Many patients with dementia with Lewy bodies (DLB) have overlapping Alzheimer's disease (AD)-related pathology, which may contribute to white matter (WM) diffusivity alterations on diffusion tensor imaging (DTI). Consecutive patients with DLB (n = 30), age- and sex-matched AD patients (n = 30), and cognitively normal controls (n = 60) were recruited. All subjects underwent DTI, 18F 2-fluoro-deoxy-d-glucose, and (11)C Pittsburgh compound B positron emission tomography scans. DLB patients had reduced fractional anisotropy (FA) in the parietooccipital WM but not elsewhere compared with cognitively normal controls, and elevated FA in parahippocampal WM compared with AD patients, which persisted after controlling for β-amyloid load in DLB. The pattern of WM FA alterations on DTI was consistent with the more diffuse posterior parietal and occipital glucose hypometabolism of 2-fluoro-deoxy-d-glucose positron emission tomography in the cortex. DLB is characterized by a loss of parietooccipital WM integrity, independent of concomitant AD-related β-amyloid load. Cortical glucose hypometabolism accompanies WM FA alterations with a concordant pattern of gray and WM involvement in the parietooccipital lobes in DLB.

Alzheimer's disease (AD) researchers commonly use MRI as a quantitative measure of disease severity. Historically, hippocampal volume has been favored. Recently, "AD signature" measurements of gray matter (GM) volumes or cortical thicknesses have gained attention. Here, we systematically evaluate multiple thickness- and volume-based candidate-methods side-by-side, built using the popular FreeSurfer, SPM, and ANTs packages, according to the following criteria: (a) ability to separate clinically normal individuals from those with AD; (b) (extent of) correlation with head size, a nuisance covariatel (c) reliability on repeated scans; and (d) correlation with Braak neurofibrillary tangle stage in a group with autopsy. We show that volume- and thickness-based measures generally perform similarly for separating clinically normal from AD populations, and in correlation with Braak neurofibrillary tangle stage at autopsy. Volume-based measures are generally more reliable than thickness measures. As expected, volume measures are highly correlated with head size, while thickness measures are generally not. Because approaches to statistically correcting volumes for head size vary and may be inadequate to deal with this underlying confound, and because our goal is to determine a measure which can be used to examine age and sex effects in a cohort across a large age range, we thus recommend thickness-based measures. Ultimately, based on these criteria and additional practical considerations of run-time and failure rates, we recommend an AD signature measure formed from a composite of thickness measurements in the entorhinal, fusiform, parahippocampal, mid-temporal, inferior-temporal, and angular gyrus ROIs using ANTs with input segmentations from SPM12.

Visually preserved metabolism in posterior cingulate cortex relative to hypometabolism in precuneus and cuneus, the cingulate island sign, is a feature of dementia with Lewy bodies (DLB) on FDG-PET. Lower cingulate island sign ratio (posterior cingulate cortex/cuneus+precuneus; FDG-CISr) values have been associated with a higher Braak neurofibrillary tangle stage in autopsied DLB. Using voxel-wise analysis, we assessed the patterns of regional cortical perfusion and metabolism, and using an atlas-based approach, we measured perfusion cingulate island sign ratio on arterial spin labeling MRI (ASL-CISr), and its associations with FDG-CISr, uptake on tau-PET and clinical severity in DLB. Our study sample (n = 114) included clinically probable DLB patients (n = 19), age-matched patients with probable Alzheimer's disease dementia (AD; n = 19) and matched controls (n = 76) who underwent MRI with 3-dimensional pseudo-continuous arterial spin labeling, 18F-FDG-PET and 18F-AV-1451 tau PET. Patterns of cortical perfusion and metabolism were derived from quantitative maps using Statistical Parametric Mapping. DLB patients showed hypoperfusion on ASL-MRI in precuneus, cuneus and posterior parieto-occipital cortices, compared to controls, and relatively spared posterior cingulate gyrus, similar to pattern of hypometabolism on FDG-PET. DLB patients had higher ASL-CISr and FDG-CISr than AD patients (p <0.001). ASL-CISr correlated with FDG-CISr in DLB patients (r = 0.67; p =0.002). Accuracy of distinguishing DLB from AD patients was 0.80 for ASL-CISr and 0.91 for FDG-CISr. Lower ASL-CISr was moderately associated with a higher composite medial temporal AV-1451 uptake (r = -0.50; p =0.03) in DLB. Lower perfusion in precuneus and cuneus was associated with worse global clinical scores. In summary, the pattern of cortical hypoperfusion on ASL-MRI is similar to hypometabolism on FDG-PET, and respective cingulate island sign ratios correlate with each other in DLB. Non-invasive and radiotracer-free ASL-MRI may be further developed as a tool for the screening and diagnostic evaluation of DLB patients in a variety of clinical settings where FDG-PET is not accessible.

Tract-Based Spatial Statistics (TBSS) is a popular software pipeline to coregister sets of diffusion tensor Fractional Anisotropy (FA) images for performing voxel-wise comparisons. It is primarily defined by its skeleton projection step intended to reduce effects of local misregistration. A white matter "skeleton" is computed by morphological thinning of the inter-subject mean FA, and then all voxels are projected to the nearest location on this skeleton. Here we investigate several enhancements to the TBSS pipeline based on recent advances in registration for other modalities, principally based on groupwise registration with the ANTS-SyN algorithm. We validate these enhancements using simulation experiments with synthetically-modified images. When used with these enhancements, we discover that TBSS's skeleton projection step actually reduces algorithm accuracy, as the improved registration leaves fewer errors to warrant correction, and the effects of this projection's compromises become stronger than those of its benefits. In our experiments, our proposed pipeline without skeleton projection is more sensitive for detecting true changes and has greater specificity in resisting false positives from misregistration. We also present comparative results of the proposed and traditional methods, both with and without the skeleton projection step, on three real-life datasets: two comparing differing populations of Alzheimer's disease patients to matched controls, and one comparing progressive supranuclear palsy patients to matched controls. The proposed pipeline produces more plausible results according to each disease's pathophysiology.

Our objective was to examine associations between glucose metabolism, as measured by (18)F-fluorodeoxyglucose positron emission tomography (FDG PET), and age and to evaluate the impact of carriage of an apolipoprotein E (APOE) ε4 allele on glucose metabolism and on the associations between glucose metabolism and age. We studied 806 cognitively normal (CN) and 70 amyloid-imaging-positive cognitively impaired participants (35 with mild cognitive impairment and 35 with Alzheimer's disease [AD] dementia) from the Mayo Clinic Study of Aging, Mayo Alzheimer's Disease Research Center and an ancillary study who had undergone structural MRI, FDG PET, and (11)C-Pittsburgh compound B (PiB) PET. Using partial volume corrected and uncorrected FDG PET glucose uptake ratios, we evaluated associations of regional FDG ratios with age and carriage of an APOE ε4 allele in CN participants between the ages of 30 and 95 years, and compared those findings with the cognitively impaired participants. In region-of-interest (ROI) analyses, we found modest but statistically significant declines in FDG ratio in most cortical and subcortical regions as a function of age. We also found a main effect of APOE ε4 genotype on FDG ratio, with greater uptake in ε4 noncarriers compared with carriers but only in the posterior cingulate and/or precuneus, lateral parietal, and AD-signature meta-ROI. The latter consisted of voxels from posterior cingulate and/or precuneus, lateral parietal, and inferior temporal. In age- and sex-matched CN participants the magnitude of the difference in partial volume corrected FDG ratio in the AD-signature meta-ROI for APOE ε4 carriers compared with noncarriers was about 4 times smaller than the magnitude of the difference between age- and sex-matched elderly APOE ε4 carrier CN compared with AD dementia participants. In an analysis in participants older than 70 years (31.3% of whom had elevated PiB), there was no interaction between PiB status and APOE ε4 genotype with respect to glucose metabolism. Glucose metabolism declines with age in many brain regions. Carriage of an APOE ε4 allele was associated with reductions in FDG ratio in the posterior cingulate and/or precuneus, lateral parietal, and AD-signature ROIs, and there was no interaction between age and APOE ε4 status. The posterior cingulate and/or precuneus and lateral parietal regions have a unique vulnerability to reductions in glucose metabolic rate as a function both of age and carriage of an APOE ε4 allele.

In 1164 cognitively unimpaired persons, aged 50-95 years, from the population-based Mayo Clinic Study of Aging, we examined the relationships of baseline cognition and cognitive changes across the full range of cortical thickness of an Alzheimer signature region of interest and global β-amyloid levels measured by Pittsburgh compound B positron emission tomography (PIB PET) standardized uptake value ratio (SUVR). In machine-learning models accounting for both biomarkers simultaneously, worsening biomarker values were additive and associated with lower baseline global cognition and greater subsequent decline in global cognition. Associations between Alzheimer's disease signature cortical thickness or PIB PET β-amyloid SUVR and baseline cognition were mainly linear. Lower Alzheimer's disease signature cortical thickness values across the entire range of thickness predicted future decline in global cognitive scores, demonstrating its close relationship to cognitive functioning. PIB PET β-amyloid SUVR also predicted cognitive decline across its full range, even when cortical thickness was accounted for. PIB PET β-amyloid's relationship to cognitive decline was nonlinear, more prominent at lower β-amyloid levels and less prominent at higher β-amyloid levels.

Hypertension is associated with development of white matter hyperintensities (WMH) in the brain, which are risk factors for mild cognitive impairment. Hormonal shifts at menopause alter vascular function putting women at risk for both hypertension and WMH. Elevations in aortic hemodynamics precede the appearance of clinically defined hypertension but the relationship of aortic hemodynamics to development of WMH in women is not known. Therefore, this study aimed to characterize aortic hemodynamics in relationship to WMH in postmenopausal women. Aortic systolic and diastolic blood pressure (BP), aortic augmentation index (Alx) and aortic round trip travel time (Aortic T R) by tonometry were examined in 53 postmenopausal women (age 60 ± 2 years). WMH was calculated from fluid-attenuated inversion recovery MRI using a semi-automated segmentation algorithm. WMH as a fraction of total white matter volume positively associated with aortic systolic BP (regression coefficient = 0.018; p = 0.04) after adjusting for age. In addition, WMH fraction was positively associated with AIx (0.025; p = 0.04), and inversely associated with Aortic T R (-0.015; p = 0.04) after adjusting for age. Our results suggest that assessing aortic hemodynamics may identify individuals at risk for accelerated development of WMH and guide early treatment to reduce WMH burden and cognitive impairment in the future.

To identify common genetic variants associated with the presence of brain microbleeds (BMBs).

Neuropathology and neuroimaging studies have identified several subtypes of Alzheimer's disease (AD): hippocampal sparing AD, typical AD, and limbic predominant AD. An unresolved question is whether hippocampal sparing AD cases can present with neurofibrillary tangles (NFT) in association cortices while completely sparing the hippocampus. To address that question, we conducted a systematic review and performed original analyses on tau positron emission tomography (PET) data. We searched EMBASE, PubMed, and Web of Science databases until October 2022. We also implemented several methods for AD subtyping on tau PET to identify hippocampal sparing AD cases. Our findings show that seven out of the eight reviewed neuropathologic studies included cases at Braak stages IV or higher and therefore, could not identify hippocampal sparing cases with NFT completely sparing the hippocampus. In contrast, tau PET did identify AD participants with tracer retention in the association cortex while completely sparing the hippocampus. We conclude that tau PET can identify hippocampal sparing AD cases with NFT completely sparing the hippocampus. Based on the accumulating data, we suggest two possible pathways of tau spread: (1) a canonical pathway with early involvement of transentorhinal cortex and subsequent involvement of limbic regions and association cortices, and (2) a less common pathway that affects association cortices with limbic involvement observed at end stages of the disease or not at all.

The clinical usefulness MRI biomarkers for aging and dementia studies relies on precise brain morphological measurements; however, scanner and/or protocol variations may introduce noise or bias. One approach to address this is post-acquisition scan harmonization. In this work, we evaluate deep learning (neural style transfer, CycleGAN and CGAN), histogram matching, and statistical (ComBat and LongComBat) methods. Participants who had been scanned on both GE and Siemens scanners (cross-sectional participants, known as Crossover (n = 113), and longitudinally scanned participants on both scanners (n = 454)) were used. The goal was to match GE MPRAGE (T1-weighted) scans to Siemens improved resolution MPRAGE scans. Harmonization was performed on raw native and preprocessed (resampled, affine transformed to template space) scans. Cortical thicknesses were measured using FreeSurfer (v.7.1.1). Distributions were checked using Kolmogorov-Smirnov tests. Intra-class correlation (ICC) was used to assess the degree of agreement in the Crossover datasets and annualized percent change in cortical thickness was calculated to evaluate the Longitudinal datasets. Prior to harmonization, the least agreement was found at the frontal pole (ICC = 0.72) for the raw native scans, and at caudal anterior cingulate (0.76) and frontal pole (0.54) for the preprocessed scans. Harmonization with NST, CycleGAN, and HM improved the ICCs of the preprocessed scans at the caudal anterior cingulate (>0.81) and frontal poles (>0.67). In the Longitudinal raw native scans, over- and under-estimations of cortical thickness were observed due to the changing of the scanners. ComBat matched the cortical thickness distributions throughout but was not able to increase the ICCs or remove the effects of scanner changeover in the Longitudinal datasets. CycleGAN and NST performed slightly better to address the cortical thickness variations between scanner change. However, none of the methods succeeded in harmonizing the Longitudinal dataset. CGAN was the worst performer for both datasets. In conclusion, the performance of the methods was overall similar and region dependent. Future research is needed to improve the existing approaches since none of them outperformed each other in terms of harmonizing the datasets at all ROIs. The findings of this study establish framework for future research into the scan harmonization problem.

Loss-of-function mutations in the progranulin gene (GRN) are one of the major causes of familial frontotemporal lobar degeneration. Our objective was to determine the rates and trajectories of lobar cortical atrophy from longitudinal structural magnetic resonance imaging in both asymptomatic and symptomatic GRN mutation carriers. Individuals in this study were from the ADRC and LEFFTDS studies at the Mayo Clinic. We identified 13 GRN mutation carriers (8 asymptomatic, 5 symptomatic) and noncarriers (n = 10) who had at least 2 serial T1-weighted structural magnetic resonance images and were followed annually with a median of 3 years (range 1.0-9.8 years). Longitudinal changes in lobar cortical volume were analyzed using the tensor-based morphometry with symmetric normalization (TBM-SyN) algorithm. Linear mixed-effect models were used to model cortical volume change over time among 3 groups. The annual rates of frontal (p < 0.05) and parietal (p < 0.01) lobe cortical atrophy were higher in asymptomatic GRN mutation carriers than noncarriers. The symptomatic GRN mutation carriers also had increased rates of atrophy in the frontal (p < 0.01) and parietal lobe (p < 0.01) cortices than noncarriers. In addition, greater rates of cortical atrophy were observed in the temporal lobe cortices of symptomatic GRN mutation carriers than noncarriers (p < 0.001). We found that a decline in frontal and parietal lobar cortical volume occurs in asymptomatic GRN mutation carriers and continues in the symptomatic GRN mutation carriers, whereas an increased rate of temporal lobe cortical atrophy is observed only in symptomatic GRN mutation carriers. This sequential pattern of cortical involvement in GRN mutation carriers has important implications for using imaging biomarkers of neurodegeneration as an outcome measure in potential treatment trials involving GRN mutation carriers.

β-Amyloid (Aβ) pathology is common in patients with probable dementia with Lewy bodies (DLB). However, the pathologic basis and the differential diagnostic performance of Aβ PET are not established in DLB. Our objective was to investigate the pathologic correlates of 11C-Pittsburgh compound B(PiB) uptake on PET in cases with antemortem diagnosis of probable DLB or Lewy body disease (LBD) at autopsy.

Late-life measures of white matter (WM) microstructural integrity may predict cognitive status, cognitive decline, and incident mild cognitive impairment (MCI) or dementia. We considered participants of the Atherosclerosis Risk in Communities study who underwent cognitive assessment and neuroimaging in 2011-2013 and were followed through 2016-2017 (n = 1775 for analyses of prevalent MCI and dementia, baseline cognitive performance, and longitudinal cognitive change and n = 889 for analyses of incident MCI, dementia, or death). Cross-sectionally, both overall WM fractional anisotropy and overall WM mean diffusivity were strongly associated with baseline cognitive performance and risk of prevalent MCI or dementia. Longitudinally, greater overall WM mean diffusivity was associated with accelerated cognitive decline, as well as incident MCI, incident dementia, and mortality, but WM fractional anisotropy was not robustly associated with cognitive change or incident cognitive impairment. Both cross-sectional and longitudinal associations were attenuated after additionally adjusting for likely downstream pathologic changes. Increased WM mean diffusivity may provide an early indication of dementia pathogenesis.

Frontotemporal dementia (FTD) represents a collection of neurobehavioral and neurocognitive syndromes that are associated with a significant degree of clinical, pathological, and genetic heterogeneity. Such heterogeneity hinders the identification of effective biomarkers, preventing effective targeted recruitment of participants in clinical trials for developing potential interventions and treatments. In the present study, we aim to automatically differentiate patients with three clinical phenotypes of FTD, behavioral-variant FTD (bvFTD), semantic variant PPA (svPPA), and nonfluent variant PPA (nfvPPA), based on their structural MRI by training a deep neural network (DNN).

Thal amyloid phase, which describes the pattern of progressive amyloid-β plaque deposition in Alzheimer's disease, was incorporated into the latest National Institute of Ageing - Alzheimer's Association neuropathologic assessment guidelines. Amyloid biomarkers (positron emission tomography and cerebrospinal fluid) were included in clinical diagnostic guidelines for Alzheimer's disease dementia published by the National Institute of Ageing - Alzheimer's Association and the International Work group. Our first goal was to evaluate the correspondence of Thal amyloid phase to Braak tangle stage and ante-mortem clinical characteristics in a large autopsy cohort. Second, we examined the relevance of Thal amyloid phase in a prospectively-followed autopsied cohort who underwent ante-mortem (11)C-Pittsburgh compound B imaging; using the large autopsy cohort to broaden our perspective of (11)C-Pittsburgh compound B results. The Mayo Clinic Jacksonville Brain Bank case series (n = 3618) was selected regardless of ante-mortem clinical diagnosis and neuropathologic co-morbidities, and all assigned Thal amyloid phase and Braak tangle stage using thioflavin-S fluorescent microscopy. (11)C-Pittsburgh compound B studies from Mayo Clinic Rochester were available for 35 participants scanned within 2 years of death. Cortical (11)C-Pittsburgh compound B values were calculated as a standard uptake value ratio normalized to cerebellum grey/white matter. In the high likelihood Alzheimer's disease brain bank cohort (n = 1375), cases with lower Thal amyloid phases were older at death, had a lower Braak tangle stage, and were less frequently APOE-ε4 positive. Regression modelling in these Alzheimer's disease cases, showed that Braak tangle stage, but not Thal amyloid phase predicted age at onset, disease duration, and final Mini-Mental State Examination score. In contrast, Thal amyloid phase, but not Braak tangle stage or cerebral amyloid angiopathy predicted (11)C-Pittsburgh compound B standard uptake value ratio. In the 35 cases with ante-mortem amyloid imaging, a transition between Thal amyloid phases 1 to 2 seemed to correspond to (11)C-Pittsburgh compound B standard uptake value ratio of 1.4, which when using our pipeline is the cut-off point for detection of clear amyloid-positivity regardless of clinical diagnosis. Alzheimer's disease cases who were older and were APOE-ε4 negative tended to have lower amyloid phases. Although Thal amyloid phase predicted clinical characteristics of Alzheimer's disease patients, the pre-mortem clinical status was driven by Braak tangle stage. Thal amyloid phase correlated best with (11)C-Pittsburgh compound B values, but not Braak tangle stage or cerebral amyloid angiopathy. The (11)C-Pittsburgh compound B cut-off point value of 1.4 was approximately equivalent to a Thal amyloid phase of 1-2.

To develop and validate a tool for Alzheimer's disease (AD) diagnosis in individual subjects using support vector machine (SVM)-based classification of structural MR (sMR) images.

The aim of this study was to investigate the rates of lobar atrophy in the asymptomatic microtubule-associated protein tau (MAPT) mutation carriers.

Identifying clinical measures that track disease in the earliest stages of frontotemporal lobar degeneration (FTLD) is important for clinical trials. Familial FTLD provides a unique paradigm to study early FTLD. Executive dysfunction is a clinically relevant hallmark of FTLD and may be a marker of disease progression.

To determine the clinical phenotypes associated with the amyloid-β PET and dopamine transporter imaging (123I-FP-CIT SPECT) findings in mild cognitive impairment (MCI) with the core clinical features of dementia with Lewy bodies (DLB; MCI-LB).

Recent advances in automated face recognition algorithms have increased the risk that de-identified research MRI scans may be re-identifiable by matching them to identified photographs using face recognition. A variety of software exist to de-face (remove faces from) MRI, but their ability to prevent face recognition has never been measured and their image modifications can alter automated brain measurements. In this study, we compared three popular de-facing techniques and introduce our mri_reface technique designed to minimize effects on brain measurements by replacing the face with a population average, rather than removing it. For each technique, we measured 1) how well it prevented automated face recognition (i.e. effects on exceptionally-motivated individuals) and 2) how it altered brain measurements from SPM12, FreeSurfer, and FSL (i.e. effects on the average user of de-identified data). Before de-facing, 97% of scans from a sample of 157 volunteers were correctly matched to photographs using automated face recognition. After de-facing with popular software, 28-38% of scans still retained enough data for successful automated face matching. Our proposed mri_reface had similar performance with the best existing method (fsl_deface) at preventing face recognition (28-30%) and it had the smallest effects on brain measurements in more pipelines than any other, but these differences were modest.