may soon be implemented. Primary prevention may target cognitively normal persons with modifiable risk factors through lifestyle and multiple domain interventions (including general cardiovascular health). While the effect on individuals may be modest, it might have a large societal impact by decreasing overall dementia incidence by up to 35%. Secondary prevention will target cognitively normal persons at high risk of dementia due to Alzheimer's disease pathology with future anti-amyloid, anti-tau, or other drugs. This approach is likely to have major benefits to both individuals and society. Memory clinics will need structural and functional changes to adapt to novel technologies and increased patients' demands, and brand-new services may need to be developed with specific skills on risk profiling, risk communication, and personalized risk reduction plans.
Cindy Birck
added an update
Marthe Smedinga, Eline M Bunnik, Edo Richard, Maartje H N Schermer
ABSTRACT
Background and Objectives: The meaning of Alzheimer’s disease (AD) is changing in research. It now refers to a pathophysiological process, regardless of whether clinical symptoms are present. In the lay literature, on the other hand, AD is understood as a form of dementia. This raises the question of whether researchers and the lay audience are still talking about the same thing. If not, how will these different understandings of AD shape perspectives on (societal) needs for people with AD?
Research Design and Methods: We use framing analysis to retrieve the understandings of the term AD that are upheld in the research literature and in national Dutch newspaper articles. We make explicit how the framings of AD steer our normative attitudes toward the disease.
Results: In the analyzed research articles, AD is framed as a pathological cascade, reflected by biomarkers, starting in cognitively healthy people and ending, inevitably, in dementia. In the lay literature, AD is used as a synonym for dementia, and an AD diagnosis is understood as an incentive to enjoy “the time that is left.”
Discussion and Implications: The two different uses of the term AD in research and in the lay literature may result in misunderstandings, especially those research framings that falsely imply that people with AD biomarkers will inevitably develop dementia. Adoption of the research understanding of AD in clinical practice will have normative implications for our view on priority setting in health care. For example, it legitimizes biomarker testing in people without dementia as improving “diagnostic” certainty
Published: 3 November 2020
The Gerontologist
 
Cindy Birck
added an update
Gaël Chételat, Javier Arbizu, Henryk Barthel, Valentina Garibotto, Ian Law, Silvia Morbelli, Elsmarieke van de Giessen, Federica Agosta, Frederik Barkhof, David J Brooks, Maria C Carrillo, Bruno Dubois, Anders M Fjell, Giovanni B Frisoni, Oskar Hansson, Karl Herholz, Brian F Hutton, Clifford R Jack Jr, Adriaan A Lammertsma, Susan M Landau, Satoshi Minoshima, Flavio Nobili, Agneta Nordberg, Rik Ossenkoppele, Wim J G Oyen, Daniela Perani, Gil D Rabinovici, Philip Scheltens, Victor L Villemagne, Henrik Zetterberg, Alexander Drzezga
Abstract: Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloidPET and ¹⁸F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies.
Published: November 2020
The Lancet Neurology
 
Cindy Birck
added an update
Fiona Heeman, Janine Hendriks, Isadora Lopes Alves, Rik Ossenkoppele, Nelleke Tolboom, Bart N. M. van Berckel, Adriaan A. Lammertsma, Maqsood Yaqub on behalf of the AMYPAD Consortium
Abstract:
Background: The standard reference region (RR) for amyloid-beta (Aβ) PET studies is the cerebellar grey matter (GMCB), while alternative RRs have mostly been utilized without prior validation against the gold standard. This study compared five commonly used RRs to gold standard plasma input-based quantification using the GMCB.
Methods: Thirteen subjects from a test–retest (TRT) study and 30 from a longitudinal study were retrospectively included (total: 17 Alzheimer’s disease, 13 mild cognitive impairment, 13 controls). Dynamic [11C]PiB PET (90 min) and T1-weighted MR scans were co-registered and time–activity curves were extracted for cortical target regions and the following RRs: GMCB, whole cerebellum (WCB), white matter brainstem/pons (WMBS), whole brainstem (WBS) and eroded subcortical white matter (WMES). A two-tissue reversible plasma input model (2T4k_Vb) with GMCB as RR, reference Logan and the simplified reference tissue model were used to derive distribution volume ratios (DVRs), and standardized uptake value (SUV) ratios were calculated for 40–60 min and 60–90 min intervals. Parameter variability was evaluated using TRT scans, and correlations and agreements with the gold standard (DVR from 2T4k_Vb with GMCB RR) were also assessed. Next, longitudinal changes in SUVs (both intervals) were assessed for each RR. Finally, the ability to discriminate between visually Aβ positive and Aβ negative scans was assessed.
Results: All RRs yielded stable TRT performance (max 5.1% variability), with WCB consistently showing lower variability. All approaches were able to discriminate between Aβ positive and Aβ negative scans, with highest effect sizes obtained for GMCB (range − 0.9 to − 0.7), followed by WCB (range − 0.8 to − 0.6). Furthermore, all approaches provided good correlations with the gold standard (r ≥ 0.78), while the highest bias (as assessed by the regression slope) was observed using WMES (range slope 0.52–0.67), followed by WBS (range slope 0.58–0.92) and WMBS (range slope 0.62–0.91). Finally, RR SUVs were stable across a period of 2.6 years for all except WBS and WMBS RRs (60–90 min interval).
Conclusions: GMCB and WCB are considered the best RRs for quantifying amyloid burden using [11C]PiB PET.
Published online: 19 October 2020
EJNMMI Research, volume 10, Article number: 123 (2020)
 
Fiona Heeman
added a research item
Background The standard reference region (RR) for amyloid-beta (Aβ) PET studies is the cerebellar grey matter (GMCB), while alternative RRs have mostly been utilized without prior validation against the gold standard. This study compared five commonly used RRs to gold standard plasma input-based quantification using the GMCB. Methods Thirteen subjects from a test–retest (TRT) study and 30 from a longitudinal study were retrospectively included (total: 17 Alzheimer’s disease, 13 mild cognitive impairment, 13 controls). Dynamic [11C]PiB PET (90 min) and T1-weighted MR scans were co-registered and time–activity curves were extracted for cortical target regions and the following RRs: GMCB, whole cerebellum (WCB), white matter brainstem/pons (WMBS), whole brainstem (WBS) and eroded subcortical white matter (WMES). A two-tissue reversible plasma input model (2T4k_Vb) with GMCB as RR, reference Logan and the simplified reference tissue model were used to derive distribution volume ratios (DVRs), and standardized uptake value (SUV) ratios were calculated for 40–60 min and 60–90 min intervals. Parameter variability was evaluated using TRT scans, and correlations and agreements with the gold standard (DVR from 2T4k_Vb with GMCB RR) were also assessed. Next, longitudinal changes in SUVs (both intervals) were assessed for each RR. Finally, the ability to discriminate between visually Aβ positive and Aβ negative scans was assessed. Results All RRs yielded stable TRT performance (max 5.1% variability), with WCB consistently showing lower variability. All approaches were able to discriminate between Aβ positive and Aβ negative scans, with highest effect sizes obtained for GMCB (range − 0.9 to − 0.7), followed by WCB (range − 0.8 to − 0.6). Furthermore, all approaches provided good correlations with the gold standard (r ≥ 0.78), while the highest bias (as assessed by the regression slope) was observed using WMES (range slope 0.52–0.67), followed by WBS (range slope 0.58–0.92) and WMBS (range slope 0.62–0.91). Finally, RR SUVs were stable across a period of 2.6 years for all except WBS and WMBS RRs (60–90 min interval). Conclusions GMCB and WCB are considered the best RRs for quantifying amyloid burden using [11C]PiB PET.
Cindy Birck
added an update
Isadora Lopes Alves, Lyduine E. Collij, Daniele Altomare, Giovanni B. Frisoni, Laure Saint‐Aubert, Pierre Payoux, Miia Kivipelto, Frank Jessen, Alexander Drzezga, Annebet Leeuwis, Alle Meije Wink, Pieter Jelle Visser, Bart N.M. van Berckel, Philip Scheltens, Katherine R. Gray, Robin Wolz, Andrew Stephens, Rossella Gismondi, Christopher Buckely, Juan Domingo Gispert, Mark Schmidt, Lisa Ford, Craig Ritchie, Gill Farrar, Frederik Barkhof, José Luis Molinuevo, the AMYPAD Consortium
Abstract:
Introduction: The Amyloid Imaging to Prevent Alzheimer's Disease (AMYPAD) Prognostic and Natural History Study (PNHS) aims at understanding the role of amyloid imaging in the earliest stages of Alzheimer's disease (AD). AMYPAD PNHS adds (semi‐)quantitative amyloid PET imaging to several European parent cohorts (PCs) to predict AD‐related progression as well as address methodological challenges in amyloid PET.
Methods: AMYPAD PNHS is an open‐label, prospective, multi‐center, cohort study recruiting from multiple PCs. Around 2000 participants will undergo baseline amyloid positron emission tomography (PET), half of whom will be invited for a follow‐up PET 12 at least 12 months later.
Results: Primary include several amyloid PET measurements (Centiloid, SUVr, BPND, R1), and secondary are their changes from baseline, relationship to other amyloid markers (cerebrospinal fluid and visual assessment), and predictive value of AD‐related decline.
Expected Impact: Determining the role of amyloid PET for the understanding of this complex disease and potentially improving secondary prevention trials.
Published: 12 April 2020
Alzheimer’s & Dementia
 
Cindy Birck
added an update
Fiona Heeman, Maqsood Yaqub, Isadora Lopes Alves, Kerstin Heurling, Santiago Bullich, Juan D Gispert, Ronald Boellaard, Adriaan A Lammertsma, on behalf of the AMYPAD Consortium
Abstract: Global and regional changes in cerebral blood flow (CBF) can result in biased quantitative estimates of amyloid load by PET imaging. Therefore, the current simulation study assessed effects of these changes on amyloid quantification using a reference tissue approach for [18F]flutemetamol and [18F]florbetaben. Previously validated pharmacokinetic rate constants were used to simulate time-activity curves (TACs) corresponding to full dynamic and dual-time-window acquisition protocols. CBF changes were simulated by varying the tracer delivery (K1) from +25 to −25%. The standardized uptake value ratio (SUVr) was computed and TACs were fitted using reference Logan (RLogan) and the simplified reference tissue model (SRTM) to obtain the relative delivery rate (R1) and volume of distribution ratio (DVR). RLogan was least affected by CBF changes (χ2 = 583 p < 0.001, χ2 =81 p < 0.001, for [18F]flutemetamol and [18F]florbetaben, respectively) and the extent of CBF sensitivity generally increased for higher levels of amyloid. Further, SRTM-derived R1 changes correlated well with simulated CBF changes (R2 > 0.95) and SUVr’s sensitivity to CBF changes improved for later uptake-times, with the exception of [18F]flutemetamol cortical changes. In conclusion, RLogan is the preferred method for amyloid quantification of [18F]flutemetamol and [18F]florbetaben studies and SRTM could be additionally used for obtaining a CBF proxy.
Published: 11 April 2020
Journal of Cerebral Blood Flow&Metabolim
 
Cindy Birck
added an update
Lyduine E. Collij, Fiona Heeman, Gemma Salvadó, Silvia Ingala, Daniele Altomare, Arno Wilde, Elles Konijnenberg, Marieke van Buchem, Maqsood Yaqub, Pawel Markiewicz, Sandeep S.V. Golla, Viktor Wottschel, Alle Meije Wink, Pieter Jelle Visser, Charlotte E. Teunissen, Adriaan A. Lammertsma, Philip Scheltens, Wiesje M. van der Flier, Ronald Boellaard, Bart N.M. van Berckel, José Luis Molinuevo, Juan Domingo Gispert, Mark E. Schmidt, Frederik Bsarkhof, Isadora Lopes Alves; for the ALFA Study; for the Alzheimer’s Disease Neuroimaging Initiative;on behalf of the AMYPAD Consortium
Abstract:
Objective: To develop and evaluate a model for staging cortical amyloid deposition using PET with high generalizability.
Methods: 3027 subjects (1763 Cognitively Unimpaired (CU), 658 Impaired, 467 Alzheimer’s disease (AD) dementia, 111 non-AD dementia, and 28 with missing diagnosis) from six cohorts (EMIF-AD, ALFA, ABIDE, ADC, OASIS-3, ADNI) who underwent amyloid PET were retrospectively included; 1049 subjects had follow-up scans. Applying dataset-specific cut-offs to global Standard Uptake Value ratio (SUVr) values from 27 regions, single-tracer and pooled multi-tracer regional rankings were constructed from the frequency of abnormality across 400 CU subjects (100 per tracer). The pooled multi-tracer ranking was used to create a staging model consisting of four clusters of regions as it displayed a high and consistent correlation with each single-tracer ranking. Relationships between amyloid stage, clinical variables and longitudinal cognitive decline were investigated.
Results: SUVr abnormality was most frequently observed in cingulate, followed by orbitofrontal, precuneal, and insular cortices, then the associative, temporal and occipital regions. Abnormal amyloid levels based on binary global SUVr classification were observed in 1.0%, 5.5%, 17.9%, 90.0%, and 100.0% of stage 0-4 subjects, respectively. Baseline stage predicted decline in MMSE (ADNI: N=867, F=67.37, p<0.001; OASIS: (N=475, F=9.12, p<0.001) and faster progression towards an MMSE≤25 (ADNI: N=787, HRstage1=2.00, HRstage2=3.53, HRstage3=4.55, HRstage4=9.91, p<0.001; OASIS: N=469, HRstage4=4.80, p<0.001).
Conclusion: The pooled multi-tracer staging model successfully classified the level of amyloid burden in >3000 subjects across cohorts and radiotracers, and detects pre-global amyloid burden and distinct risk profiles of cognitive decline within globally amyloid-positive subjects.
Published: 16 July 2020
Neurology
 
Cindy Birck
added a research item
Objective To develop and evaluate a model for staging cortical amyloid deposition using PET with high generalizability. Methods 3027 subjects (1763 Cognitively Unimpaired (CU), 658 Impaired, 467 Alzheimer’s disease (AD) dementia, 111 non-AD dementia, and 28 with missing diagnosis) from six cohorts (EMIF-AD, ALFA, ABIDE, ADC, OASIS-3, ADNI) who underwent amyloid PET were retrospectively included; 1049 subjects had follow-up scans. Applying dataset-specific cut-offs to global Standard Uptake Value ratio (SUVr) values from 27 regions, single-tracer and pooled multi-tracer regional rankings were constructed from the frequency of abnormality across 400 CU subjects (100 per tracer). The pooled multi-tracer ranking was used to create a staging model consisting of four clusters of regions as it displayed a high and consistent correlation with each single-tracer ranking. Relationships between amyloid stage, clinical variables and longitudinal cognitive decline were investigated. Results SUVr abnormality was most frequently observed in cingulate, followed by orbitofrontal, precuneal, and insular cortices, then the associative, temporal and occipital regions. Abnormal amyloid levels based on binary global SUVr classification were observed in 1.0%, 5.5%, 17.9%, 90.0%, and 100.0% of stage 0-4 subjects, respectively. Baseline stage predicted decline in MMSE (ADNI: N= 867, F =67.37, p< 0.001; OASIS: ( N= 475, F =9.12, p< 0.001) and faster progression towards an MMSE≤25 (ADNI: N= 787, HR stage1 =2.00, HR stage2 =3.53, HR stage3 =4.55, HR stage4 =9.91, p< 0.001; OASIS: N= 469, HR stage4 =4.80, p< 0.001). Conclusion The pooled multi-tracer staging model successfully classified the level of amyloid burden in >3000 subjects across cohorts and radiotracers, and detects pre-global amyloid burden and distinct risk profiles of cognitive decline within globally amyloid-positive subjects.
Cindy Birck
added a research item
Introduction: The Amyloid Imaging to Prevent Alzheimer's Disease (AMYPAD) Prognostic and Natural History Study (PNHS) aims at understanding the role of amyloid imaging in the earliest stages of Alzheimer's disease (AD). AMYPAD PNHS adds (semi-)quantitative amyloid PET imaging to several European parent cohorts (PCs) to predict AD-related progression as well as address methodological challenges in amyloid PET. Methods: AMYPAD PNHS is an open-label, prospective, multi-center, cohort study recruiting from multiple PCs. Around 2000 participants will undergo baseline amyloid positron emission tomography (PET), half of whom will be invited for a follow-up PET 12 at least 12 months later. Results: Primary include several amyloid PET measurements (Centiloid, SUVr, BPND , R1 ), and secondary are their changes from baseline, relationship to other amyloid markers (cerebrospinal fluid and visual assessment), and predictive value of AD-related decline. Expected impact: Determining the role of amyloid PET for the understanding of this complex disease and potentially improving secondary prevention trials.
Fiona Heeman
added a research item
Global and regional changes in cerebral blood flow (CBF) can result in biased quantitative estimates of amyloid load by PET imaging. Therefore, the current simulation study assessed effects of these changes on amyloid quantification using a reference tissue approach for [¹⁸F]flutemetamol and [¹⁸F]florbetaben. Previously validated pharmacokinetic rate constants were used to simulate time-activity curves (TACs) corresponding to full dynamic and dual-time-window acquisition protocols. CBF changes were simulated by varying the tracer delivery (K1) from +25 to −25%. The standardized uptake value ratio (SUVr) was computed and TACs were fitted using reference Logan (RLogan) and the simplified reference tissue model (SRTM) to obtain the relative delivery rate (R1) and volume of distribution ratio (DVR). RLogan was least affected by CBF changes (χ² = 583 p < 0.001, χ² = 81 p < 0.001, for [¹⁸F]flutemetamol and [¹⁸F]florbetaben, respectively) and the extent of CBF sensitivity generally increased for higher levels of amyloid. Further, SRTM-derived R1 changes correlated well with simulated CBF changes (R² > 0.95) and SUVr’s sensitivity to CBF changes improved for later uptake-times, with the exception of [¹⁸F]flutemetamol cortical changes. In conclusion, RLogan is the preferred method for amyloid quantification of [¹⁸F]flutemetamol and [¹⁸F]florbetaben studies and SRTM could be additionally used for obtaining a CBF proxy.
Cindy Birck
added an update
Jessen F, Amariglio RE, Buckley RF, van der Flier WM, Han Y, Molinuevo JL, Rabin L, Rentz DM, Rodriguez-Gomez O, Saykin AJ, Sikkes SAM, Smart CM, Wolfsgruber S, Wagner M
Abstract: A growing awareness about brain health and Alzheimer's disease in the general population is leading to an increasing number of cognitively unimpaired individuals, who are concerned that they have reduced cognitive function, to approach the medical system for help. The term subjective cognitive decline (SCD) was conceived in 2014 to describe this condition. Epidemiological data provide evidence that the risk for mild cognitive impairment and dementia is increased in individuals with SCD. However, the majority of individuals with SCD will not show progressive cognitive decline. An individually tailored diagnostic process might be reasonable to identify or exclude underlying medical conditions in an individual with SCD who actively seeks medical help. An increasing number of studies are investigating the link between SCD and the very early stages of Alzheimer's disease and other neurodegenerative diseases.
Published: 17 January 2020
The Lancet Neurology
 
Cindy Birck
added an update
Enrico Fantoni, Lyduine Collij, Isadora Lopes Alves, Christopher Buckley, Gill Farrar, on behalf of the AMYPAD consortium
Abstract: While clinical routine focuses on dichotomous and visual interpretation of amyloid PET, in a research setting, regional image assessment may yield additional opportunities. Understanding the regional-temporal evolution of amyloid pathology may enable the earlier identification of subjects who are in the Alzheimer’s Disease pathological continuum, as well as a more fine-grained assessment of pathology beyond traditional dichotomous measures. This review summarises the current research in the detection of regional amyloid deposition patterns and its potential for staging amyloid pathology. Pathology studies, cross-sectional and longitudinal PET-only studies, and comparative PET and autopsy studies are included. Despite certain differences, cortical deposition generally precedes striatal pathology, and in PET-only studies, medial cortical regions are seen to accumulate amyloid earlier than lateral regions. Based on regional amyloid PET, multiple studies have developed and implemented models for staging amyloid pathology which could improve subject selection into secondary prevention trials and visual assessment in clinical routine.
Published: 13 December 2019
The Journal of Nuclear Medicine

 
Cindy Birck
added a research item
While clinical routine focuses on dichotomous and visual interpretation of amyloid PET, in a research setting, regional image assessment may yield additional opportunities. Understanding the regional-temporal evolution of amyloid pathology may enable the earlier identification of subjects who are in the Alzheimer's Disease pathological continuum, as well as a more fine-grained assessment of pathology beyond traditional dichotomous measures. This review summarises the current research in the detection of regional amyloid deposition patterns and its potential for staging amyloid pathology. Pathology studies, cross-sectional and longitudinal PET-only studies, and comparative PET and autopsy studies are included. Despite certain differences, cortical deposition generally precedes striatal pathology, and in PET-only studies, medial cortical regions are seen to accumulate amyloid earlier than lateral regions. Based on regional amyloid PET, multiple studies have developed and implemented models for staging amyloid pathology which could improve subject selection into secondary prevention trials and visual assessment in clinical routine.
Cindy Birck
added a research item
In the last decades, progress in neuroimaging techniques and cerebrospinal fluid assays has enabled the characterization of several Alzheimer's disease (AD) biomarkers. This knowledge has shifted the conceptualization of AD from a clinical-pathological construct, where its diagnosis required the presence of dementia with distinct pathologic features, toward a clinical-biological one that recognizes AD as a pathological continuum with a clinical picture that ranges from normal cognition to a dementia stage. Specifically, AD is now divided into three stages: preclinical (abnormal biomarkers and no or only subtle cognitive impairment), mild cognitive impairment or prodromal AD (abnormal pathophysiological biomarkers and episodic memory impairment), and dementia (abnormal biomarkers and clear cognitive and functional impairment). The possibility of assessing AD pathophysiology in vivo before the onset of clinical symptoms in the preclinical stage provides the unprecedented opportunity to intervene at earlier stages of the continuum in secondary prevention trials. Currently, large cohort studies of cognitively healthy participants are undergoing with the main aim of disentangling the natural history of AD to identify individuals with an increased risk of developing AD in the near future to be recruited in these clinical trials. In this paper, we review how the concept of AD has changed over the years as well as discuss the implications of this conceptual change.
Cindy Birck
added an update
Damiano Archetti, Silvia Ingala, Vikram Venkatraghavan, Viktor Wottschel, Alexandra L.Young, Maura Bellio, Esther E Bron, Stefan Klein, Frederik Barkhof, Daniel C. Alexander, Neil P. Oxtoby, Giovanni B.Frisoni, Alberto Redolfi, for the Alzheimer's Disease Neuroimaging Initiative, for EuroPOND Consortium
Abstract:
Understanding the sequence of biological and clinical events along the course of Alzheimer's disease provides insights into dementia pathophysiology and can help participant selection in clinical trials. Our objective is to train two data-driven computational models for sequencing these events, the Event Based Model (EBM) and discriminative-EBM (DEBM), on the basis of well-characterized research data, then validate the trained models on subjects from clinical cohorts characterized by less-structured data-acquisition protocols.
Seven independent data cohorts were considered totalling 2389 cognitively normal (CN), 1424 mild cognitive impairment (MCI) and 743 Alzheimer's disease (AD) patients. The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set was used as training set for the constriction of disease models while a collection of multi-centric data cohorts was used as test set for validation. Cross-sectional information related to clinical, cognitive, imaging and cerebrospinal fluid (CSF) biomarkers was used.
Event sequences obtained with EBM and DEBM showed differences in the ordering of single biomarkers but according to both the first biomarkers to become abnormal were those related to CSF, followed by cognitive scores, while structural imaging showed significant volumetric decreases at later stages of the disease progression. Staging of test set subjects based on sequences obtained with both models showed good linear correlation with the Mini Mental State Examination score (R2EBM = 0.866; R2DEBM = 0.906). In discriminant analyses, significant differences (p-value ≤ 0.05) between the staging of subjects from training and test sets were observed in both models. No significant difference between the staging of subjects from the training and test was observed (p-value > 0.05) when considering a subset composed by 562 subjects for which all biomarker families (cognitive, imaging and CSF) are available.
Event sequence obtained with DEBM recapitulates the heuristic models in a data-driven fashion and is clinically plausible. We demonstrated inter-cohort transferability of two disease progression models and their robustness in detecting AD phases. This is an important step towards the adoption of data-driven statistical models into clinical domain.
23 July 2019
NeuroImage: Clinical, 2019 Jul 23;24:101954
 
Cindy Birck
added an update
Fiona Heeman, Maqsood Yaqub, Isadora Lopes Alves, Kerstin Heurling, Johannes Berkhof, Juan Domingo Gispert, Santiago Bullich, Christopher Foley, Adriaan A. Lammertsma and on behalf of the AMYPAD Consortium
Background: A long dynamic scanning protocol may be required to accurately measure longitudinal changes in amyloid load. However, such a protocol results in a lower patient comfort and scanning efficiency compared to static scans. A compromise can be achieved by implementing dual-time-window protocols. This study aimed to optimize these protocols for quantitative [18F]flutemetamol and [18F]florbetaben studies. Methods: Rate constants for subjects across the Alzheimer’s disease spectrum (i.e., non-displaceable binding potential (BPND) in the range 0.02–0.77 and 0.02–1.04 for [18F]flutemetamol and [18F]florbetaben, respectively) were established based on clinical [18F]flutemetamol (N = 6) and [18F]florbetaben (N = 20) data, and used to simulate tissue time-activity curves (TACs) of 110 min using a reference tissue and plasma input model. Next, noise was added (N = 50) and data points corresponding to different intervals were removed from the TACs, ranging from 0 (i.e., 90–90 = full-kinetic curve) to 80 (i.e., 10–90) minutes, creating a dual-time-window. Resulting TACs were fitted using the simplified reference tissue method (SRTM) to estimate the BPND, outliers (≥ 1.5 × BPND max) were removed and the bias was assessed using the distribution volume ratio (DVR = BPND + 1). To this end, acceptability curves, which display the fraction of data below a certain bias threshold, were generated and the area under those curves were calculated. Results: [18F]Flutemetamol and [18F]florbetaben data demonstrated an increased bias in amyloid estimate for larger intervals and higher noise levels. An acceptable bias (≤ 3.1%) in DVR could be obtained with all except the 10–90 and 20–90-min intervals. Furthermore, a reduced fraction of acceptable data and most outliers were present for these two largest intervals (maximum percentage outliers 48 and 32 for [18F]flutemetamol and [18F]florbetaben, respectively). Conclusions: The length of the interval inversely correlates with the accuracy of the BPND estimates. Consequently, a dual-time-window protocol of 0–30 and 90–110 min (=maximum of 60 min interval) allows for accurate estimation of BPND values for both tracers.
EJNMMI Res. 2019 Mar 27;9(1):32
27 March 2019
 
Cindy Birck
added an update
GB Frisoni, IL Alves, F Barkhof
Amyloid PET has made the dream of dementia specialists come true, enabling visualisation in vivo and with high accuracy of the amyloid deposits that Alois Alzheimer described as senile plaques more than a century ago. Until recently, such visualisation could only be appreciated post mortem—far too late to be of any practical use. As is often the case, enthusiasm on this technological advancement was followed by more sobering observations. A large proportion (20–30%) of people aged 65 years and older who have intact cognitive function have a positive amyloid PET scan, making the exam more suitable to rule out than to rule in the disease (ie, a negative amyloid PET rules out Alzheimer's disease pathology as the cause of cognitive impairment, but a positive scan does not imply Alzheimer's disease pathology as the underlying factor). Additionally, amyloid is just one of two pathophysiological markers of Alzheimer's disease, the other being tau, which is more closely associated with symptom onset and for which PET tracers are emerging. In this apparently grim scenario, how can a diagnostic test of brain amyloidosis improve clinical outcomes?
Lancet Neurol. 2019 Jun;18(6):519-520
 
Cindy Birck
added a research item
Understanding the sequence of biological and clinical events along the course of Alzheimer's disease provides insights into dementia pathophysiology and can help participant selection in clinical trials. Our objective is to train two data-driven computational models for sequencing these events, the Event Based Model (EBM) and discriminative-EBM (DEBM), on the basis of well-characterized research data, then validate the trained models on subjects from clinical cohorts characterized by less-structured data-acquisition protocols. Seven independent data cohorts were considered totalling 2389 cognitively normal (CN), 1424 mild cognitive impairment (MCI) and 743 Alzheimer's disease (AD) patients. The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set was used as training set for the constriction of disease models while a collection of multi-centric data cohorts was used as test set for validation. Cross-sectional information related to clinical, cognitive, imaging and cerebrospinal fluid (CSF) biomarkers was used. Event sequences obtained with EBM and DEBM showed differences in the ordering of single biomarkers but according to both the first biomarkers to become abnormal were those related to CSF, followed by cognitive scores, while structural imaging showed significant volumetric decreases at later stages of the disease progression. Staging of test set subjects based on sequences obtained with both models showed good linear correlation with the Mini Mental State Examination score (R2EBM = 0.866; R2DEBM = 0.906). In discriminant analyses, significant differences (p-value ≤ 0.05) between the staging of subjects from training and test sets were observed in both models. No significant difference between the staging of subjects from the training and test was observed (p-value > 0.05) when considering a subset composed by 562 subjects for which all biomarker families (cognitive, imaging and CSF) are available. Event sequence obtained with DEBM recapitulates the heuristic models in a data-driven fashion and is clinically plausible. We demonstrated inter-cohort transferability of two disease progression models and their robustness in detecting AD phases. This is an important step towards the adoption of data-driven statistical models into clinical domain.
Cindy Birck
added 5 research items
The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.
Cindy Birck
added 3 research items
Introduction: Reimbursement of amyloid-positron emission tomography (PET) is lagging due to the lack of definitive evidence on its clinical utility and cost-effectiveness. The Amyloid Imaging to Prevent Alzheimer's Disease-Diagnostic and Patient Management Study (AMYPAD-DPMS) is designed to fill this gap. Methods: AMYPAD-DPMS is a phase 4, multicenter, prospective, randomized controlled study. Nine hundred patients with subjective cognitive decline plus, mild cognitive impairment, and dementia possibly due to Alzheimer's disease will be randomized to ARM1, amyloid-PET performed early in the diagnostic workup; ARM2, amyloid-PET performed after 8 months; and ARM3, amyloid-PET performed whenever the physician chooses to do so. Endpoints: The primary endpoint is the difference between ARM1 and ARM2 in the proportion of patients receiving a very-high-confidence etiologic diagnosis after 3 months. Secondary endpoints address diagnosis and diagnostic confidence, diagnostic/therapeutic management, health economics and patient-related outcomes, and methods for image quantitation. Expected impacts: AMYPAD-DPMS will supply physicians and health care payers with real-world data to plan management decisions.
Background In Alzheimer’s disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations. Main body Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation. Conclusion We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI. Electronic supplementary material The online version of this article (10.1186/s13195-018-0438-z) contains supplementary material, which is available to authorized users.
Objective: Determine the optimal approach for assessing amyloid pathology in a cognitively normal elderly population. Methods: Dynamic [18F]flutemetamol PET scans acquired using a coffee-break protocol (0-30 and 90-110 min. scan) from 190 cognitively normal elderly (mean age 70.4 years, 60% female) were included. Parametric images were generated from standard uptake value ratio (SUVr) and non-displaceable binding potential (BPND) methods, with cerebellar grey matter as a reference region and were visually assessed by three trained readers. Inter-reader agreement was calculated using Kappa statistics and (semi-)quantitative values were obtained. Global cut-offs were calculated for both SUVr and BPND using a ROC analysis and the Youden Index. Visual assessment was related to (semi-)quantitative classifications. Results: Inter-reader agreement in visual assessment was moderate for SUVr (κ = 0.57) and good for BPND images (κ = 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BPND, with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BPND values were 1.33 (± 0.21) and 0.16 (± 0.12), respectively. Most of the 35 cases (91%) where SUVr image assessment was discordant between readers, were classified as negative based on (semi-) quantitative measurements. Conclusion: The use of parametric BPND images for visual assessment of [18F]flutemetamol in a population with low amyloid burden improves inter-reader agreement. Implementing semi-quantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population.
Fiona Heeman
added a research item
Background A long dynamic scanning protocol may be required to accurately measure longitudinal changes in amyloid load. However, such a protocol results in a lower patient comfort and scanning efficiency compared to static scans. A compromise can be achieved by implementing dual-time-window protocols. This study aimed to optimize these protocols for quantitative [18F]flutemetamol and [18F]florbetaben studies. Methods Rate constants for subjects across the Alzheimer’s disease spectrum (i.e., non-displaceable binding potential (BPND) in the range 0.02–0.77 and 0.02–1.04 for [18F]flutemetamol and [18F]florbetaben, respectively) were established based on clinical [18F]flutemetamol (N = 6) and [18F]florbetaben (N = 20) data, and used to simulate tissue time-activity curves (TACs) of 110 min using a reference tissue and plasma input model. Next, noise was added (N = 50) and data points corresponding to different intervals were removed from the TACs, ranging from 0 (i.e., 90–90 = full-kinetic curve) to 80 (i.e., 10–90) minutes, creating a dual-time-window. Resulting TACs were fitted using the simplified reference tissue method (SRTM) to estimate the BPND, outliers (≥ 1.5 × BPND max) were removed and the bias was assessed using the distribution volume ratio (DVR = BPND + 1). To this end, acceptability curves, which display the fraction of data below a certain bias threshold, were generated and the area under those curves were calculated. Results [18F]Flutemetamol and [18F]florbetaben data demonstrated an increased bias in amyloid estimate for larger intervals and higher noise levels. An acceptable bias (≤ 3.1%) in DVR could be obtained with all except the 10–90 and 20–90-min intervals. Furthermore, a reduced fraction of acceptable data and most outliers were present for these two largest intervals (maximum percentage outliers 48 and 32 for [18F]flutemetamol and [18F]florbetaben, respectively). Conclusions The length of the interval inversely correlates with the accuracy of the BPND estimates. Consequently, a dual-time-window protocol of 0–30 and 90–110 min (=maximum of 60 min interval) allows for accurate estimation of BPND values for both tracers. [18F]flutemetamol: EudraCT 2007-000784-19, registered 8 February 2007, [18F]florbetaben: EudraCT 2006-003882-15, registered 2006.
Cindy Birck
added an update
Mara ten Kate†, Silvia Ingala†, Adam J. Schwarz, Nick C. Fox, Gaël Chételat, Bart N. M. van Berckel, Michael Ewers, Christopher Foley, Juan Domingo Gispert, Derek Hill, Michael C. Irizarry, Adriaan A. Lammertsma, José Luis Molinuevo, Craig Ritchie, Philip Scheltens, Mark E. Schmidt, Pieter Jelle Visser, Adam Waldman, Joanna Wardlaw, Sven Haller and Frederik Barkhof
†Contributed equally
Abstract:
Background: In Alzheimer’s disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations.
Main body: Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation.
Conclusion: We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.
Alzheimer's Research & Therapy 201810:112
 
Cindy Birck
added an update
*Lyduine E. Collij, *Elles Konijnenberg, Juhan Reimand, Mara ten Kate, Anouk den Braber, Isadora Lopes Alves, Marissa Zwan, Maqsood Yaqub, Daniëlle M.E. van Assema, Alle Meije Wink, Adriaan A. Lammertsma, Philip Scheltens, Pieter Jelle Visser, Frederik Barkhof & Bart N.M. van Berckel *Authors contributed equally
Abstract:
Objective: Determine the optimal approach for assessing amyloid pathology in a cognitively normal elderly population.
Methods: Dynamic 18F-Flutemetamol PET scans acquired using a coffee-break protocol (0-30 and 90110 min. scan) from 190 cognitively normal elderly (mean age 70.4 years, 60% female) were included. Parametric images were generated from standard uptake value ratio (SUVr) and non-displaceable binding potential (BPND) methods, with cerebellar grey matter as a reference region and were visually assessed by three trained readers. Inter-reader agreement was calculated using Kappa statistics and (semi)quantitative values were obtained. Global cut-offs were calculated for both SUVr and BPND using a ROC analysis and the Youden Index. Visual assessment was related to (semi-)quantitative classifications.
Results: Inter-reader agreement in visual assessment was moderate for SUVr (κ = 0.57) and good for BPND images (κ = 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BPND, with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BPND values were 1.33 (± 0.21) and 0.16 (± 0.12), respectively. Most of the 35 cases (91%) where SUVr image assessment was discordant between readers, were classified as negative based on (semi-) quantitative measurements.
Conclusion: The use of parametric BPND images for visual assessment of 18F-Flutemetamol in a population with low amyloid burden improves inter-reader agreement. Implementing semi-quantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population.
Journal of Nuclear Medicine
 
Cindy Birck
added an update
Giovanni B. Frisoni, Frederik Barkhof, Daniele Altomare, Johannes Berkhof, Marina Boccardi, Elisa Canzoneri, Lyduine Collij, Alexander Drzezga, Gill Farrar, Valentina Garibotto, Rossella Gismondi, Juan-Domingo Gispert, Frank Jessen, Miia Kivipelto, Isadora Lopes Alves, José-Luis Molinuevo, Agneta Nordberg, Pierre Payoux, Craig Ritchie, Irina Savicheva, Philip Scheltens, Mark E. Schmidt, Jonathan Schott, Andrew Stephens, Bart van Berckel, Bruno Vellas, Zuzana Walker, Nicola Raffa
Abstract:
Introduction: Reimbursement of amyloid-PET is lagging due to the lack of definitive evidence on its clinical utility and cost-effectiveness. The Amyloid Imaging to Prevent Alzheimer's Disease–Diagnostic and Patient Management Study (AMYPAD-DPMS) is designed to fill this gap.
Methods: AMYPAD-DPMS is a phase 4, multicenter, prospective, randomized controlled study. Nine hundred patients with subjective cognitive decline plus, mild cognitive impairment, and dementia possibly due to Alzheimer's disease will be randomized to ARM1, amyloid-PET performed early in the diagnostic workup; ARM2, amyloid-PET performed after 8 months; and ARM3, amyloid-PET performed whenever the physician chooses to do so.
Endpoints: The primary endpoint is the difference between ARM1 and ARM2 in the proportion of patients receiving a very-high-confidence etiologic diagnosis after 3 months. Secondary endpoints address diagnosis and diagnostic confidence, diagnostic/therapeutic management, health economics and patient-related outcomes, and methods for image quantitation.
Expected Impacts: AMYPAD-DPMS will supply physicians and health care payers with real-world data to plan management decisions.
Alzheimer’s & Dementia

 
Cindy Birck
added an update
Matthias J. Ehrhardt, Pawel Markiewicz, Antonin Chambolle, Peter Richtárik, Jonathan Schott, Carola-Bibiane Schönlieb
Image reconstruction in positron emission tomography (PET) is computationally challenging due to Poisson noise, constraints and potentially non-smooth priors-let alone the sheer size of the problem. An algorithm that can cope well with the first three of the aforementioned challenges is the primal-dual hybrid gradient algorithm (PDHG) studied by Chambolle and Pock in 2011. However, PDHG updates all variables in parallel and is therefore computationally demanding on the large problem sizes encountered with modern PET scanners where the number of dual variables easily exceeds 100 million. In this work, we numerically study the usage of SPDHG-a stochastic extension of PDHG-but is still guaranteed to converge to a solution of the deterministic optimization problem with similar rates as PDHG. Numerical results on a clinical data set show that by introducing randomization into PDHG, similar results as the deterministic algorithm can be achieved using only around 10 % of operator evaluations. Thus, making significant progress towards the feasibility of sophisticated mathematical models in a clinical setting.
Proceedings Volume 10394, Wavelets and Sparsity XVII, 103941O (2017)
 
Cindy Birck
added an update
Molinuevo JL, Minguillon C, Rami L, Gispert JD
In the last decades, progress in neuroimaging techniques and cerebrospinal fluid assays has enabled the characterization of several Alzheimer's disease (AD) biomarkers. This knowledge has shifted the conceptualization of AD from a clinical-pathological construct, where its diagnosis required the presence of dementia with distinct pathologic features, toward a clinical-biological one that recognizes AD as a pathological continuum with a clinical picture that ranges from normal cognition to a dementia stage. Specifically, AD is now divided into three stages: preclinical (abnormal biomarkers and no or only subtle cognitive impairment), mild cognitive impairment or prodromal AD (abnormal pathophysiological biomarkers and episodic memory impairment), and dementia (abnormal biomarkers and clear cognitive and functional impairment). The possibility of assessing AD pathophysiology in vivo before the onset of clinical symptoms in the preclinical stage provides the unprecedented opportunity to intervene at earlier stages of the continuum in secondary prevention trials. Currently, large cohort studies of cognitively healthy participants are undergoing with the main aim of disentangling the natural history of AD to identify individuals with an increased risk of developing AD in the near future to be recruited in these clinical trials. In this paper, we review how the concept of AD has changed over the years as well as discuss the implications of this conceptual change.
J Alzheimers Dis. 2018;62(3):1067-1077
 
Cindy Birck
added an update
Markiewicz PJ,, Ehrhardt MJ, Erlandsson K, Noonan PJ, Barnes A, Schott JM, Atkinson D, Arridge SR, Hutton BF, Ourselin S.
We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.
Published Online in Neuroinformatics on December, 2017
 
Cindy Birck
added a project goal
AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) is a collaborative research initiative (IMI) aiming to improve the understanding, diagnosis and management of Alzheimer’s disease through the utilization of amyloid PET imaging.
For further details visit: https://amypad.eu/
 
Isadora Lopes Alves
added an update
Project goal
AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) is a collaborative research initiative (IMI) aiming to improve the understanding, diagnosis and management of Alzheimer’s disease through the utilization of amyloid PET imaging.
Background and motivation
β‐amyloid deposition in the brain is one of the neuropathological hallmarks on the path  towards  development  of  Alzheimer’s  disease  (AD). It may  improve an early diagnosis of AD, and, when recognized in a pre‐symptomatic population, even provide  an  opportunity  for  secondary  prevention  of  AD.  However,  the  full  value  of  this  relatively  novel  technology and its optimal position in the diagnostic workup of patients is not yet fully understood.  Therefore, understanding the value of imaging of β‐amyloid using PET provides a unique opportunity to achieve 3  major goals: 1) improve the diagnostic workup of people suspected to have AD and their management;  2)  understand  the  natural  history  of AD in  the  pre-symptomatic stage; 3) select people for treatment trials aiming at preventing AD by ensuring a more homogeneous and appropriate enrolment.