MR-linac: role of artificial intelligence and automation.

The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5 years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanced consistency, accuracy, and efficiency in clinical practice. Magnetic resonance (MR)-guided linear accelerators (MR-linacs) have greatly improved treatment accuracy and real-time plan adaptation, particularly for tumors near radiosensitive organs.

Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.

Background: This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and patients.

Methods: Six questions about definitive radiotherapy for prostate cancer were designed based on common patient inquiries. These questions were presented to different LLMs [ChatGPT‑4, ChatGPT-4o (both OpenAI Inc.

Implant-based reconstruction and adjuvant radiotherapy in breast cancer patients-current status and DEGRO recommendations.

Purpose: The aim of this review is to give an overview of the results of prospective and retrospective studies using allogenic reconstruction and postmastectomy radiotherapy (PMRT) in breast cancer and to make recommendations regarding this interdisciplinary approach.

Materials And Methods: A PubMed search was conducted to extract relevant articles from 2000 to 2024. The search was performed using the following terms: (breast cancer) AND (reconstruction OR implant OR expander) AND (radiotherapy OR radiation).

Characterisation of GPR17-expressing oligodendrocyte precursors in human ischaemic lesions and correlation with reactive glial responses.

White matter damage and subsequent demyelination significantly contribute to long-term functional impairment after ischaemic stroke. Identifying novel pharmacological targets to restore myelin integrity by promoting the maturation of oligodendrocyte precursor cells (OPCs) into new myelinating oligodendrocytes may open new perspectives for ischaemic stroke treatment. In this respect, previous studies highlighted the role of the G protein-coupled membrane receptor 17 (GPR17) as a key regulator of OPC differentiation in experimental models of brain injury, including ischaemic stroke.

Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen.

Background: Manual contour corrections during fractionated magnetic resonance (MR)-guided radiotherapy (MRgRT) are time-consuming. Conventional population models for deep learning auto-segmentation might be suboptimal for MRgRT at MR-Linacs since they do not incorporate manual segmentation from treatment planning and previous fractions.

Purpose: In this work, we investigate patient-specific (PS) auto-segmentation methods leveraging expert-segmented planning and prior fraction MR images (MRIs) to improve auto-segmentation on consecutive treatment days.