Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.

Background: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer great opportunities to support cancer diagnosis. The inability to interpret the extracted features and model predictions is one of the major issues limiting the acceptance of AI models in clinical practice, and a clear representation of the relevance of the extracted features and model predictions is lacking. Focusing on the problem of prostate cancer (PCa) diagnosis and grading, this study aims to detect which are the most discriminant features for distinguishing malignant from non-malignant tissue and Gleason patterns, leaving the evaluation of models' classification performances as a secondary goal.

Psychometric properties of the Italian version of scale for outcomes in Parkinson's disease psychiatric complications in Parkinson disease.

The Scales for Outcomes in Parkinson's disease-Psychiatric Complications (SCOPA-PC) is a validated tool to score psychotic and compulsive symptoms in Parkinson's disease (PD). We translated into Italian the SCOPA-PC and evaluated its psychometric properties and clinical correlates in different subgroups of PD patients. The scale underwent translation, back-translation, and cognitive pretesting before being administered to a calculated sample of 135 PD patients.

[18F]flutemetamol uptake in the colon of a memory clinic population and its association with brain amyloidosis and the gut microbiota profile: an exploratory study.

Purpose: Some Alzheimer's disease (AD) patients report gastro-intestinal symptoms and present alterations in the gut microbiota (GM) composition. Elevated colonic amyloid immunoreactivity has been shown in patients and animal models. We evaluated the colonic uptake of the amyloid positron emission tomography (PET) imaging agent [18F]flutemetamol (FMM) in a memory clinic population and investigated its association with brain amyloidosis and GM composition.

Microstructural assessment of the locus coeruleus-entorhinal cortex pathway and association with ATN markers in cognitive impairment.

Introduction: Whether Alzheimer's disease pathology involves white matter pathways connecting the locus coeruleus (LC) to the entorhinal cortex (EC) is unclear. In this cross-sectional observational study, we investigated the microstructural integrity of the LC-EC pathway in relation to amyloid, tau, and neurodegeneration (ATN) biomarkers along the cognitive spectrum from normal cognition to dementia.

Methods: One hundred twenty-four participants underwent clinical assessment, diffusion-weighted imaging, structural magnetic resonance imaging (N), amyloid (A), and tau (T) positron emission tomography.

Fist-Palm Test May Identify Mild Cognitive Impairment and Freezing of Gait in Parkinson's Disease: A Machine Learning Approach.

Background: Mild cognitive impairment (MCI) and freezing of gait (FOG) are two common symptoms in Parkinson's disease (PD).

Objectives: The objectives were to test the strength of association of fist-palm test (FiPaT), a nonverbal motor test, with both MCI and FOG in PD and investigate the predictive ability of FiPaT in the identification of PD patients with MCI or FOG.

Methods: We enrolled 74 PD patients: 47 of 74 patients had MCI (PD + MCI), 27 of 74 were cognitively unimpaired (PD-NC), 29 of 74 presented FOG (PD + FOG), and 45 of 74 were without FOG (PD-FOG).

Reliability assessment of accelerated MR sequences for the estimation of structural and vascular markers in dementia.

Estimating the volume of brain structures and white matter lesions has been demonstrated to be crucial as diagnostic markers of dementia. In this context, employing accelerated MR sequences could be particularly suitable for deploying comfortable imaging protocols. The aims of the study are twofold.

Lack of pre-movement facilitation as neurophysiological hallmark of fatigue in patients with Parkinson's disease: A single pulse TMS study.

Background: Fatigue is a debilitating symptom in Parkinson's disease (PD), significantly affecting quality of life. Despite its prevalence, the underlying neurophysiological mechanisms remain poorly understood. Recent evidence suggests that deficits in cortical motor preparation processes may contribute to PD-related fatigue.

Text mining approach for feature extraction and cartilage disease grade classification using knee MRI radiology reports.

MRI radiology reporting processes can be improved by exploiting structured and semantically labelled data that can be fed to artificial intelligence (AI) tools. AI-based tools assisting radiology reporting can help to automatically individuate cartilage grading in textual magnetic resonance imaging (MRI) reports, thus supporting clinicians' decisions regarding medical imaging utilisation, diagnosis and treatment. In this study, we extracted information (clinical findings, observations, anatomical regions, etc.

Exploratory Analysis of Radiomics and Pathomics in Uterine Corpus Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (EC) is one of the most common malignancies in the female reproductive system, characterized by tumor heterogeneity at both radiological and pathological scales. Both radiomics and pathomics have the potential to assess this heterogeneity and support EC diagnosis. This study examines the correlation between radiomics features from Apparent Diffusion Coefficient (ADC) maps and post-contrast T1 (T1C) images with pathomic features from pathology images in 32 patients from the CPTAC-UCEC database.

Association of radiomic features with genomic signatures in thyroid cancer: a systematic review.

Background: There is a growing interest on the association of radiomic features with genomic signatures in oncology. Using computational methods, quantitative radiomic data are extracted from various imaging techniques and integrated with genomic information to construct predictive models aimed at advancing diagnostic strategies in cancer patient management. In this context, the aim of this systematic review was to assess the current knowledge on potential application of this association in patients with thyroid cancer (TC).

Neuroimaging in Nonsyndromic Craniosynostosis: Key Concepts to Unlock Innovation.

Craniosynostoses (CRS) are caused by the premature fusion of one or more cranial sutures, with isolated nonsyndromic CRS accounting for most of the clinical manifestations. Such premature suture fusion impacts both skull and brain morphology and involves regions far beyond the immediate area of fusion. The combined use of different neuroimaging tools allows for an accurate depiction of the most prominent clinical-radiological features in nonsyndromic CRS but can also contribute to a deeper investigation of more subtle alterations in the underlying nervous tissue organization that may impact normal brain development.

Biobank for craniosynostosis and faciocraniosynostosis, rare pediatric congenital craniofacial disorders: a study protocol.

Purpose: Craniosynostosis (CRS) is a rare congenital cranial malformation in which 1 or more cranial or facial sutures are fused in utero or rapidly fused in early infancy. The cranial sutures separate the skull bone plates and enable rapid growth of the skull in the first 2 years of life, in which growth is largely dictated by growth of the brain. CRS is a rare disease that occurs in 1 in 2100 to 1 in 2500 births and may be either nonsyndromic (also referred to as isolated) or syndromic.

The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data.

Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Public access to the training methodology for these solutions remains absent.

The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown.

Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine.

Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical data from diagnostic domains such as clinical imaging, pathology, and next-generation sequencing (NGS), which help characterize individual differences in patients. However, this information needs to be available and suitable to promote and support scientific research and technological development, supporting the effective adoption of the precision medicine approach in clinical practice. Digital biobanks can catalyze this process, facilitating the sharing of curated and standardized imaging data, clinical, pathological and molecular data, crucial to enable the development of a comprehensive and personalized data-driven diagnostic approach in disease management and fostering the development of computational predictive models.

Primary adrenal insufficiency induced by immune checkpoint inhibitors: biological, clinical, and radiological aspects.

Immune checkpoint inhibitors (ICI) have become a cornerstone in medical oncology, with evolving therapeutic strategies and applications. These monoclonal antibodies, designed to enhance immune responses, have revealed a spectrum of immune-related adverse events (irAEs). While many irAEs exhibit favorable responses to corticosteroid or immunosuppressive therapy, most ICI-related endocrinopathies necessitate lifelong replacement therapy and pose significant clinical challenges.

The impact of COVID-19 on cancer patients.

The COVID-19 pandemic poses a significant challenge for individuals with compromised immune systems, such as patients with cancer, as they face a heightened susceptibility to severe infections compared to the general population. Such severe infections substantially increase the risk of morbidity and mortality among these patients. Notable risk factors for mortality include advanced age (> 70 years), current or past smoking history, advanced disease stage, the use of cytotoxic chemotherapy, and an Eastern Cooperative Oncology Group (ECOG) score of 2 or higher.

A Biobanking System for Diagnostic Images: Architecture Development, COVID-19-Related Use Cases, and Performance Evaluation.

Background: Systems capable of automating and enhancing the management of research and clinical data represent a significant contribution of information and communication technologies to health care. A recent advancement is the development of imaging biobanks, which are now enabling the collection and storage of diagnostic images, clinical reports, and demographic data to allow researchers identify associations between lifestyle and genetic factors and imaging-derived phenotypes.

Objective: The aim of this study was to design and evaluate the system performance of a network for an operating biobank of diagnostic images, the Bio Check Up Srl (BCU) Imaging Biobank, based on the Extensible Neuroimaging Archive Toolkit open-source platform.

Malignant Pleural Mesothelioma: Staging and Radiological Response Criteria in Patients Treated with Immune Checkpoint Inhibitors.

Malignant pleural mesothelioma (MPM) is a rare and challenging cancer associated with asbestos fiber exposure, which offers limited treatment options. Historically, platinum-based chemotherapy has been the primary approach, but recent developments have introduced immunotherapy as a promising alternative for the treatment of this disease. Nevertheless, the unique growth patterns and occasionally ambiguous progressive characteristics of MPM make the interpretation of radiological assessments complex.

Topological changes of fast large-scale brain dynamics in mild cognitive impairment predict early memory impairment: a resting-state, source reconstructed, magnetoencephalography study.

Functional connectivity has been used as a framework to investigate widespread brain interactions underlying cognitive deficits in mild cognitive impairment (MCI). However, many functional connectivity metrics focus on the average of the periodic activities, disregarding the aperiodic bursts of activity (i.e.