Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.

PURPOSE: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA). METHODS: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level. RESULTS: Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912). CONCLUSION: Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

Structural and metabolic brain correlates of arithmetic word-problem solving in Huntington's disease.

Individuals with pre-manifest and early symptomatic Huntington's disease (HD) have shown deficits in solving arithmetic word-problems. However, the neural correlates of these deficits in HD are poorly understood. We explored the structural (gray-matter volume; GMV) and metabolic (18F-FDG PET; SUVr) brain correlates of arithmetic performance using the recently developed HD-word problem arithmetic task (HD-WPA) in seventeen preHD and sixteen HD individuals. Symptomatic participants showed significantly lower scores in the HD-WPA than preHD participants. Lower performance in the HD-WPA was associated with reduced GMV in subcortical, medial frontal, and several posterior-cortical clusters in HD participants. No significant GMV loss was found in preHD participants. 18F-FDG data revealed a widespread pattern of hypometabolism in association with lower arithmetic performance in all participants. In preHD participants, this pattern was restricted to the ventrolateral and orbital prefrontal cortex, the insula, and the precentral gyrus. In HD participants, the pattern extended to several parietal-temporal regions. Word-problem solving arithmetic deficits in HD is subserved by a pattern of asynchronous metabolic and structural compromise across the cerebral cortex as a function of disease stage. In preHD individuals, arithmetic deficits were associated with prefrontal alterations, whereas in symptomatic HD patients, more severe arithmetic deficits are associated with the compromise of several frontal-subcortical and temporo-parietal regions. Our results support the hypothesis that cognitive deficits in HD are not exclusively dominated by frontal-striatal dysfunctions but also involve fronto-temporal and parieto-occipital damage.

The Kappa Opioid Receptor and the Sleep of Reason: Cortico-Subcortical Imbalance Following Salvinorin-A.

BACKGROUND: The mechanisms through which kappa opioid receptor (KOR) agonists induce psychotomimetic effects are largely unknown, although the modulation of this receptor has attracted attention for its clinical use. In this work, we characterize the neuropharmacological effects of salvinorin-A, a highly selective KOR agonist. METHODS: Changes in multimodal electroencephalography, single-photon emission computed tomography, and subjective effects following the acute administration of salvinorin-A are reported. The study included 2 sub-studies that employed a double-blind, crossover, randomized, placebo-controlled design. RESULTS: The electroencephalography measures showed a marked increase in delta and gamma waves and a decrease in alpha waves while subjects were under the effect of salvinorin-A. Regarding single-photon emission computed tomography measures, significant decreases in regional cerebral blood flow were detected in multiple regions of the frontal, temporal, parietal, and occipital cortices. Significant regional cerebral blood flow increases were observed in some regions of the medial temporal lobe, including the amygdala, the hippocampal gyrus, and the cerebellum. The pattern of subjective effects induced by salvinorin-A was similar to those observed in relation to other psychotomimetic drugs but with an evidently dissociative nature. No dysphoric effects were reported. CONCLUSION: The salvinorin-A-mediated KOR agonism induced dramatic psychotomimetic effects along with a generalized decrease in cerebral blood flow and electric activity within the cerebral cortex.

A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET.

PURPOSE: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer's disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare model's performance to that of multiple expert nuclear medicine physicians' readers. MATERIALS AND METHODS: Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimer's disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human readers on the same independent test set. The model's performance was analyzed with sensitivity, specificity, precision, F1 score, receiver operating characteristic (ROC). The regional metabolic changes driving classification were visualized using uniform manifold approximation and projection (UMAP) and network attention. RESULTS: The proposed model achieved area under the ROC curve of 96.2% (95% confidence interval: 90.6-100) on predicting the final diagnosis of DLB in the independent test set, 96.4% (92.7-100) in AD, 71.4% (51.6-91.2) in MCI-AD, and 94.7% (90-99.5) in CN, which in ROC space outperformed human readers performance. The network attention depicted the posterior cingulate cortex is important for each neurodegenerative disease, and the UMAP visualization of the extracted features by the proposed model demonstrates the reality of development of the given disorders. CONCLUSION: Using only 18F-FDG PET of the brain, a 3D deep learning model could predict the final diagnosis of the most common neurodegenerative disorders which achieved a competitive performance compared to the human readers as well as their consensus.

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones.

Clinical and biomarker changes of Alzheimer's disease in adults with Down syndrome: a cross-sectional study.

BACKGROUND: Alzheimer's disease and its complications are the leading cause of death in adults with Down syndrome. Studies have assessed Alzheimer's disease in individuals with Down syndrome, but the natural history of biomarker changes in Down syndrome has not been established. We characterised the order and timing of changes in biomarkers of Alzheimer's disease in a population of adults with Down syndrome. METHODS: We did a dual-centre cross-sectional study of adults with Down syndrome recruited through a population-based health plan in Barcelona (Spain) and through services for people with intellectual disabilities in Cambridge (UK). Cognitive impairment in participants with Down syndrome was classified with the Cambridge Cognitive Examination for Older Adults with Down Syndrome (CAMCOG-DS). Only participants with mild or moderate disability were included who had at least one of the following Alzheimer's disease measures: apolipoprotein E allele carrier status; plasma concentrations of amyloid ß peptides 1-42 and 1-40 and their ratio (Aß1-42/1-40), total tau protein, and neurofilament light chain (NFL); tau phosphorylated at threonine 181 (p-tau), and NFL in cerebrospinal fluid (CSF); and one or more of PET with 18F-fluorodeoxyglucose, PET with amyloid tracers, and MRI. Cognitively healthy euploid controls aged up to 75 years who had no biomarker abnormalities were recruited from the Sant Pau Initiative on Neurodegeneration. We used a first-order locally estimated scatterplot smoothing curve to determine the order and age at onset of the biomarker changes, and the lowest ages at the divergence with 95% CIs are also reported where appropriate. FINDINGS: Between Feb 1, 2013, and June 28, 2019 (Barcelona), and between June 1, 2009, and Dec 31, 2014 (Cambridge), we included 388 participants with Down syndrome (257 [66%] asymptomatic, 48 [12%] with prodromal Alzheimer's disease, and 83 [21%] with Alzheimer's disease dementia) and 242 euploid controls. CSF Aß1-42/1-40 and plasma NFL values changed in individuals with Down syndrome as early as the third decade of life, and amyloid PET uptake changed in the fourth decade. 18F-fluorodeoxyglucose PET and CSF p-tau changes occurred later in the fourth decade of life, followed by hippocampal atrophy and changes in cognition in the fifth decade of life. Prodromal Alzheimer's disease was diagnosed at a median age of 50·2 years (IQR 47·5-54·1), and Alzheimer's disease dementia at 53·7 years (49·5-57·2). Symptomatic Alzheimer's disease prevalence increased with age in individuals with Down syndrome, reaching 90-100% in the seventh decade of life. INTERPRETATION: Alzheimer's disease in individuals with Down syndrome has a long preclinical phase in which biomarkers follow a predictable order of changes over more than two decades. The similarities with sporadic and autosomal dominant Alzheimer's disease and the prevalence of Down syndrome make this population a suitable target for Alzheimer's disease preventive treatments. FUNDING: Instituto de Salud Carlos III, Fundació Bancaria La Caixa, Fundació La Marató de TV3, Medical Research Council, and National Institutes of Health.

AMYQ: An index to standardize quantitative amyloid load across PET tracers.

INTRODUCTION: Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations. METHODS: We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance. RESULTS: AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs. DISCUSSION: AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.

Associations among education, age, and the dementia with Lewy bodies (DLB) metabolic pattern: A European-DLB consortium project.

INTRODUCTION: We assessed the influence of education as a proxy of cognitive reserve and age on the dementia with Lewy bodies (DLB) metabolic pattern. METHODS: Brain 18F-fluorodeoxyglucose positron emission tomography and clinical/demographic information were available in 169 probable DLB patients included in the European DLB-consortium database. Principal component analysis identified brain regions relevant to local data variance. A linear regression model was applied to generate age- and education-sensitive maps corrected for Mini-Mental State Examination score, sex (and either education or age). RESULTS: Age negatively covaried with metabolism in bilateral middle and superior frontal cortex, anterior and posterior cingulate, reducing the expression of the DLB-typical cingulate island sign (CIS). Education negatively covaried with metabolism in the left inferior parietal cortex and precuneus (making the CIS more prominent). DISCUSSION: These findings point out the importance of tailoring interpretation of DLB biomarkers considering the concomitant effect of individual, non-disease-related variables such as age and cognitive reserve.

Metabolic patterns across core features in dementia with lewy bodies.

OBJECTIVE: To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern. METHODS: Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map. RESULTS: Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in the medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, and orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobe metabolism. MMSE positively covaried with metabolism in the left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in the insula, medial frontal gyrus, hippocampus in the left hemisphere, and right cerebellum. INTERPRETATION: Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated with more prominent hypometabolism in specific regions, thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. Ann Neurol 2019;85:715-725.

Preservation of brain metabolism in recently diagnosed Parkinson's impulse control disorders.

BACKGROUND: Impulse control disorders (ICD) are a common and disrupting complication of Parkinson's disease (PD) treatment. Although their relationship with dopaminergic activity is well studied, their brain metabolic correlates are mostly unknown. METHODS: In this work we studied brain metabolism using brain 18F-FDG-PET. We performed a case-control study nested within a cohort of PD patients free of ICD at baseline to compare ICD patients right after ICD diagnosis and prior to any treatment modification with matched ICD-free patients. We also compared both PD groups with healthy controls. RESULTS: When compared with ICD-free PD patients, PD patients with recently diagnosed ICD showed higher glucose metabolism in widespread areas comprising prefrontal cortices, both amygdalae and default mode network hubs (p < 0.05, corrected). When compared to healthy controls, they did not show hypermetabolism, and the only hypometabolic region was the right caudate. In turn, ICD-free patients showed diffuse hypometabolism when compared to healthy controls. CONCLUSION: Our results suggest brain metabolism is more preserved in PD patients with ICD than patients without ICD. This metabolic preservation could be related to ICD development.

Superior performance of 18F-fluorocholine digital PET/CT in the detection of parathyroid adenomas.

OBJECTIVE: To compare detectability of hyperfunctioning parathyroid tissue (HPT) by digital and analog 18F-fluorocholine PET/CT in patients with primary hyperparathyroidism and negative/inconclusive 99mTc-MIBI scintigraphy-SPECT/CT. MATERIALS AND METHODS: Thirty-three patients with primary hyperparathyroidism and negative/inconclusive 99mTc-MIBI scintigraphy-SPECT/CT were prospectively included. All patients accepted to be scanned by digital and analog PET/CT in the same imaging session after a single injection of 18F-fluorocholine. Three nuclear medicine physicians evaluated the digital and analog PET/CT datasets to assess the detection rate of HPT. Maximum standard uptake values (SUVmax) of HPT and locoregional lymph nodes were measured in both systems. RESULTS: HPT was detected in 30/33 patients by the digital system, whereas it was detected in 22/33 patients by the analog system (p < 0.01). Moreover, in 21 of these 33 patients, both systems detected one focal 18F-fluorocholine uptake, and in one patient the digital system detected two foci. Histopathology demonstrated HPT in 32 patients and it was inconclusive in one patient. The digital PET/CT detected HPT in 29 of the 32 patients, and the analog system in 22 of the 32 (p < 0.01). All HPT suspected lesions resected and detected only by the digital system (n = 8) were < 10 mm (7.5 ± 1.3 mm), while those detected by both systems (n = 22) were > 10 mm (13 ± 3.8 mm). SUVmax of HPT lesions was significantly higher than SUVmax of locoregional lymph node independently of the PET/CT system used (4.5 ± 1.9 vs. 2.9 ± 1.3, p < 0.0001). CONCLUSIONS: Digital PET/CT offers superior performance over analog system in patients with suspected HPT and previous negative/inconclusive imaging examinations, particularly in sub-centimeter lesions. SUVmax can help in the differentiation between HTP and locoregional lymph nodes.

Correction to: Superior performance of 18F-fluorocholine digital PET/CT in the detection of parathyroid adenomas.

The correct administered activity of 18F-FCH is 0.1-0.14 mCi/Kg, which is equivalent to 3.7-5.2 MBq/kg.

Metabolic Correlates of Dopaminergic Loss in Dementia with Lewy Bodies.

BACKGROUND: Striatal dopamine deficiency and metabolic changes are well-known phenomena in dementia with Lewy bodies and can be quantified in vivo by 123 I-Ioflupane brain single-photon emission computed tomography of dopamine transporter and 18 F-fluorodesoxyglucose PET. However, the linkage between both biomarkers is ill-understood. OBJECTIVE: We used the hitherto largest study cohort of combined imaging from the European consortium to elucidate the role of both biomarkers in the pathophysiological course of dementia with Lewy bodies. METHODS: We compared striatal dopamine deficiency and glucose metabolism of 84 dementia with Lewy body patients and comparable healthy controls. After normalization of data, we tested their correlation by region-of-interest-based and voxel-based methods, controlled for study center, age, sex, education, and current cognitive impairment. Metabolic connectivity was analyzed by inter-region coefficients stratified by dopamine deficiency and compared to healthy controls. RESULTS: There was an inverse relationship between striatal dopamine availability and relative glucose hypermetabolism, pronounced in the basal ganglia and in limbic regions. With increasing dopamine deficiency, metabolic connectivity showed strong deteriorations in distinct brain regions implicated in disease symptoms, with greatest disruptions in the basal ganglia and limbic system, coincident with the pattern of relative hypermetabolism. CONCLUSIONS: Relative glucose hypermetabolism and disturbed metabolic connectivity of limbic and basal ganglia circuits are metabolic correlates of dopamine deficiency in dementia with Lewy bodies. Identification of specific metabolic network alterations in patients with early dopamine deficiency may serve as an additional supporting biomarker for timely diagnosis of dementia with Lewy bodies. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Correction to: Digital vs. analog PET/CT: intra-subject comparison of the SUVmax in target lesions and reference regions.

The article Digital vs. analog PET/CT: intra-subject comparison of the SUVmax in target lesions and reference regions, written by Francisco Fuentes-Ocampo, Diego Alfonso López-Mora, Albert Flotats, Gabriela Paillahueque.

Digital vs. analog PET/CT: intra-subject comparison of the SUVmax in target lesions and reference regions.

PURPOSE: The purpose of this study was to assess whether digital photon counting technology in digital PET/CT influences the quantification of SUVmax in target lesions and regions of reference compared to analog PET/CT before an interchangeable use of either system in follow up studies. METHODS: From January to June of 2018, 100 oncological patients underwent successive PET/CT imaging with digital and analog systems in the same day. Fifty-eight patients underwent analog imaging first and digital imaging thereafter, and 42 patients the other way round. SUVmax was measured in reference regions (liver and mediastinal blood pool) and in the most metabolically active target lesion in each patient. According to the sequence order of PET/CT acquisition, two groups of SUVmax values were obtained, i.e. group 1: analog PET/CT performed first; group 2: digital PET/CT performed first. RESULTS: Mean SUVmax in the total sample (regardless of the order of PET/CT acquisition) in the target lesions with the analog PET/CT was 8.14 ± 6.39 and the digital 9.97 ± 6.14 (P = 0.000). Total mean SUVmax in the liver with the analog was 4.39 ± 2.59 and the digital 4.46 ± 3.18 (P = 0.477). Total mean SUVmax in the mediastinal blood pool with the analog was 2.30 ± 0.67 and the digital 2.54 ± 0.74 (P = 0.000). Group 1: mean SUVmax in the target lesions with the analog system was 6.64 ± 4.71 and the digital 9.48 ± 5.60 (P = 0.000). Mean liver SUVmax with the analog was 4.70 ± 2.90 and the digital 4.80 ± 3.72 (P = 0.088). Mediastinal blood pool SUVmax with the analog was 2.33 ± 0.66 and the digital 2.45 ± 0.73 (P = 0.041). Group 2: mean SUVmax in target lesions with the digital system was 10.63 ± 6.88 and the analog 10.16 ± 7.76 (P = 0.046). Mean liver SUVmax with the digital was 3.99 ± 2.20 and the analog 3.96 ± 2.04 (P = 0.218). Mediastinal blood pool SUVmax with the digital was 2.66 ± 0.75 and the analog 2.27 ± 0.68 (P = 0.000). No significant differences between both time delays were found. CONCLUSIONS: Improved photon counting technology in the digital PET/CT, and the effect of delayed increased uptake and retention significantly increases SUVmax values. This has to be taken into account before interchangeable use of either system in follow up studies.

Cortical atrophic-hypometabolic dissociation in the transition from premanifest to early-stage Huntington's disease.

PURPOSE: Huntington's disease (HD) is a fatal neurodegenerative disorder with no effective treatment currently available. Although the pathological hallmark of HD is massive striatal atrophy, it has been suggested that cortical deterioration may concomitantly occur and play a major role in the patient's functional independence. Our objective was to characterize cortical structural and metabolic neurodegeneration in the transition from premanifest to early-stage Huntington's disease (HD). METHODS: Using a surface-based neuroimaging approach, we compared cortical thickness and intracortical FDG-PET uptake in 19 early-symptomatic HD patients with respect to 21 premanifest HD individuals. RESULTS: Early-HD patients showed significant cortical atrophy and intracortical hypometabolism when compared to premanifest subjects (p < 0.05, corrected for multiple comparisons). However, whereas the atrophy pattern was restricted to precentral and parieto-occipital regions, a pronounced frontotemporal hypometabolism was observed. Importantly, structural changes correlated with motor and cognitive performance, and metabolic changes were associated with the presence and severity of apathy in this population, a core neuropsychiatric feature of this disorder. CONCLUSION: Our findings reveal an asynchronous neuronal loss and metabolic compromise across the cerebral cortex in early HD. Hence, the use of structural and metabolic imaging indicators to characterize disease progression in this population should take into consideration the dissociation which occurs between cortical atrophy and hypometabolism.

Comparison of image quality and lesion detection between digital and analog PET/CT.

OBJECTIVE: The purpose of this study was to compare image quality and lesion detection capability between a digital and an analog PET/CT system in oncological patients. MATERIALS AND METHODS: One hundred oncological patients (62 men, 38 women; mean age of 65 ± 12 years) were prospectively included from January-June 2018. All patients, who accepted to be scanned by two systems, consecutively underwent a single day, dual imaging protocol (digital and analog PET/CT). Three nuclear medicine physicians evaluated image quality using a 4-point scale (-1, poor; 0, fair; 1, good; 2, excellent) and detection capability by counting the number of lesions with increased radiotracer uptake. Differences were considered significant for a p value <0.05. RESULTS: Improved image quality in the digital over the analog system was observed in 54% of the patients (p = 0.05, 95% CI, 44.2-63.5). The percentage of interrater concordance in lesion detection capability between the digital and analog systems was 97%, with an interrater measure agreement of κ = 0.901 (p < 0.0001). Although there was no significant difference in the total number of lesions detected by the two systems (digital: 5.03 ± 10.6 vs. analog: 4.53 ± 10.29; p = 0.7), the digital system detected more lesions in 22 of 83 of PET+ patients (26.5%) (p = 0.05, 95% CI, 17.9-36.7). In these 22 patients, all lesions detected by the digital PET/CT (and not by the analog PET/CT) were < 10 mm. CONCLUSION: Digital PET/CT offers improved image quality and lesion detection capability over the analog PET/CT in oncological patients, and even better for sub-centimeter lesions.

Structural and metabolic brain correlates of apathy in Huntington's disease.

BACKGROUND: Apathy is the most prevalent and characteristic neuropsychiatric feature of Huntington's disease. Congruent with the main early pathological changes, apathy is primarily associated with subcortical damage in frontal-striatal circuits. However, little is known about its precise subserving mechanisms and the contribution of regions other than the basal ganglia. OBJECTIVES: We aimed to define the neural correlates of apathy in Huntington's disease based on gray matter volume and PET/CT of 18 F-fluorodeoxyglucose metabolism. METHODS: We rated the severity of apathy in 40 mild Huntington's disease participants using the Problem Behaviors Assessment for Huntington's disease. Voxelwise regression analysis was performed, controlling for effects of potential confounders, and PET/CT results were corrected for the effects of gray matter atrophy. RESULTS: Apathy was strongly associated with decreased gray matter within a spatially distributed cortico-subcortical network, with major compromise of the bilateral amygdala and temporal cortex. PET metabolism was significantly decreased in frontotemporal and parietal regions. Metabolic uptake and gray matter values in the identified clusters showed significant correlations with multiple clinical measures. CONCLUSIONS: Our findings indicate that apathy in Huntington's disease is not exclusively a consequence of basal ganglia and related frontal-executive alterations. It is subserved by a complex cortico-subcortical network where critical reward and emotional-related prefrontal, temporal, and limbic nodes contribute strongly to its severity. This highlights the contribution of damage in regions other than the basal ganglia to the clinical expression of Huntington's disease. © 2018 International Parkinson and Movement Disorder Society.

Striatal hypometabolism in premanifest and manifest Huntington's disease patients.

PURPOSE: To assess metabolic changes in cerebral 18F-FDG PET/CT in premanifest and manifest Huntington's disease (HD) subjects compared to a control group and to correlate 18F-FDG uptake patterns with different disease stages. MATERIALS AND METHODS: Thirty-three gene-expanded carriers (Eight males; mean age: 43 y/o; CAG > 39) were prospectively included. Based on the Unified Huntington's Disease Rating Scale Total Motor Score and the Total Functional Capacity, subjects were classified as premanifest (preHD = 15) and manifest (mHD = 18). Estimated time disease-onset was calculated using the Langbehn formula, which allowed classifying preHD as far-to (preHD-A) and close-to (PreHD-B) disease-onset. Eighteen properly matched participants were included as a control group (CG). All subjects underwent brain 18F-FDG PET/CT and MRI. 18F-FDG PET/CT were initially assessed by two nuclear medicine physicians identifying qualitative metabolic changes in the striatum. Quantitative analysis was performed using SPM8 with gray matter atrophy correction using the BPM toolbox. RESULTS: Visual analysis showed a marked striatal hypometabolism in mHD. A normal striatal distribution of 18F-FDG uptake was observed for most of the preHD subjects. Quantitative analysis showed a significant striatal hypometabolism in mHD subjects compared to CG (p < 0.001 uncorrected, k = 50 voxels). In both preHD groups we observed a significant striatal hypometabolism with respect to CG (p < 0.001 uncorrected, k = 50 voxels). In mHD subjects we observed a significant striatal hypometabolism with respect to both preHD groups (p < 0.001 uncorrected, k = 50 voxels). CONCLUSION: 18F-FDG PET/CT might be a helpful tool to identify patterns of glucose metabolism in the striatum across the stages of HD and might be relevant in assessing the clinical status of gene-expanded HD carriers due to the fact that dysfunctional glucose metabolism begins at early preHD stages of the disease. 18F-FDG PET/CT appears as a promising method to monitor the response to disease-modifying therapies even if applied in premanifest subjects.