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Radiotherapy Dosage

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Deep learning based super-resolution for CBCT dose reduction in radiotherapy.

Medical physics Dec 3, 2024
BACKGROUND: Cone-beam computed tomography (CBCT) is a crucial daily imaging modality in image-guided and adaptive radiotherapy. However, the use of ionizing radiation in CBCT imaging increases the risk of secondary cancers, which is particularly conc...
Humans Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Radiotherapy, Image-Guided Head and Neck Neoplasms Radiation Dosage Radiotherapy Dosage
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Evaluating the dosimetric impact of deep-learning-based auto-segmentation in prostate cancer radiotherapy: Insights into real-world clinical implementation and inter-observer variability.

Journal of applied clinical medical physics Dec 1, 2024
PURPOSE: This study aimed to investigate the dosimetric impact of deep-learning-based auto-contouring for clinical target volume (CTV) and organs at risk (OARs) delineation in prostate cancer radiotherapy planning. Additionally, we compared the geome...
Deep Learning Humans Imaging, Three-Dimensional Observer Variation Prostatic Neoplasms Feasibility Studies Radiotherapy Dosage Prostate Organs at Risk Radiotherapy, Intensity-Modulated Retrospective Studies Radiotherapy Planning, Computer-Assisted Radiometry Tomography, X-Ray Computed Male
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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.
Knowledge Bases Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Humans Algorithms Quality Assurance, Health Care Radiotherapy Dosage Head and Neck Neoplasms
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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 ...
Algorithms Organs at Risk Humans Retrospective Studies Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed Artificial Intelligence Radiotherapy, Intensity-Modulated Male Image Processing, Computer-Assisted Magnetic Resonance Imaging Prostatic Neoplasms
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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 ...
Radiotherapy, Intensity-Modulated Cone-Beam Computed Tomography Male Humans Radiotherapy Planning, Computer-Assisted Middle Aged Feasibility Studies Image Processing, Computer-Assisted Female Deep Learning Organs at Risk Radiotherapy Dosage Lung Neoplasms 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...
Artificial Intelligence Tomography, X-Ray Computed Humans Radiotherapy, Intensity-Modulated Patient Positioning Phantoms, Imaging Workflow Brain Neoplasms Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Image Processing, Computer-Assisted Radiotherapy Dosage Magnetic Resonance Imaging
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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...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiosurgery Monte Carlo Method Lung Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Algorithms Deep Learning
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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.
Proton Therapy Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Retrospective Studies Cone-Beam Computed Tomography Deep Learning Head and Neck Neoplasms Humans Organs at Risk Algorithms
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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...
Boron Neutron Capture Therapy Patient Positioning Phantoms, Imaging Radiometry Humans Algorithms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Neoplasms Robotics
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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...
Humans Machine Learning Neoplasms Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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