The hippocampus within the medial temporal lobe is highly vulnerable to age- related pathology such as vascular disease. We examined hippocampal vascularization patterns by harnessing the ultra-high resolution of 7 Tesla MR angiography. Dual-supply hemispheres with a contribution of the anterior choroidal artery to hippocampal blood supply were distinguished from single-supply ones with a sole dependence on the posterior cerebral artery. A recent study indicated that a dual vascular supply is related to preserved cognition and structural hippocampal integrity in old age and vascular disease. Here, we examined regional specificity of these structural benefits at the level of medial temporal lobe sub- regions and hemispheres. In a cross-sectional study with an older cohort of 17 patients with cerebral small vessel disease (70.7±9.0 years, 35.5% female) and 27 controls (71.1±8.2 years, 44.4% female), we demonstrate that differences in grey matter volumes related to the hippocampal vascularization pattern were specifically observed in the anterior hippocampus and entorhinal cortex. These regions were especially bigger in dual-supply hemispheres, but also seemed to benefit from a contralateral dual supply. We further show that total grey matter volumes were greater in people with at least one dual-supply hemisphere, indicating that the hippocampal vascularization pattern has more far-reaching structural implications beyond the medial temporal lobe. A mediation analysis identified total grey matter as a mediator of differences in global cognition. However, our analyses on multiple neuroimaging markers for cerebral small vessel disease did not reveal any evidence that an augmented hippocampal vascularization conveys resistance nor resilience against vascular pathology. We propose that an augmented hippocampal vascularization might contribute to maintaining structural integrity in the brain and preserving cognition despite age-related degeneration. As such, the binary hippocampal vascularization pattern could have major implications for brain structure and function in aging and dementia independent of vascular pathology, while presenting a simple framework with potential applicability to the clinical setting.
BackgroundThe association between cerebral blood supply and cognition has gained increasing interest, considering the remarkable anatomical variability of the circle of Willis. Thus, qualitative classifications of the arteries contributing to the hippocampal supply has been performed in previous studies to determine whether the additional presence of vessels might translate into cognitive differences and cerebral structural changes when coexisting with vascular pathology, to the extent of constituting a cognitive reserve. Nevertheless, the promising results in these regards are not without controversy. Hence, Vessel Distance Mapping (VDM) is here introduced, in order to ascertain the correlation of VDM‐metrics with each other and with cognitive status, as well as to elucidate which metrics have the greatest impact on cognition.MethodA battery of cognitive tests was used (including ADAScog and MoCA) in 51 subjects (71 ± 8.5yrs) with (n=20) and without (n=31) cerebral small vessel disease. Their hippocampal‐related vessels were manually segmented by using high‐resolution 7T Time‐of‐Flight‐MRI. Vessel distance maps were generated by computing the distances of each voxel to its nearest vessel, obtaining 3 VDM‐metrics: global‐VDM (vessel density surrogate), VS‐VDM (vessel‐specific supply), and COMD (distance to the center of mass, reflecting vessel distribution). Hippocampal masks were used to assess the whole and subregional hippocampus. Regression models were applied for evaluating the interrelation among the metrics, and their association with cognition.ResultHigh correlations were observed for intra‐metric comparisons, as well as when comparing whole hippocampal vs. sub‐hippocampal metrics. Greater values of VDM‐metrics reflecting higher distances among vessels were associated with poorer cognitive outcomes only in subjects affected by vascular pathology (global‐VDM R²=0.7248, p=0.0054; COMD R²=0.7248, p=0.0013). Metrics revealing vascular distribution (p=0,0053) and density (p=0,0169) were the most influential on cognition, and in this context those for the whole hippocampus predominated over the subregional ones.ConclusionA mixed contribution of vessel distribution and density is proposed to confer cognitive resilience, in a way consistent with anatomical fundamentals and with previous research findings. VDM provides a new, structure‐driven approach on which to raise new questions supported by the statistical robustness of a quantitative method with potential clinical implications.
Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as informative covariates, vascular risks, brain activity, neuropsychological test etc.,) might provide useful predictions of clinical outcomes during progression towards Alzheimer's disease (AD). The Bayesian approach aims to provide a trade-off by employing relevant features combinations to build decision support systems in clinical settings where uncertainties are relevant. We tested the approach in the MRI data across 959 subjects, aged 59-89 years and 453 subjects with available neuropsychological test scores and CSF biomarker status (amyloid-beta (Aβ)42/40 & and phosphorylated tau (pTau)) from a large sample multi-centric observational cohort (DELCODE). In order to explore the beneficial combinations of information from different sources, we presented a MRI-based predictive modelling of memory performance and CSF biomarker status (positive or negative) in the healthy ageing group as well as subjects at risk of Alzheimer's disease using a Gaussian process multi-kernel framework. Furthermore, we systematically evaluated predictive combinations of input feature sets and their model variations, i.e. (A) combinations of brain tissue classes and feature type (modulated vs. unmodulated), choices of filter size of smoothing (ranging from 0 to 15 mm full width at half maximum), and image resolution (1mm, 2mm, 4mm and 8mm); (B) incorporating demography and covariates (C) the impact of the size of the training data set (i.e., number of subjects); (D) the influence of reducing the dimensions of data and (E) choice of kernel types. Finally, the approach was tested to reveal individual cognitive scores at follow-up (up to 4 years) using the baseline features. The highest accuracy for memory performance prediction was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF-biomarkers explaining 57% of outcome variance in out of sample predictions. The best accuracy for Aβ42/40 status classification was achieved for combination demographics, ApoE4 and memory score while usage of structural MRI improved the classification of individual patient's pTau status.
BackgroundThe new consensus definition of cognitive reserve (CR) provides a framework to study individual differences in cognitive functioning relative to aging and disease. CR denotes a property of the brain that allows for better than expected cognitive performance given the degree of age‐related brain changes or disease. More specifically, individual differences in patterns of brain activity during fMRI tasks might explain the differential susceptibility to pathological burden.MethodAccording to the consensus definitions, we sought to identify and quantify CR from fMRI novelty‐contrast maps in a large multi‐centric sample (DELCODE) consisting of 215 participants with SCD, 79 with MCI, 30 with AD dementia, 56 AD relatives and 156 cognitively normal controls (CN). CSF amyloid‐42/40 ratio, CSF p‐tau and hippocampal volume (ATN) were reduced to a single number, representing a (Alzheimer’s) disease progression (DP) score. To identify a CR network, voxel‐wise linear regression models determined where functional task‐activation moderates the relationship between DP and cognition. Finally, task‐related activity within the CR network was extracted to obtain individual fMRI‐based CR scores.ResultThe DP score showed a strong negative quadratic association with baseline memory scores. CR voxels, in which higher or lower activation were associated with better cognition, weakening the effect of DP, were mainly located within the novelty network. They included lateral‐occipital and superior‐parietal regions, lingual and fusiform gyrus, cuneus and small parts of cingulate. While there was no association between the CR score and cognition in CNs, higher CR scores in MCI and AD patients were related to higher PACC5 scores.ConclusionWe established a DP score that collapses the ATN measures into a single number, while retaining its deleterious effect on an individual’s memory score. Furthermore, a newly identified task‐dependent CR network could be used to establish a CR score, which was related to higher PACC5 scores in MCI and AD patients, suggesting a functional compensation mechanism at later stages of AD that is not yet present in CN. Thus, targeted alteration of brain activity might be a promising route to modify cognitive trajectories in MCI and AD patients. Further, detailed examination of individuals with high CR might reveal additional disease‐modifying factors.
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