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Positron emission tomography/magnetic resonance imaging (PET/MRI) is an innovative imaging technology that allows the simultaneous acquisition of metabolic, structural, and functional information for an accurate characterization of tissues. The qualitative interpretation of PET/MR images has shown great potential in tumor diagnosis, treatment planning, and follow-up. Furthermore, PET/MRI also potentially provides several quantitative imaging biomarkers, also called “radiomic features,” for tumor characterization extracted both from PET and MRI. In the new era of precision medicine, radiomics is an emerging translational field of research aiming to extract a large number of quantitative features followed by their interpretation through various analyses and integration into predictive models. In this chapter, different clinical applications of radiomics based on PET, MRI, and PET/MR images will be presented, with a specific focus on the characterization of brain tumors, breast cancer, pancreatic neuroendocrine tumors, and prostate cancer. Finally, some other applications of artificial intelligence applied to PET/MR images that can shortly enter into clinical practice will be shown.

Item does not contain fulltext, Background: CSF and imaging biomarkers are needed for the etiological diagnosis of neurocognitive disorders, but evidence is incomplete on their rational use in the clinic. Since October 2020, a European task force has been defining an evidence-based diagnostic workflow, where incomplete evidence is filled by the opinion of experts. Herein, we report the preliminary results through January 2022. Method: A Delphi method was used to reach consensus. Eleven pertinent European scientific societies delegated two panelists each to join Delphi rounds and voting. Consensus was set at 70% of consistent responses. Result: In the 5 voting rounds completed so far, panelists defined clinical setting (specialist outpatient service) and stage of application (prodromal and mild dementia) of the workflow, patients’ age window of biomarkers use (strongly encouraged below 70 years and of limited usefulness over 85). Workflow is configurated to be patient-centered and structured on three levels of assessment (W): W1, definition of clinical profiles based on the combined results of MRI, neuropsychology, blood tests; W2, choice of first-line biomarkers according to the main clinical suspicion (i.e., FDG-PET for frontotemporal lobar degeneration and motor tauopathies, dopamine SPECT/PET for Lewy body spectrum disorders, and CSF biomarkers either for Alzheimer’s disease or in cases with inconclusive neuropsychological and/or MRI findings, whereas no biomarker was indicated in suspected vascular cognitive impairment); W3, selection of a second-line biomarker when results of first-line biomarkers are inconsistent with diagnostic hypothesis (i.e., not typical FDG-PET pattern) or uninformative (i.e., borderline CSF amyloid results) or not sufficient to rule out other etiologies (i.e., amyloid-positive and tau-negative CSF results) or when a diagnosis remains possible despite a negative first-line biomarker (e.g., normal dopamine SPECT/PET in suspected prodromal dementia with Lewy bodies). Conc

The logopenic variant of primary progressive aphasia (lvPPA) is the most recent variant of primary progressive aphasia (PPA) to be identified; thus far, it has been poorly investigated. Despite being typically associated with Alzheimer disease (AD), lvPPA has recently been linked to frontotemporal lobe degeneration (FTLD), with distinctive cognitive and neural features that are worthy of further investigation. Here, we describe the neuropsychological and linguistic profile, as well as cerebral abnormalities, of an individual exhibiting PPA and carrying a pathogenetic variant in the GRN gene, from a 3-year longitudinal perspective. The individual's initial profile resembled lvPPA because it was characterized by word-finding difficulties and phonological errors in spontaneous speech in addition to sentence repetition and phonological short-term memory impairments. The individual's structural and metabolic imaging data demonstrated left temporal and bilateral frontal atrophy and hypometabolism, respectively. On follow-up, as the pathology progressed, dysprosody, stereotypical speech patterns, agrammatism, and orofacial apraxia appeared, suggesting an overlap with the nonfluent variant of PPA (nfvPPA). Severe sentence comprehension impairment also became evident. Our longitudinal and multidisciplinary diagnostic approach allowed us to better characterize the progression of a GRN-positive lvPPA profile, providing neuropsychological and imaging indicators that might be helpful to improve classification between different PPA variants and to address a nosological issue. Finally, we discuss the importance of early diagnosis of PPA given the possible overlap between different PPA variants during the progression of the pathology.

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 an

Background: amyloid-PET reading has been classically implemented as a binary assessment, although the clinical experience has shown that the number of borderline cases is non negligible not only in epidemiological studies of asymptomatic subjects but also in naturalistic groups of symptomatic patients attending memory clinics. In this work we develop a model to compare and integrate visual reading with two independent semi-quantification methods in order to obtain a tracer-independent multi-parametric evaluation. Methods: We retrospectively enrolled three cohorts of cognitively impaired patients submitted to 18 F-florbetaben (53 subjects), 18 F-flutemetamol (62 subjects), 18 F-florbetapir (60 subjects)PET/CT respectively, in 6 European centres belonging to the EADC. The 175 scans were visually classified as positive/negative following approved criteria and further classified with a 5-step grading as negative, mild negative, borderline, mild positive, positive by 5 independent readers, blind to clinical data. Scan quality was also visually assessed and recorded. Semi-quantification was based on two quantifiers: the standardized uptake value (SUVr)and the ELBA method. We used a sigmoid model to relate the grading with the quantifiers. We measured the readers accord and inconsistencies in the visual assessment as well as the relationship between discrepancies on the grading and semi-quantifications. Conclusion: It is possible to construct a map between different tracers and different quantification methods without resorting to ad-hoc acquired cases. We used a 5-level visual scale which, together with a mathematical model, delivered cut-offs and transition regions on tracers that are (largely)independent from the population. All fluorinated tracers appeared to have the same contrast and discrimination ability with respect to the negative-to-positive grading. We validated the integration of both visual reading and different quantifiers in a more robust framework thus bri

Contains fulltext : 228656.pdf (publisher's version ) (Open Access), Neurofeedback (NFB) is a brain-based training method that enables users to control their own cortical oscillations using real-time feedback from the electroencephalogram (EEG). Importantly, no investigations to date have directly explored the potential impact of NFB on the brain's key neuromodulatory systems. Our study's objective was to assess the capacity of NFB to induce dopamine release as revealed by positron emission tomography (PET). Thirty-two healthy volunteers were randomized to either EEG-neurofeedback (NFB) or EEG-electromyography (EMG), and scanned while performing self-regulation during a single session of dynamic PET brain imaging using the high affinity D2/3 receptor radiotracer, [18F]Fallypride. NFB and EMG groups down-regulated cortical alpha power and facial muscle tone, respectively. Task-induced effects on endogenous dopamine release were estimated in the frontal cortex, anterior cingulate cortex, and thalamus, using the linearized simplified reference region model (LSRRM), which accounts for time-dependent changes in radiotracer binding following task initiation. Contrary to our hypothesis of a differential effect for NFB vs. EMG training, significant dopamine release was observed in both training groups in the frontal and anterior cingulate cortex, but not in thalamus. Interestingly, a significant negative correlation was observed between dopamine release in frontal cortex and pre-to-post NFB change in spontaneous alpha power, suggesting that intra-individual changes in brain state (i.e., alpha power) could partly result from changes in neuromodulatory tone. Overall, our findings constitute the first direct investigation of neurofeedback's effect on the endogenous release of a key neuromodulator, demonstrating its feasibility and paving the way for future studies using this methodology.

Purpose In 2017, the Geneva Alzheimer's disease (AD) Biomarker Roadmap initiative adapted the framework of the systematic validation of oncological diagnostic biomarkers to AD biomarkers, with the aim to accelerate their development and implementation in clinical practice. With this work, we assess the maturity of [F-18]flortaucipir PET and define its research priorities. Methods The level of maturity of [F-18]flortaucipir was assessed based on the AD Biomarker Roadmap. The framework assesses analytical validity (phases 1-2), clinical validity (phases 3-4), and clinical utility (phase 5). Results The main aims of phases 1 (rationale for use) and 2 (discriminative ability) have been achieved. [F-18]Flortaucipir binds with high affinity to paired helical filaments of tau and has favorable kinetic properties and excellent discriminative accuracy for AD. The majority of secondary aims of phase 2 were fully achieved. Multiple studies showed high correlations between ante-mortem [F-18]flortaucipir PET and post-mortem tau (as assessed by histopathology), and also the effects of covariates on tracer binding are well studied. The aims of phase 3 (early detection ability) were only partially or preliminarily achieved, and the aims of phases 4 and 5 were not achieved. Conclusion Current literature provides partial evidence for clinical utility of [F-18]flortaucipir PET. The aims for phases 1 and 2 were mostly achieved. Phase 3 studies are currently ongoing. Future studies including representative MCI populations and a focus on healthcare outcomes are required to establish full maturity of phases 4 and 5.

Contains fulltext : 229556.pdf (Publisher’s version ) (Closed access), Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and (18)F-fluorodeoxyglucose ((18)F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and (18)F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies.

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.

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM) Maps generated via a new optimized SPM procedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimer's Disease-AD, Frontotemporal Lobar Degeneration-FTLD, Dementia with Lewy bodies-DLB and Mild Cognitive Impairment-MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPM Maps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPM Maps showed the highest predictive prognostic value (mean LOC = 2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions