Biology subjects

Bedford, S. A.

Publications and source records attributed to Bedford, S. A..

4 recordsLinked to original sources

bioRxiv2023

Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease

White matter hyperintensities (WMHs) are clinically significant MRI abnormalities often detected in the elderly and early stages of Alzheimers Disease. They are indicative of vascular pathology but represent a mixture of microstructural tissue alterations that is highly variable between individuals. To better understand these alterations, we leveraged the signal of different MRI contrasts sampled within WMHs, which have differential sensitivity to microstructural properties. Subsequently, we sought to examine the asso of these WMH signal measures to clinically-relevant measures such as cortical and global brain atrophy, cognitive function, diagnostic and demographic differences, and Alzheimers Disease-relevant cardiovascular risk factors. Our sample of 118 subjects was composed of healthy controls (n=30), high-risk of Alzheimers Disease due to familial history (n=47), mild cognitive impairment (n=32), and clinical Alzheimers Disease (n=9) as a means of ascertaining a spectrum of impairment. We sampled the median signal within WMHs on weighted MRI images that are commonly acquired (T1-weighted [T1w], T2-weighted [T2w], T1w/T2w ratio, Fluid-Attenuated Inversion Recovery [FLAIR]), and the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. Main analyses were performed with a periventricular/deep/superficial white matter parcellation and were repeated with a lobar white matter parcellation. We demonstrated that the correlations between WMH signal measures were variable, suggesting that they are likely influenced by different microstructural properties. We observed that the WMH qT2* and FLAIR measures displayed different age- and disease-related trends compared to normal-appearing white matter, highlighting sensitivity to WMH-specific tissue deterioration. Further, WMH qT2* particularly in periventricular and occipital white matter regions was consistently associated with several of our clinical variables of interest using both parcellation schemes in univariate analyses, and further showed high contributions to a pattern of brain variables that was associated with age and cognitive variables in multivariate Partial Least Squares Correlation analyses. qT1 and FLAIR measures showed consistent clinical relationships in multivariate analyses only, while T1w, T2w, and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to WMHs. Combining volumetric and signal measures of WMH, particularly qT2* and to a lesser extent qT1 and FLAIR, should be considered to more precisely characterize the severity of WMHs in vivo. These findings may have implications in determining the reversibility of WMHs and potential efficacy of cardio- and cerebrovascular treatments.

neuroscience↗

bioRxiv2022

Variation in subcortical anatomy: relating interspecies differences, heritability, and brain-behavior relationships

There has been an immense research focus on the topic of cortical reorganization in human evolution, but much less is known regarding the reorganization of subcortical circuits which are intimate working partners of the cortex. Here, by combining advanced image analysis techniques with comparative neuroimaging data, we systematically map organizational differences in striatal, pallidal and thalamic anatomy between humans and chimpanzees. We relate interspecies differences, a proxy for evolutionary changes, to genetics and behavioral correlates. We show that highly heritable morphological measures are significantly expanded across species, in contrast to previous findings in the cortex. The identified morphological-cognitive latent variables were associated with striatal expansion, and affective latent variables were associated with more evolutionarily-conserved areas in the thalamus and globus pallidus. These findings provide new insight into the architecture of these subcortical hubs and can provide greater information on the role of these structures in health and illness.

neuroscience↗

bioRxiv2022

High spatial overlap but diverging age-related trajectories of cortical MRI markers aiming to represent intracortical myelin and microstructure

Cortical thickness (CT), gray-white matter contrast (GWC), boundary sharpness coefficient (BSC), and T1-weighted/T2-weighted ratio (T1w/T2w) are cortical metrics derived from standard T1- and T2-weighted magnetic resonance imaging (MRI) images that are often interpreted as representing or being influenced by intracortical myelin content. However, there is little empirical evidence to justify these interpretations nor have the homologies or differences between these measures been examined. We examined differences and similarities in group mean and age-related trends with the underlying hypothesis that different measures sensitive to similar changes in underlying myelo- and microstructural processes should be highly related. We further probe their sensitivity to cellular organization using the BigBrain, a high-resolution digitized volume stemming from a whole human brain histologically stained for cell bodies with the Merker stain. The measures were generated on both the MRI-derived images of 127 healthy subjects, aged 18 to 81, and on the BigBrain volume using cortical surfaces that were generated with the CIVET 2.1.0 pipeline. Comparing MRI markers between themselves, our results revealed generally high overlap in spatial distribution (i.e., group mean), but mostly divergent age trajectories in the shape, direction, and spatial distribution of the linear age effect. Significant spatial relationships were found between the BSC and GWC and their BigBrain equivalent, as well as a correlation approaching significance between the BigBrain intensities and the T1w/T2w ratio in gray matter (GM) both sampled at half cortical depth. We conclude that the microstructural properties at the source of spatial distributions of MRI cortical markers (e.g. GM myelin) can be different from microstructural changes that affect these markers in aging. While our findings highlight a discrepancy in the interpretation of the biological underpinnings of the cortical markers, they also highlight their potential complementarity, as they are largely independent in aging. Our BigBrain results indicate a general trend of GM T1w signal and myelin being spatially related to the density of cells, which is possibly more pronounced in superficial cortical layers. Highlights- Different MRI cortical markers aim to represent myelin and microstructure - These markers show high spatial overlap, but mostly divergent age trajectories - It is unlikely that myelin changes are the source of the age effect for all markers - Trend of MRI signal being related to cell density in more superficial cortical layers

neuroscience↗

bioRxiv2021

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure. Furthermore, we provide open resources to support future advances towards adoption of brain charts as standards for quantitative benchmarking of typical or atypical brain MRI scans.

neuroscience↗