Positive relation between dopamine neuron degeneration and metabolic connectivity disruption in the MPTP plus probenecid mouse model of Parkinson's disease.

The clinical manifestation of Parkinson's disease (PD) appears when neurodegeneration is already advanced, compromising the efficacy of disease-modifying treatment approaches. Biomarkers to identify the early stages of PD are therefore of paramount importance for the advancement of the therapy of PD. In the present study, by using a mouse model of PD obtained by subchronic treatment with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and the clearance inhibitor probenecid (MPTPp), we identified prodromal markers of PD by combining in vivo positron emission tomography (PET) imaging and ex vivo immunohistochemistry. Longitudinal PET imaging of the dopamine transporter (DAT) by [18F]-N-(3-fluoropropyl)-2ß-carboxymethoxy-3ß-(4-iodophenyl) nortropane ([18F]-FP-CIT), and brain glucose metabolism by 2-deoxy-2-[18F]-fluoroglucose ([18F]-FDG) were performed before MPTPp treatment and after 1, 3, and 10 MPTPp administrations, in order to assess relation between dopamine neuron integrity and brain connectivity. The results show that in vivo [18F]-FP-CIT in the dorsal striatum was not modified after the first administration of MPTPp, tended to decrease after 3 administrations, and significantly decreased after 10 MPTPp administrations. Post-mortem immunohistochemical analyses of DAT and tyrosine hydroxylase (TH) in the striatum showed a positive correlation with [18F]-FP-CIT, confirming the validity of repeated MPTPp-treated mice as a model that can reproduce the progressive pathological changes in the early phases of PD. Analysis of [18F]-FDG uptake in several brain areas connected to the striatum showed that metabolic connectivity was progressively disrupted, starting from the first MPTPp administration, and that significant connections between cortical and subcortical regions were lost after 10 MPTPp administrations, suggesting an association between dopamine neuron degeneration and connectivity disruption in this PD model. The results of this study provide a relevant model, where new drugs that can alleviate neurodegeneration in PD could be evaluated preclinically.

Atypical brain FDG-PET patterns increase the risk of long-term cognitive and motor progression in Parkinson's disease.

INTRODUCTION: Brain hypometabolism patterns have been previously associated with cognitive decline in Parkinson's disease (PD). Our aim is to evaluate the impact of single-subject fluorodeoxyglucose (FDG)-PET brain hypometabolism on long-term cognitive and motor outcomes in PD. METHODS: Forty-nine non-demented PD patients with baseline brain FDG-PET data underwent an extensive clinical follow-up for 8 years. The ability of FDG-PET to predict long-term cognitive and motor progression was evaluated using Cox regression and mixed ANCOVA models. RESULTS: Participants were classified according to FDG-PET pattern in PD with typical (n = 26) and atypical cortical metabolism (n = 23). Patients with atypical brain hypometabolic patterns showed higher incidence of dementia (60% vs 3%; HR = 18.3), hallucinations (56% vs 7%, HR = 7.3) and faster motor decline compared to typical pattern group. CONCLUSION: This study argues for specific patterns of FDG-PET cortical hypometabolism in PD as a prognostic marker for long term cognitive and motor outcomes at single-subject level.

Neurobiological Dysfunctional Substrates for the Self-Medication Hypothesis in Adult Individuals with Attention-Deficit Hyperactivity Disorder and Cocaine Use Disorder: A Fluorine-18-Fluorodeoxyglucose Positron Emission Tomography Study.

Objectives: Attention-deficit hyperactivity disorder (ADHD) in adulthood shows high co-occurrence rates with cocaine use disorder (CoUD). The self-medication hypothesis (SMH) provides a theoretical explanation for this comorbidity. This study investigates the neurobiological mechanisms that could support SMH in adult patients with attention-deficit hyperactivity disorder with cocaine use disorder (ADHD-CoUD). Materials and Methods: We included 19 ADHD-CoUD patients (84.2% male; age: 32.11 years [7.18]) and 16 CoUD patients (68.7% male; age: 36.63 years [8.12]). All subjects underwent a fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET) brain scan. We tested brain metabolism differences between ADHD-CoUD and CoUD patients using voxel-based and regions of interest (ROIs)-based analyses. The correlation between dependence/abstinence duration and regional brain metabolism was also assessed in the two groups. Lastly, we investigated the integrity of brain metabolic connectivity of mesocorticolimbic and nigrostriatal dopaminergic systems, and large-scale brain networks involved in ADHD and addictions. Results: The voxel-wise and ROIs-based approaches showed that ADHD-CoUD patients had a lower metabolism in the thalamus and increased metabolism in the amygdala and parahippocampus, bilaterally, than CoUD subjects and healthy controls (HCs). Metabolism in the thalamus negatively correlated with years of dependence in ADHD-CoUD patients. Moreover, connectivity analyses revealed that ADHD-CoUD patients had a more preserved metabolic connectivity than CoUD patients in the dopaminergic networks and large-scale networks involved in self-regulation mechanisms of attention and behaviors (i.e., anterior default mode network [ADMN], executive network [ECN], and anterior salience network [aSAN]). Conclusions: We demonstrated distinct neuropathological substrates underlying substance-use behaviors in ADHD-CoUD and CoUD patients. Furthermore, we provided neurobiological evidence in support of SMH, demonstrating that ADHD-CoUD patients might experience short-term advantages of cocaine assumption (i.e., compensation of dopaminergic deficiency and related cognitive-behavioral deficits).

Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study.

Background: Tumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging. Objectives: This study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity. Materials and Methods: Seventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats' spatial distribution, quantitative features and histopathological characteristics were analyzed. Results: A highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed. Conclusion: Preliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.

Association of Microglial Activation With Spontaneous ARIA-E and CSF Levels of Anti-Aß Autoantibodies.

BACKGROUND AND OBJECTIVES: Amyloid-related imaging abnormalities suggestive of vasogenic edema or sulcal effusion (ARIA-E) are the most common adverse events complicating Alzheimer disease (AD) immunotherapy with anti-ß-amyloid (Aß) monoclonal antibodies. ARIA-E can also occur spontaneously in cerebral amyloid angiopathy-related inflammation (CAA-ri), a rare autoimmune encephalopathy associated with increased CSF levels of anti-Aß autoantibodies. Although the pathophysiologic mechanisms of ARIA-E remain to be fully elucidated, experimental evidence from ex vivo studies suggests that gantenerumab and aducanumab enable microglial activation. However, the in vivo evidence for a direct association between neuroinflammation and ARIA-E in patients with high CSF anti-Aß (auto)antibody levels has never been demonstrated. METHODS: The spatial distribution and temporal variations of microglial activation associated with levels of anti-Aß autoantibodies at (sub)acute presentation of ARIA-E and after corticosteroid therapy were evaluated in a longitudinal case series of patients with CAA-ri, the spontaneous variant of the iatrogenic ARIA-E reported in Aß-lowering immunotherapy with monoclonal antibodies. Multimodal and multiparametric MRI was used for CAA and ARIA-E severity quantification, according to validated scoring system; CSF testing for anti-Aß autoantibodies and AD biomarkers; 11C-PK11195 PET for activated microglia. RESULTS: At (sub)acute presentation, we found focal peaks of microglial activation having a greater spatial colocalization with ARIA-E compared with chronic age-related white matter change imaging abnormalities. The severity of ARIA-E and the magnitude of the associated microglial activation were greater in patients having AD and severe CAA concomitant disease compared with patients having CAA only. CSF anti-Aß autoantibodies at presentation were high in all patients and markedly decreased at posttreatment follow-up, in parallel with clinical resolution of acute symptoms, reduced ARIA-E severity, and reduced microglial activation. DISCUSSION: Our findings extend the current notion of ARIA-E by providing the first in vivo 11C-PK11195 PET evidence for an association between microglial activation and the magnitude and severity of ARIA-E in patients with increased CSF concentration of anti-Aß autoantibodies and comorbid AD and CAA disease. Our results highlight CSF testing for anti-Aß autoantibodies as a promising diagnostic, prognostic, and therapy response biomarker to help guide future treatment and management decisions in real clinical practice and clinical trials.

Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre-Mild Cognitive Impairment.

BACKGROUND AND OBJECTIVE: Multicenter study aiming at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre-Mild Cognitive Impairment, pre-MCI). METHODS: Data were obtained from the Network-AD project (NET-2011-02346784). The included subjects underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and, amyloid-PET. We used Principal Component Analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism. RESULTS: A total of 105 subjects (SCD=49, pre-MCI=56) were included. FDG-PET was normal in 45% of subjects and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the subjects that underwent amyloid-PET (n=60). PCA resulted in three neuropsychological factors: 1) executive/visuo-motor, correlating with hypometabolism in frontal, occipital cortices and basal ganglia; 2) memory, correlating with hypometabolism in temporo-parietal regions; 3) visuo-spatial/constructional, correlating with hypometabolism in fronto-parietal cortices. Two factors emerged from the neuropsychiatric PCA: 1) affective, correlating with hypometabolism in orbito-frontal, cingulate cortex, insula; 2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal and parietal regions. DISCUSSION: FDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre-MCI subjects. These results indicate that SCD and pre-MCI represent heterogeneous populations. Consistently, different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.

18F-FDG PET/CT May Predict Tumor Type and Risk Score in Gestational Trophoblastic Disease.

PURPOSE: The aim of this study was to investigate the role of 18F-FDG PET/CT in predicting pathological prognostic factors, including tumor type and International Federation of Gynecology and Obstetrics (FIGO) score, in gestational trophoblastic disease (GTD). METHODS: Retrospective monocentric study including 24 consecutive patients who underwent to 18F-FDG PET/CT from May 2005 to March 2021 for GTD staging purpose. The following semiquantitative PET parameters were measured from the primary tumor and used for the analysis: maximum standardized uptake value (SUVmax), SUVmean, metabolic tumor volume (MTV) and total lesion glycolisis (TLG). Statistical analysis included Spearman correlation coefficient to evaluate the correlations between imaging parameters and tumor type (nonmolar trophoblastic vs postmolar trophoblastic tumors) and risk groups (high vs low, defined according to the FIGO score), whereas area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the predictive value of the PET parameters. Mann-Whitney U test was used to further describe the parameter's potential in differentiating the populations. RESULTS: SUVmax and SUVmean resulted fair (AUC, 0.783; 95% confidence interval [CI], 0.56-0.95) and good (AUC, 0.811; 95% CI, 0.59-0.97) predictors of tumor type, respectively, showing a low (ρ = 0.489, adjusted P = 0.030) and moderate (ρ = 0.538, adjusted P = 0.027) correlation. According to FIGO score, TLG was instead a fair predictor (AUC, 0.770; 95% CI, 0.50-0.99) for patient risk stratification. CONCLUSIONS: 18F-FDG PET parameters have a role in predicting GTD pathological prognostic factors, with SUVmax and SUVmean being predictive for tumor type and TLG for risk stratification.

Evaluation of a 2D UNet-Based Attenuation Correction Methodology for PET/MR Brain Studies.

Deep learning (DL) strategies applied to magnetic resonance (MR) images in positron emission tomography (PET)/MR can provide synthetic attenuation correction (AC) maps, and consequently PET images, more accurate than segmentation or atlas-registration strategies. As first objective, we aim to investigate the best MR image to be used and the best point of the AC pipeline to insert the synthetic map in. Sixteen patients underwent a 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) and a PET/MR brain study in the same day. PET/CT images were reconstructed with attenuation maps obtained: (1) from CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with a 2D UNet trained on MR image/attenuation map pairs. As for MR, T1-weighted and Zero Time Echo (ZTE) images were considered; as for attenuation maps, CTs and 511 keV low-resolution attenuation maps were assessed. As second objective, we assessed the ability of DL strategies to provide proper AC maps in presence of cranial anatomy alterations due to surgery. Three 11C-methionine (METH) PET/MR studies were considered. PET images were reconstructed with attenuation maps obtained: (1) from diagnostic coregistered CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with 2D UNets trained on the sixteen FDG anatomically normal patients. Only UNets taking ZTE images in input were considered. FDG and METH PET images were quantitatively evaluated. As for anatomically normal FDG patients, UNet AC models generally provide an uptake estimate with lower bias than atlas-based or segmentation-based methods. The intersubject average bias on images corrected with UNet AC maps is always smaller than 1.5%, except for AC maps generated on too coarse grids. The intersubject bias variability is the lowest (always lower than 2%) for UNet AC maps coming from ZTE images, larger for other methods. UNet models working on MR ZTE images and generating synthetic CT or 511 keV low-resolution attenuation maps therefore provide the best results in terms of both accuracy and variability. As for METH anatomically altered patients, DL properly reconstructs anatomical alterations. Quantitative results on PET images confirm those found on anatomically normal FDG patients.

In vivo susceptibility to energy failure parkinsonism and LRRK2 kinase activity.

The G2019S mutation of LRRK2 represents a risk factor for idiopathic Parkinson's disease. Here, we investigate whether LRRK2 kinase activity regulates susceptibility to the environmental toxin 1-methyl-4-phenyl-1,2,5,6-tetrahydropyridine (MPTP). G2019S knock-in mice (bearing enhanced kinase activity) showed greater nigro-striatal degeneration compared to LRRK2 knock-out, LRRK2 kinase-dead and wild-type mice following subacute MPTP treatment. LRRK2 kinase inhibitors PF-06447475 and MLi-2, tested under preventive or therapeutic treatments, protected against nigral dopamine cell loss in G2019S knock-in mice. MLi-2 also rescued striatal dopaminergic terminal degeneration in both G2019S knock-in and wild-type mice. Immunoblot analysis of LRRK2 Serine935 phosphorylation levels confirmed target engagement of LRRK2 inhibitors. However, MLi-2 abolished phosphoSerine935 levels in the striatum and midbrain of both wild-type and G2019S knock-in mice whereas PF-06447475 partly reduced phosphoSerine935 levels in the midbrain of both genotypes. In vivo and ex vivo uptake of the 18-kDa translocator protein (TSPO) ligand [18F]-VC701 revealed a similar TSPO binding in MPTP-treated wild-type and G2019S knock-in mice which was consistent with an increased GFAP striatal expression as revealed by Real Time PCR. We conclude that LRRK2 G2019S, likely through enhanced kinase activity, confers greater susceptibility to mitochondrial toxin-induced parkinsonism. LRRK2 kinase inhibitors are neuroprotective in this model.

State of the art of radiomic analysis in the clinical management of prostate cancer: A systematic review.

We present the current clinical applications of radiomics in the context of prostate cancer (PCa) management. Several online databases for original articles using a combination of the following keywords: "(radiomic or radiomics) AND (prostate cancer or prostate tumour or prostate tumor or prostate neoplasia)" have been searched. The selected papers have been pooled as focus on (i) PCa detection, (ii) assessing the clinical significance of PCa, (iii) biochemical recurrence prediction, (iv) radiation-therapy outcome prediction and treatment efficacy monitoring, (v) metastases detection, (vi) metastases prediction, (vii) prediction of extra-prostatic extension. Seventy-six studies were included for qualitative analyses. Classifiers powered with radiomic features were able to discriminate between healthy tissue and PCa and between low- and high-risk PCa. However, before radiomics can be proposed for clinical use its methods have to be standardized, and these first encouraging results need to be robustly replicated in large and independent cohorts.

In vivo human molecular neuroimaging of dopaminergic vulnerability along the Alzheimer's disease phases.

BACKGROUND: Preclinical and pathology evidence suggests an involvement of brain dopamine (DA) circuitry in Alzheimer's disease (AD). We in vivo investigated if, when, and in which target regions [123I]FP-CIT-SPECT regional binding and molecular connectivity are damaged along the AD course. METHODS: We retrospectively selected 16 amyloid-positive subjects with mild cognitive impairment due to AD (AD-MCI), 22 amyloid-positive patients with probable AD dementia (AD-D), and 74 healthy controls, all with available [123I]FP-CIT-SPECT imaging. We tested whether nigrostriatal vs. mesocorticolimbic dopaminergic targets present binding potential loss, via MANCOVA, and alterations in molecular connectivity, via partial correlation analysis. Results were deemed significant at p < 0.05, after Bonferroni correction for multiple comparisons. RESULTS: We found significant reductions of [123I]FP-CIT binding in both AD-MCI and AD-D compared to controls. Binding reductions were prominent in the major targets of the ventrotegmental-mesocorticolimbic pathway, namely the ventral striatum and the hippocampus, in both clinical groups, and in the cingulate gyrus, in patients with dementia only. Within the nigrostriatal projections, only the dorsal caudate nucleus showed reduced [123I]FP-CIT binding, in both groups. Molecular connectivity assessment revealed a widespread loss of inter-connections among subcortical and cortical targets of the mesocorticolimbic network only (poor overlap with the control group as expressed by a Dice coefficient ≤ 0.25) and no alterations of the nigrostriatal network (high overlap with controls, Dice coefficient = 1). CONCLUSION: Local- and system-level alterations of the mesocorticolimbic dopaminergic circuitry characterize AD, already in prodromal disease phases. These results might foster new therapeutic strategies for AD. The clinical correlates of these findings deserve to be carefully considered within the emergence of both neuropsychiatric symptoms and cognitive deficits.

Preliminary Results of an Ongoing Prospective Clinical Trial on the Use of 68Ga-PSMA and 68Ga-DOTA-RM2 PET/MRI in Staging of High-Risk Prostate Cancer Patients.

The aim of the present study is to investigate the synergic role of 68Ga-PSMA PET/MRI and 68Ga-DOTA-RM2 PET/MRI in prostate cancer (PCa) staging. We present pilot data on twenty-two patients with biopsy-proven PCa that underwent 68Ga-PSMA PET/MRI for staging purposes, with 19/22 also undergoing 68Gaa-DOTA-RM2 PET/MRI. TNM classification based on image findings was performed and quantitative imaging parameters were collected for each scan. Furthermore, twelve patients underwent radical prostatectomy with the availability of histological data that were used as the gold standard to validate intraprostatic findings. A DICE score between regions of interest manually segmented on the primary tumour on 68Ga-PSMA PET, 68Ga-DOTA-RM2 PET and on T2 MRI was computed. All imaging modalities detected the primary PCa in 18/19 patients, with 68Ga-DOTA-RM2 PET not detecting any lesion in 1/19 patients. In the remaining patients, 68Ga-PSMA and MRI were concordant. Seven patients presented seminal vesicles involvement on MRI, with two of these being also detected by 68Ga-PSMA, and 68Ga-DOTA-RM2 PET being negative. Regarding extraprostatic disease, 68Ga-PSMA PET, 68Ga-DOTA-RM2 PET and MRI resulted positive in seven, four and five patients at lymph-nodal level, respectively, and at a bone level in three, zero and one patients, respectively. These preliminary results suggest the potential complementary role of 68Ga-PSMA PET, 68Ga-DOTA-RM2 PET and MRI in PCa characterization during the staging phase.

Brain Metabolism and Microglia Activation in Mild Cognitive Impairment: A Combined [18F]FDG and [11C]-(R)-PK11195 PET Study.

BACKGROUND: Mild cognitive impairment (MCI) is a transitional condition between normal cognition and dementia. [18F]FDG-PET reveals brain hypometabolism patterns reflecting neuronal/synaptic dysfunction, already in the prodromal MCI phase. Activated microglia is part of the pathogenetic processes leading to neurodegeneration. OBJECTIVE: Using [11C]-(R)-PK11195 and [18F]FDG-PET, we aimed to in vivo investigate the presence of microglial activation, and the relationship with brain glucose metabolism, in single MCI subjects. METHODS: Eight MCI subjects underwent both [18F]FDG-PET and [11C]-(R)-PK11195 PET. We used validated quantification methods to obtain brain hypometabolism maps and microglia activation peaks in single subjects. We investigated both the spatial overlap and the relationship between brain glucose hypometabolism and microglia activation, by means of Dice similarity coefficient and using Pearson's correlation at single subject level. RESULTS: Each MCI showed a specific brain hypometabolism pattern indicative of different possible etiologies, as expected in MCI population (i.e., Alzheimer's disease-like, frontotemporal dementia-like, hippocampal-type, normal aging type). [11C]-(R)-PK11195 PET analysis revealed a spatial concordance with regional hypometabolism in all subjects with several clusters of significant microglia activation showing an inverse correlation with the regional metabolism. This was proportional to the strength of between-signals correlation coefficient (ß â€Š=  -0.804; p = 0.016). CONCLUSION: Microglia activation is present in the prodromal MCI phase of different underlying etiologies, showing spatial concordance and inverse correlation with brain glucose metabolism at single-subject level. These findings suggest a possible contribution of activated microglia to neurodegeneration, showing important implications for local immune activity in the early neurodegenerative processes.

Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps.

PURPOSE: An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level. METHODS: Selection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB. RESULTS: Two-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes. CONCLUSIONS: The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Biomarker-based stability in limbic-predominant amnestic mild cognitive impairment.

BACKGROUND: The amnestic presentation of mild cognitive impairment (aMCI) represents the most common prodromal stage of Alzheimer's disease (AD) dementia. There is, however, some evidence of aMCI with typical amnestic syndrome but showing long-term clinical stability. The ability to predict stability or progression to dementia in the aMCI condition is important, particularly for the selection of candidates in clinical trials. We aimed to establish the role of in vivo biomarkers, as assessed by cerebrospinal fluid (CSF) measures and [18 F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging, in predicting prognosis in a large aMCI cohort. METHODS: We conducted a retrospective study, including 142 aMCI subjects who had a long follow-up (4-19 years), baseline CSF data and [18 F]FDG-PET scans individually assessed by validated voxel-based procedures, classifying subjects into either limbic-predominant or AD-like hypometabolism patterns. RESULTS: The two aMCI cohorts were clinically comparable at baseline. At follow-up, the aMCI group with a limbic-predominant [18 F]FDG-PET pattern showed clinical stability over a very long follow-up (8.20 ± 3.30 years), no decline in Mini-Mental State Examination score, and only 7% conversion to dementia. Conversely, the aMCI group with an AD-like [18 F]FDG-PET pattern had a high rate of dementia progression (86%) over a shorter follow-up (6.47 ± 2.07 years). Individual [18 F]FDG-PET hypometabolism patterns predicted stability or conversion with high accuracy (area under the curve = 0.89), sensitivity (0.90) and specificity (0.89). In the limbic-predominant aMCI cohort, CSF biomarkers showed large variability and no prognostic value. CONCLUSIONS: In a large series of clinically comparable subjects with aMCI at baseline, the specific [18 F]FDG-PET limbic-predominant hypometabolism pattern was associated with clinical stability, making progression to AD very unlikely. The identification of a biomarker-based benign course in aMCI subjects has important implications for prognosis and in planning clinical trials.

Neural correlates of naming errors across different neurodegenerative diseases: An FDG-PET study.

OBJECTIVE: To investigate the types of errors produced in a picture naming task by patients with neurodegenerative dementia due to different etiologies and their neural correlates. METHODS: The same standardized picture naming test was administered to a consecutive sample of patients (n = 148) who had been studied with [18F] FDG-PET. The errors were analyzed in 3 categories (visual, semantic, and phonologic). The PET data were analyzed using an optimized single-subject procedure, and the statistical parametric mapping multiple regression design was used to explore the correlation between each type of error and brain hypometabolism in the whole group. Metabolic connectivity analyses were run at the group level on 7 left hemisphere cortical areas corresponding to an a priori defined naming network. RESULTS: Semantic errors were predominant in most patients, independent of clinical diagnosis. In the whole group analysis, visual errors correlated with hypometabolism in the right inferior occipital lobe and in the left middle occipital lobe. Semantic errors correlated with hypometabolism in the left fusiform gyrus, the inferior and middle temporal gyri, and the temporal pole. Phonologic errors were associated with hypometabolism in the left superior and middle temporal gyri. Both positive (occipital-posterior fusiform) and negative (anterior fusiform gyrus and the superior anterior temporal lobe) connectivity changes were associated with semantic errors. CONCLUSIONS: Naming errors reflect the dysfunction of separate stages of the naming process and are specific markers for different patterns of brain involvement. These correlations are not limited to primary progressive aphasia but extend to other neurodegenerative dementias.

Dual tracer 68Ga-DOTATOC and 18F-FDG PET/computed tomography radiomics in pancreatic neuroendocrine neoplasms: an endearing tool for preoperative risk assessment.

AIM: To explore the potentiality of radiomics analysis, performed on Ga-DOTATOC and fluorine-18-fluorodeoxyglucose (F-FDG) PET/computed tomography (CT) images, in predicting tumour aggressiveness and outcome in patients candidate to surgery for pancreatic neuroendocrine neoplasms (PanNENs). PATIENTS AND METHODS: Retrospective study including 61 patients who underwent Ga-DOTATOC and F-FDG PET/CT before surgery for PanNEN. Semiquantitative variables [SUVmax and somatostatin receptor density (SRD) for Ga-DOTATOC PET; SUVmax and MTV for F-FDG PET] and texture features [intensity variability, size zone variability (SZV), zone percentage, entropy; homogeneity, dissimilarity and coefficient of variation (Co-V)] have been analysed to evaluate their possible role in predicting tumour characteristics. Principal component analysis (PCA) was firstly performed and then multiple regression analyses were performed by using the extracted principal components. RESULTS: Regarding Ga-DOTATOC PET, SZV, entropy, intensity variability and SRD were predictive for tumour dimension. Regarding F-FDG PET, intensity variability, SZV, homogeneity, SUVmax and MTV were predictive for tumour dimension. Four principal components were extracted from PCA: PC1 correlated with all F-FDG variables, while PC2, PC3 and PC4 with Ga-DOTATOC variables. PC1 was the only significantly predicting angioinvasion (P = 0.0222); PC4 was the only one significantly predicting lymph nodal involvement (P = 0.0151). All principal components except PC4 significantly predicted tumour dimension (P <0.0001 for PC1, P = 0.0016 for PC2 and P < 0.0001 for PC3). Co-V from Ga-DOTATOC PET/CT was predictive of the outcome. CONCLUSION: Specific texture features derived from preoperative Ga-DOTATOC and F-FDG PET/CT could noninvasively predict specific tumour characteristics and patients' outcome, delineating the potential role of dual tracer technique and texture analysis in the risk assessment of patients with PanNENs.

11 C-PK11195 PET-based molecular study of microglia activation in SOD1 amyotrophic lateral sclerosis.

OBJECTIVE: Neuroinflammation is considered a key driver for neurodegeneration in several neurological diseases, including amyotrophic lateral sclerosis (ALS). SOD1 mutations cause about 20% of familial ALS, and related pathology might generate microglial activation triggering neurodegeneration. 11 C-PK11195 is the prototypical and most validated PET radiotracer, targeting the 18-kDa translocator protein which is overexpressed in activated microglia. In this study, we investigated microglia activation in asymptomatic (ASYM) and symptomatic (SYM) SOD1 mutated carriers, by using 11 C-PK11195 and PET imaging. METHODS: We included 20 subjects: 4 ASYM-carriers, neurologically normal, 6 SYM-carriers with probable ALS, and 10 healthy controls. A receptor parametric mapping procedure estimated 11 C-PK11195 binding potentials and voxel-wise statistical comparisons were performed at group and single-subject levels. RESULTS: Both the SYM- and ASYM-carriers showed significant microglia activation in cortical and subcortical structures, with variable patterns at individual level. Clusters of activation were present in occipital and temporal regions, cerebellum, thalamus, and medulla oblongata. Notably, SYM-carriers showed microglia activation also in supplementary and primary motor cortices and in the somatosensory regions. INTERPRETATION: In vivo neuroinflammation occurred in all SOD1 mutated cases since the presymptomatic stages, as shown by a significant cortical and subcortical microglia activation. The involvement of sensorimotor cortex became evident at the symptomatic disease stage. Although our data indicate the role of in vivo PET imaging for assessing resident microglia in the investigation of SOD1-ALS pathophysiology, further studies are needed to clarify the temporal and spatial dynamics of microglia activation and its relationship with neurodegeneration.

The combined effects of microglia activation and brain glucose hypometabolism in early-onset Alzheimer's disease.

BACKGROUND: Early-onset Alzheimer's disease (EOAD) is characterized by young age of onset (< 65 years), severe neurodegeneration, and rapid disease progression, thus differing significantly from typical late-onset Alzheimer's disease. Growing evidence suggests a primary role of neuroinflammation in AD pathogenesis. However, the role of microglia activation in EOAD remains a poorly explored field. Investigating microglial activation and its influence on the development of synaptic dysfunction and neuronal loss in EOAD may contribute to the understanding of its pathophysiology and to subject selection in clinical trials. In our study, we aimed to assess the amount of neuroinflammation and neurodegeneration and their relationship in EOAD patients, through positron emission tomography (PET) measures of microglia activation and brain metabolic changes. METHODS: We prospectively enrolled 12 EOAD patients, classified according to standard criteria, who underwent standard neurological and neuropsychological evaluation, CSF analysis, brain MRI, and both [18F]-FDG PET and [11C]-(R)-PK11195 PET. Healthy controls databases were used for statistical comparison. [18F]-FDG PET brain metabolism in single subjects and as a group was assessed by an optimized SPM voxel-wise single-subject method. [11C]-PK11195 PET binding potentials were obtained using reference regions selected with an optimized clustering procedure followed by a parametric analysis. We performed a topographic interaction analysis and correlation analysis in AD-signature metabolic dysfunctional regions and regions of microglia activation. A network connectivity analysis was performed using the interaction regions of hypometabolism and [11C]-PK11195 PET BP increases. RESULTS: EOAD patients showed a significant and extended microglia activation, as [11C]-PK11195 PET binding potential increases, and hypometabolism in typical AD-signature brain regions, i.e., temporo-parietal cortex, with additional variable frontal and occipital hypometabolism in the EOAD variants. There was a spatial concordance in the interaction areas and significant correlations between the two biological changes. The network analysis showed a disruption of frontal connectivity induced by the metabolic/microglia effects. CONCLUSION: The severe microglia activation characterizing EOAD and contributing to neurodegeneration may be a marker of rapid disease progression. The coupling between brain glucose hypometabolism and local immune response in AD-signature regions supports their biological interaction.