The hippocampus has been extensively studied in various neuropsychiatric disorders throughout the lifespan. However, inconsistent results have been reported with respect to which subfield volumes are most related to age. Here, we investigate whether these discrepancies may be explained by experimental design differences that exist between studies. Multiple datasets were used to collect 1690 magnetic resonance scans from healthy individuals aged 18-95 years old. Standard T1-weighted (T1w; MPRAGE sequence, 1 mm 3 voxels), high-resolution T2-weighted (T2w; SPACE sequence, 0.64 mm 3 voxels) and slab T2-weighted (Slab; 2D turbo spin echo, 0.4 x 0.4 x 2 mm 3 voxels) images were acquired. The MAGeT Brain algorithm was used for segmentation of the hippocampal grey matter (GM) subfields and peri-hippocampal white matter (WM) subregions. Linear mixed-effect models and Akaike information criterion were used to examine linear, second or third order natural splines relationship between hippocampal volumes and age. We demonstrated that stratum radiatum/lacunosum/moleculare and fornix subregions expressed the highest relative volumetric decrease, while the cornus ammonis 1 presented a relative volumetric preservation of its volume with age. We also found that volumes extracted from slab images were often underestimated and demonstrated different age-related relationships compared to volumes extracted from T1w and T2w images. The current work suggests that although T1w, T2w and slab derived subfield volumetric outputs are largely homologous, modality choice plays a meaningful role in the volumetric estimation of the hippocampal subfields.

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Statistical effects of cortical metrics derived from standard T1‐ and T2‐weighted magnetic resonance imaging (MRI) images, such as gray–white matter contrast (GWC), boundary sharpness coefficient (BSC), T1‐weighted/T2‐weighted ratio (T1w/T2w), and cortical thickness (CT), are often interpreted as representing or being influenced by intracortical myelin content with little empirical evidence to justify these interpretations. We first examined spatial correspondence with more biologically specific microstructural measures, and second compared between‐marker age‐related trends with the underlying hypothesis that different measures primarily driven by similar changes in myelo‐ and microstructural underpinnings should be highly related. Cortical MRI markers were derived from MRI images of 127 healthy subjects, aged 18–81, using cortical surfaces that were generated with the CIVET 2.1.0 pipeline. Their gross spatial distributions were compared with gene expression‐derived cell‐type densities, histology‐derived cytoarchitecture, and quantitative R1 maps acquired on a subset of participants. We then compared between‐marker age‐related trends in their shape, direction, and spatial distribution of the linear age effect. The gross anatomical distributions of cortical MRI markers were, in general, more related to myelin and glial cells than neuronal indicators. Comparing MRI markers, our results revealed generally high overlap in spatial distribution (i.e., group means), but mostly divergent age trajectories in the shape, direction, and spatial distribution of the linear age effect. We conclude that the microstructural properties at the source of spatial distributions of MRI cortical markers can be different from microstructural changes that affect these markers in aging.

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The study of the hippocampus across the healthy adult lifespan has rendered inconsistent findings. While volumetric measurements have often been a popular technique for analysis, more advanced morphometric techniques have demonstrated compelling results that highlight the importance and improved specificity of shape-based measures. Here, the MAGeT Brain algorithm was applied on 134 healthy individuals aged 18-81 years old to extract hippocampal subfield volumes and hippocampal shape measurements, notably : local surface area (SA) and displacement. We used linear, second or third order natural splines to examine the relationships between hippocampal measures and age. In addition, partial least squares analyses were performed to relate measurements with cognitive and demographic information. Volumetric results indicated a relative preservation of the right cornus ammonis 1 with age and a global volume reduction linked with older age, female sex, lower levels of education and cognitive performance. Vertex-wise analysis demonstrated an SA preservation in the anterior hippocampus with a peak during the sixth decade, while the posterior hippocampal SA gradually decreased across lifespan. Overall, SA decrease was linked to older age, female sex and, to a lesser extent lower levels of education and cognitive performance. Outward displacement in the lateral hippocampus and inward displacement in the medial hippocampus were enlarged with older age, lower levels of cognition and education, indicating an accentuation of the hippocampal C shape with age. Taken together, our findings suggest that vertex-wise analyses have higher spatial specifity and that sex, education and cognition are implicated in the differential impact of age on hippocampal subregions throughout its antero-posterior and medial-lateral axes.

White matter hyperintensities (WMHs) are clinically significant MRI abnormalities often detected in the elderly and early stages of Alzheimer′s 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 associations of these WMH signal measures to clinically-relevant measures such as cortical and global brain atrophy, cognitive function, diagnostic and demographic differences, and Alzheimer′s Disease-relevant cardiovascular risk factors. Our sample of 118 subjects was composed of healthy controls (n=30), high-risk of Alzheimer′s Disease due to familial history (n=47), mild cognitive impairment (n=32), and clinical Alzheimer′s 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.