AIMC Topic: Organs at Risk

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Towards improved prescription metrics in novel radiotherapy techniques: a machine learning study.

Physics in medicine and biology Apr 14, 2025
FLASH radiotherapy (RT), microbeam RT (MRT) and minibeam RT (MBRT) are novel RT techniques that have been shown to reduce normal tissue complication probabilities, by modulating the dose distributions through different parameters in space and time. T...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy Prescriptions Machine Learning Humans Neoplasms Organs at Risk
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Evaluating the dosimetric and positioning accuracy of a deep learning based synthetic-CT model for liver radiotherapy treatment planning.

Biomedical physics & engineering express Apr 11, 2025
An MRI-only workflow requires synthetic computed tomography (sCT) images to enable dose calculation. This study evaluated the dosimetric and patient positioning accuracy of deep learning-generated sCT for liver radiotherapy.sCT images were generated ...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Patient Positioning Radiometry Image Processing, Computer-Assisted Liver Organs at Risk Deep Learning Liver Neoplasms Cone-Beam Computed Tomography Algorithms Tomography, X-Ray Computed Humans
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Open-source deep-learning models for segmentation of normal structures for prostatic and gynecological high-dose-rate brachytherapy: Comparison of architectures.

Journal of applied clinical medical physics Apr 5, 2025
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...
Tomography, X-Ray Computed Female Male Deep Learning Humans Algorithms Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Genital Neoplasms, Female Brachytherapy Image Processing, Computer-Assisted Prostatic Neoplasms Organs at Risk
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An extension to the OVH concept for knowledge-based dose volume histogram prediction in lung tumor volumetric-modulated arc therapy.

Journal of applied clinical medical physics Apr 3, 2025
PURPOSE: Volumetric-modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs-at-risk (OARs). Particularly in the case of lung tumors, de...
Humans Radiotherapy Dosage Algorithms Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Lung Neoplasms Knowledge Bases
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Trade-off of different deep learning-based auto-segmentation approaches for treatment planning of pediatric craniospinal irradiation autocontouring of OARs for pediatric CSI.

Medical physics Apr 1, 2025
BACKGROUND: As auto-segmentation tools become integral to radiotherapy, more commercial products emerge. However, they may not always suit our needs. One notable example is the use of adult-trained commercial software for the contouring of organs at ...
Tomography, X-Ray Computed Deep Learning Organs at Risk Adolescent Radiotherapy Planning, Computer-Assisted Child, Preschool Child Humans Automation Image Processing, Computer-Assisted Craniospinal Irradiation
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Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Apr 1, 2025
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...
Supervised Machine Learning Organs at Risk Radiotherapy Planning, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Brachytherapy Humans Tomography, X-Ray Computed
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Deep learning-based segmentation of head and neck organs at risk on CBCT images with dosimetric assessment for radiotherapy.

Physics in medicine and biology Mar 26, 2025
Cone beam computed tomography (CBCT) has become an essential tool in head and neck cancer (HNC) radiotherapy (RT) treatment delivery. Automatic segmentation of the organs at risk (OARs) on CBCT can trigger and accelerate treatment replanning but is s...
Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Radiometry Radiotherapy Dosage Humans Head and Neck Neoplasms Radiotherapy, Image-Guided Organs at Risk
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A deep learning model based on Mamba for automatic segmentation in cervical cancer brachytherapy.

Scientific reports Mar 24, 2025
This study developed and evaluated an automatic segmentation model based on the Mamba framework (AM-UNet) for rapid and precise delineation of high-risk clinical target volume (HRCTV) and organs at risk (OARs) in cervical cancer brachytherapy. Using ...
Middle Aged Deep Learning Organs at Risk Radiotherapy Planning, Computer-Assisted Aged Humans Brachytherapy Adult Tomography, X-Ray Computed Radiotherapy Dosage Uterine Cervical Neoplasms Female
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Closing the gap in plan quality: Leveraging deep-learning dose prediction for adaptive radiotherapy.

Journal of applied clinical medical physics Mar 19, 2025
PURPOSE: Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re-optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a hi...
Deep Learning Head and Neck Neoplasms Organs at Risk Humans Algorithms Retrospective Studies Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated
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Enhanced dose prediction for head and neck cancer artificial intelligence-driven radiotherapy based on transfer learning with limited training data.

Journal of applied clinical medical physics Mar 14, 2025
PURPOSE: Training deep learning dose prediction models for the latest cutting-edge radiotherapy techniques, such as AI-based nodal radiotherapy (AINRT) and Daily Adaptive AI-based nodal radiotherapy (DA-AINRT), is challenging due to limited data. Thi...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Head and Neck Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Artificial Intelligence Algorithms Deep Learning
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