Subregional neuroanatomical change as a biomarker for Alzheimer's disease

Department of Neurosciences, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 12/2009; 106(49):20954-9. DOI: 10.1073/pnas.0906053106
Source: PubMed


Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.


Available from: Anders M Dale
    • "Research projects and clinical practice often demand simultaneous application of structural and functional images by two or more imaging modalities [6] [7] [8]. In these cases special matching and proper aligning of two or more images are required. "
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    ABSTRACT: Clinical practice often requires simultaneous information obtained by two different imaging modalities. Registration algorithms are commonly used for this purpose. Automated procedures are very helpful in cases when the same kind of registration has to be performed on images of a high number of subjects. Radiotherapists would prefer to use the best automated method to assist therapy planning, however there are not accepted procedures for ranking the different registration algorithms. We were interested in developing a method to measure the population level performance of CT-MRI registration algorithms by a parameter of values in the [0,1] interval. Pairs of CT and MRI images were collected from 1051 subjects. Results of an automated registration were corrected manually until a radiologist and a neurosurgeon expert both accepted the result as good. This way 1051 registered MRI images were produced by the same pair of experts to be used as gold standards for the evaluation of the performance of other registration algorithms. Pearson correlation coefficient, mutual information, normalized mutual information, Kullback-Leibler divergence, L1 norm and square L2 norm (dis)similarity measures were tested for sensitivity to indicate the extent of (dis)similarity of a pair of individual mismatched images. The square Hellinger distance proved suitable to grade the performance of registration algorithms at population level providing the developers with a valuable tool to rank algorithms. The developed procedure provides an objective method to find the registration algorithm performing the best on the population level out of newly constructed or available preselected ones. Copyright © 2015. Published by Elsevier GmbH.
    Zeitschrift für Medizinische Physik 08/2015; DOI:10.1016/j.zemedi.2015.07.001 · 2.96 Impact Factor
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    • "A variety of imaging modalities, including structural and functional ones, has shown distinctive changes in the brains of patients within the AD spectrum [11]. Overt dementia presents marked atrophy in the medial temporal lobe structures [12] [13] along with progressive thinning of the parietotemporal and frontal cortices [14] [15]. The pattern observed in MCI is similar, but to a lesser degree, to that of AD. "
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    ABSTRACT: The aim of this study was to characterize the neuropsychological and neuroimaging profiles of mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients, and to study the magnitude of the differences by comparing both outcomes with healthy subjects in a cross-sectional manner. Five hundred and thirty-five subjects (356 cognitively normal adults (CONT), 79 MCI, and 100 AD) were assessed with the NEURONORMA neuropsychological battery. Thirty CONT, 23 MCI, and 23 AD subjects from this sample were included in the neuroimaging substudy. Patients' raw cognitive scores were converted to age and education-adjusted scaled ones (range 2-18) using co-normed reference values. Medians were plotted to examine the cognitive profile. MRIs were processed by means of FreeSurfer. Effect size indices (Cohen's d) were calculated in order to compare the standardized differences between patients and healthy subjects. Graphically, the observed cognitive profiles for MCI and AD groups produced near to parallel lines. Verbal and visual memories were the most impaired domains in both groups, followed by executive functions and linguistic/semantic ones. The largest effect size between AD and cognitively normal subjects was found for the FCSRT (d = 4.05, AD versus CONT), which doubled the value obtained by the best MRI measure, the right hippocampus (d = 1.65, AD versus CONT). Our results support the notion of a continuum in cognitive profile between MCI and AD. Neuropsychological outcomes, in particular the FCSRT, are better than neuroimaging ones at detecting differences among subjects.
    Journal of Alzheimer's disease: JAD 04/2014; 41(3). DOI:10.3233/JAD-132186 · 4.15 Impact Factor
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    • "However, for the individual patient the presence of focal injury (contusions, hemorrhages) also plays a significant role for outcome, but it was beyond the scope of the present paper to evaluate the interaction between focal injuries and the atrophy in different brain structures. It should be noted that the volume change measures obtained using independent NeuroQuant segmentations would not be expected to have the spatial specificity and power to detect subtle change that many across time point registration methods might provide (Holland et al., 2009; Fox et al., 2001; Thompson et al., 2004). On the other hand, NeuroQuant has previously been shown to have results comparable to that of hand segmentation of subregional volumes by anatomical experts (Brewer et al., 2009), and thus provides an identifiable and translatable measure of structure volume. "
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    ABSTRACT: The objectives of this prospective study in 62 moderate–severe TBI patients were to investigate volume change in cortical gray matter (GM), hippocampus, lenticular nucleus, lobar white matter (WM), brainstem and ventricles using a within subject design and repeated MRI in the early phase (1–26 days) and 3 and 12 months postinjury and to assess changes in GM apparent diffusion coefficient (ADC) in normal appearing tissue in the cortex, hippocampus and brainstem. The impact of Glasgow Coma Scale (GCS) score at admission, duration of post-traumatic amnesia (PTA), and diffusion axonal injury (DAI) grade on brain volumes and ADC values over time was assessed. Lastly, we determined if MRI-derived brain volumes from the 3-month scans provided additional, significant predictive value to 12-month outcome classified with the Glasgow Outcome Scale—Extended after adjusting for GCS, PTA and age.
    Clinical neuroimaging 03/2014; 5:128-40. DOI:10.1016/j.nicl.2014.03.012 · 2.53 Impact Factor
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