AIMC Topic: 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 Algorithms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Lung Neoplasms Knowledge Bases Organs at Risk
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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 ...
Humans Tomography, X-Ray Computed Deep Learning Adolescent Automation Child, Preschool Image Processing, Computer-Assisted Craniospinal Irradiation Organs at Risk Child Radiotherapy Planning, Computer-Assisted
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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 ...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans Radiotherapy Planning, Computer-Assisted Brachytherapy Lung Neoplasms Supervised Machine Learning Organs at Risk
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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...
Radiometry Radiotherapy, Image-Guided Cone-Beam Computed Tomography Image Processing, Computer-Assisted Head and Neck Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Deep Learning
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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 ...
Adult Uterine Cervical Neoplasms Middle Aged Tomography, X-Ray Computed Female Aged Brachytherapy Radiotherapy Dosage Humans Deep Learning Organs at Risk Radiotherapy Planning, Computer-Assisted
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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...
Humans Radiotherapy Dosage Radiotherapy, Intensity-Modulated Head and Neck Neoplasms Algorithms Organs at Risk Retrospective Studies Radiotherapy Planning, Computer-Assisted Deep Learning
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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, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Deep Learning Head and Neck Neoplasms Artificial Intelligence Algorithms
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Direct-to-Treatment Adaptive Radiation Therapy: Live Planning of Spine Metastases Using Novel Cone Beam Computed Tomography.

International journal of radiation oncology, biology, physics Mar 9, 2025
PURPOSE: Cone beam computed tomography (CBCT)-based online adaptive radiation therapy is carried out using a synthetic CT (sCT) created through deformable registration between the patient-specific fan-beam CT, fan-beam computed tomography (FBCT), and...
Humans Spinal Neoplasms Radiotherapy Dosage Phantoms, Imaging Radiotherapy, Image-Guided Cone-Beam Computed Tomography Organs at Risk Radiotherapy Planning, Computer-Assisted
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Geometric and Dosimetric Evaluation of a RayStation Deep Learning Model for Auto-Segmentation of Organs at Risk in a Real-World Head and Neck Cancer Dataset.

Clinical oncology (Royal College of Radiologists (Great Britain)) Mar 1, 2025
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).
Radiotherapy Planning, Computer-Assisted Humans Radiotherapy Dosage Female Radiotherapy, Intensity-Modulated Proton Therapy Deep Learning Radiometry Aged Head and Neck Neoplasms Male Organs at Risk Middle Aged
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Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy.

Scientific reports Feb 25, 2025
This study was conducted to develop and validate a novel deep reinforcement learning (DRL) algorithm incorporating the segment anything model (SAM) to enhance the accuracy of automatic contouring organs at risk during radiotherapy for cervical cancer...
Middle Aged Female Deep Learning Humans Adult Radiotherapy Planning, Computer-Assisted Organs at Risk Algorithms Uterine Cervical Neoplasms Reinforcement Machine Learning Tomography, X-Ray Computed
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