Radiation-Enhanced AF1q Moves Center Stage as a Key Driver to Favorable Tumor Stage in Rectal Cancer Patients.

Background: Enhanced protein expression of ALL1-fused gene from chromosome 1q (AF1Q) after (chemo)radiotherapy has been described in vitro, but is largely understudied in gastrointestinal cancer. We aimed to investigate AF1q expression in rectal cancer (RC) patients treated with short-term radiation therapy and a possible correlation with markers crucial for RC prognosis.

Methods: A cohort of 75 RC patients scheduled for surgery was defined and patients with moderately locally advanced tumors (cT3Nx) received preoperative hyperfractionated short-term radiation therapy (cumulative dose 25 Gy).

Enhancing clinical safety in radiation oncology: A data-driven approach to risk management.

Purpose: To demonstrate a data-driven risk management (RM) strategy in radiation oncology using an in-house developed web-based incident reporting system. The system leverages real-time analytics to enhance clinical risk prioritization and management, improving patient safety and treatment efficiency.

Methods: We developed and implemented a web-based incident reporting system that allows any staff member to report incidents in real time, supporting anonymous submissions and capturing detailed incident data.

Ultra-fast, one-click radiotherapy treatment planning outside a treatment planning system.

We present an automated radiation oncology treatment planning pipeline that operates between segmentation and plan review, minimizing manual interaction and reliance on traditional planning systems. Two AI models work in sequence: the first generates a dose distribution, and the second creates a deliverable DICOM-RT plan. Trained and validated on 276 plans, and tested on 151 datasets, the system produced clinically deliverable plans-complete with all VMAT parameters-in about 38 s.

Corrigendum to "Explicitly encoding the cyclic nature of breathing signal allows for accurate breathing motion prediction in radiotherapy with minimal training data" [Phys. Imaging Radiat. Oncol. 30 (2024) 100594].

[This corrects the article DOI: 10.1016/j.phro.

Development of an MR-only radiotherapy treatment planning workflow using a commercial synthetic CT generator for brain and head & neck tumor patients.

Background: In magnetic resonance (MR)-only radiotherapy (RT) workflows, synthetic computed tomography images (sCT) are needed as a surrogate for a dose calculation. Commercial and certified sCT algorithms became recently available, but many have not been evaluated in a clinical setting, especially in the head and neck tumor (HN) region. In this study, an MRI-only workflow using a commercial sCT generator for photon beam therapy in brain and HN body sites was evaluated in terms of dose calculation accuracy, modelling of immobilization devices, as well as usability for autosegmentation.