UNASSIGNED: Prostate cancer (PCa) is a prevalent malignancy in European men, often treated with radiotherapy (RT) for localized disease. While modern RT achieves high success rates, concerns about late gastrointestinal (GI) toxicities persist. This retrospective study aims to identify predictors for late GI toxicities following definitive conventionally fractionated external beam RT (EBRT) for PCa, specifically exploring the dose to the rectal wall.
UNASSIGNED: A cohort of 96 intermediate- to high-risk PCa patients underwent EBRT between 2008 and 2016. Rectum and rectum wall contours were delineated, and 3D dose matrices were extracted. Volumetric and dosimetric indices were computed, and statistical analyses were performed to identify predictors using the Mann-Whitney U-rank test, logistic regression, and recursive feature elimination.
UNASSIGNED: In our cohort, 15 out of 96 patients experienced grade II late proctitis. Our analysis reveals distinct optimal predictors for rectum and rectum wall (RW) structures varying with α/β values (3.0 and 2.3 Gy) across prescribed doses of 68 to 76 Gy. Despite variability, RW predictors demonstrate greater consistency, notably V68Gy[%] to V74Gy[%] for α/β 3.0 Gy, and V68Gy[%] to V70Gy[%] for α/β 2.3 Gy. The model with α/β 2.3 Gy, featuring RW volume receiving 70 Gy (V70Gy[%]), stands out with a BIC value of 62.92, indicating its superior predictive effectiveness. Finally, focusing solely on the rectum structure, the V74Gy[%] emerges the best predictor for α/β 3.0 Gy, with a BIC value of 66.73.
UNASSIGNED: This investigation highlights the critical role of V70Gy[%] in the rectum wall as a robust predictor for grade II late gastrointestinal (GI) toxicity following external beam radiation therapy (EBRT) for prostate cancer (PCa). Furthermore, our findings suggest that focusing on the rectum wall specifically, rather than the entire rectum, may offer improved accuracy in assessing proctitis development. A V70Gy (in EQD2 with α/β 2.3 Gy) of ≤5% and if possible ≤1% for the rectal wall should be achieved to minimize the risk of late grade II proctitis.

Primary thyroid cancer metastasizing to the spine portends poor survival and low quality of life. Current management strategies continue to evolve. This single-institution retrospective study analyzes outcomes after spinal stereotactic radiosurgery for patients with spinal metastases from thyroid cancer.
Nineteen patients (median age: 64.5 years) were treated with stereotactic radiosurgery (SRS) for spinal primary thyroid metastases (40 metastases, 47 vertebral levels) between 2003 and 2023. Nineteen (47.5%) lesions had epidural involvement and 20 (50%) lesions were classified as potentially unstable or unstable via the Spinal Instability Neoplastic Score. The median tumor volume per lesion was 33 cc (range: 1.5-153). The median single fraction prescription dose was 20 Gy (range: 12-23.5).
The median follow-up period was 15 months (range: 2-40). Five (12.8%) lesions locally progressed at a median of 9 months (range: 4-26) after SRS. The 1-, 2-, and 3-year local tumor control rates per lesion were 90.4%, 83.5%, and 75.9%, respectively. On univariate analysis, age at SRS >70 years (P = 0.05, hazard ratio: 6.86, 95% confidence interval: 1.01-46.7) was significantly correlated with lower rates of local tumor control. The median overall survival was 35 months (range: 2-141). The 1-, 2-, and 3-year overall survival rates were 73.7%, 50.4%, and 43.2%, respectively. For 33 lesions initially associated with pain, patients reported pain improvement (22 lesions, 66.7%), stability (10 lesions, 30.3%), and worsening (1 lesion, 3.0%) after SRS. One patient developed dysphagia 4 months after SRS treatment.
SRS can be utilized as an effective and safe primary and adjuvant treatment option for primary thyroid metastases to the spine.

Objective.This study addresses radiation-induced toxicity (RIT) challenges in radiotherapy (RT) by developing a personalized treatment planning framework. It leverages patient-specific data and dosimetric information to create an optimization model that limits adverse side effects using constraints learned from historical data.Approach.The study uses the optimization with constraint learning (OCL) framework, incorporating patient-specific factors into the optimization process. It consists of three steps: optimizing the baseline treatment plan using population-wide dosimetric constraints; training a machine learning (ML) model to estimate the patient\'s RIT for the baseline plan; and adapting the treatment plan to minimize RIT using ML-learned patient-specific constraints. Various predictive models, including classification trees, ensembles of trees, and neural networks, are applied to predict the probability of grade 2+ radiation pneumonitis (RP2+) for non-small cell lung (NSCLC) cancer patients three months post-RT. The methodology is assessed with four high RP2+ risk NSCLC patients, with the goal of optimizing the dose distribution to constrain the RP2+ outcome below a pre-specified threshold. Conventional and OCL-enhanced plans are compared based on dosimetric parameters and predicted RP2+ risk. Sensitivity analysis on risk thresholds and data uncertainty is performed using a toy NSCLC case.Main results.Experiments show the methodology\'s capacity to directly incorporate all predictive models into RT treatment planning. In the four patients studied, mean lung dose and V20 were reduced by an average of 1.78 Gy and 3.66%, resulting in an average RP2+ risk reduction from 95% to 42%. Notably, this reduction maintains tumor coverage, although in two cases, sparing the lung slightly increased spinal cord max-dose (0.23 and 0.79 Gy).Significance.By integrating patient-specific information into learned constraints, the study significantly reduces adverse side effects like RP2+ without compromising target coverage. This unified framework bridges the gap between predicting toxicities and optimizing treatment plans in personalized RT decision-making.

Many breast cancer (BC) predisposition genes encode proteins involved in DNA damage repair (DDR). Identification of germline pathogenic va-riants (PV) in DDR genes raises the question whether their presence can influence the treatment outcomes and potential radiation-induced toxicity in their carriers treated by adjuvant radiotherapy, which has not yet been answered conclusively. We retrospectively examined records of 213 BC patients treated by adjuvant radiotherapy, including 39 (18.3 %) BRCA1/2 PV carriers, 25 carriers (11.7 %) of PV in other breast cancer-predisposing genes, and 149 (70 %) non-carriers. Our goal was to examine 5-year disease-free survival (5y DFS) rates among the study groups and determine the impact of radiotherapy-induced lymphopoenia (RIL) on this outcome. While we found no significant difference in 5y DFS between non-carriers and carriers of BRCA mutations (86.4 % vs 78.4 % P = 0.24) or between non-carriers and other studied mutations (86.4 % vs 93.3 %; P = 0.27), respectively, we observed that the entire group of PV carriers had a significantly lower proportion of patients without RIL (P = 0.04) than the non-carriers. In contrast, subsequent analyses indicated a non-significant trend toward an increased 5y DFS in PV carriers with RIL. Our single-centre study indicated that the presence of PV in BC patients has an insignificant impact on DFS but can reduce the risk of RIL associated with adjuvant radiotherapy. It remains unclear whether this may result from the paradoxical activation of anti-tumour immunity in PV carriers with higher lymphocyte consumption resulting from higher immune effectiveness.

Polymorphous low-grade adenocarcinoma (PLGA) is an extremely rare finding in the nasopharynx. There are no guidelines for the treatment of PLGA in this localization. Radiotherapy may be administered to treat this malignancy; however, in radiosensitive individuals, it is associated with a risk of severe radiotherapy-induced toxicity.
We present a case of a 73-year-old woman with locally advanced polymorphous low-grade adenocarcinoma of the nasopharynx who developed a severe adverse acute reaction to radiotherapy leading to treatment discontinuation. Despite intensive treatment, the patient died 40 days after RT initiation. Whole genome sequencing was performed using DNA from peripheral blood mononuclear cells in the search for variants that could explain such extreme toxicity.
We identified a combination of pathogenic variants that may have contributed to the patient\'s reaction to radiation therapy, including predisposing variants in XRCC1, XRCC3, and LIG4. We also identified candidate variants, not previously described in this context, which could be associated with radiation toxicity based on plausible mechanisms. We discuss previous reports of this rare tumor from the literature and known contributors to radiation-induced toxicity.
Genetic causes should be considered in cases of extreme radiosensitivity, especially when is not explained by clinical factors.

UNASSIGNED: Head and neck cancer (HNC) patients treated with radiotherapy often suffer from radiation-induced toxicities. Normal Tissue Complication Probability (NTCP) modeling can be used to determine the probability to develop these toxicities based on patient, tumor, treatment and dose characteristics. Since the currently used NTCP models are developed using supervised methods that discard unlabeled patient data, we assessed whether the addition of unlabeled patient data by using semi-supervised modeling would gain predictive performance.
UNASSIGNED: The semi-supervised method of self-training was compared to supervised regression methods with and without prior multiple imputation by chained equation (MICE). The models were developed for the most common toxicity outcomes in HNC patients, xerostomia (dry mouth) and dysphagia (difficulty swallowing), measured at six months after treatment, in a development cohort of 750 HNC patients. The models were externally validated in a validation cohort of 395 HNC patients. Model performance was assessed by discrimination and calibration.
UNASSIGNED: MICE and self-training did not improve performance in terms of discrimination or calibration at external validation compared to current regression models. In addition, the relative performance of the different models did not change upon a decrease in the amount of (labeled) data available for model development. Models using ridge regression outperformed the logistic models for the dysphagia outcome.
UNASSIGNED: Since there was no apparent gain in the addition of unlabeled patient data by using the semi-supervised method of self-training or MICE, the supervised regression models would still be preferred in current NTCP modeling for HNC patients.

OBJECTIVE: The RadioTransNet project is a French initiative structuring preclinical and translational research in radiation therapy for cancer at national level. The network\'s activities are organized around four chosen priorities, which are: target definition, normal tissue, combined treatments and dose modelling. The subtargets linked to these four major priorities are unlimited. They include all aspects associated with fundamental radiobiology, preclinical studies, imaging, medical physics research and transversal components clearly related to these scientific areas, such as medical oncology, radio-diagnostics, nuclear medicine and cost-effectiveness considerations.
METHODS: During its first phase of activity, four workshops following the consensus conference model and based on scientific and medical state of the art in radiotherapy and radiobiology were organized on the four above-mentioned objectives to identify key points. Then a road map has been defined and served as the basis for the opening in 2022 of a dedicated call, SEQ-RTH22, proposed by the French cancer national institute (INCa).
RESULTS: Four research projects submitted by RadioTransNet partners have been selected to be supported by INCa: the first by Professor Anne Laprie from Oncopole Claudius-Regaud and Inserm ToNic in Toulouse on neurocognition and health after pediatric irradiation, the second submitted by Fabien Milliat from IRSN aims to study decryption and targeting of endothelial cell-immune cells interactions to limit radiation-induced intestinal toxicity, the third project, submitted by Yolanda Prezado from institut Curie-CNRS on proton minibeam radiotherapy as a new approach to reduce toxicity, and the latest project proposed by R. de Crevoisier from centre Eugène-Marquis in Rennes on predictive multiscale models of head and neck radiotoxicity induced for optimized personalized radiation therapy. Topics of each of these projects are presented here.
CONCLUSIONS: RadioTransNet project has been launched in 2018, supported by INCa, in order to structure and promote preclinical research in oncology radiotherapy and to favor collaboration between the actors of this research. INCa relied on RadioTransNet initiatives and activities, resulting in the opening of dedicated call for projects. Beyond its first main goals, RadioTransNet network is able to help to fund the human and technical resources necessary to conduct optimal translational and preclinical research in radiation oncology.

UNASSIGNED: Radiation-induced toxicities are common adverse events in lung cancer (LC) patients undergoing radiotherapy (RT). An accurate prediction of these adverse events might facilitate an informed and shared decision-making process between patient and radiation oncologist with a clearer view of life-balance implications in treatment choices. This work provides a benchmark of machine learning (ML) approaches to predict radiation-induced toxicities in LC patients built upon a real-world health dataset based on a generalizable methodology for their implementation and external validation.
UNASSIGNED: Ten feature selection (FS) methods were combined with five ML-based classifiers to predict six RT-induced toxicities (acute esophagitis, acute cough, acute dyspnea, acute pneumonitis, chronic dyspnea, and chronic pneumonitis). A real-world health dataset (RWHD) built from 875 consecutive LC patients was used to train and validate the resulting 300 predictive models. Internal and external accuracy was calculated in terms of AUC per clinical endpoint, FS method, and ML-based classifier under analysis.
UNASSIGNED: Best performing predictive models obtained per clinical endpoint achieved comparable performances to methods from state-of-the-art at internal validation (AUC ≥ 0.81 in all cases) and at external validation (AUC ≥ 0.73 in 5 out of 6 cases).
UNASSIGNED: A benchmark of 300 different ML-based approaches has been tested against a RWHD achieving satisfactory results following a generalizable methodology. The outcomes suggest potential relationships between underrecognized clinical factors and the onset of acute esophagitis or chronic dyspnea, thus demonstrating the potential that ML-based approaches have to generate novel data-driven hypotheses in the field.

A 62-year-old woman with a 40-pack-year smoking history and severe chronic obstructive pulmonary disease with early-stage right upper lobe non-small cell lung cancer (NSCLC) was treated with stereotactic ablative radiotherapy (SABR). Two years after treatment, a surveillance computerized tomography scan showed lesions of the posterior 4th and 5th ribs including expansion of the medulla that was unusual and of concern for possible malignant infiltration. A follow-up magnetic resonance imaging (MRI) scan revealed these lesions to be healing fractures post-radiotherapy. Although generally well tolerated, SABR is known to produce inflammatory and fibrotic changes both in-field and in organs at risk, and rib fractures are a well-established adverse event. MRI has high diagnostic accuracy and sensitivity for rib fractures and was able to rule out malignant spread. This case demonstrates the need for regular follow-up following SABR for early-stage NSCLC, as well as the challenge of interpreting indeterminate post-SABR radiography findings.

A prolonged interval (>4 weeks) between short-course radiotherapy (25 Gy in five fractions) (SCRT-delay) and total mesorectal excision for rectal cancer has been associated with a decreased postoperative complication rate and offers the possibility of organ preservation in the case of a complete tumour response. This prospective cohort study systematically evaluated patient-reported bowel dysfunction and physician-reported radiation-induced toxicity for 8 weeks following SCRT-delay.
Patients who were referred for SCRT-delay for intermediate risk, oligometastatic or locally advanced rectal cancer were included. Repeated measurements were done for patient-reported bowel dysfunction (measured by the low anterior resection syndrome [LARS] questionnaire and categorized as no, minor or major LARS) and physician-reported radiation-induced toxicity (according to Common Terminology Criteria for Adverse Events version 4.0) before start of treatment (baseline), at completion of SCRT and 1, 2, 3, 4, 6 and 8 weeks thereafter.
Fifty-one patients were included; 31 (61%) were men and the median age was 67 years (range 44-91). Patient-reported bowel dysfunction and physician-reported radiation-induced toxicity peaked at weeks 1-2 after completion of SCRT and gradually declined thereafter. Major LARS was reported by 44 patients (92%) at some time during SCRT-delay. Grade 3 radiation-induced toxicity was reported in 17 patients (33%) and concerned predominantly diarrhoea. No Grade 4-5 radiation-induced toxicity occurred.
During SCRT-delay, almost every patient experiences temporary mild-moderate radiation-induced toxicity and major LARS, but life-threatening toxicity is rare. SCRT-delay is a safe alternative to SCRT-direct surgery that should be proposed when counselling rectal cancer patients on neoadjuvant strategies.