Citations

AbstractBackgroundThe Mayo Clinic Study of Aging and Alzheimer’s Disease Research Center used GE scanners exclusively for MRI from 2005‐2017, employing consistent imaging parameters throughout. In 2017 the MRI protocol was updated and migrated to Siemens Prisma scanners; 113 participants were scanned with each configuration. The GE protocol included a 2D FLAIR. The Siemens protocol includes 3D FLAIR and T2‐weighted images. Both vendor protocols included a 3D T1. Experience with multi‐center trials suggests such changes may introduce systematic variations.MethodsGE scanning was carried out on 3T scanners with 12 channel phased array head coils. Siemens Prisma scanning was carried out with 64 channel head/neck coils. Imaging sequences and parameters are given in Table 1. We used the MCALT template and priors to perform standard six‐class segmentation on T1‐weighted (T1w) images. SPM12 unified segmentation supports the simultaneous use of multiple input contrasts; segmentation of multi‐contrast inputs was done using eight tissue classes including deep grey and white matter hyperintensity (WMH) priors. For a given MRI study (either GE or Siemens) all images were registered and resampled to the study’s T1w image. Two‐channel (T1+FLAIR) segmentation was performed on GE scans. Two and three‐channel segmentations were performed on Siemens scans. Comparisons included total intracranial volume, total tissue volume and total grey matter volumes, as well as hippocampal volumes and grey matter volume in a temporal lobe meta‐ROI.ResultsFour participants were excluded for poor image quality: one poor GE T1w quality, one poor Siemens T1, T2 and FLAIR quality, and two poor Siemens T2 quality. Comparisons were made among 109 participants aged 34–97 (Table 2). By visual assessment, adding T2‐weighted images always improved intracranial volume correctness. Using the combination of single‐channel GE and three‐channel Siemens generally improved cross‐vendor agreement on grey matter volumes with the exceptions of hippocampal and intracranial volume estimates.ConclusionRequiring multiple input channels increases the likelihood that the result of a study being excluded. Combining T1w, FLAIR and T2w images allows the delineation of WMH and deep grey matter probability outputs but may introduce differences in GM volumes.

AbstractBackgroundOptimizing software to measure Flortaucipir (AV‐1451) tau PET SUVR change‐over‐time is crucial for longitudinal observational studies and potential trials of anti‐tau agents. Ideal measurements should have good repeatability (low noise), and should clearly separate clinical cognitive groups.MethodWe compared 456 software methods varying in their use of: two major packages, each with cross‐sectional and longitudinal variants (FreeSurfer and an in‐house pipeline using SPM12, MCALT, and ANTs); three temporal‐lobe target regions (each with/without adjacent WM); seven reference regions; five PVC methods; and two statistics (mean vs. median). We used linear mixed‐effects models to compare methods using scans from 88 Mayo Clinic participants (46 cognitively impaired, 42 impaired, excluding those with symptoms inconsistent with the AD pathology imaged by Flortaucipir), each with three visits with PET and MRI. From these models, we calculated two criteria for each pipeline: relative measurement error (residual from the linear mixed model), and the t‐statistic for testing differences in group‐wise rates of change (which has a Cohen’s d interpretation of effect size for longitudinal data). We plotted both criteria orthogonally, then ranked methods overall according to the average of their ranks on both individual criteria.ResultMethods using the entorhinal cortex target region performed poorly in both criteria (Figure 1). The top 10 methods by the combined criteria (top‐left in Figure 2) all used the Mayo SPM12‐based pipeline with an eroded supratentorial WM (eSWM) or composite (eSWM + pons + cerebellum) reference region. Among them, 9/10 used the longitudinal variant, 8/10 used 2‐compartment PVC, and 7/10 used median. Altogether, our results favored SUVR methods with a longitudinal design (simultaneously calculating all time‐points), a temporal‐lobe meta‐ROI including adjacent WM, a composite reference region, 2‐class voxel‐based (Meltzer) PVC, and median statistics. Methods using GTM‐Tau PVC (Baker et al., Data in Brief, 2017) had the highest group separation but relatively large measurement error, giving them ranks 197 and 199 out of 456 with the joint (average rank) criteria.ConclusionCompared with popular FreeSurfer‐based methods (ranks 176, 258; Figure 2), our top‐ranked approaches approximately halved error in SUVR measurements while maintaining or improving group separation.

AbstractIntroductionWe examined the temporal sequence of the core features in probable dementia with Lewy bodies (DLB).MethodsIn 488 patients with probable DLB, the onset of each core feature and time to diagnosis was determined for men and women, and a pathologic subgroup (n = 209).ResultsREM sleep behavior disorder (RBD) developed before the other core features in men and women. Men were more likely to have RBD and were diagnosed with probable DLB earlier than women. Visual hallucinations developed after the other core features in men, but in women, they appeared earlier and concurrently with fluctuations and parkinsonism. Women were older and more cognitively impaired at first visit, were less likely to have RBD, more likely to be diagnosed with probable DLB later than men, and more likely to have neocortical tangles.DiscussionAn earlier latency to probable DLB was associated with men, RBD, and Lewy body disease without neocortical tangles.

A rare APOE variant APOE3 -Jac reduces self-aggregation and promotes healthy brain aging.

Abstract Normal brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging at respective age ranges. Here, we developed a deep learning-based brain age prediction model using fluorodeoxyglucose (FDG) PET and structural MRI and tested how the brain age gap relates to degenerative cognitive syndromes including mild cognitive impairment, AD, frontotemporal dementia, and Lewy body dementia. Occlusion analysis, performed to facilitate interpretation of the model, revealed that the model learns an age- and modality-specific pattern of brain aging. The elevated brain age gap in dementia cohorts was highly correlated with the cognitive impairment and AD biomarker. However, regions generating brain age gaps were different for each diagnosis group of which the AD continuum showed similar patterns to normal aging in the CU.

The objective of this study was to investigate the cross-sectional associations of atrial fibrillation with neuroimaging measures of cerebrovascular disease and Alzheimer’s disease-related pathology, and their interaction with cognitive impairment. MRI scans of non-demented individuals (n=1044) from the population-based Mayo Clinic Study of Aging were analyzed for infarctions, total grey matter, hippocampal and white matter hyperintensity volumes. A subset of 496 individuals underwent FDG and C-11 Pittsburgh compound B (PiB) PET scans. We assessed the associations of atrial fibrillation with i) categorical MRI measures (cortical and subcortical infarctions) using multivariable logistic regression models, and with ii) continuous MRI measures ( hippocampal, total grey matter, and white matter hyperintensity volumes) and FDG-PET and PiB-PET measures using multivariable linear regression models, and adjusting for confounders. Among participants who underwent MRI (median age, 77.8, 51.6% male), 13.5% had atrial fibrillation. Presence of atrial fibrillation was associated with subcortical infarctions (odds ratio [OR], 1.83; p=0.002), cortical infarctions (OR, 1.91; p=0.03), total grey matter volume (Beta [β], -.025, p<.0001) after controlling for age, education, gender, APOE e4 carrier status, coronary artery disease, diabetes, history of clinical stroke, and hypertension. However, atrial fibrillation was not associated with white matter hyperintensity volume, hippocampal volume, Alzheimer’s pattern of FDG hypometabolism or PiB uptake. There was a significant interaction of cortical infarction (p for interaction=0.004) and subcortical infarction (p for interaction =0.015) with atrial fibrillation with regards to odds of mild cognitive impairment (MCI). Using subjects with no atrial fibrillation and no infarction as the reference, the OR (95% confidence intervals [CI]) for MCI was 2.98 (1.66, 5.35;p = 0.0002) among participants with atrial fibrillation and any infarction, 0.69 (0.36, 1.33;p= 0.27) for atrial fibrillation and no infarction, and 1.50 (0.96, 2.32;p = 0.07) for no atrial fibrillation and any infarction. These data highlight that atrial fibrillation is associated with MCI in the presence of infarctions.

Hypertension is highly prevalent in the elderly population and microinfarcts are the most common vascular brain pathology identified in older adults at autopsy. We investigated the associations between systolic and diastolic blood pressures measured antemortem and the presence of microinfarcts at autopsy. Study subjects (n=302; age range=71-95) were participants in the population-based Mayo Clinic Study of Aging autopsy study, who had blood pressure measurements recorded during life. We investigated both cross-sectional systolic and diastolic blood pressure measurements at the baseline visit and the change in blood pressure (slope). Presence and location (subcortical or cortical) of chronic microinfarcts was abstracted from the autopsy reports. Of the 302 study subjects, 47 (16%) had cerebral microinfarcts, and, of those, 18 (38%) had subcortical microinfarcts and 29 (62%) had only cortical microinfarcts. The baseline blood pressures were not different between subjects with no microinfarcts, subcortical microinfarcts, and only cortical microinfarcts. In a logistic regression model including time between last blood pressure measurement and death, a greater decline in systolic [OR= 1.06 (1.01, 1.11); p=0.02]) and greater decline in diastolic [OR= 1.11 (1.02, 1.20); p=0.01] blood pressures were predictors of the presence of subcortical microinfarcts at autopsy. However, these variables were not associated with the presence of cortical microinfarcts. In conclusion, microinfarcts are common in the older adult population, and most of them are located in the cortex. A greater decline in both systolic and diastolic blood pressures and their association with subcortical microinfarcts, but not with cortical microinfarcts, may have implications for aggressive lowering of blood pressure in the elderly population.

Introduction: Cortical superficial siderosis (cSS) refers to deposition of blood breakdown products along the cerebral cortex, causing characteristic staining patterns seen with iron-sensitive MRI techniques. Cortical superficial siderosis is a relatively rare disorder, but has been linked to cerebral amyloid angiopathy and Alzheimer’s disease. The objective of this study was to determine the frequency and natural history of cSS in the general elderly population. Methods: MRI scans from the Mayo Clinic Study of Aging (MCSA), an ongoing population-based study of elderly residents in Olmsted County, Minnesota, were reviewed by neuroradiologists. Participants with cSS were identified based on linear pattern of hypointensity on gradient recalled echo imaging consistent with cSS. Exclusion criteria were: 1) MRI findings not consistent with cSS or 2) alternative explanation for MRI findings (such as aneurysmal subarachnoid hemorrhage, intracranial surgery, or trauma). Additional data abstracted included extent of cSS, presence of cerebral microbleeds, and clinical outcome. Results: Eleven out of 1,441 participants had MRI scans showing cSS (0.8%). When stratified by age, the frequency was 0.4% in those 50 to 70 years old and 1.1% in those over 70 years old. Six participants had only focal involvement of cSS (restricted to three or fewer sulci) and five had disseminated involvement (affecting more than three sulci). Microbleeds were seen in four of five (80%) participants with disseminated cSS, but none with focal cSS. Five participants (2 focal, 3 disseminated cSS) had follow up MRI scans, with an average follow up of 25 months. There was no further hemorrhage in those with focal cSS. However, all three participants with disseminated cSS experienced additional hemorrhage: one with new microbleeds, one with new microbleeds and lobar hemorrhage, and one with sulcal subarachnoid hemorrhage and lobar hemorrhage. Conclusion: Although rare, cSS may be encountered in the general elderly population. Extent of involvement of cSS and concomitant microbleeds may be important risk factors for progression of disease and intracerebral hemorrhage. The clinical significance of focal cSS occurring in the absence of microbleeds requires further investigation.