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Simple Summary: The prognostic performance of traditional methodologies in advanced nasopharyngeal carcinoma does not allow to successfully stratify patients. Previous studies showed that MRI-radiomics has been used to give additional information to improve the prognosis for this type of pathology in patients from endemic areas (Asia). The purpose of this study was to use MRI-radiomics to develop prognostic models for overall survival in patients from non-endemic areas (Europe or United States). In particular, T1-weighted and T2-weighted MRI were used for the purpose. Radiomic features from those images allowed to successfully train a prognostic signature that improved the prognostic performance of models based on clinical variables alone for different clinical endpoints (overall survival, disease-free survival and loco-regional recurrence-free survival). These results suggest how MRI-radiomics is a useful additional tool for prognosis in nasopharyngeal cancer. Advanced stage nasopharyngeal cancer (NPC) shows highly variable treatment outcomes, suggesting the need for independent prognostic factors. This study aims at developing a magnetic resonance imaging (MRI)-based radiomic signature as a prognostic marker for different clinical endpoints in NPC patients from non-endemic areas. A total 136 patients with advanced NPC and available MRI imaging (T1-weighted and T2-weighted) were selected. For each patient, 2144 radiomic features were extracted from the main tumor and largest lymph node. A multivariate Cox regression model was trained on a subset of features to obtain a radiomic signature for overall survival (OS), which was also applied for the prognosis of other clinical endpoints. Validation was performed using 10-fold cross-validation. The added prognostic value of the radiomic features to clinical features and volume was also evaluated. The radiomics-based signature had good prognostic power for OS and loco-regional recurrence-free survival (LRFS), with C-index of 0.68 and 0.72, respectively. In all the cases, the addition of radiomics to clinical features improved the prognostic performance. Radiomic features can provide independent prognostic information in NPC patients from non-endemic areas. [ABSTRACT FROM AUTHOR]

• To validate models published for late rectal bleeding after RT for prostate cancer. • The analysis was performed on a large international pooled population (1633 pts) • Clinical and dosimetric risk factors were confirmed on the validation set. • Best calibration plots are obtained for volume parameters pointing to medium–high dose. To validate published models for the risk estimate of grade ≥ 1 (G1+), grade ≥ 2 (G2+) and grade = 3 (G3) late rectal bleeding (LRB) after radical radiotherapy for prostate cancer in a large pooled population from three prospective trials. The external validation population included patients from Europe, and Oceanian centres enrolled between 2003 and 2014. Patients received 3DCRT or IMRT at doses between 66–80 Gy. IMRT was administered with conventional or hypofractionated schemes (2.35–2.65 Gy/fr). LRB was prospectively scored using patient-reported questionnaires (LENT/SOMA scale) with a 3-year follow-up. All Normal Tissue Complication Probability (NTCP) models published until 2021 based on the Equivalent Uniform Dose (EUD) from the rectal Dose Volume Histogram (DVH) were considered for validation. Model performance in validation was evaluated through calibration and discrimination. Sixteen NTCP models were tested on data from 1633 patients. G1+ LRB was scored in 465 patients (28.5%), G2+ in 255 patients (15.6%) and G3 in 112 patients (6.8%). The best performances for G2+ and G3 LRB highlighted the importance of the medium–high doses to the rectum (volume parameters n = 0.24 and n = 0.18, respectively). Good performance was seen for models of severe LRB. Moreover, a multivariate model with two clinical factors found the best calibration slope. Five published NTCP models developed on non-contemporary cohorts were able to predict a relative increase in the toxicity response in a more recent validation population. Compared to QUANTEC findings, dosimetric results pointed toward mid-high doses of rectal DVH. The external validation cohort confirmed abdominal surgery and cardiovascular diseases as risk factors. [ABSTRACT FROM AUTHOR]

Purpose: Within the Italian Association of Medical Physics and Health Physics (AIFM) working group "FutuRuS" we carried out a survey regarding the number of the peer-reviewed articles by AIFM members., Methods: We surveyed papers published in the years 2015-2019. Data extracted from Scopus included information regarding authors, title, journal, impact factor (IF), leading or standard authorship by AIFM members, keywords, type of collaboration (monocentric/multicentric/international), area of interest [radiation oncology (RO), radiology (RAD), nuclear medicine (NM), radioprotection (RP) and professional issue (PI)] and topics., Results: We found 1210 papers published in peer-reviewed journals: 48%, 22%, 16%, 6%, 2 and 6% in RO, RAD, NM, RP, PI and other topics, respectively. Forty-seven percent of the papers involved monocentric teams, 31% multicentric and 22% international collaborations. Leading authorship of AIFM members was in 56% of papers, with a corresponding IF equal to 52% of the total IF (3342, IF mean  = 2.8, IF max  = 35.4). The most represented journal was Physica Medica, with 15% of papers, while a relevant fraction of IF (54%) appeared in clinically oriented journals. The number of papers increased significantly between 2015 and 2016 and remained almost constant in 2017-2019., Conclusions: This survey led to the first quantitative assessment of the number and theme distribution of peer-reviewed scientific articles contributed by AIFM members. It constitutes a ground basis to support future AIFM strategies and promote working groups on scientific activity of medical physicists, and to build the basis for rational comparison with other countries, first of all within Europe., (Copyright © 2021 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)