AIMC Topic: Radiotherapy Planning, Computer-Assisted

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Deep nets vs expert designed features in medical physics: An IMRT QA case study.

Medical physics
PURPOSE: The purpose of this study was to compare the performance of Deep Neural Networks against a technique designed by domain experts in the prediction of gamma passing rates for Intensity Modulated Radiation Therapy Quality Assurance (IMRT QA).

Creation of knowledge-based planning models intended for large scale distribution: Minimizing the effect of outlier plans.

Journal of applied clinical medical physics
Knowledge-based planning (KBP) can be used to estimate dose-volume histograms (DVHs) of organs at risk (OAR) using models. The task of model creation, however, can result in estimates with differing accuracy; particularly when outlier plans are not p...

Functional-guided radiotherapy using knowledge-based planning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring co...

Fully automated searching for the optimal VMAT jaw settings based on Eclipse Scripting Application Programming Interface (ESAPI) and RapidPlan knowledge-based planning.

Journal of applied clinical medical physics
PURPOSE: Eclipse treatment planning system has not been able to optimize the jaw positions for Volumetric Modulated Arc Therapy (VMAT). The arbitrary and planner-dependent jaw placements define the maximum field size within which multi-leaf-collimato...

A machine learning approach to the accurate prediction of monitor units for a compact proton machine.

Medical physics
PURPOSE: Clinical treatment planning systems for proton therapy currently do not calculate monitor units (MUs) in passive scatter proton therapy due to the complexity of the beam delivery systems. Physical phantom measurements are commonly employed t...

Impact of database quality in knowledge-based treatment planning for prostate cancer.

Practical radiation oncology
PURPOSE: This article investigates dose-volume prediction improvements in a common knowledge-based planning (KBP) method using a Pareto plan database compared with using a conventional, clinical plan database.

Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology.

PloS one
PURPOSE: Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great potential to generate hypotheses for cancer treatment, since they directly provide medical data on a large scale. In order to gather a significant am...

A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy.

Physics in medicine and biology
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendo...

Chest wall dose reduction using noncoplanar volumetric modulated arc radiation therapy for lung stereotactic ablative radiation therapy.

Practical radiation oncology
PURPOSE: Stereotactic ablative radiation therapy (SABR) to lung tumors close to the chest wall can cause rib fractures or chest wall pain. We evaluated and propose a clinically practical solution of using noncoplanar volumetric modulated arc radiatio...

A method to combine target volume data from 3D and 4D planned thoracic radiotherapy patient cohorts for machine learning applications.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV)....