[Show abstract][Hide abstract] ABSTRACT: In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI dataset of 86 healthy adults (41 males) with age ranging from 19 to 85 years. We expect the complexity of the resting state fMRI signals measured to be consistent with the Goldberger/Lipsitz model for robustness where healthier (younger) and more robust systems exhibit more complexity in their physiological output and system complexity decrease with age. The mean whole brain fApEn demonstrated significant negative correlation (r = -0.472, p<0.001) with age. In comparison, SampEn produced a non-significant negative correlation (r = -0.099, p = 0.367). fApEn also demonstrated a significant (p < 0.05) negative correlation with age regionally (frontal, parietal, limbic, temporal and cerebellum parietal lobes). There was no significant correlation regionally between the SampEn maps and age. These results support the Goldberger/Lipsitz model for robustness and have shown that fApEn is potentially a sensitive new method for the complexity analysis of fMRI data.
[Show abstract][Hide abstract] ABSTRACT: Brain morphology and cognitive ability change with age. Grey and white matter volumes decrease markedly by the 7th decade of life when cognitive decreases first become readily detectable. As a consequence, the shape complexity of the cortical mantle may also change. The purpose of this study is to examine changes over a five year period in brain structural complexity in late life, and to investigate cognitive correlates of any changes. Brain magnetic resonance images at 1.5 Tesla were acquired from the Aberdeen 1936 Birth Cohort at about ages 68 years (243 participants) and 73 years (148 participants returned). Measures of brain complexity were extracted using fractal dimension (FD) and calculated using the box-counting method. White matter complexity, brain volumes and cognitive performance were measured at both 68 and 73 years. Childhood ability was measured at age 11 using the Moray House Test. FD and brain volume decrease significantly from age 68 to 73 years. Using a multilevel linear modelling approach, we conclude that individual decreases in late life white matter complexity are not associated with differences in executive function but are linked to information processing speed, auditory-verbal learning, and reasoning in specific models-with adjustment for childhood mental ability. A significant association was found after adjustment for age, brain volume and childhood mental ability. Complexity of white matter is associated with higher fluid cognitive ability and, in a longitudinal study, predicts retention of cognitive ability within late life.
[Show abstract][Hide abstract] ABSTRACT: We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.
PLoS ONE 05/2014; 9(5):e95146. DOI:10.1371/journal.pone.0095146 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background:
Cytotoxic chemotherapy remains the main systemic therapy for gastro-oesophageal adenocarcinoma, but resistance to chemotherapy is common, resulting in ineffective and often toxic treatment for patients. Predictive biomarkers for chemotherapy response would increase the probability of successful therapy, but none are currently recommended for clinical use. We used global gene expression profiling of tumour biopsies to identify novel predictive biomarkers for cytotoxic chemotherapy.
Tumour biopsies from patients (n=14) with TNM stage IB–IV gastro-oesophageal adenocarcinomas receiving platinum-based combination chemotherapy were used as a discovery cohort and profiled with Affymetrix ST1.0 Exon Genechips. An independent cohort of patients (n=154) treated with surgery with or without neoadjuvant platinum combination chemotherapy and gastric adenocarcinoma cell lines (n=22) were used for qualification of gene expression profiling results by immunohistochemistry. A cisplatin-resistant gastric cancer cell line, AGS Cis5, and the oesophageal adenocarcinoma cell line, OE33, were used for in vitro validation investigations.
We identified 520 genes with differential expression (Mann–Whitney U, P<0.020) between radiological responding and nonresponding patients. Gene enrichment analysis (DAVID v6.7) was used on this list of 520 genes to identify pathways associated with response and identified the adipocytokine signalling pathway, with higher leptin mRNA associated with lack of radiological response (P=0.011). Similarly, in the independent cohort (n=154), higher leptin protein expression by immunohistochemistry in the tumour cells was associated with lack of histopathological response (P=0.007). Higher leptin protein expression by immunohistochemistry was also associated with improved survival in the absence of neoadjuvant chemotherapy, and patients with low leptin protein-expressing tumours had improved survival when treated by neoadjuvant chemotherapy (P for interaction=0.038). In the gastric adenocarcinoma cell lines, higher leptin protein expression was associated with resistance to cisplatin (P=0.008), but not to oxaliplatin (P=0.988) or 5fluorouracil (P=0.636). The leptin receptor antagonist SHLA increased the sensitivity of AGS Cis5 and OE33 cell lines to cisplatin.
In gastro-oesophageal adenocarcinomas, tumour leptin expression is associated with chemoresistance but a better therapy-independent prognosis. Tumour leptin expression determined by immunohistochemistry has potential utility as a predictive marker of resistance to cytotoxic chemotherapy, and a prognostic marker independent of therapy in gastro-oesophageal adenocarcinoma. Leptin antagonists have been developed for clinical use and leptin and its associated pathways may also provide much needed novel therapeutic targets for gastro-oesophageal adenocarcinoma.
British Journal of Cancer 02/2014; 110(6). DOI:10.1038/bjc.2014.45 · 4.84 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background
Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.
Materials and Methods
We acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer’s disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.
In both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5th percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects.
While more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.
PLoS ONE 01/2014; 9(1). DOI:10.1371/annotation/21fb1298-a831-423f-a247-205641dda40c · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: OBJECTIVE: MRI at 3 T is said to be more accurate than 1.5 T MR, but costs and other practical differences mean that it is unclear which to use. METHODS: We systematically reviewed studies comparing diagnostic accuracy at 3 T with 1.5 T. We searched MEDLINE, EMBASE and other sources from 1 January 2000 to 22 October 2010 for studies comparing diagnostic accuracy at 1.5 and 3 T in human neuroimaging. We extracted data on methodology, quality criteria, technical factors, subjects, signal-to-noise, diagnostic accuracy and errors according to QUADAS and STARD criteria. RESULTS: Amongst 150 studies (4,500 subjects), most were tiny, compared old 1.5 T with new 3 T technology, and only 22 (15 %) described diagnostic accuracy. The 3 T images were often described as "crisper", but we found little evidence of improved diagnosis. Improvements were limited to research applications [functional MRI (fMRI), spectroscopy, automated lesion detection]. Theoretical doubling of the signal-to-noise ratio was not confirmed, mostly being 25 %. Artefacts were worse and acquisitions took slightly longer at 3 T. CONCLUSION: Objective evidence to guide MRI purchasing decisions and routine diagnostic use is lacking. Rigorous evaluation accuracy and practicalities of diagnostic imaging technologies should be the routine, as for pharmacological interventions, to improve effectiveness of healthcare. KEY POINTS : • Higher field strength MRI may improve image quality and diagnostic accuracy. • There are few direct comparisons of 1.5 and 3 T MRI. • Theoretical doubling of the signal-to-noise ratio in practice was only 25 %. • Objective evidence of improved routine clinical diagnosis is lacking. • Other aspects of technology improved images more than field strength.
European Radiology 06/2012; 22(11):2295-2303. DOI:10.1007/s00330-012-2500-8 · 4.01 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To investigate in older adults without dementia the relationships between socioeconomic status (SES) in childhood and magnetic resonance imaging (MRI)-derived brain volume measures typical of brain aging and Alzheimer's disease (AD).
Using a cross-sectional and longitudinal observation approach, we invited volunteers without dementia, all born in 1936, and who were participants in the 1947 Scottish Mental Survey, for MR brain imaging; 249 of 320 (77%) agreed. We measured whole brain and hippocampal volumes and recorded childhood SES history, the number of years of education undertaken, and adult SES history. Mental ability at age 11 years was recorded in 1947 and was also available.
Analysis shows a significant association between childhood SES and hippocampal volume after adjusting for mental ability at age 11 years, adult SES, gender, and education.
A significant association between childhood SES and hippocampal volumes in late life is consistent with the established neurodevelopmental findings that early life conditions have an effect on structural brain development. This remains detectable more than 50 years later.
Annals of Neurology 05/2012; 71(5):653-60. DOI:10.1002/ana.22631 · 9.98 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Fractal measures such as fractal dimension (FD) can quantify the structural complexity of the brain. These have been used in clinical neuroscience to investigate brain development, ageing and in studies of psychiatric and neurological disorders. Here, we examined associations between the FD of white matter and cognitive changes across the life course in the absence of detectable brain disease. The FD was calculated from segmented cerebral white matter MR images in 217 subjects aged about 68years, in whom archived intelligence scores from age 11years were available. Cognitive test scores of fluid and crystallised intelligence were obtained at the time of MR imaging. Significant differences were found (intracranial volume, brain volume, white matter volume and Raven's Progressive Matrices score) between men and women at age 68years and novel associations were found between FD and measures of cognitive change over the life course from age 11 to 68years. Those with greater FD were found to have greater than expected fluid abilities at age 68years than predicted by their childhood intelligence and less cognitive decline from age 11 to 68years. These results are consistent with other reports that FD measures of cortical structural complexity increase across the early life course during maturation of the cerebral cortex and add new data to support an association between FD and cognitive ageing.
[Show abstract][Hide abstract] ABSTRACT: Breast cancers are evolving, multi-scale systems that are characterized by varied complex spatial structures. In this study, we measured the structural characteristics of 33 breast tumours in patients who were to receive neoadjuvant chemotherapy using dynamic contrast enhanced MRI and fractal geometry. The results showed a significant association between fractal measurements and tumour characteristics. The fractal dimension was associated with receptor status (ER and PR) and the fractal fit was associated with response to chemotherapy, measured using a validated pathological response scale, tumour grade and size. This study describes structure measures that may be a consequence of known prognostic factors during the initial and/or maturation phase of tumour growth. These results suggest that measuring tumour structure in this way can predict an individual's response to neoadjuvant therapy and may identify those who will benefit least from neoadjuvant chemotherapy, allowing alternative treatment options to be selected in those patients.
Breast Cancer Research and Treatment 03/2012; 133(3):1199-206. DOI:10.1007/s10549-012-2014-8 · 3.94 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of dementia.
We systematically reviewed published brain image databanks (print literature and Internet) concerned with normal ageing brain structure.
From nine eligible databanks, there appeared to be 944 normal subjects aged ≥60 years. However, many subjects were in more than one databank and not all were fully representative of normal ageing clinical characteristics. Therefore, there were approximately 343 subjects aged ≥60 years with metadata representative of normal ageing, but only 98 subjects were openly accessible. No databank had the range of MR image sequences, e.g. T2*, fluid-attenuated inversion recovery (FLAIR), required to effectively characterise the features of brain ageing. No databank supported random subject retrieval; therefore, manual selection bias and errors may occur in studies that use these subjects as controls. Finally, no databank stored results from statistical analyses of its brain image and metadata that may be validated with analyses of further data.
Brain image databanks require open access, more subjects, metadata, MR image sequences, searchability and statistical results to improve understanding of normal ageing brain structure and diagnoses of dementia. KEY POINTS : • We reviewed databanks with structural MR brain images of normal older people. • Among these nine databanks, 98 normal subjects ≥60 years were openly accessible. • None had all the required sequences, random subject retrieval or statistical results. • More access, subjects, sequences, metadata, searchability and results are needed. • These may improve understanding of normal brain ageing and diagnoses of dementia.
European Radiology 02/2012; 22(7):1385-94. DOI:10.1007/s00330-012-2392-7 · 4.01 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The variation of the native T(1) (T(10)) of different tissues and B(1) transmission-field inhomogeneity at 3 T are major contributors of errors in the quantification of breast dynamic contrast-enhanced MRI. To address these issues, we have introduced new enhancement indices derived from saturation-recovery snapshot-FLASH (SRSF) images. The stability of the new indices, i.e., the SRSF enhancement factor (EF(SRSF)) and its simplified version (EF'(SRSF)) with respect to differences in T(10) and B(1) inhomogeneity was compared against a typical index used in breast dynamic contrast-enhanced MRI, i.e., the enhancement ratio (ER), by using computer simulations. Imaging experiments with Gd-DTPA-doped gel phantoms and a female volunteer were also performed. A lower error was observed in the new indices compared to enhancement ratio in the presence of typical T(10) variation and B(1) inhomogeneity. At changes of relaxation rate (ΔR(1)) of 8 s(-1), the differences between a T(10) of 1266 and 566 ms are <1, 12, and 58%, respectively, for EF(SRSF), EF'(SRSF), and ER, whereas differences of 20, 8, and 51%, respectively, result from a 50% B(1) field reduction at the same ΔR(1). These quantification techniques may be a solution to minimize the effect of T(10) variation and B(1) inhomogeneity on dynamic contrast-enhanced MRI of the breast at 3 T.
Magnetic Resonance in Medicine 02/2012; 67(2):531-40. DOI:10.1002/mrm.23021 · 3.57 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The cognitive reserve hypothesis explains the disparity between clinical and pathological phenotypes and why, in two individuals with the same extent of neuropathology, one may be demented while the other remains cognitively intact. We examined the balance between brain magnetic resonance imaging measures of the two most common pathologies associated with brain ageing, cerebrovascular disease and Alzheimer's disease, and parameters of cerebral reserve in well-characterized participants born in 1936, for whom childhood intelligence is known. Brain magnetic resonance imaging was carried out at 1.5T using fluid attenuation inversion recovery and T(1)-weighted volumetric sequences in 249 participants. Cerebrovascular disease was quantified by measuring brain white matter hyperintensities on fluid attenuation inversion recovery images using Scheltens' scale and Alzheimer's disease was measured from volumetric data using FreeSurfer to extract whole brain volume and hippocampal volumes in turn. The effect of these measures of brain burden on life-long cognitive ageing from the age of 11 to 68 years was compared with the effect of educational attainment and occupational grade using structural equation modelling. Complete brain burden and reserve data were available in 224 participants. We found that educational attainment, but not occupation, has a measurable and positive effect, with a standardized regression weight of +0.23, on late life cognitive ability in people without cognitive impairment aged 68 years, allowing for the influence of childhood intelligence and the two most common subclinical brain pathological burdens in the ageing brain. In addition, we demonstrate that the magnitude of the contribution of education is greater than the negative impact of either neuropathological burden alone, with standardized regression weights of -0.14 for white matter hyperintensities and -0.20 for hippocampal atrophy. This study illustrates how education counteracts the deleterious effects of cerebrovascular disease and Alzheimer's disease and highlights the importance of quantifying cognitive reserve in dementia research.
[Show abstract][Hide abstract] ABSTRACT: Aberrant motor behaviour (AMB) in Alzheimer's disease shares behavioural correlates with obsessive compulsive disorder (OCD). We investigated whether AMB was also comparable in terms of metabolic activity in the orbitofrontal cortex (OFC), an area shown to be hyperactive in OCD. In this study 135 patients meeting research criteria for Alzheimer's disease were identified from a database of patients recruited as part of a phase II drug trial. These patients were assessed using the Neuropsychiatric Inventory, the Alzheimer's disease assessment scale, cognitive subscale and perfusion SPECT performed with 99Tc(m) hexamethylpropyleneamine oxime. Regions of interest were created for orbitofrontal cortices and basal ganglia. In 35 patients with AMB, adjusted tracer uptake was greater in the OFC. This reached statistical significance in right superior, left superior, right medial and left medial orbital gyri (p < 0.05). The association between AMB and hyperactivity in the OFC remained significant after adjusting for the presence of anxiety. These results parallel the OFC hypermetabolism consistently seen in OCD. One model of OCD, proposes that dysfunctional interactions between frontal regions, including the OFC, produce the characteristic symptoms of OCD. The behaviour is though to be brought about by a perceived incompleteness of performing a task and is caused by an error in normal reward signals initiated upon task completion. These finding indicate that AMB in Alzheimer's disease are brought about by the same mechanistic failure.
Behavioural brain research 09/2011; 222(2):375-9. DOI:10.1016/j.bbr.2011.04.003 · 3.03 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We investigated the association between individual differences in cognitive performance in old age and the approximate entropy (ApEn) measured from functional magnetic resonance imaging (fMRI) data acquired from 40 participants of the Aberdeen Birth Cohort 1936 (ABC1936), while undergoing a visual information processing task: inspection time (IT). Participants took a version of the Moray House Test (MHT) No. 12 at age 11, a valid measure of childhood intelligence. The same individuals completed a test of non-verbal reasoning (Raven's Standard Progressive Matrices [RPM]) aged about 68 years. The IT, MHT and RPM scores were used as indicators of cognitive performance. Our results show that higher regional signal entropy is associated with better cognitive performance. This finding was independent of ability in childhood but not independent of current cognitive ability. ApEn is used for the first time to identify a potential source of individual differences in cognitive ability using fMRI data.