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Methods: This study assessed data from two cohorts of patients with alpha‐synucleinopathies (University of Brescia and University of Rome Tor‐Vergata cohorts). Consecutive participants with video‐polysomnography‐confirmed iRBD, Parkinson's disease (PD), dementia with Lewy bodies (DLB) and controls underwent neurological, clinical and 123I‐FP‐CIT SPECT imaging assessments. Individuals with iRBD were longitudinally monitored to collect clinical phenoconversion to PD or DLB. The main outcome was to identify whole brain 123 I‐FP‐CIT SPECT measures reflecting monoaminergic deficits in each clinical group as compared to controls. Results: The cohort (n = 184) included 45 patients with iRBD, 47 PD, 42 DLB and 50 age‐matched controls. Individuals with iRBD were categorized as RBD‐DAT− (n = 32) and RBD‐DAT+ (n = 13), according to nigrostriatal assessment used in clinical practice. Compared to controls, RBD‐DAT− showed an early involvement of the left insula, which increased in RBD‐DAT+, and was present in patients with Parkinson's disease and dementia with Lewy bodies. Longitudinal cox regression analyses revealed a higher risk of phenoconversion in individuals with iRBD and insular monoaminergic deficits [HR = 3.387; CI 95%: 1.18–10.27]. Interpretation: In this study, altered insular monoaminergic binding in iRBD was associated with phenoconversion to DLB or PD. These findings may provide a helpful stratification approach for future pharmacological or non‐pharmacological interventions. [ABSTRACT FROM AUTHOR]

Super‐resolution strategies expand the applicability of imaging modalities toward previously inaccessible spatial scales. Herein, photoactivated far‐infrared thermography is pushed from the millimeter to the micrometer scale by a 2D super‐resolution imaging approach capable of tackling the resolution barriers imposed by both diffraction‐limited signal collection and lateral spatiotemporal heat diffusion. The proposed imaging strategy relies on a full‐wave forward model of far‐infrared thermography and on an image‐inversion approach, which reconstructs the surface distribution of the sample photothermal absorbers via gradient‐descent optimization as the one yielding the best match between predicted and experimental images. With minute‐long acquisitions on a commercial low‐cost far‐infrared camera, less‐than‐5 μm spatial resolution is demonstrated on both synthetic samples and human liver biopsies ex vivo, thereby exemplifying the applicability of super‐resolution photothermal imaging to the fast nondestructive characterization of biological specimens well below the tissue spatial scale. [ABSTRACT FROM AUTHOR]

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 preoperative 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 fluidattenuated 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. Materials and Methods: Seventeen patients harboring HGGs underwent a preoperative 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 fluidattenuated 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. 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. [ABSTRACT FROM AUTHOR]

Background: Time-of-Flight (TOF) is a leading technological development of Positron Emission Tomography (PET) scanners. It reduces noise at the Maximum-Likelihood solution, depending on the coincidence–timing–resolution (CTR). However, in clinical applications, it is still not clear how to best exploit TOF information, as early stopped reconstructions are generally used. Methods: A contrast-recovery (CR) matching rule for systems with different CTRs and non-TOF systems is theoretically derived and validated using (1) digital simulations of objects with different contrasts and background diameters, (2) realistic phantoms of different sizes acquired on two scanners with different CTRs. Results: With TOF, the CR matching rule prescribes modifying the iterations number by the CTRs ratio. Without TOF, the number of iterations depends on the background dimension. CR matching was confirmed by simulated and experimental data. With TOF, image noise followed the square root of the CTR when the rule was applied on simulated data, while a significant reduction was obtained on phantom data. Without TOF, preserving the CR on larger objects significantly increased the noise. Conclusions: TOF makes PET reconstructions less dependent on background dimensions, thus, improving the quantification robustness. Better CTRs allows performing fewer updates, thus, maintaining accuracy while minimizing noise. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 [18F]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 [18F]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 [18F]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 [18F]FDG‐PET pattern had a high rate of dementia progression (86%) over a shorter follow‐up (6.47 ± 2.07 years). Individual [18F]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 [18F]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. [ABSTRACT FROM AUTHOR]

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 (β  =  -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. [ABSTRACT FROM AUTHOR]

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. 11C‐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 11C‐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 11C‐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. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is characterized by an involvement of brain dopamine (DA) circuitry, the presence of which has been associated with emergence of both neuropsychiatric symptoms and cognitive deficits.Objective: In order to investigate whether and how the DA pathways are involved in the pathophysiology of AD, we assessed by in vivo neuroimaging the structural and metabolic alterations of subcortical and cortical DA pathways and targets.Methods: We included 54 healthy control participants, 53 amyloid-positive subjects with mild cognitive impairment due to AD (MCI-AD), and 60 amyloid-positive patients with probable dementia due to AD (ADD), all with structural 3T MRI and 18F-FDG-PET scans. We assessed MRI-based gray matter reductions in the MCI-AD and ADD groups within an anatomical a priori-defined Nigrostriatal and Mesocorticolimbic DA pathways, followed by 18F-FDG-PET metabolic connectivity analyses to evaluate network-level metabolic connectivity changes.Results: We found significant tissue loss in the Mesocorticolimbic over the Nigrostriatal pathway. Atrophy was evident in the ventral striatum, orbitofrontal cortex, and medial temporal lobe structures, and already plateaued in the MCI-AD stage. Degree of atrophy in Mesocorticolimbic regions positively correlated with the severity of depression, anxiety, and apathy in MCI-AD and ADD subgroups. Additionally, we observed significant alterations of metabolic connectivity between the ventral striatum and fronto-cingulate regions in ADD, but not in MCI-AD. There were no metabolic connectivity changes within the Nigrostriatal pathway.Conclusion: Our cross-sectional data support a clinically-meaningful, yet stage-dependent, involvement of the Mesocorticolimbic system in AD. Longitudinal and clinical correlation studies are needed to further establish the relevance of DA system involvement in AD. [ABSTRACT FROM AUTHOR]

Positron Emission Tomography image reconstruction needs a map of photon attenuation probability to provide the correct solution. This map is generally provided by an independent imaging modality. However, it might suffer for artifacts due to patient motion in sequential systems or from intrinsic limitation of the second modality (e.g.: bones that cannot be identified in MR images). It has been shown that such map can be estimated from the PET data themselves, but the solution to this problem has much worse conditioning than the tomographic problem. In this work we propose a new algorithm based on the use of multiple L1 regularization terms in the attenuation sub-problem, to incorporate prior knowledge. We also chose optimal maximizers for both sub-problems: preconditioned gradient descent for the emission one and split-Bregman for the attenuation one. The algorithm was then tested using digital phantom simulations. The proposed algorithm proved to provide accurate quantification over a large range of strength of the regularization terms. The algorithm is also able to reconstruct objects outside of the region where the problem is uniquely determined and it is able to fix the undetermined global scaling factor of joint attenuation and emission estimation. Thanks to the maximizers chosen, the algorithm is computationally less expensive than the current standard. [ABSTRACT FROM AUTHOR]

Rationale: Pathological response to neo-adjuvant chemotherapy (NAC) represents a commonly used predictor of survival in triple negative breast cancer (TNBC) and the need to identify markers that predict response to NAC is constantly increasing. Aim of this study was to evaluate the potential usefulness of PET imaging with [18F]FDG and [18F]FLT for the discrimination of TNBC responders to Paclitaxel (PTX) therapy compared to the response assessed by an adapted Response Evaluation Criteria In Solid Tumors (RECIST) criteria based on tumor volume (Tumor Volume Response). Methods: Nu/nu mice bearing TNBC lesions of different size were evaluated with [18F]FDG and [18F]FLT PET before and after PTX treatment. SUVmax, Metabolic Tumor Volume (MTV) and Total Lesion Glycolysis (TLG) and Proliferation (TLP) were assessed using a graph-based random walk algorithm. Results: We found that in our TNBC model the variation of [18F]FDG and [18F]FLT SUVmax similarly defined tumor response to therapy and that SUVmax variation represented the most accurate parameter. Response evaluation using Tumor Volume Response (TVR) showed that the effectiveness of NAC with PTX was completely independent from lesions size at baseline. Conclusions: Our study provided interesting results in terms of sensitivity and specificity of PET in TNBC, revealing the similar performances of [18F]FDG and [18F]FLT in the identification of responders to Paclitaxel. [ABSTRACT FROM AUTHOR]

Microgliosis is part of the immunobiology of Creutzfeldt-Jakob disease (CJD). This is the first report using 11C-(R)-PK11195 PET imaging in vivo to measure 18 kDa translocator protein (TSPO) expression, indexing microglia activation, in symptomatic CJD patients, followed by a postmortem neuropathology comparison. One genetic CJD (gCJD) patient, two sporadic CJD (sCJD) patients, one variant CJD (vCJD) patient (mean ± SD age, 47.50 ± 15.95 years), and nine healthy controls (mean ± SD age, 44.00 ± 11.10 years) were included in the study. TSPO binding potentials were estimated using clustering and parametric analyses of reference regions. Statistical comparisons were run at the regional and at the voxel-wise levels. Postmortem evaluation measured scrapie prion protein (PrPSc) immunoreactivity, neuronal loss, spongiosis, astrogliosis, and microgliosis. 11C-(R)-PK11195-PET showed a significant TSPO overexpression at the cortical level in the two sCJD patients, as well as thalamic and cerebellar involvement; very limited parieto-occipital activation in the gCJD case; and significant increases at the subcortical level in the thalamus, basal ganglia, and midbrain and in the cerebellum in the vCJD brain. Along with misfolded prion deposits, neuropathology in all patients revealed neuronal loss, spongiosis and astrogliosis, and a diffuse cerebral and cerebellar microgliosis which was particularly dense in thalamic and basal ganglia structures in the vCJD brain. These findings confirm significant microgliosis in CJD, which was variably modulated in vivo and more diffuse at postmortem evaluation. Thus, TSPO overexpression in microglia activation, topography, and extent can vary in CJD subtypes, as shown in vivo, possibly related to the response to fast apoptotic processes, but reaches a large amount at the final disease course. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Postmortem studies reported significant microglia activation in association with neuronal apoptosis in Fatal Familial Insomnia (FFI), indicating a specific glial response, but negative evidence also exists. An in vivo study of local immune responses over FFI natural course may contribute to the understanding of the underlying pathogenesis. Methods: We included eight presymptomatic subjects (mean ± SD age:44.13 ± 3.83 years) carrying the pathogenic D178N‐129met FFI mutation, one symptomatic patient (male, 45 yrs. old), and nine healthy controls (HC) (mean ± SD age: 44.00 ± 11.10 years.) for comparisons. 11C‐(R)‐PK11195 PET allowed the measurement of Translocator Protein (TSPO) overexpression, indexing microglia activation. A clustering algorithm was adopted to define subject‐specific reference regions. Voxel‐wise statistical analyses were performed on 11C‐(R)‐PK11195 binding potential (BP) images both at the group and individual level. Results: The D178N‐129met/val FFI patient showed significant 11C‐(R)‐PK11195 BP increases in the midbrain, cerebellum, anterior thalamus, anterior cingulate cortex, orbitofrontal cortex, and anterior insula, bilaterally. Similar TSPO increases, but limited to limbic structures, were observed in four out of eight presymptomatic carriers. The only carrier with the codon 129met/val polymorphism was the only one showing an additional TSPO increase in the anterior thalamus. Interpretation: In comparison to nonprion neurodegenerative diseases, the observed lack of a diffuse brain TSPO overexpression in preclinical and the clinical FFI cases suggests the presence of a different microglia response. The involvement of limbic structures might indicate a role for microglia activation in these key pathologic regions, known to show the most significant neuronal loss and functional deafferentation in FFI. [ABSTRACT FROM AUTHOR]

Cognitive reserve (CR) and brain reserve (BR) are protective factors against age-associated cognitive decline and neurodegenerative disorders. Very limited evidence exists about gender effects on brain aging and on the effect of CR on brain modulation in healthy aging and Alzheimer's Dementia (AD). We investigated gender differences in brain metabolic activity and resting-state network connectivity, as measured by 18F-FDG-PET, in healthy aging and AD, also considering the effects of education and occupation. The clinical and imaging data were retrieved from large datasets of healthy elderly subjects (HE) (225) and AD patients (282). In HE, males showed more extended age-related reduction of brain metabolism than females in frontal medial cortex. We also found differences in brain modulation as metabolic increases induced by education and occupation, namely in posterior associative cortices in HE males and in the anterior limbic-affective and executive networks in HE females. In AD patients, the correlations between education and occupation levels and brain hypometabolism showed gender differences, namely a posterior temporo-parietal association in males and a frontal and limbic association in females, indicating the involvement of different networks. Finally, the metabolic connectivity in both HE and AD aligned with these results, suggesting greater efficiency in the posterior default mode network for males, and in the anterior frontal executive network for females. The basis of these brain gender differences in both aging and AD, obtained exploring cerebral metabolism, metabolic connectivity and the effects of education and occupation, is likely at the intersection between biological and sociodemographic factors. Hum Brain Mapp 38:4212-4227, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

F-fluoro-deoxy-glucose Positron Emission Tomography (FDG-PET) allows early identification of neurodegeneration in dementia. The use of an optimized method based on the SPM software package highly improves diagnostic accuracy. However, the impact of different scanners for data acquisition on the SPM results and the effects of different pools of healthy subjects on the statistical comparison have not been investigated yet. Images from 144 AD patients acquired using six different PET scanners were analysed with an optimized single-subject SPM procedure to identify the typical AD hypometabolism pattern at single subject level. We compared between-scanners differences on the SPM outcomes in a factorial design. Single-subject SPM comparison analyses were also performed against a different group of healthy controls from the ADNI initiative. The concordance between the two analyses (112 vs. 157 control subjects) was tested using Dice scores. In addition, we applied the optimized single-subject SPM procedure to the FDG-PET data acquired with 3 different scanners in 57 MCI subjects, in order to assess for tomograph influence in early disease phase. All the patients showed comparable AD-like hypometabolic patterns, also in the prodromal phase, in spite of being acquired with different PET scanners. SPM statistical comparisons performed with the two different healthy control databases showed a high degree of concordance (76% average pattern volume overlap and 90% voxel-wise agreement in AD-related brain structures). The validated optimized SPM-based single-subject procedure is influenced neither by the scanners used for image acquisition, nor by differences in healthy control groups, thus implying a great reliability of this method for longitudinal and multicentre studies. [ABSTRACT FROM AUTHOR]