Rates of brain atrophy derived from serial magnetic resonance (MR) studies may be used to assess therapies for Alzheimer's disease (AD). These measures may be confounded by changes in scanner voxel sizes. For this reason, the Alzheimer's Disease Neuroimaging Initiative (ADNI) included the imaging of a geometric phantom with every scan. This study compares voxel scaling correction using a phantom with correction using a 9 degrees of freedom (9DOF) registration algorithm. We took 129 pairs of baseline and 1-year repeat scans, and calculated the volume scaling correction, previously measured using the phantom. We used the registration algorithm to quantify any residual scaling errors, and found the algorithm to be unbiased, with no significant (p=0.97) difference between control (n=79) and AD subjects (n=50), but with a mean (SD) absolute volume change of 0.20 (0.20) % due to linear scalings. 9DOF registration was shown to be comparable to geometric phantom correction in terms of the effect on atrophy measurement and unbiased with respect to disease status. These results suggest that the additional expense and logistic effort of scanning a phantom with every patient scan can be avoided by registration-based scaling correction. Furthermore, based upon the atrophy rates in the AD subjects in this study, sample size requirements would be approximately 10-12% lower with (either) correction for voxel scaling than if no correction was used.

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.

We aimed to determine whether network-level functional connectivity differs in 2 clinical variants of Alzheimer's disease: logopenic primary progressive aphasia (lvPPA) and dementia of the Alzheimer's type (DAT). Twenty-four lvPPA subjects with amyloid deposition on positron emission tomography and task-free functional magnetic resonance imaging were matched to 24 amyloid-positive DAT subjects and 24 amyloid-negative controls. Independent-component analysis and spatial-temporal dual regression were used to assess functional connectivity within the language network, left and right working memory networks, and ventral default mode network. lvPPA showed reduced connectivity in left temporal language network and inferior parietal and prefrontal regions of the left working memory network compared with controls and DAT. Both groups showed reduced connectivity in the parietal regions of the right working memory network compared with controls. Only DAT showed reduced ventral default mode network connectivity compared with controls. Aphasia severity correlated with connectivity in the left working memory network within lvPPA. Patterns of network dysfunction differ across these 2 clinical variants of Alzheimer's disease, with lvPPA particularly associated with disruptions in the language and left working memory networks.

The objective of our study was to evaluate whether cognitively normal (CN) elderly participants showing elevated cortical beta-amyloid (Aβ) deposition have a consistent neuroanatomical signature of brain atrophy that may characterize preclinical Alzheimer's disease (AD). 115 CN participants who were Aβ-positive (CN +) by amyloid PET imaging; 115 CN participants who were Aβ-negative (CN -); and 88 Aβ-positive mild cognitive impairment or AD participants (MCI/AD +) were identified. Cortical thickness (FreeSurfer) and gray matter volume (SPM5) were measured for 28 regions-of-interest (ROIs) across the brain and compared across groups. ROIs that best discriminated CN - from CN + differed for FreeSurfer cortical thickness and SPM5 gray matter volume. Group-wise discrimination was poor with a high degree of uncertainty in terms of the rank ordering of ROIs. In contrast, both techniques showed strong and consistent findings comparing MCI/AD + to both CN - and CN + groups, with entorhinal cortex, middle and inferior temporal lobe, inferior parietal lobe, and hippocampus providing the best discrimination for both techniques. Concordance across techniques was higher for the CN - and CN + versus MCI/AD + comparisons, compared to the CN - versus CN + comparison. The weak and inconsistent nature of the findings across technique in this study cast doubt on the existence of a reliable neuroanatomical signature of preclinical AD in elderly PiB-positive CN participants.

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.

To test the hypotheses predicted in a hypothetical model of Alzheimer disease (AD) biomarkers that rates of β-amyloid (Aβ) accumulation on PET imaging are not related to hippocampal neurodegeneration whereas rates of neurodegenerative brain atrophy depend on the presence of both amyloid and neurodegeneration in a population-based sample.

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.

Measures of brain change can be computed from sequential MRI scans, providing valuable information on disease progression, e.g., for patient monitoring and drug trials. Tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of tissue growth or atrophy, but its sensitivity depends on the contrast and geometric stability of the images. As part of the Alzheimer's Disease Neuroimaging Initiative (ADNI), 17 normal elderly subjects were scanned twice (at a 2-week interval) with several 3D 1.5 T MRI pulse sequences: high and low flip angle SPGR/FLASH (from which Synthetic T1 images were generated), MP-RAGE, IR-SPGR (N = 10) and MEDIC (N = 7) scans. For each subject and scan type, a 3D deformation map aligned baseline and follow-up scans, computed with a nonlinear, inverse-consistent elastic registration algorithm. Voxelwise statistics, in ICBM stereotaxic space, visualized the profile of mean absolute change and its cross-subject variance; these maps were then compared using permutation testing. Image stability depended on: (1) the pulse sequence; (2) the transmit/receive coil type (birdcage versus phased array); (3) spatial distortion corrections (using MEDIC sequence information); (4) B1-field intensity inhomogeneity correction (using N3). SPGR/FLASH images acquired using a birdcage coil had least overall deviation. N3 correction reduced coil type and pulse sequence differences and improved scan reproducibility, except for Synthetic T1 images (which were intrinsically corrected for B1-inhomogeneity). No strong evidence favored B0 correction. Although SPGR/FLASH images showed least deviation here, pulse sequence selection for the ADNI project was based on multiple additional image analyses, to be reported elsewhere.

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.

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.

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.

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

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.

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.

Using positron emission tomography (PET)-derived amyloid and tau measurements from 1,495 participants, we explore the evolution of these values over time via an accelerated failure time (AFT) model. The AFT model assumes a shared pattern of progression, but one which is shifted earlier or later in time for each individual; an individual's time shift for amyloid and for tau are assumed to be linked. The resulting pattern for each outcome consists of an earlier indolent phase followed by sharp progression of the accumulation rate. APOE ε4 shifts the amyloid curve leftward (earlier) by 6.1 years, and the tau curve leftward by 2.6 years. Female sex shifts the amyloid curve leftward by 2.4 years and the tau curve leftward by 2.6 years. Per-person shifts (i.e., the individual's deviation from the population mean) for the onset of amyloid accumulation ranged from 13 years earlier to 13 years later (10th to 90th percentile) than average and 11 years earlier to 14 years later for tau, with an estimated correlation of 0.49. The average delay between amyloid increase and tau increase was 13.3 years.

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.

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.

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).