Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 11, 2019
PURPOSE: This study assessed the dosimetric accuracy of synthetic CT images generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy, using a deep learning approach.
Stochastic frontier analysis (SFA) is used as a novel knowledge-based technique in order to develop a predictive model of dosimetric features from significant geometric parameters describing a patient morphology. 406 patients treated with VMAT for pr...
The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the target. Tr...
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...
PURPOSE: Knowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority o...
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 ...
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...
With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would alleviate thi...
OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate canc...