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Radiotherapy Dosage

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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
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
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
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
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
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
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...

Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.

Medical physics
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...

Knowledge-based dose prediction models for head and neck cancer are strongly affected by interorgan dependency and dataset inconsistency.

Medical physics
PURPOSE: The goal of this study was to generate a large treatment plan database for head and neck (H&N) cancer patients that can be considered as the gold standard to train and validate models for knowledge-based (KB) treatment planning and QA. With ...

Deep-learning based surface region selection for deep inspiration breath hold (DIBH) monitoring in left breast cancer radiotherapy.

Physics in medicine and biology
Deep inspiration breath hold (DIBH) with surface supervising is a common technique for cardiac dose reduction in left breast cancer radiotherapy. Surface supervision accuracy relies on the characteristics of surface region. In this study, a convoluti...