AIMC Topic: Radiotherapy Dosage
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Impact of nominal photon energies on normal tissue sparing in knowledge-based radiotherapy treatment planning for rectal cancer patients.
PloS one
Mar 7, 2019
The interactive adjustment of the optimization objectives during the treatment planning process has made it difficult to evaluate the impact of beam quality exclusively in radiotherapy. Without consensus in the published results, the arbitrary select...
Machine learning for automated quality assurance in radiotherapy: A proof of principle using EPID data description.
Medical physics
Mar 4, 2019
PURPOSE: Developing automated methods to identify task-driven quality assurance (QA) procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use of machine learning (ML) methods for possible visualization, automation,...
Automated noncoplanar treatment planning strategy in stereotactic radiosurgery of multiple cranial metastases: HyperArc and CyberKnife dose distributions.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Mar 1, 2019
The purpose of this study was to evaluate and compare the dosimetric effects of HyperArc-based stereotactic radiosurgery (SRS) and a robotic radiosurgery system-based planning using CyberKnife for multiple cranial metastases. In total, 11 cancer pati...
A trial for EBT3 film without batch-specific calibration using a neural network.
Physics in medicine and biology
Feb 27, 2019
This note reports a trial to establish an ANN (artificial neural network) method applying to EBT3 films of different batches without batch-specific calibration. Based on Pytorch (Facebook, https://pytorch.org/), a feed-forward ANN model was built to ...
Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Feb 1, 2019
Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast over computed tomographies (CTs), without the ionizing radiation exposure. However, it requires the generation of a s...
Prediction of skin dose in low-kV intraoperative radiotherapy using machine learning models trained on results of in vivo dosimetry.
Medical physics
Jan 25, 2019
PURPOSE: The purpose of this study was to implement a machine learning model to predict skin dose from targeted intraoperative (TARGIT) treatment resulting in timely adoption of strategies to limit excessive skin dose.
Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jan 23, 2019
BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for locally advanced non-small cell lung cancer (LA-NSCLC). Prior studies have proposed relevant dosimetric constraints to limit this toxicity. Using machine ...
Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.
Clinical lung cancer
Dec 29, 2018
INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive o...
Efficacy and safety of CT-guided high-dose-rate interstitial brachytherapy in primary and secondary malignancies of the pancreas.
European journal of radiology
Dec 28, 2018
PURPOSE: To evaluate efficacy and safety of CT-guided iBT in patients with primary and secondary malignancies of the pancreas.
Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.
Medical physics
Dec 28, 2018
PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., random forests) and single-model methods (e.g., logistic regression and decision trees) in predictive modeling of post-RT treatment failure and adverse eve...
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