A5064664249- Eosinophilic Esophagitis
- Gastroesophageal reflux and treatments
- Radiomics and Machine Learning in Medical Imaging
- Cardiomyopathy and Myosin Studies
- Cardiac electrophysiology and arrhythmias
- Eosinophilic Disorders and Syndromes
- Cardiovascular Function and Risk Factors
- Advanced MRI Techniques and Applications
- Artificial Intelligence in Healthcare and Education
- Probabilistic and Robust Engineering Design
- Simulation-Based Education in Healthcare
- Esophageal and GI Pathology
- Prostate Cancer Diagnosis and Treatment
- MRI in cancer diagnosis
- Traumatic Brain Injury and Neurovascular Disturbances
- Microfluidic and Capillary Electrophoresis Applications
- IL-33, ST2, and ILC Pathways
- AI in cancer detection
- Microscopic Colitis
- Educational Games and Gamification
- Cardiac Valve Diseases and Treatments
- Machine Learning and Data Classification
- Optimal Experimental Design Methods
- Hemodynamic Monitoring and Therapy
- Neuroscience and Neural Engineering
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
2023-2025
National Research Council
2023-2025
Gran Sasso Science Institute
2020-2023
There is currently no recommendation regarding preferred drugs for active eosinophilic oesophagitis (EoE) because their relative efficacy unclear. We conducted an up-to-date network meta-analysis to compare proton pump inhibitors, off-label and EoE-specific topical steroids, biologics in EoE.We searched MEDLINE, Embase, Embase Classic the Cochrane Central Register of Controlled Trials from inception June 2023. included randomised controlled trials (RCTs) comparing all versus each other, or...
Abstract The recruitment of patients for rare or complex cardiovascular diseases is a bottleneck clinical trials and digital twins the human heart have recently been proposed as viable alternative. In this paper we present an unprecedented computer model which, relying on latest GPU-acceleration technologies, replicates full multi-physics dynamics within few hours per heartbeat. This opens way to extensive simulation campaigns study response synthetic cohorts disorders, novel prosthetic...
The Lyon Consensus designates Los Angeles (LA) grade C/D esophagitis or acid exposure time (AET) >6% on impedance-pH monitoring (MII-pH) as conclusive for gastroesophageal reflux disease (GERD). We aimed to evaluate proportions with objective GERD among symptomatic patients LA A, B, and C endoscopy.Demographics, clinical data, endoscopy findings, proton-pump inhibitor response were collected from prospectively enrolled 2 referral centers. Off-therapy MII-pH parameters included AET, number of...
The role of inhaled and swallowed aeroallergens in treatment outcomes adult patients with eosinophilic esophagitis (EoE) is unclear. We hypothesized that the pollen season contributes to failure 6-food elimination diet (SFED) EoE.We compared EoE who underwent SFED during vs outside season. Consecutive skin prick test (SPT) for birch grass were included. Individual sensitization count data analyzed define whether each patient had been assessed or after SFED. All active (≥15...
Eosinophilic esophagitis (EoE) requires maintenance therapy to avoid recurrence. We investigated the efficacy of a second course proton pump inhibitors (scPPIs) maintain steroid-induced histological remission (HR) in patients with EoE who had previously failed induction PPIs.We retrospectively included 18 achieved HR topical steroids but could not be maintained on long-term steroids. Treatment outcomes were assessed after 12 weeks scPPIs.Most (67%) high-dose PPI monotherapy at week 12.scPPIs...
Chicago classification version 4.0 (CCv4.0) introduced stringent diagnostic criteria for oesophagogastric junction outflow obstruction (EGJOO), in order to increase the clinical relevance of diagnosis, although this has not yet been demonstrated.To determine prevalence EGJOO using CCv4.0 patients with CCv3.0-based EGJOO, and assess if provocative manoeuvres can predict a conclusive diagnosis EGJOO.Clinical presentation, high resolution manometry (HRM) rapid drink challenge (RDC), timed...
Abstract Breast cancer holds the highest diagnosis rate among female tumors and is leading cause of death women. Quantitative analysis radiological images shows potential to address several medical challenges, including early detection classification breast tumors. In P.I.N.K study, 66 women were enrolled. Their paired Automated Volume Scanner (ABVS) Digital Tomosynthesis (DBT) images, annotated with cancerous lesions, populated first ABVS+DBT dataset. This enabled not only a radiomic for...
The social restrictions imposed by the COVID-19 pandemic have disrupted traditional teaching methods and encouraged development of innovative safer approaches based on distance learning. Among these novel techniques, digital game-based learning (DGBL) is a method that facilitates through efficient use interactive software tailored to user.
Serious games, and especially digital game based learning (DGBL) methodologies, have the potential to strengthen classic methodology in all medical procedures characterized by a flowchart (e.g., neonatal resuscitation algorithm). However, few studies compared short- long-term knowledge retention DGBL methodologies with control group undergoing specialist training led experienced operators. In particular, resident doctors' still has limited representation simulation-based education...
We present a multi--physics computational model of the human heart accounting for electrophysiology, elasto-mechanics, and hemodynamics, including their complex interactions. The is accurate computationally efficient and, thanks to implementation on GPU architectures, it allows cardiovascular simulations physiologic pathologic configurations within time--to--solution compatible with clinical practice. Results are shown healthy conditions myocardial infarction aim assessing reliability...
The limited availability of specialized image databases (particularly in hospitals, where tools vary between providers) makes it difficult to train deep learning models. This paper presents a few-shot methodology that uses pre-trained ResNet integrated with an encoder as backbone encode conditional shape information for the classification neonatal resuscitation equipment from less than 100 natural images. model is also strengthened by incorporating reliability score, which enriches...
Lymphocytic esophagitis (LyE) and eosinophilic (EoE) are immune-mediated esophageal diseases. Clinical characteristics, endoscopic findings, treatment outcomes of LyE were compared with EoE. This was an international retrospective study on adults enrolled at 3 centers in Europe. We recorded clinical characteristics endoscopy findings baseline symptoms, histology, after patients Demographics, presentation, comorbidities, largely different 35 59 Proton pump inhibitor response generally lower...
Abstract Objectives Radiomics-based analyses encompass multiple steps, leading to ambiguity regarding the optimal approaches for enhancing model performance. This study compares effect of several feature selection methods, machine learning (ML) classifiers, and sources radiomic features, on models’ performance diagnosis clinically significant prostate cancer (csPCa) from bi-parametric MRI. Methods Two multi-centric datasets, with 465 204 patients each, were used extract 1246 features per...
Modelling the cardiac electrophysiology entails dealing with uncertainties related to input parameters such as heart geometry and electrical conductivities of tissues, thus calling for an uncertainty quantification (UQ) results. Since chambers have different shapes in order make problem affordable, here we focus on left ventricle aim identifying which uncertain inputs mostly affect its electrophysiology. In a first phase, is evaluated using data available from literature output quantities...
Abstract The recruitment of patients for rare or complex cardiovascular diseases is a bottleneck clinical trials and digital twins the human heart have recently been proposed as viable alternative. In this paper we present an unprecedented computer model which, relying on latest GPU–acceleration technologies, replicates full cardiac dynamics within few hours. This opens way to extensive simulation campaigns study response synthetic cohorts disorders, novel prosthetic devices surgical...
Background: Ustekinumab (UST) has demonstrated effectiveness in treating patients with Crohn's disease. Monitoring treatment response can improve disease management and reduce healthcare costs. We investigated whether UST trough levels (TLs), serum IL22, Oncostatin M (OSM) could be early indicators of non-response by analysing their correlation clinical biochemical outcomes CD. Methods: Patients CD initiating from October 2018 to September 2020 were enrolled at six Italian centres for...