Min, Hoon‐Ki

AbstractINTRODUCTIONThe implications of positive tau positron emission tomography (T) with negative beta amyloid positron emission tomography (A) are not well understood. We investigated cognitive performance in participants who were T+ but A‐.METHODSWe evaluated 98 participants from the Mayo Clinic who were T+ and A‐. Participants were matched 2:1 to A‐ and T‐ cognitively unimpaired (CU) controls. Cognitive test scores were compared between different groups.RESULTSThe A‐T+ group demonstrated lower performance than the A‐T‐ group on the Mini‐Mental Status Exam (MMSE) (p < 0.001), Wechsler Memory Scale‐Revised Logical Memory I (p < 0.001) and Logical Memory II (p < 0.001), Auditory Verbal Learning Test (AVLT) delayed recall (p = 0.004), category fluency (animals p = 0.005; vegetables p = 0.021), Trail Making Test A and B (p < 0.001), and others. There were no significant differences in demographic features or apolipoprotein E (APOE) e4 genotype between CU A‐T+ and CI A‐T+.DISCUSSIONA‐T+ participants show an association with lower cognitive performance.

Abstract Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer’s disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging’s use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

AbstractAlterations 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.

OBJECTIVE Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established neurosurgical treatment for the motor symptoms of Parkinson’s disease (PD). While often highly effective, DBS does not always yield optimal therapeutic outcomes, and stimulation-induced adverse effects, including paresthesia, muscle contractions, and nausea/lightheadedness, commonly occur and can limit the efficacy of stimulation. Currently, objective metrics do not exist for monitoring neural changes associated with stimulation-induced therapeutic and adverse effects. METHODS In the present study, the authors combined intraoperative functional MRI (fMRI) with STN DBS in 20 patients with PD to test the hypothesis that stimulation-induced blood oxygen level–dependent signals contained predictive information concerning the therapeutic and adverse effects of stimulation. RESULTS As expected, DBS resulted in blood oxygen level–dependent activation in myriad motor regions, including the primary motor cortex, caudate, putamen, thalamus, midbrain, and cerebellum. Across the patients, DBS-induced improvements in contralateral Unified Parkinson’s Disease Rating Scale tremor subscores correlated with activation of thalamic, brainstem, and cerebellar regions. In addition, improvements in rigidity and bradykinesia subscores correlated with activation of the primary motor cortex. Finally, activation of specific sensorimotor-related subregions correlated with the presence of DBS-induced adverse effects, including paresthesia and nausea (cerebellar cortex, sensorimotor cortex) and unwanted muscle contractions (caudate and putamen). CONCLUSIONS These results suggest that DBS-induced activation patterns revealed by fMRI contain predictive information with respect to the therapeutic and adverse effects of DBS. The use of fMRI in combination with DBS therefore may hold translational potential to guide and improve clinical stimulator optimization in patients.

AbstractIntroductionComparison of tau (flortaucipir) positron emission tomography (FTP‐PET) to autopsy is important to demonstrate the relationship of FTP‐PET to neuropathologic findings.MethodsAutopsies were performed on 26 participants who had antemortem FTP‐PET. FTP‐PET standardized uptake value ratios (SUVRs) were compared to autopsy diagnoses and Braak tangle stage. Quantitative tau burden was compared to regional FTP‐PET signal.ResultsParticipants with Braak stages of IV or greater had elevated FTP‐PET signal. FTP‐PET was elevated in participants with Alzheimer's disease. An FTP‐PET SUVR cut point of 1.29 was determined to be optimal. Quantitative measurements of hippocampal and temporal lobe tau burden were highly correlated to FTP‐PET signal (rho's from 0.61 to 0.70, P ≤ .02).DiscussionElevated FTP‐PET reflects Braak IV or greater neuropathology. Participants with primary age‐related tauopathy and hippocampal sclerosis did not show elevated FTP‐PET signal. Secondary neuropathologic diagnoses of Alzheimer's disease neuropathologic change can lead to borderline elevated FTP‐PET signal.

Abstract Introduction While the clinical efficacy of deep brain stimulation (DBS) the treatment of motor‐related symptoms is well established, the mechanism of action of the resulting cognitive and behavioral effects has been elusive. Methods By combining functional magnetic resonance imaging (fMRI) and DBS, we investigated the pattern of blood‐oxygenation‐level‐dependent (BOLD) signal changes induced by stimulating the nucleus accumbens in a large animal model. Results We found that diffused BOLD activation across multiple functional networks, including the prefrontal, limbic, and thalamic regions during the stimulation, resulted in a significant change in inter‐regional functional connectivity. More importantly, the magnitude of the modulation was closely related to the strength of the inter‐regional resting‐state functional connectivity. Conclusions Nucleus accumbens stimulation affects the functional activity in networks that underlie cognition and behavior. Our study provides an insight into the nature of the functional connectivity, which mediates activation effect via brain networks.