[Physical activity in people with borderline personality disorder: a study protocol for a randomised controlled trial.].

Purpose: Treatments for mental disorders, such as pharmacotherapy and psychosocial interventions, do not always guarantee symptomatic remission. The effectiveness of Physical Activity (PA) in improving the psychophysical health of individuals with various mental disorders is well-established; however, its effects on borderline personality disorder (BPD) have yet to be adequately studied. Currently, there are not approved pharmacological treatments for BPD, and access to effective psychotherapeutic interventions remains limited.

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA.

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables.

FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI.

Introduction: Amnestic mild cognitive impairment (aMCI) is emerging as a heterogeneous condition.

Methods: We looked at a cohort of N = 207 aMCI subjects, with baseline fluorodeoxyglucose positron emission tomography (FDG-PET), T1 magnetic resonance imaging, cerebrospinal fluid (CSF), apolipoprotein E (APOE), and neuropsychological assessment. An algorithm based on FDG-PET hypometabolism classified each subject into subtypes, then compared biomarker measures and clinical progression.

MRI data quality assessment for the RIN - Neuroimaging Network using the ACR phantoms.

Purpose: Generating big-data is becoming imperative with the advent of machine learning. RIN-Neuroimaging Network addresses this need by developing harmonized protocols for multisite studies to identify quantitative MRI (qMRI) biomarkers for neurological diseases. In this context, image quality control (QC) is essential.

Italian, European, and international neuroinformatics efforts: An overview.

Neuroinformatics is a research field that focusses on software tools capable of identifying, analysing, modelling, organising and sharing multiscale neuroscience data. Neuroinformatics has exploded in the last two decades with the emergence of the Big Data phenomenon, characterised by the so-called 3Vs (volume, velocity and variety), which provided neuroscientists with an improved ability to acquire and process data faster and more cheaply thanks to technical improvements in clinical, genomic and radiological technologies. This situation has led to a 'data deluge', as neuroscientists can routinely collect more study data in a few days than they could in a year just a decade ago.

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network.

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing.

Norms for Automatic Estimation of Hippocampal Atrophy and a Step Forward for Applicability to the Italian Population.

Introduction: Hippocampal volume is one of the main biomarkers of Alzheimer's Dementia (AD). Over the years, advanced tools that performed automatic segmentation of Magnetic Resonance Imaging (MRI) T13D scans have been developed, such as FreeSurfer (FS) and ACM-Adaboost (AA). Hippocampal volume is considered abnormal when it is below the 5th percentile of the normative population.

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts.

With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.

Test-Retest Reliability of Pain Measures in Institutionalized Older Adults: Number of Painful Body Sites, Pain Intensity, and Pain Extent.

Objective: The reliability of pain assessment in frail and older adults has seldom been assessed. This study aims to assess the test-retest reliability of (1) the number of painful body sites, (2) pain intensity, and (3) pain extent in institutionalized older adults.

Methods: Seventy-four older adults who were institutionalized were assessed in 2 separate sessions, 2 days to 1 week apart, for pain intensity, number of painful body sites, and pain extent (in pixels) using a vertical pain numeric scale (0 to 10), a body chart divided into 50 body regions, and ImageJ, respectively.

Simulation of Image-Guided Intervention in Medical Imaging Education.

Introduction/background: Medical imaging education programs across Europe, despite their variability, include clinical practice as a guarantee of quality because learning in a clinical context is more effective and allows for constructive qualification of students. Learning in a clinical simulation context is a strategy to promote simulated clinical experience and assure patient safety. In this work, a learning experience, consisting of simulating a pacemaker implantation, implemented over 3 years with students pursuing the Medical Imaging and Radiotherapy degree at the University of Aveiro was evaluated.

A randomized controlled trial of respiratory physiotherapy in lower respiratory tract infections.

Introduction: Physiotherapy may play a role in the recovery of signs, symptoms and function of patients with lower respiratory tract infections (LRTI) but its effectiveness is still controversial.

Objectives: To assess the effects of respiratory physiotherapy compared with standard pharmacological care on symptoms and function in outpatients with LRTI.

Design: Single-blind, randomised controlled trial.

Improving access to community-based pulmonary rehabilitation: 3R protocol for real-world settings with cost-benefit analysis.

Background: Pulmonary rehabilitation (PR) has demonstrated patients' physiological and psychosocial improvements, symptoms reduction and health-economic benefits whilst enhances the ability of the whole family to adjust to illness. However, PR remains highly inaccessible due to lack of awareness of its benefits, poor referral and availability mostly in hospitals. Novel models of PR delivery are needed to enhance its implementation while maintaining cost-efficiency.

Artifact level produced by different femoral head prostheses in CT imaging: diamond coated silicon nitride as total hip replacement material.

Commercial femoral head prostheses (cobalt-chromium alloy, yttria partially stabilized zirconia (Y-PSZ) and alumina) and new silicon nitride ceramic ones (nanocrystalline diamond coated and uncoated) were compared in terms of artifact level production by computed tomography (CT). Pelvis examination by CT allows the correct diagnosis of some pathologies (e.g.