Publications by authors named "G P Gavelli"

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWI) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task.

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Background And Objective: We present a fully automatic system based on learning approaches, which aims to localization and identification (labeling) of vertebrae in 3D computed tomography (CT) scans of possibly incomplete spines in patients with bone metastases and vertebral compressions.

Methods: The framework combines a set of 3D algorithms for i) spine detection using a convolution neural network (CNN) ii) spinal cord tracking based on combination of a CNN and a novel growing sphere method with a population optimization, iii) intervertebral discs localization using a novel approach of spatially variant filtering of intensity profiles and iv) vertebra labeling using a CNN-based classification combined with global dynamic optimization.

Results: The proposed algorithm has been validated in testing databases, including also a publicly available dataset.

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Background: Concurrent chemotherapy and radiation using conventional fractionation is the standard treatment for inoperable, locally advanced non-small-cell lung cancer (NSCLC). We tested accelerated hypofractionated radiotherapy (AHR) and chemotherapy for the treatment of locally advanced NSCLC.

Methods: Eligible patients with locally advanced NSCLC were treated with induction chemotherapy (cisplatin and docetaxel), followed by AHR using tomotherapy and consolidation chemotherapy.

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Objectives: The aim of this study is to present the results of the Italian survey on the management of pulmonary nodules incidentally identified at computed tomography (CT).

Materials And Methods: An online electronic survey, consisting of 23 multiple-choice questions, was created using the SurveyMonkey web-based tool. The questionnaire was developed by the Board of the Italian College of Chest Radiology of the Italian Society of Medical and Interventional Radiology (SIRM) and by an experienced group of Italian Academic Chest Radiologists.

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Objectives: To characterize tumour baseline blood flow (BF) in two lung cancer subtypes, adenocarcinoma (AC) and squamous cell carcinoma (SCC), also investigating those "borderline" cases whose perfusion value is closer to the group mean of the other histotype.

Materials And Methods: 26 patients (age range 36-81 years) with primary Non-Small Cell Lung Cancer (NSCLC), subdivided into 19 AC and 7 SCC, were enrolled in this study and underwent a CT perfusion, at diagnosis. BF values were computed according to the maximum-slope method and unreliable values ( arising from artefacts or vessels) were automatically removed.

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