Predictive Value of \u3csup\u3e18\u3c/sup\u3eF-Florbetapir and \u3csup\u3e18\u3c/sup\u3eF-FDG PET for Conversion from Mild Cognitive Impairment to Alzheimer Dementia

© 2020 by the Society of Nuclear Medicine and Molecular Imaging. The present study examined the predictive values of amyloid PET, 18F-FDG PET, and nonimaging predictors (alone and in combination) for development of Alzheimer dementia (AD) in a large population of patients with mild cognitive impairment (MCI). Methods: The study included 319 patients with MCI from the Alzheimer Disease Neuroimaging Initiative database. In a derivation dataset (n = 159), the following Cox proportional-hazards models were constructed, each adjusted for age and sex: amyloid PET using 18F-florbetapir (pattern expression score of an amyloid-β AD conversion-related pattern, constructed by principle-components analysis); 18F-FDG PET (pattern expression score of a previously defined 18F-FDG-based AD conversion-related pattern, constructed by principle-components analysis); nonimaging (functional activities questionnaire, apolipoprotein E, and mini-mental state examination score); 18F-FDG PET + amyloid PET; amyloid PET + nonimaging; 18F-FDG PET + nonimaging; and amyloid PET + 18F-FDG PET + nonimaging. In a second step, the results of Cox regressions were applied to a validation dataset (n = 160) to stratify subjects according to the predicted conversion risk. Results: On the basis of the independent validation dataset, the 18F-FDG PET model yielded a significantly higher predictive value than the amyloid PET model. However, both were inferior to the nonimaging model and were significantly improved by the addition of nonimaging variables. The best prediction accuracy was reached by combining 18F-FDG PET, amyloid PET, and nonimaging variables. The combined model yielded 5-y free-of-conversion rates of 100%, 64%, and 24% for the low-, medium- and high-risk groups, respectively. Conclusion:18F-FDG PET, amyloid PET, and nonimaging variables represent complementary predictors of conversion from MCI to AD. Especially in combination, they enable an accurate stratification of patients according to their conversion risks, which is of great interest for patient care and clinical trials

Learning Optimal Deep Projection of 18^{18}F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes

Several diseases of parkinsonian syndromes present similar symptoms at early stage and no objective widely used diagnostic methods have been approved until now. Positron emission tomography (PET) with $^{18}$F-FDG was shown to be able to assess early neuronal dysfunction of synucleinopathies and tauopathies. Tensor factorization (TF) based approaches have been applied to identify characteristic metabolic patterns for differential diagnosis. However, these conventional dimension-reduction strategies assume linear or multi-linear relationships inside data, and are therefore insufficient to distinguish nonlinear metabolic differences between various parkinsonian syndromes. In this paper, we propose a Deep Projection Neural Network (DPNN) to identify characteristic metabolic pattern for early differential diagnosis of parkinsonian syndromes. We draw our inspiration from the existing TF methods. The network consists of a (i) compression part: which uses a deep network to learn optimal 2D projections of 3D scans, and a (ii) classification part: which maps the 2D projections to labels. The compression part can be pre-trained using surplus unlabelled datasets. Also, as the classification part operates on these 2D projections, it can be trained end-to-end effectively with limited labelled data, in contrast to 3D approaches. We show that DPNN is more effective in comparison to existing state-of-the-art and plausible baselines.Comment: 8 pages, 3 figures, conference, MICCAI DLMIA, 201

Metabolic resting-state brain networks in health and disease

The delineation of resting state networks (RSNs) in the human brain relies on the analysis of temporal fluctuations in functional MRI signal, representing a small fraction of total neuronal activity. Here, we used metabolic PET, which maps nonfluctuating signals related to total activity, to identify and validate reproducible RSN topographies in healthy and disease populations. In healthy subjects, the dominant (first component) metabolic RSN was topographically similar to the default mode network (DMN). In contrast, in Parkinson\u27s disease (PD), this RSN was subordinated to an independent disease-related pattern. Network functionality was assessed by quantifying metabolic RSN expression in cerebral blood flow PET scans acquired at rest and during task performance. Consistent task-related deactivation of the DMN-like dominant metabolic RSN was observed in healthy subjects and early PD patients; in contrast, the subordinate RSNs were activated during task performance. Network deactivation was reduced in advanced PD; this abnormality was partially corrected by dopaminergic therapy. Time-course comparisons of DMN loss in longitudinal resting metabolic scans from PD and Alzheimer\u27s disease subjects illustrated that significant reductions appeared later for PD, in parallel with the development of cognitive dysfunction. In contrast, in Alzheimer\u27s disease significant reductions in network expression were already present at diagnosis, progressing over time. Metabolic imaging can directly provide useful information regarding the resting organization of the brain in health and disease

Atypical disengagement from faces and its modulation by the control of eye fixation in children with Autism Spectrum Disorder

By using the gap overlap task, we investigated disengagement from faces and objects in children (9–17 years old) with and without autism spectrum disorder (ASD) and its neurophysiological correlates. In typically developing (TD) children, faces elicited larger gap effect, an index of attentional engagement, and larger saccade-related event-related potentials (ERPs), compared to objects. In children with ASD, by contrast, neither gap effect nor ERPs differ between faces and objects. Follow-up experiments demonstrated that instructed fixation on the eyes induces larger gap effect for faces in children with ASD, whereas instructed fixation on the mouth can disrupt larger gap effect in TD children. These results suggest a critical role of eye fixation on attentional engagement to faces in both groups

Automatic covariance pattern analysis outperforms visual reading of 18 F‐fluorodeoxyglucose‐positron emission tomography (FDG‐PET) in variant progressive supranuclear palsy

Background: To date, studies on positron emission tomography (PET) with F-18-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS). Objectives: To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice. Methods: This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern. Results: Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample. Conclusions: Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. (C) 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Cerebral activations related to ballistic, stepwise interrupted and gradually modulated movements in parkinson patients

Patients with Parkinson's disease (PD) experience impaired initiation and inhibition of movements such as difficulty to start/stop walking. At single-joint level this is accompanied by reduced inhibition of antagonist muscle activity. While normal basal ganglia (BG) contributions to motor control include selecting appropriate muscles by inhibiting others, it is unclear how PD-related changes in BG function cause impaired movement initiation and inhibition at single-joint level. To further elucidate these changes we studied 4 right-hand movement tasks with fMRI, by dissociating activations related to abrupt movement initiation, inhibition and gradual movement modulation. Initiation and inhibition were inferred from ballistic and stepwise interrupted movement, respectively, while smooth wrist circumduction enabled the assessment of gradually modulated movement. Task-related activations were compared between PD patients (N = 12) and healthy subjects (N = 18). In healthy subjects, movement initiation was characterized by antero-ventral striatum, substantia nigra (SN) and premotor activations while inhibition was dominated by subthalamic nucleus (STN) and pallidal activations, in line with the known role of these areas in simple movement. Gradual movement mainly involved antero-dorsal putamen and pallidum. Compared to healthy subjects, patients showed reduced striatal/SN and increased pallidal activation for initiation, whereas for inhibition STN activation was reduced and striatal-thalamo-cortical activation increased. For gradual movement patients showed reduced pallidal and increased thalamo-cortical activation. We conclude that PD-related changes during movement initiation fit the (rather static) model of alterations in direct and indirect BG pathways. Reduced STN activation and regional cortical increased activation in PD during inhibition and gradual movement modulation are better explained by a dynamic model that also takes into account enhanced responsiveness to external stimuli in this disease and the effects of hyper-fluctuating cortical inputs to the striatum and STN in particular

Prefrontal and anterior cingulate cortex abnormalities in Tourette Syndrome: evidence from voxel-based morphometry and magnetization transfer imaging

<p>Abstract</p> <p>Background</p> <p>Pathophysiological evidence suggests an involvement of fronto-striatal circuits in Tourette syndrome (TS). To identify TS related abnormalities in gray and white matter we used optimized voxel-based morphometry (VBM) and magnetization transfer imaging (MTI) which are more sensitive to tissue alterations than conventional MRI and provide a quantitative measure of macrostructural integrity.</p> <p>Methods</p> <p>Volumetric high-resolution anatomical T1-weighted MRI and MTI were acquired in 19 adult, unmedicated male TS patients without co-morbidities and 20 age- and sex-matched controls on a 1.5 Tesla neuro-optimized GE scanner. Images were pre-processed and analyzed using an optimized version of VBM in SPM2.</p> <p>Results</p> <p>Using VBM, TS patients showed significant decreases in gray matter volumes in prefrontal areas, the anterior cingulate gyrus, sensorimotor areas, left caudate nucleus and left postcentral gyrus. Decreases in white matter volumes were detected in the right inferior frontal gyrus, the left superior frontal gyrus and the anterior corpus callosum. Increases were found in the left middle frontal gyrus and left sensorimotor areas. In MTI, white matter reductions were seen in the right medial frontal gyrus, the inferior frontal gyrus bilaterally and the right cingulate gyrus. Tic severity was negatively correlated with orbitofrontal structures, the right cingulate gyrus and parts of the parietal-temporal-occipital association cortex bilaterally.</p> <p>Conclusion</p> <p>Our MRI <it>in vivo </it>neuropathological findings using two sensitive and unbiased techniques support the hypothesis that alterations in frontostriatal circuitries underlie TS pathology. We suggest that anomalous frontal lobe association and projection fiber bundles cause disinhibition of the cingulate gyrus and abnormal basal ganglia function.</p

Knowledge gaps and research recommendations for essential tremor

Essential tremor (ET) is a common cause of significant disability, but its etiologies and pathogenesis are poorly understood. Research has been hampered by the variable definition of ET and by non-standardized research approaches. The National Institute of Neurological Disorders and Stroke (USA) invited experts in ET and related fields to discuss current knowledge, controversies, and gaps in our understanding of ET and to develop recommendations for future research. Discussion focused on phenomenology and phenotypes, therapies and clinical trials, pathophysiology, pathology, and genetics. Across all areas, the need for collaborative and coordinated research on a multinational level was expressed. Standardized data collection using common data elements for genetic, clinical, neurophysiological, and pathological studies was recommended. Large cohorts of patients should be studied prospectively to collect bio-samples, characterize the natural history of the clinical syndrome including patient-oriented outcomes, investigate potential etiologies of various phenotypes, and identify pathophysiological mechanisms. In particular, cellular and system-level mechanisms of tremor oscillations should be elucidated because they may yield effective therapeutic targets and biomarkers. A neuropathology consortium was recommended to standardize postmortem analysis and further characterize neuropathological observations in the cerebellum and elsewhere. Furthermore, genome-wide association studies on large patient cohorts (>10,000 patients) may allow the identification of common genes contributing to risk, and whole exome or genome sequencing may enable the identification of genetic risk and causal mutations in cohorts and well-characterized families