AIMC Topic: Radiotherapy, Intensity-Modulated

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A prognostic and predictive model based on deep learning to identify optimal candidates for intensity-modulated radiotherapy alone in patients with stage II nasopharyngeal carcinoma: A retrospective multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Dec 5, 2024
PURPOSE: To develop and validate a prognostic and predictive model integrating deep learning MRI features and clinical information in patients with stage II nasopharyngeal carcinoma (NPC) to identify patients with a low risk of progression for whom i...
Middle Aged Deep Learning Magnetic Resonance Imaging Neoplasm Staging Radiotherapy, Intensity-Modulated Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Female Aged Adult Male Humans Prognosis Retrospective Studies
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Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy.

Journal of applied clinical medical physics Dec 3, 2024
PURPOSE: Optimal head-and-neck cancer (HNC) treatment planning requires accurate and feasible planning goals to meet dosimetric constraints and generate robust online adaptive treatment plans. A new x-ray-based adaptive radiotherapy (ART) treatment p...
Precision Medicine Retrospective Studies Head and Neck Neoplasms Organs at Risk Humans Artificial Intelligence Algorithms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated
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Breast radiotherapy planning: A decision-making framework using deep learning.

Medical physics Dec 3, 2024
BACKGROUND: Effective breast cancer treatment planning requires balancing tumor control while minimizing radiation exposure to healthy tissues. Choosing between intensity-modulated radiation therapy (IMRT) and three-dimensional conformal radiation th...
Retrospective Studies Female Breast Neoplasms Deep Learning Humans Radiotherapy, Conformal Decision Making Radiotherapy Dosage Organs at Risk Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted
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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...
Male Deep Learning Imaging, Three-Dimensional Prostatic Neoplasms Humans Retrospective Studies Tomography, X-Ray Computed Observer Variation Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiometry Prostate Feasibility Studies Organs at Risk Radiotherapy Planning, Computer-Assisted
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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.
Algorithms Head and Neck Neoplasms Knowledge Bases Organs at Risk Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Radiotherapy Dosage Humans Radiotherapy, Intensity-Modulated
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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 Radiotherapy Dosage Artificial Intelligence Radiotherapy, Intensity-Modulated Algorithms 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 ...
Image Processing, Computer-Assisted Humans Lung Neoplasms Male Organs at Risk Feasibility Studies Middle Aged Female Radiotherapy Planning, Computer-Assisted Deep Learning Aged Radiotherapy Dosage Cone-Beam Computed Tomography Radiotherapy, Intensity-Modulated
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Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter.

Medical physics Nov 28, 2024
BACKGROUND: The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the pat...
Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Scattering, Radiation Electrical Equipment and Supplies Deep Learning Humans Time Factors Image Processing, Computer-Assisted Neural Networks, Computer
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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...
Magnetic Resonance Imaging Artificial Intelligence Workflow Radiotherapy Dosage Humans Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Tomography, X-Ray Computed Quality Assurance, Health Care Patient Positioning Brain Neoplasms Phantoms, Imaging Image Processing, Computer-Assisted
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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...
Humans Algorithms Deep Learning Lung Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiosurgery Monte Carlo Method
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