AIMC Topic: Radiometry

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Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based three-dimensional convolutional neural network.

Medical physics
PURPOSE: To develop and evaluate a patch-based convolutional neural network (CNN) to generate synthetic computed tomography (sCT) images for magnetic resonance (MR)-only workflow for radiotherapy of head and neck tumors. A patch-based deep learning m...

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

European radiology
OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated constru...

Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.

Physics in medicine and biology
An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and quality. Recently machine learning techniques have been proposed for IMRT dose prediction based on pati...

Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics.

European radiology
PURPOSE: To investigate the treatment response prediction feasibility and accuracy of an integrated model combining computed tomography (CT) radiomic features and dosimetric parameters for patients with esophageal cancer (EC) who underwent concurrent...

Stochastic frontier analysis as knowledge-based model to improve sparing of organs-at-risk for VMAT-treated prostate cancer.

Physics in medicine and biology
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...

Dosimetric study on learning-based cone-beam CT correction in adaptive radiation therapy.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
INTRODUCTION: Cone-beam CT (CBCT) image quality is important for its quantitative analysis in adaptive radiation therapy. However, due to severe artifacts, the CBCTs are primarily used for verifying patient setup only so far. We have developed a lear...

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...

Automated Triage Radiation Biodosimetry: Integrating Imaging Flow Cytometry with High-Throughput Robotics to Perform the Cytokinesis-Block Micronucleus Assay.

Radiation research
The cytokinesis-block micronucleus (CBMN) assay has become a fully-validated and standardized method for radiation biodosimetry. The assay is typically performed using microscopy, which is labor intensive, time consuming and impractical after a large...

Dosimetric features-driven machine learning model for DVH prediction in VMAT treatment planning.

Medical physics
PURPOSE: Few features characterizing the dosimetric properties of the patients are included in currently available dose-volume histogram (DVH) prediction models, making it intractable to build a correlative relationship between the input and output p...

Multi-Institutional Validation of a Knowledge-Based Planning Model for Patients Enrolled in RTOG 0617: Implications for Plan Quality Controls in Cooperative Group Trials.

Practical radiation oncology
PURPOSE: This study aimed to evaluate the feasibility of using a single-institution, knowledge-based planning (KBP) model as a dosimetric plan quality control (QC) for multi-institutional clinical trials. The efficacy of this QC tool was retrospectiv...