Benign breast disease and breast cancer risk in African women: a case-control study

PURPOSE

To examine the association between benign breast disease (BBD) and breast cancer (BC) in a heterogeneous population of African women.

METHODS

BC cases and controls were enrolled in three sub-Saharan African countries, Nigeria, Cameroon, and Uganda, between 1998 and 2018. Multivariable logistic regression was used to test the association between BBD and BC. Risk factors dually associated with BBD and BC were selected. Using a parametric mediation analysis model, we assessed if selected BC risk factors were mediated by BBD.

RESULTS

Of 6,274 participants, 55.6% (3,478) were breast cancer cases. 360 (5.7%) self-reported BBD. Fibroadenoma (46.8%) was the most commonly reported BBD. Women with a self-reported history of BBD had greater odds of developing BC than those without (adjusted odds ratio [aOR] 1.47, 95% CI 1.13-1.91). Biopsy-confirmed BBD was associated with BC (aOR 2.25, 95% CI 1.26-4.02). BBD did not significantly mediate the effects of any of the selected BC risk factors.

CONCLUSIONS

In this study, BBD was associated with BC and did not significantly mediate the effects of selected BC risk factors.

External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population

Purpose

To externally evaluate a mammography-based deep learning (DL) model (Mirai) in a high-risk racially diverse population and compare its performance with other mammographic measures.

Materials and Methods

A total of 6435 screening mammograms in 2096 female patients (median age, 56.4 years ± 11.2 [SD]) enrolled in a hospital-based case-control study from 2006 to 2020 were retrospectively evaluated. Pathologically confirmed breast cancer was the primary outcome. Mirai scores were the primary predictors. Breast density and Breast Imaging Reporting and Data System (BI-RADS) assessment categories were comparative predictors. Performance was evaluated using area under the receiver operating characteristic curve (AUC) and concordance index analyses.

Results

Mirai achieved 1- and 5-year AUCs of 0.71 (95% CI: 0.68, 0.74) and 0.65 (95% CI: 0.64, 0.67), respectively. One-year AUCs for nondense versus dense breasts were 0.72 versus 0.58 (P = .10). There was no evidence of a difference in near-term discrimination performance between BI-RADS and Mirai (1-year AUC, 0.73 vs 0.68; P = .34). For longer-term prediction (2-5 years), Mirai outperformed BI-RADS assessment (5-year AUC, 0.63 vs 0.54; P < .001). Using only images of the unaffected breast reduced the discriminatory performance of the DL model (P < .001 at all time points), suggesting that its predictions are likely dependent on the detection of ipsilateral premalignant patterns.

Conclusion

A mammography DL model showed good performance in a high-risk external dataset enriched for African American patients, benign breast disease, and BRCA mutation carriers, and study findings suggest that the model performance is likely driven by the detection of precancerous changes.Keywords: Breast, Cancer, Computer Applications, Convolutional Neural Network, Deep Learning Algorithms, Informatics, Epidemiology, Machine Learning, Mammography, Oncology, Radiomics Supplemental material is available for this article. © RSNA, 2023See also commentary by Kontos and Kalpathy-Cramer in this issue.

Benign breast disease and breast cancer risk in African women: A case-control study

Purpose

To examine the association between benign breast disease (BBD) and breast cancer (BC) in a heterogeneous population of African women.

Methods

BC cases and matched controls were enrolled in three sub-Saharan African countries, Nigeria Cameroon, and Uganda, between 1998-2018. Multivariable logistic regression was used to test the association between BBD and BC. Risk factors dually associated with BBD and BC were selected. Using a parametric mediation analysis model, we assessed if selected BC risk factors were mediated by BBD.

Results

Of 6418 participants, 55.7% (3572) were breast cancer cases. 360 (5.7%) self-reported BBD. Fibroadenoma (46.8%) was the most reported BBD. Women with a self-reported history of BBD had greater odds of developing BC than those without (adjusted odds ratio [aOR] = 1.47, 95% CI: 1.13-1.91). Biopsy-confirmed BBD was associated with BC (aOR = 3.11, 95% CI: 1.78-5.44). BBD did not significantly mediate the effects of any of the selected BC risk factors.

Conclusions

In this study, BBD was associated with BC and did not significantly mediate the effects of selected BC risk factors.

Sleep quality, perivascular spaces and brain health markers in ageing - A longitudinal study in the Lothian Birth Cohort 1936

BACKGROUND

Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s.

METHOD

We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life.

RESULTS

Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (β = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = -0.20, P < 0.001), and with increasing white matter damage metric (β = -0.122, P = 0.018) and faster WMH growth (β = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (β = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (β = -0.16, P = 0.012) and increasing white matter damage metric (β = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes.

CONCLUSION

Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.

Polygenic Architecture of Human Neuroanatomical Diversity

We analyzed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26 000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r ~ 0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (~51%) captured ~1.5 times more genetic variance than the rest, and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF <5% captured <one fourth of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG ~ 0.45. Genetic correlations were similar to phenotypic and environmental correlations; however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available athttps://github.com/neuroanatomy/genomic-architecture.

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Sleep and brain morphological changes in the eighth decade of life

OBJECTIVE

Sleep is important for brain health. We analysed associations between usual sleep habits and magnetic resonance imaging (MRI) markers of neurodegeneration (brain atrophy), vascular damage (white matter hyperintensities, WMH) and waste clearance (perivascular spaces, PVS) in older community-dwelling adults.

METHOD

We collected self-reported usual sleep duration, quality and medical histories from the Lothian Birth Cohort 1936 (LBC1936) age 76 years and performed brain MRI. We calculated sleep efficiency, measured WMH and brain volumes, quantified PVS, and assessed associations between sleep measures and brain markers in multivariate models adjusted for demographic and medical history variables.

RESULTS

In 457 subjects (53% males, mean age 76 ± 0.65 years), we found: brain and white matter loss with increased weekend daytime sleep (β = -0.114, P = 0.03; β = -0.122, P = 0.007 respectively), white matter loss with less efficient sleep (β = 0.132, P = 0.011) and PVS increased with interrupted sleep (OR 1.84 95% CI, P = 0.025).

CONCLUSION

Cross-sectional associations of sleep parameters with brain atrophy and more PVS suggest adverse relationships between usual sleep habits and brain health in older people that should be evaluated longitudinally.

Identification of the presence of ischaemic stroke lesions by means of texture analysis on brain magnetic resonance images

•

Radiomics in conventionally segmented tissues can identify MRI scans that had a stroke.

•

Patient’s advanced age can negatively influence classification results.

•

Feature selection and stroke subtype influence but do not determine accuracy.

•

Stroke subtype cannot be ascertained from texture analysis in brain tissues.

Background

The differential quantification of brain atrophy, white matter hyperintensities (WMH) and stroke lesions is important in studies of stroke and dementia. However, the presence of stroke lesions is usually overlooked by automatic neuroimage processing methods and the-state-of-the-art deep learning schemes, which lack sufficient annotated data. We explore the use of radiomics in identifying whether a brain magnetic resonance imaging (MRI) scan belongs to an individual that had a stroke or not.

Materials and methods

We used 1800 3D sets of MRI data from three prospective studies: one of stroke mechanisms and two of cognitive ageing, evaluated 114 textural features in WMH, cerebrospinal fluid, deep grey and normal-appearing white matter, and attempted to classify the scans using a random forest and support vector machine classifiers with and without feature selection. We evaluated the discriminatory power of each feature independently in each population and corrected the result against Type 1 errors. We also evaluated the influence of clinical parameters in the classification results.

Results

Subtypes of ischaemic strokes (i.e. lacunar vs. cortical) cannot be discerned using radiomics, but the presence of a stroke-type lesion can be ascertained with accuracies ranging from 0.7 < AUC < 0.83. Feature selection, tissue type, stroke subtype and MRI sequence did not seem to determine the classification results. From all clinical variables evaluated, age correlated with the proportion of images classified correctly using either different or the same descriptors (Pearson r = 0.31 and 0.39 respectively, p < 0.001).

Conclusions

Texture features in conventionally automatically segmented tissues may help in the identification of the presence of previous stroke lesions on an MRI scan, and should be taken into account in transfer learning strategies of the-state-of-the-art deep learning schemes.

Remission of Human Type 2 Diabetes Requires Decrease in Liver and Pancreas Fat Content but Is Dependent upon Capacity for β Cell Recovery

The Diabetes Remission Clinical Trial reported return and persistence of non-diabetic blood glucose control in 46% of people with type 2 diabetes of up to 6 years duration. Detailed metabolic studies were performed on a subgroup (intervention, n = 64; control, n = 26). In the intervention group, liver fat content decreased (16.0% ± 1.3% to 3.1% ± 0.5%, p < 0.0001) immediately after weight loss. Similarly, plasma triglyceride and pancreas fat content decreased whether or not glucose control normalized. Recovery of first-phase insulin response (0.04[-0.05-0.32] to 0.11[0.0005-0.51] nmol/min/m², p < 0.0001) defined those who returned to non-diabetic glucose control and this was durable at 12 months (0.11[0.005-0.81] nmol/min/m², p = 0.0001). Responders were similar to non-responders at baseline but had shorter diabetes duration (2.7 ± 0.3 versus 3.8 ± 0.4 years; p = 0.02). This study demonstrates that β cell ability to recover long-term function persists after diagnosis, changing the previous paradigm of irreversible loss of β cell function in type 2 diabetes.

Longitudinal serum S100β and brain aging in the Lothian Birth Cohort 1936

Elevated serum and cerebrospinal fluid concentrations of S100β, a protein predominantly found in glia, are associated with intracranial injury and neurodegeneration, although concentrations are also influenced by several other factors. The longitudinal association between serum S100β concentrations and brain health in nonpathological aging is unknown. In a large group (baseline N = 593; longitudinal N = 414) of community-dwelling older adults at ages 73 and 76 years, we examined cross-sectional and parallel longitudinal changes between serum S100β and brain MRI parameters: white matter hyperintensities, perivascular space visibility, white matter fractional anisotropy and mean diffusivity (MD), global atrophy, and gray matter volume. Using bivariate change score structural equation models, correcting for age, sex, diabetes, and hypertension, higher S100β was cross-sectionally associated with poorer general fractional anisotropy (r = -0.150, p = 0.001), which was strongest in the anterior thalamic (r = -0.155, p < 0.001) and cingulum bundles (r = -0.111, p = 0.005), and survived false discovery rate correction. Longitudinally, there were no significant associations between changes in brain imaging parameters and S100β after false discovery rate correction. These data provide some weak evidence that S100β may be an informative biomarker of brain white matter aging.

Coupled changes in hippocampal structure and cognitive ability in later life

Introduction

The hippocampus plays an important role in cognitive abilities which often decline with advancing age.

Methods

In a longitudinal study of community-dwelling adults, we investigated whether there were coupled changes in hippocampal structure and verbal memory, working memory, and processing speed between the ages of 73 (N = 655) and 76 years (N = 469). Hippocampal structure was indexed by hippocampal volume, hippocampal volume as a percentage of intracranial volume (H_ICV), fractional anisotropy (FA), mean diffusivity (MD), and longitudinal relaxation time (T1).

Results

Mean levels of hippocampal volume, H_ICV, FA, T1, and all three cognitive abilities domains decreased, whereas MD increased, from age 73 to 76. At baseline, higher hippocampal volume was associated with better working memory and verbal memory, but none of these correlations survived correction for multiple comparisons. Higher FA, lower MD, and lower T1 at baseline were associated with better cognitive abilities in all three domains; only the correlation between baseline hippocampal MD and T1, and change in the three cognitive domains, survived correction for multiple comparisons. Individuals with higher hippocampal MD at age 73 experienced a greater decline in all three cognitive abilities between ages 73 and 76. However, no significant associations with changes in cognitive abilities were found with hippocampal volume, FA, and T1 measures at baseline. Similarly, no significant associations were found between cognitive abilities at age 73 and changes in the hippocampal MRI biomarkers between ages 73 and 76.

Conclusion

Our results provide evidence to better understand how the hippocampus ages in healthy adults in relation to the cognitive domains in which it is involved, suggesting that better hippocampal MD at age 73 predicts less relative decline in three important cognitive domains across the next 3 years. It can potentially assist in diagnosing early stages of aging-related neuropathologies, because in some cases, accelerated decline could predict pathologies.

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.

Risk and protective factors for structural brain ageing in the eighth decade of life

Individuals differ markedly in brain structure, and in how this structure degenerates during ageing. In a large sample of human participants (baseline n = 731 at age 73 years; follow-up n = 488 at age 76 years), we estimated the magnitude of mean change and variability in changes in MRI measures of brain macrostructure (grey matter, white matter, and white matter hyperintensity volumes) and microstructure (fractional anisotropy and mean diffusivity from diffusion tensor MRI). All indices showed significant average change with age, with considerable heterogeneity in those changes. We then tested eleven socioeconomic, physical, health, cognitive, allostatic (inflammatory and metabolic), and genetic variables for their value in predicting these differences in changes. Many of these variables were significantly correlated with baseline brain structure, but few could account for significant portions of the heterogeneity in subsequent brain change. Physical fitness was an exception, being correlated both with brain level and changes. The results suggest that only a subset of correlates of brain structure are also predictive of differences in brain ageing.

Associations between hippocampal morphology, diffusion characteristics, and salivary cortisol in older men

High, unabated glucocorticoid (GC) levels are thought to selectively damage certain tissue types. The hippocampus is thought to be particularly susceptible to such effects, and though findings from animal models and human patients provide some support for this hypothesis, evidence for associations between elevated GCs and lower hippocampal volumes in older age (when GC levels are at greater risk of dysregulation) is inconclusive. To address the possibility that the effects of GCs in non-pathological ageing may be too subtle for gross volumetry to reliably detect, we analyse associations between salivary cortisol (diurnal and reactive measures), hippocampal morphology and diffusion characteristics in 88 males, aged ∼73 years. However, our results provide only weak support for this hypothesis. Though nominally significant peaks in morphology were found in both hippocampi across all salivary cortisol measures (standardised β magnitudes<0.518, p_uncorrected>0.0000003), associations were both positive and negative, and none survived false discovery rate correction. We found one single significant association (out of 12 comparisons) between a general measure of hippocampal diffusion and reactive cortisol slope (β=0.290, p=0.008) which appeared to be driven predominantly by mean diffusivity but did not survive correction for multiple testing. The current data therefore do not clearly support the hypothesis that elevated cortisol levels are associated with subtle variations in hippocampal shape or microstructure in non-pathological older age.

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Associations between education and brain structure at age 73 years, adjusted for age 11 IQ

Objective:

To investigate how associations between education and brain structure in older age were affected by adjusting for IQ measured at age 11.

Methods:

We analyzed years of full-time education and measures from an MRI brain scan at age 73 in 617 community-dwelling adults born in 1936. In addition to average and vertex-wise cortical thickness, we measured total brain atrophy and white matter tract fractional anisotropy. Associations between brain structure and education were tested, covarying for sex and vascular health; a second model also covaried for age 11 IQ.

Results:

The significant relationship between education and average cortical thickness (β = 0.124, p = 0.004) was reduced by 23% when age 11 IQ was included (β = 0.096, p = 0.041). Initial associations between longer education and greater vertex-wise cortical thickness were significant in bilateral temporal, medial-frontal, parietal, sensory, and motor cortices. Accounting for childhood intelligence reduced the number of significant vertices by >90%; only bilateral anterior temporal associations remained. Neither education nor age 11 IQ was significantly associated with total brain atrophy or tract-averaged fractional anisotropy.

Conclusions:

The association between years of education and brain structure ≈60 years later was restricted to cortical thickness in this sample; however, the previously reported associations between longer education and a thicker cortex are likely to be overestimates in terms of both magnitude and distribution. This finding has implications for understanding, and possibly ameliorating, life-course brain health.

3D shape analysis of the brain's third ventricle using a midplane encoded symmetric template model

BACKGROUND

Structural changes of the brain's third ventricle have been acknowledged as an indicative measure of the brain atrophy progression in neurodegenerative and endocrinal diseases. To investigate the ventricular enlargement in relation to the atrophy of the surrounding structures, shape analysis is a promising approach. However, there are hurdles in modeling the third ventricle shape. First, it has topological variations across individuals due to the inter-thalamic adhesion. In addition, as an interhemispheric structure, it needs to be aligned to the midsagittal plane to assess its asymmetric and regional deformation.

METHOD

To address these issues, we propose a model-based shape assessment. Our template model of the third ventricle consists of a midplane and a symmetric mesh of generic shape. By mapping the template's midplane to the individuals' brain midsagittal plane, we align the symmetric mesh on the midline of the brain before quantifying the third ventricle shape. To build the vertex-wise correspondence between the individual third ventricle and the template mesh, we employ a minimal-distortion surface deformation framework. In addition, to account for topological variations, we implement geometric constraints guiding the template mesh to have zero width where the inter-thalamic adhesion passes through, preventing vertices crossing between left and right walls of the third ventricle. The individual shapes are compared using a vertex-wise deformity from the symmetric template.

RESULTS

Experiments on imaging and demographic data from a study of aging showed that our model was sensitive in assessing morphological differences between individuals in relation to brain volume (i.e. proxy for general brain atrophy), gender and the fluid intelligence at age 72. It also revealed that the proposed method can detect the regional and asymmetrical deformation unlike the conventional measures: volume (median 1.95ml, IQR 0.96ml) and width of the third ventricle. Similarity measures between binary masks and the shape model showed that the latter reconstructed shape details with high accuracy (Dice coefficient ≥0.9, mean distance 0.5mm and Hausdorff distance 2.7mm).

CONCLUSIONS

We have demonstrated that our approach is suitable to morphometrical analyses of the third ventricle, providing high accuracy and inter-subject consistency in the shape quantification. This shape modeling method with geometric constraints based on anatomical landmarks could be extended to other brain structures which require a consistent measurement basis in the morphometry.

Vascular risk factors and progression of white matter hyperintensities in the Lothian Birth Cohort 1936

We aimed to determine associations between multiple vascular risk factors (VRF) at ∼73 years and progression of white matter hyperintensities (WMH) from ∼73 years to ∼76 years. We calculated correlations and generalized estimating equation models of a comprehensive range of VRF at 73 years and change in WMH volume from 73 years to 76 years. Higher systolic (rho = 0.126, p = 0.009) and diastolic (rho = 0.120, p = 0.013) blood pressure at 73 years were significant predictors for greater WMH volume at 76 years in a simple correlation model. However, neither measured blood pressure nor self-reported hypertension at 73 years was significant predictors of WMH volume change in a fully adjusted model which accounted for initial WMH volume at 73 years. Lower high-density lipoprotein cholesterol (beta = −0.15 % intracranial, −1.80 mL; p < 0.05) and current smoking (beta = 0.43 % intracranial, 5.49 mL; p < 0.05) were the only significant VRF predictors of WMH volume change from 73 years to 76 years. A focus on smoking cessation and lipid lowering, not just antihypertensives, may lead to a reduction in WMH growth in the eighth decade of life.

Progression of White Matter Disease and Cortical Thinning Are Not Related in Older Community-Dwelling Subjects

Background and Purpose—

We assessed cross-sectional and longitudinal relationships between whole brain white matter hyperintensity (WMH) volume and regional cortical thickness.

Methods—

We measured WMH volume and regional cortical thickness on magnetic resonance imaging at ≈73 and ≈76 years in 351 community-dwelling subjects from the Lothian Birth Cohort 1936. We used multiple linear regression to calculate cross-sectional and longitudinal associations between regional cortical thickness and WMH volume controlling for age, sex, Mini Mental State Examination, education, intelligence quotient at age 11, and vascular risk factors.

Results—

We found cross-sectional associations between WMH volume and cortical thickness within and surrounding the Sylvian fissure at 73 and 76 years (rho=−0.276, Q=0.004). However, we found no significant longitudinal associations between (1) baseline WMH volume and change in cortical thickness; (2) baseline cortical thickness and change in WMH volume; or (3) change in WMH volume and change in cortical thickness.

Conclusions—

Our results show that WMH volume and cortical thinning both worsen with age and are associated cross-sectionally within and surrounding the Sylvian fissure. However, changes in WMH volume and cortical thinning from 73 to 76 years are not associated longitudinally in these relatively healthy older subjects. The underlying cause(s) of WMH growth and cortical thinning have yet to be fully determined.

Brain volumetric changes and cognitive ageing during the eighth decade of life

Later‐life changes in brain tissue volumes—decreases in the volume of healthy grey and white matter and increases in the volume of white matter hyperintensities (WMH)—are strong candidates to explain some of the variation in ageing‐related cognitive decline. We assessed fluid intelligence, memory, processing speed, and brain volumes (from structural MRI) at mean age 73 years, and at mean age 76 in a narrow‐age sample of older individuals (n = 657 with brain volumetric data at the initial wave, n = 465 at follow‐up). We used latent variable modeling to extract error‐free cognitive levels and slopes. Initial levels of cognitive ability were predictive of subsequent brain tissue volume changes. Initial brain volumes were not predictive of subsequent cognitive changes. Brain volume changes, especially increases in WMH, were associated with declines in each of the cognitive abilities. All statistically significant results were modest in size (absolute r‐values ranged from 0.114 to 0.334). These results build a comprehensive picture of macrostructural brain volume changes and declines in important cognitive faculties during the eighth decade of life. Hum Brain Mapp 36:4910–4925, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc

Voxel-based analysis in neuroferritinopathy expands the phenotype and determines radiological correlates of disease severity

Neuroferritinopathy is an autosomal dominant adult-onset movement disorder which occurs due to mutations in the ferritin light chain gene (FTL). Extensive iron deposition and cavitation are observed post-mortem in the basal ganglia, but whether more widespread pathological changes occur, and whether they correlate with disease severity is unknown. 3D-T1w and quantitative T2 whole brain MRI scans were performed in 10 clinically symptomatic patients with the 460InsA FTL mutation and 10 age-matched controls. Voxel-based morphometry (VBM) and voxel-based relaxometry (VBR) were subsequently performed. Clinical assessment using the Unified Dystonia Rating Scale (UDRS) and Unified Huntington's Disease Rating Scale (UHDRS) was undertaken in all patients. VBM detected significant tissue changes within the substantia nigra, midbrain and dentate together with significant cerebellar atrophy in patients (FWE, p < 0.05). Iron deposition in the caudate head and cavitation in the lateral globus pallidus correlated with UDRS score (p < 0.001). There were no differences between groups with VBR. Our data show that progressive iron accumulation in the caudate nucleus, and cavitation of the globus pallidus correlate with disease severity in neuroferritinopathy. We also confirm sub-clinical cerebellar atrophy as a feature of the disease. We suggest that VBM is an effective technique to detect regions of iron deposition and cavitation, with potential wider utility to determine radiological markers of disease severity for all NBIA disorders.

Common genetic variants influence human subcortical brain structures

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

White matter hyperintensities and normal-appearing white matter integrity in the aging brain

White matter hyperintensities (WMH) of presumed vascular origin are a common finding in brain magnetic resonance imaging of older individuals and contribute to cognitive and functional decline. It is unknown how WMH form, although white matter degeneration is characterized pathologically by demyelination, axonal loss, and rarefaction, often attributed to ischemia. Changes within normal-appearing white matter (NAWM) in subjects with WMH have also been reported but have not yet been fully characterized. Here, we describe the in vivo imaging signatures of both NAWM and WMH in a large group of community-dwelling older people of similar age using biomarkers derived from magnetic resonance imaging that collectively reflect white matter integrity, myelination, and brain water content. Fractional anisotropy (FA) and magnetization transfer ratio (MTR) were significantly lower, whereas mean diffusivity (MD) and longitudinal relaxation time (T1) were significantly higher, in WMH than NAWM (p < 0.0001), with MD providing the largest difference between NAWM and WMH. Receiver operating characteristic analysis on each biomarker showed that MD differentiated best between NAWM and WMH, identifying 94.6% of the lesions using a threshold of 0.747 × 10⁻⁹ m²s⁻¹ (area under curve, 0.982; 95% CI, 0.975–0.989). Furthermore, the level of deterioration of NAWM was strongly associated with the severity of WMH, with MD and T1 increasing and FA and MTR decreasing in NAWM with increasing WMH score, a relationship that was sustained regardless of distance from the WMH. These multimodal imaging data indicate that WMH have reduced structural integrity compared with surrounding NAWM, and MD provides the best discriminator between the 2 tissue classes even within the mild range of WMH severity, whereas FA, MTR, and T1 only start reflecting significant changes in tissue microstructure as WMH become more severe.

White matter correlates of cognitive dysfunction after mild traumatic brain injury

OBJECTIVE

To relate neurophysiologic changes after mild/moderate traumatic brain injury to cognitive deficit in a longitudinal diffusion tensor imaging investigation.

METHODS

Fifty-three patients were scanned an average of 6 days postinjury (range = 1-14 days). Twenty-three patients were rescanned 1 year later. Thirty-three matched control subjects were recruited. At the time of scanning, participants completed cognitive testing. Tract-Based Spatial Statistics was used to conduct voxel-wise analysis on diffusion changes and to explore regressions between diffusion metrics and cognitive performance.

RESULTS

Acutely, increased axial diffusivity drove a fractional anisotropy (FA) increase, while decreased radial diffusivity drove a negative regression between FA and Verbal Letter Fluency across widespread white matter regions, but particularly in the ascending fibers of the corpus callosum. Raised FA is hypothesized to be caused by astrogliosis and compaction of axonal neurofilament, which would also affect cognitive functioning. Chronically, FA was decreased, suggesting myelin sheath disintegration, but still regressed negatively with Verbal Letter Fluency in the anterior forceps.

CONCLUSIONS

Acute mild/moderate traumatic brain injury is characterized by increased tissue FA, which represents a clear neurobiological link between cognitive dysfunction and white matter injury after mild/moderate injury.

Blood pressure, internal carotid artery flow parameters, and age-related white matter hyperintensities

White matter hyperintensities (WMH) are associated with hypertension. We examined interactions among blood pressure (BP), internal carotid artery (ICA) flow velocity parameters, and WMH. We obtained BP measurements from 694 community-dwelling subjects at mean ages 69.6 (±0.8) years and again at 72.6 (±0.7) years, plus brain MRI and ICA ultrasound at age 73±1 years. Diastolic and mean BP decreased and pulse pressure increased, but systolic BP did not change between 70 and 73 years. Multiple linear regression, corrected for vascular disease and risk factors, showed that WMH at the age of 73 years were associated with history of hypertension (β=0.13; P<0.001) and with BP at the age of 70 years (systolic β=0.08, mean β=0.09, diastolic β=0.08; all P<0.05); similar but attenuated associations were seen for BP at the age of 73 years. Lower diastolic BP and higher pulse pressure were associated with higher ICA pulsatility index at the age 73 years (diastolic BP age 70 years: standardized β=-0.24, P<0.001; pulse pressure age 70 years: β=0.19, P<0.001). WMH were associated with higher ICA pulsatility index (β=0.13; P=0.002) after adjusting for BP and correction for multiple testing. Therefore, falling diastolic BP and increased pulse pressure are associated with increased ICA pulsatility index, which in turn is associated with WMH. This suggests that hypertension and WMH may either associate indirectly because hypertension increases arterial stiffness that leads to WMH over time, or coassociate through advancing age and stiffer vessels, or both. Reducing vascular stiffness may reduce WMH progression and should be tested in randomized trials, in addition to testing antihypertensive therapy.

Circulating inflammatory markers are associated with magnetic resonance imaging-visible perivascular spaces but not directly with white matter hyperintensities

BACKGROUND AND PURPOSE

White matter hyperintensities (WMH) and perivascular spaces (PVS) are features of small vessel disease, found jointly on MRI of older people. Inflammation is a prominent pathological feature of small vessel disease. We examined the association between inflammation, PVS, and WMH in the Lothian Birth Cohort 1936 (N=634).

METHODS

We measured plasma fibrinogen, C-reactive protein, and interleukin-6 and rated PVS in 3 brain regions. We measured WMH volumetrically and visually using the Fazekas scale. We derived latent variables for PVS, WMH, and Inflammation from measured PVS, WMH, and inflammation markers and modelled associations using structural equation modelling.

RESULTS

After accounting for age, sex, stroke, and vascular risk factors, PVS were significantly associated with WMH (β=0.47; P<0.0001); Inflammation was weakly but significantly associated with PVS (β=0.12; P=0.048), but not with WMH (β=0.02; P=NS).

CONCLUSIONS

Circulating inflammatory markers are weakly associated with MR-visible PVS, but not directly with WMH. Longitudinal studies should examine whether visible PVS predate WMH progression and whether inflammation modulators can prevent small vessel disease.

Quantitative multi-modal MRI of the Hippocampus and cognitive ability in community-dwelling older subjects

Hippocampal structural integrity is commonly quantified using volumetric measurements derived from brain magnetic resonance imaging (MRI). Previously reported associations with cognitive decline have not been consistent. We investigate hippocampal integrity using quantitative MRI techniques and its association with cognitive abilities in older age.

Participants from the Lothian Birth Cohort 1936 underwent brain MRI at mean age 73 years. Longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) were measured in the hippocampus. General factors of fluid-type intelligence (g), cognitive processing speed (speed) and memory were obtained at age 73 years, as well as childhood IQ test results at age 11 years. Amongst 565 older adults, multivariate linear regression showed that, after correcting for ICV, gender and age 11 IQ, larger left hippocampal volume was significantly associated with better memory ability (β = .11, p = .003), but not with speed or g. Using quantitative MRI and after correcting for multiple testing, higher T1 and MD were significantly associated with lower scores of g (β range = −.11 to −.14, p < .001), speed (β range = −.15 to −.20, p < .001) and memory (β range = −.10 to −.12, p < .001). Higher MTR and FA in the hippocampus were also significantly associated with higher scores of g (β range = .17 to .18, p < .0001) and speed (β range = .10 to .15, p < .0001), but not memory.

Quantitative multi-modal MRI assessments were more sensitive at detecting cognition-hippocampal integrity associations than volumetric measurements, resulting in stronger associations between MRI biomarkers and age-related cognition changes.

Associations between level and change in physical function and brain volumes

BACKGROUND

Higher levels of fitness or physical function are positively associated with cognitive outcomes but the potential underlying mechanisms via brain structure are still to be elucidated in detail. We examined associations between brain structure and physical function (contemporaneous and change over the previous three years) in community-dwelling older adults.

METHODOLOGY/PRINCIPAL FINDINGS

Participants from the Lothian Birth Cohort 1936 (N=694) underwent brain MRI at age 73 years to assess intracranial volume, and the volumes of total brain tissue, ventricles, grey matter, normal-appearing white matter, and white matter lesions. At ages 70 and 73, physical function was assessed by 6-meter walk, grip strength, and forced expiratory volume. A summary 'physical function factor' was derived from the individual measures using principal components analysis. Performance on each individual physical function measure declined across the three year interval (p<0.001). Higher level of physical function at ages 70 and 73 was associated with larger total brain tissue and white matter volumes, and smaller ventricular and white matter lesion volumes (standardized β ranged in magnitude from 0.07 to 0.17, p<0.001 to 0.034). Decline in physical function from age 70 to 73 was associated with smaller white matter volume (0.08, p<0.01, though not after correction for multiple testing), but not with any other brain volumetric measurements.

CONCLUSIONS/SIGNIFICANCE

Physical function was related to brain volumes in community-dwelling older adults: declining physical function was associated with less white matter tissue. Further study is required to explore the detailed mechanisms through which physical function might influence brain structure, and vice versa.

Differentiation of calcified regions and iron deposits in the ageing brain on conventional structural MR images

PURPOSE

In the human brain, minerals such as iron and calcium accumulate increasingly with age. They typically appear hypointense on T2*-weighted MRI sequences. This study aims to explore the differentiation and association between calcified regions and noncalcified iron deposits on clinical brain MRI in elderly, otherwise healthy subjects.

MATERIALS AND METHODS

Mineral deposits were segmented on co-registered T1- and T2*-weighted sequences from 100 1.5 Tesla MRI datasets of community-dwelling individuals in their 70s. To differentiate calcified regions from noncalcified iron deposits we developed a method based on their appearance on T1-weighted images, which was validated with a purpose-designed phantom. Joint T1- and T2*-weighted intensity histograms were constructed to measure the similarity between the calcified and noncalcified iron deposits using a Euclidean distance based metric.

RESULTS

We found distinct distributions for calcified regions and noncalcified iron deposits in the cumulative joint T1- and T2*-weighted intensity histograms across all subjects (correlations ranging from 0.02 to 0.86; mean = 0.26 ± 0.16; t = 16.93; P < 0.001) consistent with differences in iron and calcium signal in the phantom. The mean volumes of affected tissue per subject for calcified and noncalcified deposits were 236.74 ± 309.70 mm(3) and 283.76 ± 581.51 mm(3); respectively. There was a positive association between the mineral depositions (β = 0.32, P < 0.005), consistent with existing literature reports.

CONCLUSION

Calcified mineral deposits and noncalcified iron deposits can be distinguished from each other by signal intensity changes on conventional 1.5T T1-weighted MRI and are significantly associated in brains of elderly, otherwise healthy subjects.

Brain white matter damage in aging and cognitive ability in youth and older age

Cerebral white matter hyperintensities (WMH) reflect accumulating white matter damage with aging and impair cognition. The role of childhood intelligence is rarely considered in associations between cognitive impairment and WMH. We studied community-dwelling older people all born in 1936, in whom IQ had been assessed at age 11 years. We assessed medical histories, current cognitive ability and quantified WMH on MR imaging. Among 634 participants, mean age 72.7 (SD 0.7), age 11 IQ was the strongest predictor of late life cognitive ability. After accounting for age 11 IQ, greater WMH load was significantly associated with lower late life general cognitive ability (β = −0.14, p < 0.01) and processing speed (β = −0.19, p < 0.001). WMH were also associated independently with lower age 11 IQ (β = −0.08, p < 0.05) and hypertension. In conclusion, having more WMH is significantly associated with lower cognitive ability, after accounting for prior ability, age 11IQ. Early-life IQ also influenced WMH in later life. Determining how lower IQ in youth leads to increasing brain damage with aging is important for future successful cognitive aging.

Morphologic, distributional, volumetric, and intensity characterization of periventricular hyperintensities

BACKGROUND AND PURPOSE

White matter hyperintensities are characteristic of old age and identifiable on FLAIR and T2-weighted MR imaging. They are typically separated into periventricular or deep categories. It is unclear whether the innermost segment of periventricular white matter hyperintensities is truly abnormal or is imaging artifacts.

MATERIALS AND METHODS

We used FLAIR MR imaging from 665 community-dwelling subjects 72-73 years of age without dementia. Periventricular white matter hyperintensities were visually allocated into 4 categories: 1) thin white line; 2) thick rim; 3) penetrating toward or confluent with deep white matter hyperintensities; and 4) diffuse ill-defined, labeled as "subtle extended periventricular white matter hyperintensities." We measured the maximum intensity and width of the periventricular white matter hyperintensities, mapped all white matter hyperintensities in 3D, and investigated associations between each category and hypertension, stroke, diabetes, hypercholesterolemia, cardiovascular disease, and total white matter hyperintensity volume.

RESULTS

The intensity patterns and morphologic features were different for each periventricular white matter hyperintensity category. Both the widths (r = 0.61, P < .001) and intensities (r = 0.51, P < .001) correlated with total white matter hyperintensity volume and with each other (r = 0.55, P < .001) for all categories with the exception of subtle extended periventricular white matter hyperintensities, largely characterized by evidence of erratic, ill-defined, and fragmented pale white matter hyperintensities (width: r = 0.02, P = .11; intensity: r = 0.02, P = .84). The prevalence of hypertension, hypercholesterolemia, and neuroradiologic evidence of stroke increased from periventricular white matter hyperintensity categories 1 to 3. The mean periventricular white matter hyperintensity width was significantly larger in subjects with hypertension (mean difference = 0.5 mm, P = .029) or evidence of stroke (mean difference = 1 mm, P < .001). 3D mapping revealed that periventricular white matter hyperintensities were discontinuous with deep white matter hyperintensities in all categories, except only in particular regions in brains with category 3.

CONCLUSIONS

Periventricular white matter hyperintensity intensity levels, distribution, and association with risk factors and disease suggest that in old age, these are true tissue abnormalities and therefore should not be dismissed as artifacts. Dichotomizing periventricular and deep white matter hyperintensities by continuity from the ventricle edge toward the deep white matter is possible.

Abstract WP186: Association Between Blood Pressure, Internal Carotid Artery Flow Parameters And Age-related White Matter Disease

Background: White matter lesions (WML) are associated with hypertension. Blood pressure (BP) is transmitted to the brain via the carotid arteries, and autoregulation helps protect the brain. We investigated if BP via carotid waveform parameters were associated with WML.

Methods: We obtained BP measurements from a cohort of community dwelling subjects at mean ages 70±1 and 73±1 years; brain MRI and carotid artery ultrasound at mean age 73±1 years. We calculated mean values of BP (systolic, diastolic, mean, variability and pulsatility), measured WML by volume, and Fazekas scale. We calculated internal carotid artery (ICA) mean blood flow velocity, pulsatility index (PI), and resistivity index (RI). We tested associations between BP and ICA flow parameters and WML using multiple linear regression, corrected for intracranial volume (ICV), age, gender, BMI, previous MI, diabetes, hypertension, smoking, hypercholesterolaemia, PVD and stroke.

Results: Amongst 694 subjects, diastolic and mean BP decreased and hence BP pulsatility increased significantly between ages 70 and 73 years. Lower diastolic BP and higher BP pulsatility were associated with higher ICA PI (standardized β, age 70= -0.24, age 73= -0.19, both p<0.001; age 70 β=0.18, p<0.001, age 73 β=0.10, p=0.008 respectively). WML volume was weakly associated with BP at age 70 (diastolic β=0.08, systolic β=0.08, mean β=0.09, all p<0.05) but not with BP variability or pulsatility. Similar but weaker associations were seen at age 73. After adjusting for BP, larger WML volume was associated with higher ICA PI (β=0.10, p=0.012), but not any other measures. All associations were the same for WML Fazekas scores.

Conclusions: The relatively weak association between BP and WML may be mediated via ICA pulsatility which is largely driven by falling diastolic BP. This questions the nature of the apparent link between BP and WML.

Close correlation between quantitative and qualitative assessments of white matter lesions

BACKGROUND

White matter lesions (WML) increase with age and are associated with stroke, cognitive decline and dementia. They can be visually rated or computationally assessed.

METHODS

We compared WML Fazekas visual rating scores and volumes, determined using a validated multispectral image-fusion technique, in Magnetic Resonance Imaging from 672 participants of the Lothian Birth Cohort 1936 and sought explanations for subjects in whom the correlation (Spearman's ρ) between the total Fazekas score (summed deep and periventricular ratings, 0-6) and WML volume did not concur (z-score difference >1). Infarcts were identified separately.

RESULTS

The median WML Fazekas score was 2 [inter-quartile range (IQR): 2], median WML volume 7.7 ml (IQR: 13.6 ml) and median infarct volume (n = 95) 0.98 ml. Score and volume were highly correlated (Spearman's ρ = 0.78, p < 0.001). Infarcts did not alter the correlation. Minor discordance occurred in 94/672 (14%) subjects, most with total Fazekas score of 1 (n = 20, WML volume = 4.5-14.8 ml) or 2 (n = 50, WML volume = 0.1-34.4 ml). The main reasons were: subtle WML identified visually but omitted from the volume; prominent ventricular caps but thin body lining giving a periventricular score of 1/2 but large WML volume, and small deep focal lesions which increase the score disproportionally when beginning to coalesce with little change in WML volume.

CONCLUSIONS

WML rating scores and volumes provide near-equivalent estimates of WML burden, therefore either can be used depending on research circumstances. Even closer agreement could result from improved computational detection of subtle WML and modified visual ratings to differentiate prominent ventricular caps from thin periventricular linings, and small non-coalescent from early coalescent deep WML.

Abstract 2363: Are White Matter Lesions Associated with Deep or Superficial Brain Atrophy or both?

Introduction White matter lesions (WMLs) are associated with cognitive decline, dementia and increased risk of stroke. Cerebral atrophy is also associated with future cognitive impairment and dementia. Both WMLs and atrophy are commonly found on MRI scans of elderly people, but whether they are related, and the strength of any relationship remains unclear.

Hypotheses We hypothesised that 1) WMLs are associated with brain atrophy, 2) are more associated with deep (white matter) than superficial (cortical) atrophy, and 3) the association is similar for volumetric and visually rated WMLs.

Methods We performed structural brain MRI on subjects from the Lothian Birth Cohort 1936 ( www.lothianbirthcohort.ed.ac.uk ) and measured intracranial (ICV), brain tissue (BTV), CSF ventricular, superficial subarachnoid space (SSS), grey matter (GM), normal appearing white matter (NAWM) and WML volumes using validated software (MCMxxxVI, http://sourceforge.net/projects/bric1936/ ). We also measured CSF + venous sinuses (V) + dural (D) volume (CSF+V+D) combined to further assess ICV changes due to brain atrophy and rated WMLs using the Fazekas scale. We used Spearman partial correlation to test associations between WMLs and brain atrophy, controlled for gender and ICV and performed general linear modelling (GLM).

Results Amongst 672 subjects, mean age 73±1year, greater WML volume correlated: with reduced BTV (r=-0.10, P=0.01) and NAWM (r= -0.15, P<0.01), increased ventricular volume (r= 0.11, P<0.01) and CSF+V+D (r=0.11, P=0.01) but not with SSS (r=0.03, P=0.39), GM (r=-0.07, P=0.09) or CSF (r=0.06, P=0.13). A 1mm 3 increase in WML volume was associated with 0.43mm 3 decrease in BTV. We found similar associations for Fazekas WML scores. Gender and original brain size (i.e. ICV) explained 77.6% and 23.8% of the variance in BTV and ventricular volume, respectively, but WMLs explained <1% of either (GLM).

Conclusions WMLs, assessed using both measured volumes and visual rating scales, are associated with brain atrophy mostly through deep white matter loss. Studies of brain atrophy in ageing or dementia should assess venous sinuses, dura and CSF, not just CSF, as sinuses and dura expand to occupy space left by brain atrophy. Further work to determine causes of age-related brain atrophy is required as WMLs only explain a small proportion of it.

Comparative study of standard space and real space analysis of quantitative MR brain data

PURPOSE

To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space.

MATERIALS AND METHODS

Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T(1)-weighted, quantitative T(1), and B(0) field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T(1) datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared.

RESULTS

Regional mean T(1) values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T(1) histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis.

CONCLUSION

Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space.