Functional pattern of Brain FDG-PET in Amyotrophic Lateral Sclerosis

Objective: We investigated a large sample of patients with amyotrophic lateral sclerosis (ALS) at rest in order to assess the value of 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) PET as a biomarker to discriminate patients from controls. Methods: A total of 195 patients with ALS and 40 controls underwent brain 18F-FDG-PET, most within 5 months of diagnosis. Spinal and bulbar subgroups of ALS were also investigated. Twenty-five bilateral cortical and subcortical volumes of interest and cerebellum were taken into account, and 18F-FDG uptakes were individually normalized by whole-brain values. Group analyses investigated the ALS-related metabolic changes. Discriminant analysis investigating sensitivity and specificity was performed using the 51 volumes of interest as well as age and sex. Metabolic connectivity was explored by voxel-wise interregional correlation analysis. Results: Hypometabolismwas found in frontal, motor, and occipital cortex and hypermetabolismin midbrain, temporal pole, and hippocampus in patients with ALS compared to controls. A similar metabolic pattern was also found in the 2 subgroups. Discriminant analysis showed a sensitivity of 95% and a specificity of 83% in separating patients from controls. Connectivity analysis found a highly significant positive correlation between midbrain and white matter in corticospinal tracts in patients with ALS. Conclusions: 18F-FDG distribution changes in ALS showed a clear pattern of hypometabolism in frontal and occipital cortex and hypermetabolism in midbrain. The latter might be interpreted as the neurobiological correlate of diffuse subcortical gliosis. Discriminant analysis resulted in high sensitivity and specificity in differentiating patients with ALS from controls. Once validated by diseased-control studies, the present methodology might represent a potentially useful biomarker for ALS diagnosis. Classificaton of evidence: This study provides Class III evidence that 18F-FDG-PET accurately distinguishes patients with ALS from normal controls (sensitivity 95.4%, specificity 82.5%)

Efficacy and safety of N-acetyl-GED-0507-34-LEVO gel in patients with moderate-to severe facial acne vulgaris: A phase 2B randomised double-blind, vehicle-controlled trial.

Background: Preliminary in vitro and in vivo studies have supported the efficacy of the peroxisome proliferator-activated receptor-γ (PPARγ) modulator N-acetyl-GED-0507-34-LEVO (NAC-GED) for the treatment of acne-inducing sebocyte differentiation, improving sebum composition and controlling the inflammatory process. Objectives: To evaluate the efficacy and safety of NAC-GED (5% and 2%) in patients with moderate-to-severe facial acne vulgaris. Methods: This double-blind phase II randomized controlled clinical trial was conducted at 36 sites in Germany, Italy and Poland. Patients aged 12-30 years with facial acne, an Investigator Global Assessment (IGA) score of 3-4, and an inflammatory and noninflammatory lesion count of 20-100 were randomized to topical application of the study drug (2% or 5%) or placebo (vehicle), once daily for 12 weeks. The co-primary efficacy endpoints were percentage change from baseline in total lesion count (TLC) and IGA success at week 12; the safety endpoints were adverse events (AEs) and serious AEs. This study was registered with EudraCT (2018-003307-19). Results: Between Q1 in 2019 and Q1 in 2020 450 patients [n = 418 (92·9%) IGA 3; n = 32 (7·1%) IGA 4] were randomly assigned to NAC-GED 5% (n = 150), NAC-GED 2% (n = 150) or vehicle (n = 150). The percentage change in TLC reduction was statistically significantly higher in both the NAC-GED 5% [-57·1%, 95% confidence interval (CI) -60·8 to -53·4; P < 0·001] and NAC-GED 2% (-44·7%, 95% CI -49·1 to -40·1; P < 0·001) groups compared with vehicle (-33·9%, 95% CI -37·6 to -30·2). A higher proportion of patients treated with NAC-GED 5% experienced IGA success (45%, 95% CI 38-53) vs. the vehicle group (24%, 95% CI 18-31; P < 0·001). The IGA success rate was 33% in the NAC-GED 2% group (P = not significant vs. vehicle). The percentage of patients who had one or more AEs was 19%, 16% and 19% in the NAC-GED 5%, NAC-GED 2% and vehicle groups, respectively. Conclusions: The topical application of NAC-GED 5% reduced TLC, increased the IGA success rate and was safe for use in patients with acne vulgaris. Thus, NAC-GED, a new PPARγ modulator, showed an effective clinical response. What is already known about this topic? Acne vulgaris, one of the most common dermatological diseases, affects more than 85% of adolescents. There is a medical need for innovative and safe treatment of acne vulgaris. The peroxisome proliferator-activated receptor-γ (PPARγ) is involved in lipid metabolism and specifically in cell differentiation, sebum production and the inflammatory reaction. What does this study add? N-acetyl-GED-0507-34-LEVO (NAC-GED 5%), a PPARγ modulator, significantly improves acne manifestations in patients with moderate-to-severe acne and is safe and well tolerated. The results suggest that the PPARγ receptor is a novel therapeutic target for acne. The results provide a basis for a large phase III trial to assess the effectiveness and safety profile of NAC-GED in combating a disease that afflicts 80-90% of adolescents

Spinal cord hypermetabolism extends to skeletal muscle in amyotrophic lateral sclerosis: a computational approach to [18F]-fluorodeoxyglucose PET/CT images

Purpose: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease leading to neuromuscular palsy and death. We propose a computational approach to [18F]-fluorodeoxyglucose (FDG) PET/CT images to analyze the structure and metabolic pattern of skeletal muscle in ALS and its relationship with disease aggressiveness. Materials and methods: A computational 3D method was used to extract whole psoas muscle\u2019s volumes and average attenuation coefficient (AAC) from CT images obtained by FDG PET/CT performed in 62 ALS patients and healthy controls. Psoas average standardized uptake value (normalized on the liver, N-SUV) and its distribution heterogeneity (defined as N-SUV variation coefficient, VC-SUV) were also extracted. Spinal cord and brain motor cortex FDG uptake were also estimated. Results: As previously described, FDG uptake was significantly higher in the spinal cord and lower in the brain motor cortex, in ALS compared to controls. While psoas AAC was similar in patients and controls, in ALS a significant reduction in psoas volume (3.6 \ub1 1.02 vs 4.12 \ub1 1.33 mL/kg; p < 0.01) and increase in psoas N-SUV (0.45 \ub1 0.19 vs 0.29 \ub1 0.09; p < 0.001) were observed. Higher heterogeneity of psoas FDG uptake was also documented in ALS (VC-SUV 8 \ub1 4%, vs 5 \ub1 2%, respectively, p < 0.001) and significantly predicted overall survival at Kaplan\u2013Meier analysis. VC-SUV prognostic power was confirmed by univariate analysis, while the multivariate Cox regression model identified the spinal cord metabolic activation as the only independent prognostic biomarker. Conclusion: The present data suggest the existence of a common mechanism contributing to disease progression through the metabolic impairment of both second motor neuron and its effector

Time-dependent recovery of brain hypometabolism in neuro-COVID-19 patients

Purpose We evaluated brain metabolic dysfunctions and associations with neurological and biological parameters in acute, subacute and chronic COVID-19 phases to provide deeper insights into the pathophysiology of the disease.Methods Twenty-six patients with neurological symptoms (neuro-COVID-19) and [F-18]FDG-PET were included. Seven patients were acute (&lt; 1 month (m) after onset), 12 subacute (4 &gt;= 1-m, 4 &gt;= 2-m and 4 &gt;= 3-m) and 7 with neuro-post-COVID-19 (3 &gt;= 5-m and 4 &gt;= 7-9-m). One patient was evaluated longitudinally (acute and 5-m). Brain hypo- and hypermetabolism were analysed at single-subject and group levels. Correlations between severity/extent of brain hypo- and hypermetabolism and biological (oxygen saturation and C-reactive protein) and clinical variables (global cognition and Body Mass Index) were assessed.Results The "fronto-insular cortex" emerged as the hypometabolic hallmark of neuro-COVID-19. Acute patients showed the most severe hypometabolism affecting several cortical regions. Three-m and 5-m patients showed a progressive reduction of hypometabolism, with limited frontal clusters. After 7-9 months, no brain hypometabolism was detected. The patient evaluated longitudinally showed a diffuse brain hypometabolism in the acute phase, almost recovered after 5 months. Brain hypometabolism correlated with cognitive dysfunction, low blood saturation and high inflammatory status. Hypermetabolism in the brainstem, cerebellum, hippocampus and amygdala persisted over time and correlated with inflammation status.Conclusion Synergistic effects of systemic virus-mediated inflammation and transient hypoxia yield a dysfunction of the fronto-insular cortex, a signature of CNS involvement in neuro-COVID-19. This brain dysfunction is likely to be transient and almost reversible. The long-lasting brain hypermetabolism seems to reflect persistent inflammation processes

Opportunistic skeletal muscle metrics as prognostic tools in metastatic castration-resistant prostate cancer patients candidates to receive Radium-223

Objective: Androgen deprivation therapy alters body composition promoting a significant loss in skeletal muscle (SM) mass through inflammation and oxidative damage. We verified whether SM anthropometric composition and metabolism are associated with unfavourable overall survival (OS) in a retrospective cohort of metastatic castration-resistant prostate cancer (mCRPC) patients submitted to 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) imaging before receiving Radium-223. Patients and methods: Low-dose CT were opportunistically analysed using a cross-sectional approach to calculate SM and adipose tissue areas at the third lumbar vertebra level. Moreover, a 3D computational method was used to extract psoas muscles to evaluate their volume, Hounsfield Units (HU) and FDG retention estimated by the standardized uptake value (SUV). Baseline established clinical, lab and imaging prognosticators were also recorded. Results: SM area predicted OS at univariate analysis. However, this capability was not additive to the power of mean HU and maximum SUV of psoas muscles volume. These factors were thus combined in the Attenuation Metabolic Index (AMI) whose power was tested in a novel uni- and multivariable model. While Prostate-Specific Antigen (PSA), Alkaline Phosphatase (ALP), Lactate Dehydrogenase and Hemoglobin, Metabolic Tumor Volume, Total Lesion Glycolysis and AMI were associated with long-term OS at the univariate analyses, only PSA, ALP and AMI resulted in independent prognosticator at the multivariate analysis. Conclusion: The present data suggest that assessing individual 'patients' SM metrics through an opportunistic operator-independent computational analysis of FDG PET/CT imaging provides prognostic insights in mCRPC patients candidates to receive Radium-223. Graphical abstract: [Figure not available: see fulltext.

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

Visual versus semi-quantitative analysis of 18F-FDG-PET in amnestic MCI. An European Alzheimer\u27s Disease Consortium (EADC) project

We aimed to investigate the accuracy of FDG-PET to detect the Alzheimer\u27s disease (AD) brain glucose hypometabolic pattern in 142 patients with amnestic mild cognitive impairment (aMCI) and 109 healthy controls. aMCI patients were followed for at least two years or until conversion to dementia. Images were evaluated by means of visual read by either moderately-skilled or expert readers, and by means of a summary metric of AD-like hypometabolism (PALZ score). Seventy-seven patients converted to AD-dementia after 28.6?19.3 months of follow-up. Expert reading was the most accurate tool to detect these MCI converters from healthy controls (sensitivity 89.6%, specificity 89.0%, accuracy 89.2%) while two moderately-skilled readers were less (p < 0.05) specific (sensitivity 85.7%, specificity 79.8%, accuracy 82.3%) and PALZ scorewas less (p < 0.001) sensitive (sensitivity 62.3%, specificity 91.7%, accuracy 79.6%). Among the remaining 67 aMCI patients, 50 were confirmed as aMCI after an average of 42.3 months, 12 developed other dementia, and 3 reverted to normalcy. In 30/50 persistent MCI patients, the expert recognized the AD hypometabolic pattern. In 13/50 aMCI, both the expert and PALZ score were negative while in 7/50, only the PALZ score was positive due to sparse hypometabolic clusters mainly in frontal lobes. Visual FDG-PET reads by an expert is the most accurate method but an automated, validated system may be particularly helpful to moderately-skilled readers because of high specificity, and should be mandatory when even a moderately-skilled reader is unavailable

Diagnostic utility of FDG-PET in the differential diagnosis between different forms of primary progressive aphasia

PURPOSE: A joint effort of the European Association of Nuclear Medicine (EANM) and the European Academy of Neurology (EAN) aims at clinical guidance for the use of FDG-PET in neurodegenerative diseases. This paper addresses the diagnostic utility of FDG-PET over clinical/neuropsychological assessment in the differentiation of the three forms of primary progressive aphasia (PPA). METHODS: Seven panelists were appointed by the EANM and EAN and a literature search was performed by using harmonized PICO (Population, Intervention, Comparison, Outcome) question keywords. The studies were screened for eligibility, and data extracted to assess their methodological quality. Critical outcomes were accuracy indices in differentiating different PPA clinical forms. Subsequently Delphi rounds were held with the extracted data and quality assessment to reach a consensus based on both literature and expert opinion. RESULTS: Critical outcomes for this PICO were available in four of the examined papers. The level of formal evidence supporting clinical utility of FDG-PET in differentiating among PPA variants was considered as poor. However, the consensual recommendation was defined on Delphi round I, with six out of seven panelists supporting clinical use. CONCLUSIONS: Quantitative evidence demonstrating utility or lack thereof is still missing. Panelists decided consistently to provide interim support for clinical use based on the fact that a typical atrophy or metabolic pattern is needed for PPA according to the diagnostic criteria, and the synaptic failure detected by FDG-PET is an earlier phenomenon than atrophy. Also, a normal FDG-PET points to a non-neurodegenerative cause

Does a 6-point scale approach to post-treatment 18F-FDG PET-CT allow to improve response assessment in head and neck squamous cell carcinoma? A multicenter study

Abstract Purpose Response assessment to definitive non-surgical treatment for head and neck squamous cell carcinoma (HNSCC) is centered on the role of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET-CT) 12 weeks after treatment. The 5-point Hopkins score is the only qualitative system available for standardized reporting, albeit limited by suboptimal positive predictive value (PPV). The aim of our study was to explore the feasibility and assess the diagnostic accuracy of an experimental 6-point scale ("Cuneo score"). Methods We performed a retrospective, multicenter study on HNSCC patients who received a curatively-intended, radiation-based treatment. A centralized, independent qualitative evaluation of post-treatment FDG-PET/CT scans was undertaken by 3 experienced nuclear medicine physicians who were blinded to patients' information, clinical data, and all other imaging examinations. Response to treatment was evaluated according to Hopkins, Cuneo, and Deauville criteria. The primary endpoint of the study was to evaluate the PPV of Cuneo score in assessing locoregional control (LRC). We also correlated semi-quantitative metabolic factors as included in PERCIST and EORTC criteria with disease outcome. Results Out of a total sample of 350 patients from 11 centers, 119 subjects (oropharynx, 57.1%; HPV negative, 73.1%) had baseline and post-treatment FDG-PET/CT scans fully compliant with EANM 1.0 guidelines and were therefore included in our analysis. At a median follow-up of 42 months (range 5-98), the median locoregional control was 35 months (95% CI, 32-43), with a 74.5% 3-year rate. Cuneo score had the highest diagnostic accuracy (76.5%), with a positive predictive value for primary tumor (Tref), nodal disease (Nref), and composite TNref of 42.9%, 100%, and 50%, respectively. A Cuneo score of 5-6 (indicative of residual disease) was associated with poor overall survival at multivariate analysis (HR 6.0; 95% CI, 1.88-19.18; p = 0.002). In addition, nodal progressive disease according to PERCIST criteria was associated with worse LRC (OR for LR failure, 5.65; 95% CI, 1.26-25.46; p = 0.024) and overall survival (OR for death, 4.81; 1.07-21.53; p = 0.04). Conclusions In the frame of a strictly blinded methodology for response assessment, the feasibility of Cuneo score was preliminarily validated. Prospective investigations are warranted to further evaluate its reproducibility and diagnostic accuracy