Schwarz, Christopher G.

AbstractBackgroundNeurodegeneration of the substantia nigra in dementia with Lewy bodies is associated with iron deposition, which increases the magnetic susceptibility of the substantia nigra on MRI. The objective of this study was to measure the magnetic susceptibility of the substantia nigra in patients with dementia with Lewy bodies (DLB) and patients with mild cognitive impairment with at least one core feature of DLB (MCI‐DLB) compared to cognitively unimpaired controls (CU) by quantitative susceptibility mapping (QSM).MethodWe studied clinically diagnosed patients with DLB (n=36), patients with MCI‐DLB (n=16), and age‐, gender‐matched CU (n=104) in a case‐control study. MR images used for QSM were performed on 3T MRI with a multi‐echo (5 echoes) 3D gradient recalled echo sequence with a bipolar‐readout. Three‐dimensional regions of interest (ROIs) of bilateral substantia nigra, based on the DISTAL atlas, were propagated from the Mayo Clinic Adult Lifespan Template (MCALT) to each subject’s T1 image using ANTs nonlinear registration. The mean susceptibility values of the substantia nigra were extracted by aligning each subjects QSM image to their T1 image and corresponding ROIs with a 6 DOF rigid registration.ResultThe mean susceptibility values of the substantia nigra bilaterally was 0.110 ± 0.026 for DLB, 0.099 ± 0.028 for MCI‐DLB and 0.091 ± 0.025 for controls (Figure 1). No difference was found across the mean susceptibility from left, right and combined bilateral substantia nigra. Compared to controls, patients with DLB had higher susceptibility in the substantia nigra (p<0.001). The susceptibility of substantia nigra showed an increasing trend from controls to MCI‐DLB and to DLB (p<0.001). There was no correlation between the Unified Parkinson's Disease Rating Scale (UPDRS) and the mean susceptibility in the substantia nigra in patients with MCI‐DLB and DLB (r=0.03; p=0.82).ConclusionQuantitative susceptibility mapping is sensitive to the increased magnetic susceptibility due to higher iron content in the substantia nigra in DLB. The trend of increasing susceptibility from CU to MCI‐DLB and to DLB suggests that iron deposition in the substantia nigra starts to increase as early as the prodromal stage in DLB and continues to increase as the disease progresses independent of the severity of Parkinsonism.

AbstractBackgroundData shared for research use must be de‐identified to protect participant confidentiality. A recent study has shown that face imagery from brain imaging studies could be used to re‐identify anonymous participants via automatic face recognition, linking them with all study‐collected protected health information. Here we measure how well existing software for removing MRI face imagery protects against this privacy threat.MethodWe recruited 153 participants with existing 3D FLAIR MRI and photographed their face from 5 varying angles. We used surf_ice to reconstruct each participant’s face from their MRI and tested whether free, publicly‐available face recognition software (Microsoft Azure) could match their photos to their correct MRI. We tested two existing programs for removing face voxels in MRI: mri_deface (FreeSurfer) and pydeface (python package), and one in‐house implementation. We observed that existing methods often left participants’ eyes intact while removing most of their nose/mouth/chin. This prevented Azure from detecting the reconstructions as faces, therefore preventing its attempt of face recognition. We hypothesized that the retained eye imagery alone could be sufficient for face recognition, if a face were detected. Therefore, we also reconstructed each de‐faced MRI after applying novel pre‐processing that replaced any removed/missing face voxels with those from our population‐average template, e.g. replacing missing noses/mouths/chins with population‐average noses/mouths/chins, before testing face recognition.ResultsWithout any MRI de‐facing, Microsoft Azure correctly matched 78% of participants’ photos to their MRI. After mri_deface and pydeface, 8% and 6% were still identified, respectively. After preprocessing the de‐faced MRI to replace missing areas with those from a population‐average template prior to face reconstruction, the face imagery remaining in the de‐faced images was enough to allow re‐identification of 23% and 20% of participants, respectively. With an in‐house face removal implementation that removes the whole face from every image, 0% of faces were re‐identified from the standard reconstructions, and 5% were identified from the “missing‐parts‐replacement” reconstructions.ConclusionsEven after applying popular MRI de‐facing software, Microsoft Azure face recognition automatically re‐identified up to 23% of participants. Better de‐facing software is needed to remove more of the face more reliably, without affecting brain measurements from de‐faced images.

AbstractBackgroundThe critical‐period theory of menopausal hormone therapy (mHT) suggests that if menopausal hormone therapy begins shortly after menopause, it may have beneficial effects on brain structure and cognitive health. We investigated white matter integrity with diffusion tensor MRI (DTI) 3 years after the end of mHT trial in recently menopausal women who were randomized shortly after menopause.MethodParticipants of this study were enrolled in the Kronos Early Estrogen Prevention Study (aged 42–56 years; 5–36 months past menopause). Participants received the following treatments: 0.45 mg/d oral conjugated equine estrogen (oCEE, n=19); 50 μg/d transdermal 17β‐estradiol (tE2, n=22); or placebo (n=33) for 4 years. Oral progesterone (200 mg/d) was given to hormone therapy groups for 12 days each month. DTI was performed 3 years after the end of 4 years of hormone therapy (n=75), which corresponded to 7 years after randomization. Voxel‐based analysis was performed on DTI to evaluate fractional anisotropy (FA) and mean diffusivity (MD) differences between treatment groups (uncorrected p<0.001).ResultVoxel based analysis showed higher FA, a measure of white matter integrity, in the superior corona radiata, anterior limb of the internal capsule and splenium of the corpus callosum of participants treated with oCEE compared to placebo (p <0.001, Figure 1A). Furthermore, higher FA was observed in the superior corona radiata, anterior limb of internal capsule and thalamus in participants treated with tE2 compared to placebo (p <0.001, Figure 1B). There were no differences in FA findings between oCEE and tE2 groups, and no MD differences between treatments groups.ConclusionA relatively higher FA in a variety of white matter regions in the oCEE and tE2 groups compared to placebo suggest that mHT may have long‐term protective effects on white matter integrity. Previously, we had shown that women in the tE2 group preserved their dorsolateral prefrontal cortex volumes better than the placebo group over 7 years. Our findings suggest that the tracts that connect the dorsolateral prefrontal cortex and the thalamus such as the superior corona radiata and the anterior limb of internal capsule may particularly benefit from mHT.

AbstractBackgroundDementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α‐synuclein aggregations, but many DLB cases show significant Alzheimer’s disease (AD) pathology in the form of β‐amyloid and tau. Our first objective was to investigate the effect of AD co‐pathology on functional network failure in DLB. Secondly, we studied how the distribution of tau relates to functional connectivity in DLB.MethodTwenty‐three DLB, 23 age‐ and sex‐matched AD, and 90 cognitively unimpaired (CU) participants underwent AV1451 tau‐PET, Pittsburgh compound‐B (PiB) PET, and resting state (rs)‐fMRI scans. The rs‐fMRI data were used to calculate the Network Failure Quotient (NFQ), a marker of functional network failure within the default mode network. The NFQ was then correlated with overall cortical tau standardized uptake value ratio (SUVr). The strength of inter‐regional functional connectivity was assessed using the Schaefer100 atlas. Tau‐PET covariance was measured as the correlation in AV1451 SUVr between any two regions across participants. The association between region‐to‐region functional connectivity and tau‐PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot‐ and coldspot) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot‐ and coldspots.ResultOverall higher cortical tau‐PET uptake correlated with higher NFQ (i.e. greater functional network failure) in DLB who were PiB+ (N=14, ρ=0.60, p=0.02), but not in DLB who were PiB‐ (N=9, ρ=‐0.06, p=0.87). Higher functional connectivity between regions was associated with higher tau covariance in CU, AD, and DLB, independent of PiB status. Higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher AV1451 SUVRs in the target region whereas higher functional connectivity to the tau coldspot (i.e. sensory‐motor cortex) was related to lower AV1451 SUVr in the target region.ConclusionGreater tau burden in DLB patients with β‐amyloid co‐pathology is associated with an AD‐like functional network failure. As previously demonstrated within the AD spectrum, functional connectivity may contribute to the spreading of tau across the brain also in DLB.

AbstractThe mechanisms through which tau and amyloid-beta (Aβ) accumulate in the brain of Alzheimer’s disease patients may differ but both are related to neuronal networks. We examined such mechanisms on neuroimaging in 58 participants with atypical Alzheimer’s disease (posterior cortical atrophy or logopenic progressive aphasia). Participants underwent Aβ-PET, longitudinal tau-PET, structural MRI and resting-state functional MRI, which was analyzed with graph theory. Regions with high levels of Aβ were more likely to be functional hubs, with a high number of functional connections important for resilience to cascading network failures. Regions with high levels of tau were more likely to have low clustering coefficients and degrees, suggesting a lack of trophic support or vulnerability to local network failures. Regions strongly functionally connected to the disease epicenters were more likely to have higher levels of tau and, less strongly, of Aβ. The regional rate of tau accumulation was associated with tau levels in functionally connected regions, in support of tau accumulation in a functional network. This study elucidates the relations of tau and Aβ to functional connectivity metrics in atypical Alzheimer’s disease, strengthening the hypothesis that the spread of the 2 proteins is driven by different biological mechanisms related to functional networks.

ObjectiveTo examine associations between tau and amyloid β (Aβ) molecular positron emission tomography (PET) and both Alzheimer‐related pathology and 4‐repeat tau pathology in autopsy‐confirmed frontotemporal lobar degeneration (FTLD).MethodsTwenty‐four patients had [18F]‐flortaucipir–PET and died with FTLD (progressive supranuclear palsy [PSP], n = 10; corticobasal degeneration [CBD], n = 10; FTLD‐TDP, n = 3; and Pick disease, n = 1). All but 1 had Pittsburgh compound B (PiB)‐PET. Braak staging, Aβ plaque and neurofibrillary tangle counts, and semiquantitative tau lesion scores were performed. Flortaucipir standard uptake value ratios (SUVRs) were calculated in a temporal meta region of interest (meta‐ROI), entorhinal cortex and cortical/subcortical regions selected to match the tau lesion analysis. Global PiB SUVR was calculated. Autoradiography was performed in 1 PSP patient, with digital pathology used to quantify tau burden.ResultsNine cases (37.5%) had Aβ plaques. Global PiB SUVR correlated with Aβ plaque count, with 100% specificity and 50% sensitivity for diffuse plaques. Twenty‐one (87.5%) had Braak stages I to IV. Flortaucipir correlated with neurofibrillary tangle counts in entorhinal cortex, but entorhinal and meta‐ROI SUVRs were not elevated in Braak IV or primary age‐related tauopathy. Flortaucipir uptake patterns differed across FTLD pathologies and could separate PSP and CBD. Flortaucipir correlated with tau lesion score in red nucleus and midbrain tegmentum across patients, but not in cortical or basal ganglia regions. Autoradiography demonstrated minimal uptake of flortaucipir, although flortaucipir correlated with quantitative tau burden across regions.InterpretationMolecular PET shows expected correlations with Alzheimer‐related pathology but lacks sensitivity to detect mild Alzheimer pathology in FTLD. Regional flortaucipir uptake was able to separate CBD and PSP. ANN NEUROL 2020;88:1009–1022

Abstract Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer’s clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P &lt; 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer’s disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.