A5027224304- Dementia and Cognitive Impairment Research
- Alzheimer's disease research and treatments
- Functional Brain Connectivity Studies
- Medical Imaging Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Rheumatoid Arthritis Research and Therapies
- Medical Image Segmentation Techniques
- Long-Term Effects of COVID-19
- Systemic Lupus Erythematosus Research
- Radiomics and Machine Learning in Medical Imaging
- Glioma Diagnosis and Treatment
- COVID-19 and healthcare impacts
- Spondyloarthritis Studies and Treatments
- Brain Tumor Detection and Classification
- Pneumothorax, Barotrauma, Emphysema
- Amyloidosis: Diagnosis, Treatment, Outcomes
- Scoliosis diagnosis and treatment
- Lung Cancer Research Studies
- Infectious Encephalopathies and Encephalitis
- Anesthesia and Sedative Agents
- Inflammatory Biomarkers in Disease Prognosis
- Bone and Joint Diseases
- Intensive Care Unit Cognitive Disorders
- Electrolyte and hormonal disorders
- COVID-19 Clinical Research Studies
Istituto Nazionale di Fisica Nucleare
2023
Istituto Nazionale di Fisica Nucleare, Sezione di Genova
2012-2021
Agostino Gemelli University Polyclinic
2017
University of Genoa
2015-2016
Istituto Nazionale di Fisica Nucleare, Sezione di Trieste
2016
Sapienza University of Rome
1996-2001
Policlinico Umberto I
1997
Abstract Introduction Hippocampal volume is a core biomarker of Alzheimer's disease (AD). However, its contribution over the standard diagnostic workup unclear. Methods Three hundred fifty‐six patients, under clinical evaluation for cognitive impairment, with suspected AD and Mini–Mental State Examination ≥20, were recruited across 17 European memory clinics. After traditional workup, confidence pathology (DCAD) was estimated by physicians in charge. The latter provided results automated...
In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of hippocampus in structural magnetic resonance imaging. multi-atlas approaches atlas selection is crucial importance accuracy segmentation. Here an optimized method based on definition small peri-hippocampal region to target learning with linear and non-linear embedded manifolds. All atlases were co-registered data driven template resulting computationally...
The assessment of in vivo18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based standardized uptake value ratio (SUVr) measurements. We target the difficulties image reading and possible shortcomings SUVr methods validating a new semi-quantitative approach named ELBA. ELBA involves minimal preprocessing does not rely small, specific regions interest (ROIs). It evaluates whole brain delivers geometrical/intensity score to be used...
The hippocampus has a key role in number of neurodegenerative diseases, such as Alzheimer's Disease. Here we present novel method for the automated segmentation from structural magnetic resonance images (MRI), based on combination multiple classifiers. is validated cohort 50 T1 MRI scans, comprehending healthy control, mild cognitive impairment, and Disease subjects. preliminary release EADC-ADNI Harmonized Protocol training labels used gold standard. fully pipeline consists registration...
This epidemiological study aimed to determine the prevalence and characteristics of second tumors (STs) in patients with bronchopulmonary carcinoids (BCs).Data on neuroendocrine carcinomas (NECs) from AIRTUM registry (1975-2011) were used for analysis. Among 32,325 NECs, we focused our analysis 3,205 (9.9%) affected by BCs. The overall ST number incidence calculated. STs was compared expected cancer healthy Italian population, standardized ratio (SIR) 95% confidence intervals calculated.The...
Background: This study aims to evaluate the use of a computer-aided, semi-quantification approach [18F]F-DOPA positron emission tomography (PET) in pediatric-type diffuse gliomas (PDGs) calculate tumor-to-background ratio. Methods: A total 18 pediatric patients with PDGs underwent magnetic resonance imaging and PET, which were analyzed using both manual automated procedures. The former provided tumor-to-normal-tissue ratio (TN) tumor-to-striatal-tissue (TS), while latter analogous scores...
Background: In clinical practice, the amy-PET is globally inspected to provide a binary outcome, but role of regional assessment has not been fully investigated yet. Objective: To deepen amyloid burden and its implication on clinical-neuropsychological features. Materials: Amy-PET complete neuropsychological (Trail Making Test, Rey Auditory Verbal Learning semantic verbal fluency, Symbol Digit, Stroop, visuoconstruction) were available in 109 patients with suspicion Alzheimer’s disease. By...
A challenging point in neuroimaging is the diagnosis of Alzheimer's disease (AD) during its asymptomatic phase. Among all biomarkers proposed literature, a measure hippocampal atrophy via Magnetic Resonance Imaging (MRI) seems to be one most reliable. Refined image processing techniques were already automatically extract boxes from images acquired with standard full brain acquisition protocol suggested by Disease Neuroimaging Initiative (ADNI). In order enhance this approach, here we propose...
<h3>Background</h3> Treatment adherence is particularly important in a serious, chronic disease like Rheumatoid Arthritis (RA). However several factors, such as the route of administration drug(s) and/or clinical and logistical conditions patient, can have negative impact on adherence. Abatacept (ABA) biologic drug indicated for treatment RA combination with methotrexate that commonly administered at hospital intravenously (iv), being availability its subcutaneous formulation only recent....
Medical image computing raises new challenges due to the scale and complexity of required analyses. databases are currently available supply clinical diagnosis. For instance, it is possible provide diagnostic information based on an imaging biomarker comparing a single case reference group (controls or patients with disease). At same time many sophisticated computationally intensive algorithms have been implemented extract useful from medical images. Many applications would take great...