Publications by authors named "P Mangili"
Purpose: The aim is to train and validate a multivariable Normal Tissue Complication Probability (NTCP) model predicting acute skin reactions in patients with breast cancer receiving adjuvant Radiotherapy (RT).
Methods And Materials: We retrospectively reviewed 1570 single-institute patients with breast cancer treated with whole breast irradiation (40 Gy/15fr). The patients were divided into training (n = 878, treated with 3d-CRT, from 2009 to 2017) and validation cohorts (n = 692, treated from 2017 to 2021, including advanced RT techniques).
Purpose: Different ML models were compared to predict toxicity in RT on a large cohort (n = 1314).
Methods: The endpoint was RTOG G2/G3 acute toxicity, resulting in 204/1314 patients with the event. The dataset, including 25 clinical, anatomical, and dosimetric features, was split into 984 for training and 330 for internal tests.
Article Synopsis
- - The study addresses how toxicity from radiotherapy impacts quality of life in breast cancer patients and aims to create a model to predict late side effects based on dosimetric and clinical factors.
- - Researchers analyzed data from over 1,000 patients treated with 40 Gy of radiation, finding a 3.8% rate of moderate to severe late side effects using a machine learning model that considered various clinical and dosimetric parameters.
- - Key findings include that post-surgery cosmetic changes and the use of Aromatase Inhibitors significantly affect the risk of late reactions, highlighting the importance of certain dosimetric thresholds in managing patient outcomes.
Background And Purpose: Artificial Intelligence (AI)-based auto-contouring for treatment planning in radiotherapy needs extensive clinical validation, including the impact of editing after automatic segmentation. The aims of this study were to assess the performance of a commercial system for Clinical Target Volumes (CTVs) (prostate/seminal vesicles) and selected Organs at Risk (OARs) (rectum/bladder/femoral heads + femurs), evaluating also inter-observer variability (manual vs automatic + editing) and the reduction of contouring time.
Materials And Methods: Two expert observers contoured CTVs/OARs of 20 patients in our Treatment Planning System (TPS).
Aims: To report long-term outcomes of relapsed prostate cancer (PC) patients treated in a prospective single-arm study with extended-nodal radiotherapy (ENRT) and [11C]-choline positron emission tomography (PET)/computed tomography (CT)-guided simultaneous integrated boost (SIB) to positive lymph nodes (LNs).
Methods: From 12/2009 to 04/2015, 60 PC patients with biochemical relapse and positive LNs only were treated in this study. ENRT at a median total dose (TD) = 51.