Radiotherapy, Intensity-Modulated

Non-coplanar CBCT image reconstruction using a generative adversarial network for non-coplanar radiotherapy.

Journal of applied clinical medical physics Aug 26, 2024

PURPOSE: To develop a non-coplanar cone-beam computed tomography (CBCT) image reconstruction method using projections within a limited angle range for non-coplanar radiotherapy.

Radiotherapy, Intensity-Modulated Phantoms, Imaging Radiotherapy, Image-Guided Algorithms Brain Neoplasms Cone-Beam Computed Tomography Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Image Processing, Computer-Assisted Organs at Risk Humans Neural Networks, Computer

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Deep learning for patient-specific quality assurance of volumetric modulated arc therapy: Prediction accuracy and cost-sensitive classification performance.

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) Aug 26, 2024

PURPOSE: To evaluate a deep learning model's performance in predicting and classifying patient-specific quality assurance (PSQA) results for volumetric modulated arc therapy (VMAT), aiming to streamline PSQA workflows and reduce the onsite measuremen...

Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Costs and Cost Analysis Humans Deep Learning

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Machine learning and deep learning prediction of patient specific quality assurance in breast IMRT radiotherapy plans using Halcyon specific complexity indices.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Aug 17, 2024

INTRODUCTION: New radiotherapy machines such as Halcyon are capable of delivering dose-rate of 600 monitor-units per minute, allowing large numbers of patients treated per day. However, patient-specific quality assurance (QA) is still required, which...

Humans Machine Learning Female Breast Neoplasms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care

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Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application.

Journal of applied clinical medical physics Aug 9, 2024

BACKGROUND: Radiotherapy has been crucial in prostate cancer treatment. However, manual segmentation is labor intensive and highly variable among radiation oncologists. In this study, a deep learning based automated contouring model is constructed fo...

Humans Algorithms Prostatic Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Male Image Processing, Computer-Assisted Prognosis Middle Aged Tomography, X-Ray Computed Aged

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Deep learning architecture with shunted transformer and 3D deformable convolution for voxel-level dose prediction of head and neck tumors.

Physical and engineering sciences in medicine Aug 5, 2024

Intensity-modulated radiation therapy (IMRT) has been widely used in treating head and neck tumors. However, due to the complex anatomical structures in the head and neck region, it is challenging for the plan optimizer to rapidly generate clinically...

Radiotherapy Dosage Radiotherapy, Intensity-Modulated Head and Neck Neoplasms Radiotherapy Planning, Computer-Assisted Radiation Dosage Humans Deep Learning

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Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer.

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) Aug 2, 2024

PURPOSE: The purpose of the study is to investigate the clinical application of deep learning (DL)-assisted automatic radiotherapy planning for lung cancer.

Humans Retrospective Studies Radiotherapy Planning, Computer-Assisted Automation Radiotherapy Dosage Deep Learning Radiotherapy, Intensity-Modulated Lung Neoplasms Organs at Risk

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Improving the performance of deep learning models in predicting and classifying gamma passing rates with discriminative features and a class balancing technique: a retrospective cohort study.

Radiation oncology (London, England) Jul 31, 2024

BACKGROUND: The purpose of this study was to improve the deep learning (DL) model performance in predicting and classifying IMRT gamma passing rate (GPR) by using input features related to machine parameters and a class balancing technique.

Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Retrospective Studies Nasopharyngeal Carcinoma Deep Learning Gamma Rays

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Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jul 14, 2024

PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT)...

Esophageal Neoplasms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiation Injuries Esophagitis Retrospective Studies Male Aged, 80 and over Humans Female Tomography, X-Ray Computed Middle Aged Adult Aged Deep Learning Radiomics

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Localized fine-tuning and clinical evaluation of deep-learning based auto-segmentation (DLAS) model for clinical target volume (CTV) and organs-at-risk (OAR) in rectal cancer radiotherapy.

Radiation oncology (London, England) Jul 2, 2024

BACKGROUND AND PURPOSE: Various deep learning auto-segmentation (DLAS) models have been proposed, some of which have been commercialized. However, the issue of performance degradation is notable when pretrained models are deployed in the clinic. This...

Humans Retrospective Studies Rectal Neoplasms Adult Organs at Risk Male Radiotherapy Planning, Computer-Assisted Middle Aged Radiotherapy Dosage Tomography, X-Ray Computed Deep Learning Radiotherapy, Intensity-Modulated Female Aged

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Development of a risk prediction model for radiation dermatitis following proton radiotherapy in head and neck cancer using ensemble machine learning.

Radiation oncology (London, England) Jun 24, 2024

PURPOSE: This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior predictiv...

Middle Aged Aged Proton Therapy Humans Risk Assessment Radiodermatitis Adult Radiotherapy Dosage Machine Learning Head and Neck Neoplasms Male Radiotherapy, Intensity-Modulated Female

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Non-coplanar CBCT image reconstruction using a generative adversarial network for non-coplanar radiotherapy.

Deep learning for patient-specific quality assurance of volumetric modulated arc therapy: Prediction accuracy and cost-sensitive classification performance.

Machine learning and deep learning prediction of patient specific quality assurance in breast IMRT radiotherapy plans using Halcyon specific complexity indices.

Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application.

Deep learning architecture with shunted transformer and 3D deformable convolution for voxel-level dose prediction of head and neck tumors.

Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer.

Improving the performance of deep learning models in predicting and classifying gamma passing rates with discriminative features and a class balancing technique: a retrospective cohort study.

Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.

Localized fine-tuning and clinical evaluation of deep-learning based auto-segmentation (DLAS) model for clinical target volume (CTV) and organs-at-risk (OAR) in rectal cancer radiotherapy.

Development of a risk prediction model for radiation dermatitis following proton radiotherapy in head and neck cancer using ensemble machine learning.

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