AIMC Topic: Radiotherapy Dosage

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Quality and mechanical efficiency of automated knowledge-based planning for volumetric-modulated arc therapy in head and neck cancer.

Journal of applied clinical medical physics Dec 1, 2024
OBJECTIVES: This study aimed to examine the effectiveness of the automated RapidPlan in assessing plan quality and to explore how beam complexity affects the mechanical performance of volumetric modulated arc therapy for head and neck cancers.
Humans Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Radiotherapy Dosage Radiotherapy, Intensity-Modulated Algorithms Head and Neck Neoplasms Knowledge Bases Organs at Risk
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Evaluation and comparison of synthetic computed tomography algorithms with 3T MRI for prostate radiotherapy: AI-based versus bulk density method.

Journal of applied clinical medical physics Nov 29, 2024
PURPOSE: Synthetic computed tomography (sCT)-algorithms, which generate computed tomography images from magnetic resonance imaging data, are becoming part of the clinical radiotherapy workflow. The aim of this retrospective study was to evaluate and ...
Retrospective Studies Tomography, X-Ray Computed Male Image Processing, Computer-Assisted Humans Artificial Intelligence Algorithms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Magnetic Resonance Imaging Prostatic Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted
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Assessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.

Journal of applied clinical medical physics Nov 29, 2024
BACKGROUND: Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) addresses uncertainties due to lung tumor dynamics. We aimed to investigate a comprehensively and systematically validated offline ART regimen with high ...
Male Image Processing, Computer-Assisted Organs at Risk Middle Aged Lung Neoplasms Radiotherapy Planning, Computer-Assisted Deep Learning Feasibility Studies Radiotherapy Dosage Cone-Beam Computed Tomography Humans Radiotherapy, Intensity-Modulated Female Aged
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Brain MR-only workflow in clinical practice: A comparison among generators for quality assurance and patient positioning.

Journal of applied clinical medical physics Nov 25, 2024
BACKGROUND AND PURPOSE: Routine quality control procedures are still required for sCT based on artificial intelligence (AI) to verify the performance of the generators. The aim of this study was to evaluate three generators based on AI or bulk densit...
Humans Artificial Intelligence Tomography, X-Ray Computed Brain Neoplasms Image Processing, Computer-Assisted Magnetic Resonance Imaging Workflow Radiotherapy, Intensity-Modulated Patient Positioning Phantoms, Imaging Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Radiotherapy Dosage
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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations.

Radiation oncology (London, England) Nov 25, 2024
BACKGROUND: Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKnife (CK) is essential for precise planning. We aim to employ deep learning to directly predict the 3D dose distribution calculated by the MC algorithm...
Monte Carlo Method Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiosurgery Deep Learning Lung Neoplasms Organs at Risk Humans Algorithms
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Deep learning-based multiple-CT optimization: An adaptive treatment planning approach to account for anatomical changes in intensity-modulated proton therapy for head and neck cancers.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Nov 23, 2024
BACKGROUNDS: Intensity-modulated proton therapy (IMPT) is particularly susceptible to range and setup uncertainties, as well as anatomical changes.
Radiotherapy, Intensity-Modulated Proton Therapy Algorithms Retrospective Studies Deep Learning Humans Head and Neck Neoplasms Organs at Risk Cone-Beam Computed Tomography Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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Automated robotic-assisted patient positioning method and dosimetric impact analysis for boron neutron capture therapy.

Scientific reports Nov 22, 2024
Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in precise targeting is well-recognized, a critical bottleneck remains in the accurate positioning of p...
Radiotherapy Dosage Patient Positioning Phantoms, Imaging Radiometry Boron Neutron Capture Therapy Algorithms Neoplasms Robotics Radiotherapy Planning, Computer-Assisted Humans
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Machine learning in image-based outcome prediction after radiotherapy: A review.

Journal of applied clinical medical physics Nov 18, 2024
The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid unique challenges. This review comprehensively examines the current scope of ML applications in various...
Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Machine Learning Neoplasms
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Attention 3D UNET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Intracavitary applicators.

Journal of applied clinical medical physics Nov 15, 2024
BACKGROUND: Formulating a clinically acceptable plan within the time-constrained clinical setting of brachytherapy poses challenges to clinicians. Deep learning based dose prediction methods have shown favorable solutions for enhancing efficiency, bu...
Humans Algorithms Retrospective Studies Female Radiotherapy Planning, Computer-Assisted Brachytherapy Radiotherapy Dosage Radiotherapy, Intensity-Modulated Uterine Cervical Neoplasms Deep Learning Imaging, Three-Dimensional Organs at Risk
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Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.

Journal of applied clinical medical physics Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Abdominal Neoplasms Radiotherapy, Image-Guided Radiographic Image Enhancement Radiotherapy Dosage Radiotherapy, Intensity-Modulated Phantoms, Imaging Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Organs at Risk Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed Radiation Dosage Humans Signal-To-Noise Ratio Female Algorithms Male Pelvic Neoplasms Prospective Studies Deep Learning
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