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INTRODUCTION: Multiple system atrophy (MSA) typically presents with parkinsonism, ataxia and/or autonomic dysfunction. Occasionally, clinically atypical (ca-MSA) cases masquerade as progressive supranuclear palsy (PSP). We aimed to investigate whether different neuroimaging modalities could facilitate differentiation and whether histopathologic characteristics could explain the atypical presentation. METHODS: We identified 3 neuropathologically-defined ca-MSA patients with clinically diagnosed PSP who underwent various antemortem brain imaging: MRI and PET imaging using (11)C-Pittsburgh compound B, (18)F-flortaucipir, and (18)F-fluorodeoxyglucose. We compared clinical features, brainstem planimetry, and radiotracer standardized uptake value ratios in ca-MSA to 10 autopsy-confirmed PSP patients and 10 healthy controls (imaging only). We also compared histologic count of neuronal loss, iron deposition and α-synuclein-immunoreactive glial cytoplasmic inclusion burden to 10 autopsy-confirmed MSA-parkinsonism (MSA-P) cases. RESULTS: Ca-MSA had better PSP Saccadic Impairment Scale scores (p=0.003) and more frequent good levodopa response (p=0.061) than PSP. Ca-MSA showed higher midbrain-to-pons ratio and lower Magnetic Resonance Parkinsonism Index than PSP (each, p=0.036) and exhibited lower glucose metabolism in the putamen and globus pallidus versus PSP (p=0.017) and controls (p=0.007). These same regions showed higher flortaucipir uptake in ca-MSA than PSP (p=0.007 for putamen, p=0.049 for pallidum) and controls (p=0.012). Lower flortaucipir retention was observed in the subthalamic nucleus versus PSP (p=0.007). The putamen-to-subthalamic ratio distinguished ca-MSA from PSP. No histopathological differences were observed for ca-MSA versus typical MSA-P. CONCLUSION: Severity of saccadic impairment, levodopa responsiveness, MRI planimetric measurements, and different patterns of fluorodeoxyglucose and flortaucipir uptake can help improve antemortem differentiation of MSA masquerading as PSP from true PSP.

Alterations of cerebral glucose metabolism can be detected in patients with isolated rapid eye movement sleep behaviour disorder, a prodromal feature of neurodegenerative diseases with α-synuclein pathology. However, metabolic characteristics that determine clinical progression in isolated rapid eye movement sleep behaviour disorder and their association with other biomarkers need to be elucidated. We investigated the pattern of cerebral glucose metabolism on 18F-fluorodeoxyglucose PET in patients with isolated rapid eye movement sleep behaviour disorder, differentiating between those who clinically progressed and those who remained stable over time. Second, we studied the association between 18F-fluorodeoxyglucose PET and lower dopamine transporter availability in the putamen, another hallmark of synucleinopathies. Patients with isolated rapid eye movement sleep behaviour disorder from the Mayo Clinic Alzheimer’s Disease Research Center and Center for Sleep Medicine (n = 22) and age-and sex-matched clinically unimpaired controls (clinically unimpaired; n = 44) from the Mayo Clinic Study of Aging were included. All participants underwent 18F-fluorodeoxyglucose PET and dopamine transporter imaging with iodine 123-radiolabeled 2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane on single-photon emission computerized tomography. A subset of patients with isolated rapid eye movement sleep behaviour disorder with follow-up evaluations (n = 17) was classified as isolated rapid eye movement sleep behaviour disorder progressors (n = 7) if they developed mild cognitive impairment or Parkinson’s disease; or isolated rapid eye movement sleep behaviour disorder stables (n = 10) if they remained with a diagnosis of isolated rapid eye movement sleep behaviour disorder with no cognitive impairment. Glucose metabolic abnormalities in isolated rapid eye movement sleep behaviour disorder were determined by comparing atlas-based regional 18F-fluorodeoxyglucose PET uptake between isolated rapid eye movement sleep behaviour disorder and clinically unimpaired. Associations between 18F-fluorodeoxyglucose PET and dopamine transporter availability in the putamen were analyzed with Pearson’s correlation within the nigrostriatal pathway structures and with voxel-based analysis in the cortex. Patients with isolated rapid eye movement sleep behaviour disorder had lower glucose metabolism in the substantia nigra, retrosplenial cortex, angular cortex, and thalamus, and higher metabolism in the amygdala and entorhinal cortex compared with clinically unimpaired. Patients with isolated rapid eye movement sleep behaviour disorder who clinically progressed over time were characterized by higher glucose metabolism in the amygdala and entorhinal cortex, and lower glucose metabolism in the cerebellum compared with clinically unimpaired. Lower dopamine transporter availability in the putamen was associated with higher glucose metabolism in the pallidum within the nigrostriatal pathway; and with higher 18F-fluorodeoxyglucose uptake in the amygdala, insula, and temporal pole on a voxel-based analysis, although these associations did not survive after correcting for multiple comparisons. Our findings suggest that cerebral glucose metabolism in isolated rapid eye movement sleep behaviour disorder is characterized by hypometabolism in regions frequently affected during the prodromal stage of synucleinopathies, potentially reflecting synaptic dysfunction. Hypermetabolism is also seen in isolated rapid eye movement sleep behaviour disorder, suggesting that synaptic metabolic disruptions may be leading to a lack of inhibition, compensatory mechanisms, or microglial activation, especially in regions associated with nigrostriatal degeneration.

Alzheimer's disease (AD) patients ≥70 years show smaller medial temporal volumes despite lessSeventy-seven participants with flortaucipir-PET and volumetric magnetic resonance imaging underwent postmortem AD and TDP-43 pathology assessments. Bivariate-response linear regression estimated the effect of age and TDP-43 pathology on volume and/or flortaucipir standardized uptake volume ratios of the hippocampus, amygdala, entorhinal, inferior temporal, and midfrontal cortices.Older participants had lower hippocampal volumes and overall flortaucipir uptake. TDP-43-immunoreactivity correlated with reduced medial temporal volumes but was unrelated to flortaucipir uptake. TDP-43 effect size was consistent across the age spectrum. However, at older ages, the cohort mean volumes moved toward those of TDP-43-positives, reflecting the increasing TDP-43 pathology frequency with age.TDP-43 pathology is a relevant contributor driving the volume-uptake mismatch in older AD participants.TDP-43 pathology affects medial temporal volume loss but not tau radiotracer uptake. Greater TDP-43 pathology effect is seen in old age due to its increasing frequency. TDP-43 pathology is a relevant driver of the volume-uptake mismatch in old AD patients.

Introduction: Cerebrovascular disease (CVD) and neuropsychiatric symptoms (NPS) are common in older adults and are independently associated with cognitive impairment. In addition, vascular depression (a late-life depression) is hypothesized to be associated with cerebrovascular pathology. Hypothesis: CVD pathology imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) are associated with depression and anxiety, and both (depression/anxiety and CVD imaging biomarkers) are independently associated with mild cognitive impairment (MCI). Methods: This cross-sectional study included 1739 Mayo Clinic Study of Aging participants (≥50 years old) without dementia, with comprehensive cognitive evaluations and available data on the Beck Depression Inventory II (BDI), the Beck Anxiety Inventory (BAI) and imaging CVD biomarkers via FLAIR-MRI (i.e., WMH% of total intracranial volume (TIV) and brain infarctions). We used linear and logistic regression models to examine the associations adjusting for age, sex, education, and apolipoprotein E ε4 status. Results: Participants’ mean age (SD) was 71.11 (10.61) years (53.3% males). Higher WMH% TIV burden was significantly associated with higher BDI (b= 0.082, 95%CI: 0.031, 0.133), p=0.002) and BAI scores (b= 0.088, 95%CI: 0.037, 0.140), p=0.001); the presence of infarctions was also associated with a higher BDI score. Both WMH %TIV burden (OR: 1.20 (95%CI:1.05, 1.38), p=0.008) and BDI score (OR: 1.38 (95%CI:1.21, 1.57), p Conclusions: CVD imaging biomarkers and NPS, as measured by BDI and BAI scores, could represent two distinct processes associated with cognitive impairment. Studies are ongoing to further examine these associations and delineate how CVD, NPS, and other pathophysiology processes (e.g., Alzheimer’s disease) interact and are associated with cognitive impairment.

BACKGROUND Interpretation of serial magnetic resonance imaging (MRI) for glioblastoma following radiation therapy (RT) is complicated by difficulty differentiating tumor from treatment-related changes, even using updated RANO criteria. The incorporation of novel imaging such as 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA) PET/CT to post-treatment serial imaging may improve prognostication and better facilitate future treatment decisions. METHODS The secondary analysis of a recent phase II prospective clinical trial of 18F-DOPA PET/CT-directed dose-escalated RT included patients with IDH-wildtype, MGMT-unmethylated glioblastoma who underwent post-treatment serial 18F-DOPA PET/CT surveillance. Quantitative features were extracted from pre-RT and post-RT serial PET/CT images, and robust prognostic features were selected using an in-house workflow. Both an automated machine learning (ML) algorithm and an interpretable ML algorithm were utilized to correlate surveillance PET image features with subsequent survival of greater than 12 months versus less than 12 months from the surveillance timepoint. Changes from pre-RT to post-RT PET/CT (delta model) were also assessed for association with post-RT survival and validated with a separate cohort. RESULTS Thirty-five patients with IDH-wildtype, MGMT-unmethylated glioblastoma who had at least one available (range: 1-14) post-treatment 18F-DOPA PET/CT were included. Twenty-four were used for model training, while 11 were used for validation. Ultimately, a five-feature post-RT model utilizing two shape, two texture, and one first-order radiomic feature was selected. For the delta model, five texture, two shape, and one first order radiomic feature were selected. The models show 90% accuracy in predicting survival < 12 months post-surveillance on the training set, and 68%-73% accuracy (AUC 0.64-0.73) for the validation cohort. Delta features were significantly associated with overall survival (p < 0.05). CONCLUSIONS Post-RT serial 18F-DOPA PET/CT imaging can help distinguish true tumor progression in patients with glioblastoma using a radiomics model. Tumor response evaluated for changes from pre-RT to post-RT 18F-DOPA PET/CT also predicted subsequent overall survival.

Mild cognitive impairment with the core clinical features of dementia with Lewy bodies is recognized as a prodromal stage of dementia with Lewy bodies. Although grey matter atrophy has been demonstrated in prodromal dementia with Lewy bodies, longitudinal rates of atrophy during progression to probable dementia with Lewy bodies are unknown. We investigated the regional patterns of cross-sectional and longitudinal rates of grey matter atrophy in prodromal dementia with Lewy bodies, including those who progressed to probable dementia with Lewy bodies. Patients with mild cognitive impairment with at least one core clinical feature of dementia with Lewy bodies (mean age = 70.5; 95% male), who were enrolled in the Mayo Clinic Alzheimer’s Disease Research Center and followed for at least two clinical evaluations and MRI examinations, were included (n = 56). A cognitively unimpaired control group (n = 112) was matched 2:1 to the patients with mild cognitive impairment by age and sex. Patients either remained stable (n = 28) or progressed to probable dementia with Lewy bodies (n = 28) during a similar follow-up period and pathologic confirmation was available in a subset of cases (n = 18). Cross-sectional and longitudinal rates of grey matter atrophy were assessed using voxel-based and atlas-based region of interest analyses. At baseline, prodromal dementia with Lewy bodies was characterized by atrophy in the nucleus basalis of Meynert both in those who remained stable and those who progressed to probable dementia with Lewy bodies (P

Our previous work demonstrated that 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (Patients with newly diagnosed, histologically confirmed glioblastoma aged ≥18 years without contraindications toBetween January 2014 and December 2018, 75 evaluable patients were enrolled (39 DE-Un, 24 methylated [DE-Mth], and 12 indeterminate). PFS6 for DE-Un was 79.5% (95% confidence interval, 63.1%-90.1%). Median PFS was longer for DE-Un patients compared with historical controls (8.7 months vs 6.6 months; P = .017). OS was similarly longer, but the difference was not significant (16.0 vs 13.5 months; P = .13). OS was significantly improved for DE-Mth patients compared with HC-Mth (35.5 vs 23.3 months; P = .049) despite nonsignificant improvement in PFS (10.7 vs 9.0 months; P = .26). Grade 3 central nervous system necrosis occurred in 13% of patients, but treatment with bevacizumab improved symptoms in all cases.

PURPOSE: Methylation of the O(6)-methylguanine methyltransferase (MGMT) gene promoter is associated with improved treatment response and survival in patients with Glioblastoma (GB), but the necessary pathological specimen can be non-diagnostic. In this study, we assessed whether radiomics features pre-treatment (18)F-DOPA PET imaging could be used to predict pathologic MGMT status. METHODS: This study included 86 patients with newly diagnosed GB, split into three groups (training, validating, predicting). We performed radiomics analysis on (18)F-DOPA PET images by extracting features two tumor-based contours: a “Gold” contour of all abnormal uptake per expert Nuclear Medicine physician, and an “HGG” contour based on a T/N > 20 representing the most aggressive components. Feature selection was performed by comparing the weighted feature importance and filtering with bivariate analysis. Optimization of model parameters was explored using grid search with selected features. The stability of the model with increasing input features was also investigated for model robustness. The model predictions were then applied by comparing the overall survival (OS) probability of the GB patients with unknown MGMT status vs those with known MGMT status. RESULTS: A radiomics signature was constructed to predict MGMT methylation status. Using features extracted HGG contour alone with a Random Forest model, we achieved 80% ± 10% accuracy for 95% confidence level in predicting MGMT status. The prediction accuracy was not improved with the addition of the Gold contour or with more input features. The model was applied to the patients with unknown MGMT methylation status. The prediction results are consistent with what is expected using OS as a surrogate. CONCLUSIONS: This study suggests that 3 features radiomics modeling of (18)F-DOPA PET imaging can predict the MGMT methylation status with reasonable accuracy. It may provide valuable therapeutic guidance for patients where MGMT testing is inconclusive or non-diagnostic.

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

Objective To characterize the shape of the trajectories of Alzheimer disease biomarkers as a function of Mini-Mental State Examination (MMSE) score. Design and Setting Longitudinal registries from the Mayo Clinic and the Alzheimer's Disease Neuroimaging Initiative. Patients Two different samples (n = 343 and n = 598) were created that spanned the cognitive spectrum from normal to Alzheimer disease dementia. Subgroup analyses were performed in members of both cohorts (n = 243 and n = 328) who were amyloid positive at baseline. Main Outcome Measures The shape of biomarker trajectories as a function of MMSE score, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebrospinal fluid (CSF) Aβ42 and tau levels, amyloid and fluorodeoxyglucose positron emission tomography imaging, and structural magnetic resonance imaging. Results Baseline biomarker values generally worsened (ie, nonzero slope) with lower baseline MMSE score. Baseline hippocampal volume, amyloid positron emission tomography, and fluorodeoxyglucose positron emission tomography values plateaued (ie, nonlinear slope) with lower MMSE score in 1 or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE score. Nonconstant within-subject rates (deceleration) of biomarker change were found in only 1 model. Conclusions Biomarker trajectory shapes by MMSE score were complex and were affected by interactions with age and APOE status. Nonlinearity was found in several baseline effects models. Nonconstant within-subject rates of biomarker change were found in only 1 model, likely owing to limited within-subject longitudinal follow-up. Creating reliable models that describe the full trajectories of Alzheimer disease biomarkers will require significant additional longitudinal data in individual participants.