AIMC Topic: Radiotherapy Dosage

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Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy.

Medical physics Jan 28, 2021
PURPOSE: This study aimed to develop and evaluate a novel strategy for establishing a deep learning-based gamma passing rate (GPR) prediction model for volumetric modulated arc therapy (VMAT) using dummy target plan data, one measurement process, and...
Gamma Rays Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Radiotherapy, Intensity-Modulated Neural Networks, Computer Deep Learning
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Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

Medical physics Jan 27, 2021
PURPOSE: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling errors with the use of radiomic features of fluence maps measured in patient-specific quality assurance (QA) for intensity-modulated radiation therapy...
Radiotherapy, Intensity-Modulated Radiometry Gamma Rays Machine Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans
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Robotic MLC-based plans: A study of plan complexity.

Medical physics Jan 21, 2021
PURPOSE: The utility of complexity metrics has been assessed for IMRT and VMAT treatment plans, but this analysis has never been performed for CyberKnife (CK) plans. The purpose of this study is to perform a complexity analysis of CK MLC plans, adapt...
Humans Algorithms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Male Robotics Robotic Surgical Procedures
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DVH Prediction for VMAT in NPC with GRU-RNN: An Improved Method by Considering Biological Effects.

BioMed research international Jan 19, 2021
PURPOSE: A recurrent neural network (RNN) and its variants such as gated recurrent unit-based RNN (GRU-RNN) were found to be very suitable for dose-volume histogram (DVH) prediction in our previously published work. Using the dosimetric information g...
Radiotherapy, Intensity-Modulated Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Neural Networks, Computer Retrospective Studies
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Deep learning-based automatic delineation of the hippocampus by MRI: geometric and dosimetric evaluation.

Radiation oncology (London, England) Jan 14, 2021
BACKGROUND: Whole brain radiotherapy (WBRT) can impair patients' cognitive function. Hippocampal avoidance during WBRT can potentially prevent this side effect. However, manually delineating the target area is time-consuming and difficult. Here, we p...
Magnetic Resonance Imaging Radiotherapy Planning, Computer-Assisted Hippocampus Male Middle Aged Deep Learning Radiotherapy Dosage Humans Female Aged Aged, 80 and over Adult Brain Neoplasms
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Performance of deep learning synthetic CTs for MR-only brain radiation therapy.

Journal of applied clinical medical physics Jan 7, 2021
PURPOSE: To evaluate the dosimetric and image-guided radiation therapy (IGRT) performance of a novel generative adversarial network (GAN) generated synthetic CT (synCT) in the brain and compare its performance for clinical use including conventional ...
Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Brain Radiotherapy, Image-Guided
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Data-driven dose calculation algorithm based on deep U-Net.

Physics in medicine and biology Dec 22, 2020
Accurate and efficient dose calculation is an important prerequisite to ensure the success of radiation therapy. However, all the dose calculation algorithms commonly used in current clinical practice have to compromise between calculation accuracy a...
Radiotherapy Planning, Computer-Assisted Radiation Dosage Radiotherapy Dosage Reproducibility of Results Humans Neoplasms Radiotherapy, Intensity-Modulated Deep Learning
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Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy.

Physics in medicine and biology Dec 12, 2020
To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, th...
Humans Radiotherapy Planning, Computer-Assisted Radiation Dosage Radiotherapy Dosage Male Machine Learning Tomography, X-Ray Computed Neoplasms Female Child
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Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Physics in medicine and biology Dec 5, 2020
Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep c...
Magnetic Resonance Imaging Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Proton Therapy Cone-Beam Computed Tomography Image Processing, Computer-Assisted Head and Neck Neoplasms Male Middle Aged Female Humans Aged Neural Networks, Computer Adult
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Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Nov 29, 2020
OBJECTIVE: Dose prediction using deep learning networks prior to radiotherapy might lead tomore efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess thei...
Radiotherapy Dosage Proton Therapy Child Humans Protons Organs at Risk Radiotherapy, Intensity-Modulated Deep Learning Radiotherapy Planning, Computer-Assisted Abdominal Neoplasms
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