Training and temporally validating an NTCP model of acute toxicity after whole breast radiotherapy, including the impact of advanced delivery techniques.

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).

Preclinical photon minibeam radiotherapy using a custom collimator: Dosimetry characterization and preliminary in-vivo results on a glioma model.

Purpose: The purpose of this study is to investigate the dosimetric characteristics of a collimator for minibeam radiotherapy (MBRT) with film dosimetry and Monte Carlo (MC) simulations. The outcome of MBRT with respect to conventional RT using a glioma preclinical model was also evaluated.

Methods: A multi-slit collimator was designed to be used with commercial small animal irradiator.

Hypofractionated radiotherapy concomitant to capecitabine after induction chemotherapy for advanced pancreatic adenocarcinoma.

Background And Purpose: To assess feasibility, toxicity and outcome of moderately hypofractionated radiotherapy concomitant to capecitabine after induction chemotherapy for advanced pancreatic cancer.

Materials And Methods: Patients with advanced pancreatic cancer without distant progression after induction chemotherapy (CHT) were considered. Radiochemotherapy (RCT) consisted of 44.

Preoperative MRI radiomic analysis for predicting local tumor progression in colorectal liver metastases before microwave ablation.

Purpose: Radiomics may aid in predicting prognosis in patients with colorectal liver metastases (CLM). Consistent data is available on CT, yet limited data is available on MRI. This study assesses the capability of MRI-derived radiomic features (RFs) to predict local tumor progression-free survival (LTPFS) in patients with CLMs treated with microwave ablation (MWA).

Radiomics-enhanced early regression index for predicting treatment response in rectal cancer: a multi-institutional 0.35 T MRI-guided radiotherapy study.

Purpose: The accurate prediction of treatment response in locally advanced rectal cancer (LARC) patients undergoing MRI-guided radiotherapy (MRIgRT) is essential for optimising treatment strategies. This multi-institutional study aimed to investigate the potential of radiomics in enhancing the predictive power of a known radiobiological parameter (Early Regression Index, ERI) to evaluate treatment response in LARC patients treated with MRIgRT.

Methods: Patients from three international sites were included and divided into training and validation sets.

Pelvic bone marrow dose-volume predictors of late lymphopenia following pelvic lymph node radiation therapy for prostate cancer.

Background And Purpose: Given the substantial lack of knowledge, we aimed to assess clinical/dosimetry predictors of late hematological toxicity on patients undergoing pelvic-nodes irradiation (PNI) for prostate cancer (PCa) within a prospective multi-institute study.

Materials And Methods: Clinical/dosimetry/blood test data were prospectively collected including lymphocytes count (ALC) at baseline, mid/end-PNI, 3/6 months and every 6 months up to 5-year after PNI. DVHs of the Body, ileum (BMILEUM), lumbosacral spine (BMLS), lower pelvis (BMPELVIS), and whole pelvis (BMTOT) were extracted.

Comparing Performances of Predictive Models of Toxicity after Radiotherapy for Breast Cancer Using Different Machine Learning Approaches.

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.

Quality of Life Longitudinal Evaluation in Prostate Cancer Patients from Radiotherapy Start to 5 Years after IMRT-IGRT.

Purpose: The purpose of this study is to study the evolution of quality of life (QoL) in the first 5 years following Intensity-modulated radiation therapy (IMRT) for prostate cancer (PCa) and to determine possible associations with clinical/treatment data.

Material And Methods: Patients were enrolled in a prospective multicentre observational trial in 2010-2014 and treated with conventional (74-80 Gy, 1.8-2 Gy/fr) or moderately hypofractionated IMRT (65-75.

Worsening of 2-year patient-reported intestinal functionality after radiotherapy for prostate cancer including pelvic node irradiation.

Background And Purpose: To quantify patient-reported 2-year intestinal toxicity (IT) from pelvic nodal irradiation (PNI) for prostate cancer. The association between baseline/acute symptoms and 2-year worsening was investigated.

Materials And Methods: Patient-reported IT was prospectively assessed through the Inflammatory Bowel Disease Questionnaire (IBDQ), filled in at baseline, radiotherapy mid-point and end, at 3 and 6 months and every 6 months until 5 years.

Impact of low skeletal muscle mass in oropharyngeal cancer patients treated with radical chemo-radiotherapy: A mono-institutional experience.

Aims: Low skeletal muscle mass index (SMI) has recently emerged as an independent prognostic factor in oncological patients and it is linked with poor survival and higher treatment toxicity. The present study aims to determine the possible impact of low SMI on survival and acute toxicity in oropharyngeal patients.

Methods: Seventy-six patients with locally advanced oropharyngeal squamous cell carcinoma (stage III-IVC) were treated in our institution with Helical TomoTherapy® (HT - Accuray, Maddison, WI, USA) between 2005 and 2021.

Real-world validation of Artificial Intelligence-based Computed Tomography auto-contouring for prostate cancer radiotherapy planning.

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).

Patient-reported persistent symptoms after radiotherapy and association with quality of life for prostate cancer survivors.

Purpose: To evaluate the persistence of symptoms after radiotherapy (RT) for localised prostate cancer (PCa) and the association with quality of life (QOL).

Materials And Methods: Prospective patient-reported outcome (PRO) from a multi-institutional study on PCa treated with radical RT (2010-2014) was analysed. Data was collected at baseline (BL) and follow-ups (FUPs) up to 5 years.

Selective sparing of bladder and rectum sub-regions in radiotherapy of prostate cancer combining knowledge-based automatic planning and multicriteria optimization.

Background And Purpose: The association between dose to selected bladder and rectum symptom-related sub-regions (SRS) and late toxicity after prostate cancer radiotherapy has been evidenced by voxel-wise analyses. The aim of the current study was to explore the feasibility of combining knowledge-based (KB) and multi-criteria optimization (MCO) to spare SRSs without compromising planning target volume (PTV) dose delivery, including pelvic-node irradiation.

Materials And Methods: Forty-five previously treated patients (74.

Limited impact of discretization/interpolation parameters on the predictive power of CT radiomic features in a surgical cohort of pancreatic cancer patients.

Purpose: To explore the variation of the discriminative power of CT (Computed Tomography) radiomic features (RF) against image discretization/interpolation in predicting early distant relapses (EDR) after upfront surgery.

Materials And Methods: Data of 144 patients with pre-surgical high contrast CT were processed consistently with IBSI (Image Biomarker Standardization Initiative) guidelines. Image interpolation/discretization parameters were intentionally changed, including cubic voxel size (0.

Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol.

Purpose: To extend the knowledge-based (KB) automatic planning approach to CyberKnife in the case of Stereotactic Body Radiation Therapy (SBRT) for prostate cancer.

Methods: Seventy-two clinical plans of patients treated according to the RTOG0938 protocol (36.25 Gy/5fr) with CyberKnife were exported from the CyberKnife system to Eclipse to train a KB-model using the Rapid Plan tool.

Deep learning-based segmentation of prostatic urethra on computed tomography scans for treatment planning.

Background And Purpose: The intraprostatic urethra is an organ at risk in prostate cancer radiotherapy, but its segmentation in computed tomography (CT) is challenging. This work sought to: i) propose an automatic pipeline for intraprostatic urethra segmentation in CT, ii) analyze the dose to the urethra, iii) compare the predictions to magnetic resonance (MR) contours.

Materials And Methods: First, we trained Deep Learning networks to segment the rectum, bladder, prostate, and seminal vesicles.

Validation of prediction models for radiation-induced late rectal bleeding: Evidence from a large pooled population of prostate cancer patients.

Purpose: 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.

Materials And Methods: 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.

Stomach and duodenum dose-volume constraints for locally advanced pancreatic cancer patients treated in 15 fractions in combination with chemotherapy.

Purpose: To assess dosimetry predictors of gastric and duodenal toxicities for locally advanced pancreatic cancer (LAPC) patients treated with chemo-radiotherapy in 15 fractions.

Methods: Data from 204 LAPC patients treated with induction+concurrent chemotherapy and radiotherapy (44.25 Gy in 15 fractions) were available.

External validation of an F-FDG-PET radiomic model predicting survival after radiotherapy for oropharyngeal cancer.

Purpose/objective: The purpose of the study is to externally validate published F-FDG-PET radiomic models for outcome prediction in patients with oropharyngeal cancer treated with chemoradiotherapy.

Material/methods: Outcome data and pre-radiotherapy PET images of 100 oropharyngeal cancer patients (stage IV:78) treated with concomitant chemotherapy to 66-69 Gy/30 fr were available. Tumors were segmented using a previously validated semi-automatic method; 450 radiomic features (RF) were extracted according to IBSI (Image Biomarker Standardization Initiative) guidelines.

CT radiomic predictors of local relapse after SBRT for lung oligometastases from colorectal cancer: a single institute pilot study.

Objectives: To assess the potential of radiomic features (RFs) extracted from simulation computed tomography (CT) images in discriminating local progression (LP) after stereotactic body radiotherapy (SBRT) in the management of lung oligometastases (LOM) from colorectal cancer (CRC).

Materials And Methods: Thirty-eight patients with 70 LOM treated with SBRT were analyzed. The largest LOM was considered as most representative for each patient and was manually delineated by two blinded radiation oncologists.

Prediction of the characteristics of aggressiveness of pancreatic neuroendocrine neoplasms (PanNENs) based on CT radiomic features.

Objectives: To predict tumor grade (G1 vs. G2/3), presence of distant metastasis (M+), metastatic lymph nodes (N+), and microvascular invasion (VI) of pancreatic neuroendocrine neoplasms (PanNEN) based on preoperative CT radiomic features (RFs), by applying a machine learning approach aimed to limit overfit.

Methods: This retrospective study included 101 patients who underwent surgery for PanNEN; the entire population was split into training (n = 70) and validation cohort (n = 31).

High weekly integral dose and larger fraction size increase risk of fatigue and worsening of functional outcomes following radiotherapy for localized prostate cancer.

Introduction: We hypothesized that increasing the pelvic integral dose (ID) and a higher dose per fraction correlate with worsening fatigue and functional outcomes in localized prostate cancer (PCa) patients treated with external beam radiotherapy (EBRT).

Methods: The study design was a retrospective analysis of two prospective observational cohorts, REQUITE (development, n=543) and DUE-01 (validation, n=228). Data were available for comorbidities, medication, androgen deprivation therapy, previous surgeries, smoking, age, and body mass index.