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Background and Purpose: The aim of this study was to evaluate brain metabolic correlates of apathy in amyotrophic lateral sclerosis (ALS)., Methods: A total of 165 ALS patients underwent 18 F-2-fluoro-2-deoxy-D-glucose positron emission tomography ( 18 F-FDG-PET) and Frontal Systems Behaviour Scale (FrSBe) evaluation. FrSBe provides "before" and "after" apathy subscores, referring to premorbid and morbid conditions. "After" apathy subscore and "before-after" gap, i.e. the difference between "before" and "after" subscores, were regressed against whole-brain metabolism. Among patients with a pathological "after" apathy subscore (i.e., ≥65), we compared patients with "before" apathy subscores ≥65 and <65, and patients with "before-after" gaps of <22 and ≥22., Results: In the whole sample, the "after" apathy subscore negatively correlated with metabolism in the dorsolateral prefrontal cortex (DLPFC), dorsomedial prefrontal cortex (DMPFC), ventrolateral prefrontal cortex (VLPFC), premotor cortex (PMC) and anterior cingulate cortex (ACC), and insula bilaterally. A positive correlation was found in the cerebellum and pons. The "before-after" gap negatively correlated with metabolism in bilateral DLPFC, DMPFC and PMC, and left VLPFC and ACC, and positively correlated with cerebellar and pontine clusters. Among patients with an "after" apathy subscore ≥65, we found no difference between those with "before" apathy subscores ≥65 and <65. Patients with a "before-after" gap ≥22, compared to patients with a gap <22, showed relative hypometabolism in bilateral DLPFC and DMPFC, and left ACC and PMC, and relative cerebellar and pontine hypermetabolism., Conclusion: No studies on brain 18 F-2-fluoro-2-deoxy-D-glucose positron emission tomography correlates of apathy have been performed in ALS. We found that FrSBe "after" apathy subscore correlated with metabolic changes in brain regions known as neuroanatomical correlates of apathy. Furthermore, our findings support the relevance of the gap between premorbid and morbid conditions to detect behavioural changes due to the neurodegenerative process underlying ALS., (© 2020 European Academy of Neurology.)

Background and Purpose: The aim of the study was to evaluate the metabolic correlates of Apolipoprotein E (APOE) genotype in amyotrophic lateral sclerosis (ALS) and to investigate the role of ε2 as a risk factor for cognitive impairment., Methods: A total of 159 ALS cases underwent APOE and ALS-related genes analysis, neuropsychological assessment and cerebral 18 F-2-fluoro-2-deoxy-D-glucose positron emission tomography. The APOE genotype was regressed against whole brain metabolism as assessed by 18 F-2-fluoro-2-deoxy-D-glucose positron emission tomography, with age, sex, education, type of onset and C9orf72 status as covariates., Results: Brain metabolism was significantly positively correlated with APOE genotype from ε2/ε2 to ε3/ε4 in the left prefrontal [Brodmann area (BA) 10], orbitofrontal (BAs 11, 45, 47) and anterior cingulate (BA 32) cortices. There was a tendency to a relative hypometabolism going towards the ε2/ε2 extreme., Conclusions: We found a highly significant, relatively lower metabolism in association with the ε2 allele in extra-motor areas typically affected in frontotemporal dementia (left prefrontal, orbitofrontal and anterior cingulate cortices), strengthening the finding of a role of ε2 as a risk factor for cognitive impairment in ALS. Our data suggested a link between cholesterol homeostasis and neurodegeneration., (© 2018 EAN.)

Background: This study addresses whether a unitary cardiac autonomic nervous system index (ANSI), obtained combining multiple metrics from heart rate variability (HRV) into a radar plot could provide an easy appreciation of autonomic performance in a clinical setting., Materials and Methods: Data are standardized using percentile ranking of autonomic proxies from a relatively large reference population (n = 1593, age 39 ± 13 years). Autonomic indices are obtained from autoregressive spectral analysis of (ECG derived) HRV at rest and during standing up. A reduced ANSI (using RR, RR variance and rest-stand difference of LFnu) is then constructed as a radar plot, quantified according to its combined area and tested against different risk subgroups., Results: With growing risk profile, there is a marked reduction of the rank value of ANSI, quantified individually by the radar plot area. The practical usefulness of the approach was tested in small groups of additional subjects putatively characterized by elevated or poor autonomic performance. Data show that elite endurance athletes are characterized by elevated values of ANSI (80·6 ± 14·9, P < 0·001) while subjects with either Type 1 or Type 2 diabetes show lower values (DM1 = 37·0 ± 18·9 and DM2 = 26·8 ± 23·3, P = 0·002), and patients with coronary artery disease (CAD) represent a nadir (17 ± 20, P < 0·001)., Conclusions: This observational study shows the feasibility of testing simpler metrics of cardiac autonomic regulation based on a multivariate unitary index in a preventive setting. This simple approach might foster a wider application of HRV in the clinical arena, and permit an easier appreciation of autonomic performance., (© 2017 Stichting European Society for Clinical Investigation Journal Foundation.)

Objectives: Positron emission tomography (PET) and volume of interest (VOI) analysis have recently shown in amyotrophic lateral sclerosis (ALS) an accuracy of 93% in differentiating patients from controls. The aim of this study was to disclose by spatial independent component analysis (ICA) the brain networks involved in ALS pathological processes and evaluate their discriminative value in separating patients from controls., Experimental Design: Two hundred fifty-nine ALS patients and 40 age- and sex-matched control subjects underwent brain 18F-2-fluoro-2-deoxy-D-glucose PET (FDG-PET). Spatial ICA of the preprocessed FDG-PET images was performed. Intensity values were converted to z-scores and binary masks were used as data-driven VOIs. The accuracy of this classifier was tested versus a validated system processing intensity signals in 27 brain meta-VOIs. A support vector machine was independently applied to both datasets and the 'leave-one-out' technique verified the general validity of results., Principal Observations: The 8 components selected as pathophysiologically meaningful discriminated patients from controls with 99.0% accuracy, the discriminating value of bilateral cerebellum/midbrain alone representing 96.3%. Among the meta-VOIs, right temporal lobe alone reached an accuracy of 93.7%., Conclusions: Spatial ICA identified in a very large cohort of ALS patients distinct spatial networks showing a high discriminatory value, improving substantially on the previously obtained accuracy. The cerebellar/midbrain component accounted for the highest accuracy in separating ALS patients from controls. Spatial ICA and multivariate analysis perform better than univariate semi-quantification methods in identifying the neurodegenerative features of ALS and pave the way for inclusion of PET in clinical trials and early diagnosis., (© 2015 Wiley Periodicals, Inc.)

Image registration brings images into a form in which each voxel corresponds to a predetermined anatomic entity and is necessary for comparisons of data across scans. Intrasubject registration is a matter of translating and rotating one image volume into correspondence with another. Intersubject registration is more difficult because it requires the removal of individual anatomy dependence from the data. This article describes, with the help of clinical examples, automated methods for intrasubject registration of scans within and between modalities, and intersubject registration used for registering a three-dimensional brain atlas with a patient's brain scan.