Sharing brain imaging data in the Open Science era: how and why?

The sharing of human neuroimaging data has great potential to accelerate the development of imaging biomarkers in neurological and psychiatric disorders; however, major obstacles remain in terms of how and why to share data in the Open Science context. In this Health Policy by the European Cluster for Imaging Biomarkers, we outline the current main opportunities and challenges based on the results of an online survey disseminated among senior scientists in the field. Although the scientific community fully recognises the importance of data sharing, technical, legal, and motivational aspects often prevent active adoption. Therefore, we provide practical advice on how to overcome the technical barriers. We also call for a harmonised application of the General Data Protection Regulation across EU countries. Finally, we suggest the development of a system that makes data count by recognising the generation and sharing of data as a highly valuable contribution to the community.

The Homunculus of unspecific bone uptakes associated with PSMA-targeted tracers: a systematic review-based definition.

PURPOSE: Prostate-Specific Membrane Antigen (PSMA)-targeted Positron Emission Tomography (PET) has revolutionised prostate cancer (PCa) diagnosis and treatment, offering superior diagnostic accuracy over traditional methods and enabling theragnostic applications. However, a significant diagnostic challenge has emerged with identifying unspecific bone uptakes (UBUs), which could lead to over-staging and inappropriate treatment decisions if misinterpreted. This systematic review explores the phenomenon of UBUs in PCa patients undergoing PSMA-PET imaging. METHODS: Studies assessing the prevalence, topographical distribution, and potential clinical implications of UBUs were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. RESULTS: The percentage of PCa patients with UBUs on PSMA-PET scans ranged from 0 to 71.7%, depending on the radiopharmaceutical used, with [18F]PSMA-1007 showing the highest incidence. The ribs are the primary site of UBUs across all PSMA-targeted radiopharmaceuticals. The spine is the second most frequent UBU site for [68Ga]Ga-PSMA-11, [18F]DCFPyL, [18F]rhPSMA-7, while the pelvic girdle represents the second most frequent site for [18F]PSMA-1007. The average maximum Standardized Uptake Value (SUVmax) of UBUs varied from 3.4 to 7.7 and was generally lower than that of bone metastases. CONCLUSIONS: Our findings underscore the need for heightened awareness and precise interpretation of UBUs to avoid potential over-staging and subsequent inappropriate treatment decisions. Considering the radiopharmaceutical used, PET-derived semiquantitative parameters, the topographical distribution of UBUs, and accurately evaluating the pre-test probability based on clinical and laboratory parameters may aid nuclear medicine physicians in interpreting PSMA-PET findings.

Diverse Imaging Methods May Influence Long-Term Oncologic Outcomes in Oligorecurrent Prostate Cancer Patients Treated with Metastasis-Directed Therapy (the PRECISE-MDT Study).

Metastasis-directed therapy (MDT) has been tested in clinical trials as a treatment option for oligorecurrent prostate cancer (PCa). However, there is an ongoing debate regarding the impact of using different imaging techniques interchangeably for defining lesions and guiding MDT within clinical trials. Methods: We retrospectively identified oligorecurrent PCa patients who had 5 or fewer nodal, bone, or visceral metastases detected by choline or prostate-specific membrane antigen (PSMA) PET/CT and who underwent MDT stereotactic body radiotherapy with or without systemic therapy in 8 tertiary-level cancer centers. Imaging-guided MDT was assessed as progression-free survival (PFS), time to systemic treatment change due to polymetastatic conversion (PFS2), and overall survival predictor. Propensity score matching was performed to account for clinical differences between groups. Results: Of 402 patients, 232 (57.7%) and 170 (42.3%) underwent MDT guided by [18F]fluorocholine and PSMA PET/CT, respectively. After propensity score matching, patients treated with PSMA PET/CT-guided MDT demonstrated longer PFS (hazard ratio [HR], 0.49 [95% CI, 0.36-0.67]; P < 0.0001), PFS2 (HR, 0.42 [95% CI, 0.28-0.63]; P < 0.0001), and overall survival (HR, 0.39 [95% CI, 0.15-0.99]; P < 0.05) than those treated with choline PET/CT-guided MDT. Additionally, we matched patients who underwent [68Ga]Ga-PSMA-11 versus [18F]F-PSMA-1007 PET/CT, observing longer PFS and PFS2 in the former subgroup (PFS: HR, 0.51 [95% CI, 0.26-1.00]; P < 0.05; PFS2: HR, 0.24 [95% CI, 0.09-0.60]; P < 0.05). Conclusion: Diverse imaging methods may influence outcomes in oligorecurrent PCa patients undergoing MDT. However, prospective, head-to-head studies, ideally incorporating a randomized design, are necessary to provide definitive evidence and facilitate the practical application of these findings.

Automatic quantification of REM sleep without atonia reliably identifies patients with REM sleep behavior disorder: a possible screening tool?

BACKGROUND: REM Sleep Behavior Disorder (RBD) is characterized by absence of physiological muscle atonia during REM sleep (REM sleep without atonia, RWA). Nigro-striatal dopaminergic impairment is a feature of Parkinson disease (PD) and can be identified in prodromal stages as well, such as idiopathic RBD (iRBD). Aims of this study are to explore the efficacy of an automatic RWA quantification in identifying RBD patients and the correlation between RWA and nigro-striatal dopaminergic function. METHODS: Forty-five iRBD, 46 PD with RBD, 24 PD without RBD patients and 11 healthy controls were enrolled in the Genoa Center (group A) and 25 patients with iRBD (group B) were enrolled in the Danish Center. Group A underwent brain [123I]FP-CIT-SPECT and group B underwent brain [18F]PE2I-PET as measures of nigro-striatal dopaminergic function. Chin muscle activity was recorded in all subjects and analyzed by applying a published automatic algorithm. Correlations between RWA and nigro-striatal dopaminergic function were explored. RESULTS: The automatic quantification of RWA significantly differentiated RBD from non-RBD subjects (AUC = 0.86), although with lower accuracy compared with conventional visual scoring (AUC = 0.99). No significant correlation was found between RWA and nigro-striatal dopaminergic function. CONCLUSION: The automatic quantification of RWA is a reliable tool to identify subjects with RBD and may be used as a first-line screening tool, but without correlations with nigro-striatal dopaminergic functioning.

Subspace corrected relevance learning with application in neuroimaging.

In machine learning, data often comes from different sources, but combining them can introduce extraneous variation that affects both generalization and interpretability. For example, we investigate the classification of neurodegenerative diseases using FDG-PET data collected from multiple neuroimaging centers. However, data collected at different centers introduces unwanted variation due to differences in scanners, scanning protocols, and processing methods. To address this issue, we propose a two-step approach to limit the influence of center-dependent variation on the classification of healthy controls and early vs. late-stage Parkinson's disease patients. First, we train a Generalized Matrix Learning Vector Quantization (GMLVQ) model on healthy control data to identify a "relevance space" that distinguishes between centers. Second, we use this space to construct a correction matrix that restricts a second GMLVQ system's training on the diagnostic problem. We evaluate the effectiveness of this approach on the real-world multi-center datasets and simulated artificial dataset. Our results demonstrate that the approach produces machine learning systems with reduced bias - being more specific due to eliminating information related to center differences during the training process - and more informative relevance profiles that can be interpreted by medical experts. This method can be adapted to similar problems outside the neuroimaging domain, as long as an appropriate "relevance space" can be identified to construct the correction matrix.

Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.

OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192.

Amyloid PET Imaging: Standard Procedures and Semiquantification.

Amyloid plaques are a neuropathologic hallmark of Alzheimer's disease (AD), which can be imaged through positron emission tomography (PET) technology using radiopharmaceuticals that selectively bind to the fibrillar aggregates of amyloid-ß plaques (Amy-PET). Several radiotracers for amyloid PET have been validated (11C-Pittsburgh compound B and the 18F-labeled compounds such as 18F-florbetaben, 18F-florbetapir, and 18F-flutemetamol). Images can be interpreted by means of visual/qualitative, semiquantitative, and quantitative criteria. Here, we summarize the main differences between the available radiotracers for Amy-PET, the proposed interpretation criteria, and main proposed quantification methods.

Autoimmune encephalitis: what the radiologist needs to know.

Autoimmune encephalitis is a relatively novel nosological entity characterized by an immune-mediated damage of the central nervous system. While originally described as a paraneoplastic inflammatory phenomenon affecting limbic structures, numerous instances of non-paraneoplastic pathogenesis, as well as extra-limbic involvement, have been characterized. Given the wide spectrum of insidious clinical presentations ranging from cognitive impairment to psychiatric symptoms or seizures, it is crucial to raise awareness about this disease category. In fact, an early diagnosis can be dramatically beneficial for the prognosis both to achieve an early therapeutic intervention and to detect a potential underlying malignancy. In this scenario, the radiologist can be the first to pose the hypothesis of autoimmune encephalitis and refer the patient to a comprehensive diagnostic work-up - including clinical, serological, and neurophysiological assessments.In this article, we illustrate the main radiological characteristics of autoimmune encephalitis and its subtypes, including the typical limbic presentation, the features of extra-limbic involvement, and also peculiar imaging findings. In addition, we review the most relevant alternative diagnoses that should be considered, ranging from other encephalitides to neoplasms, vascular conditions, and post-seizure alterations. Finally, we discuss the most appropriate imaging diagnostic work-up, also proposing a suggested MRI protocol.

Neurological Disorders and Women's Health: Contribution of Molecular Neuroimaging Techniques.

Sex differences in brain physiology and the mechanisms of drug action have been extensively reported. These biological variances, from structure to hormonal and genetic aspects, can profoundly influence healthy functioning and disease mechanisms and might have implications for treatment and drug development. Molecular neuroimaging techniques may help to disclose sex's impact on brain functioning, as well as the neuropathological changes underpinning several diseases. This narrative review summarizes recent lines of evidence based on PET and SPECT imaging, highlighting sex differences in normal conditions and various neurological disorders.

European intersocietal recommendations for the biomarker-based diagnosis of neurocognitive disorders.

The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.

Diagnostic performance of molecular imaging methods in predicting the progression from mild cognitive impairment to dementia: an updated systematic review.

PURPOSE: Epidemiological and logistical reasons are slowing the clinical validation of the molecular imaging biomarkers in the initial stages of neurocognitive disorders. We provide an updated systematic review of the recent advances (2017-2022), highlighting methodological shortcomings. METHODS: Studies reporting the diagnostic accuracy values of the molecular imaging techniques (i.e., amyloid-, tau-, [18F]FDG-PETs, DaT-SPECT, and cardiac [123I]-MIBG scintigraphy) in predicting progression from mild cognitive impairment (MCI) to dementia were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Main eligibility criteria were as follows: (1) ≥ 50 subjects with MCI, (2) follow-up ≥ 3 years, (3) gold standard: progression to dementia or diagnosis on pathology, and (4) measures of prospective accuracy. RESULTS: Sensitivity (SE) and specificity (SP) in predicting progression to dementia, mainly to Alzheimer's dementia were 43-100% and 63-94% for [18F]FDG-PET and 64-94% and 48-93% for amyloid-PET. Longitudinal studies were lacking for less common disorders (Dementia with Lewy bodies-DLB and Frontotemporal lobe degeneration-FTLD) and for tau-PET, DaT-SPECT, and [123I]-MIBG scintigraphy. Therefore, the accuracy values from cross-sectional studies in a smaller sample of subjects (n > 20, also including mild dementia stage) were chosen as surrogate outcomes. DaT-SPECT showed 47-100% SE and 71-100% SP in differentiating Lewy body disease (LBD) from non-LBD conditions; tau-PET: 88% SE and 100% SP in differentiating DLB from Posterior Cortical Atrophy. [123I]-MIBG scintigraphy differentiated LBD from non-LBD conditions with 47-100% SE and 71-100% SP. CONCLUSION: Molecular imaging has a moderate-to-good accuracy in predicting the progression of MCI to Alzheimer's dementia. Longitudinal studies are sparse in non-AD conditions, requiring additional efforts in these settings.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy.

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

Incident anti-LGI1 autoimmune encephalitis during dementia with Lewy bodies: when Occam razor is a double-edged sword.

In Dementia with Lewy bodies (DLB), rapid cognitive decline and seizures seldom complicate the typical clinical course. Nevertheless, concurrent, treatable conditions may be responsible. We report a case of DLB with superimposed anti-LGI1 encephalitis, emphasizing the importance of thorough diagnostic reasoning beyond the simplest explanation amid distinct clinical cues.