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Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
15.6K
Fully automated treatment planning for MLC-based robotic radiotherapy
Bastiaan W K Schipaanboord1, Marta K Giżyńska1, Linda Rossi1
1Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, Zuid Holland, 3015GD, The Netherlands.
Medical Physics
|May 26, 2021
Summary
A new automated CyberKnife® treatment planning system significantly reduces treatment times by decreasing beam and segment numbers. This automated solution offers clinically acceptable plans comparable to manual methods, improving efficiency for prostate SBRT.
Area of Science:
- Medical Physics
- Radiation Oncology
- Medical Imaging and Imaging Devices
Background:
- CyberKnife® stereotactic radiosurgery utilizes advanced treatment planning for precise radiation delivery.
- Manual treatment planning is time-consuming and can be subject to inter-observer variability.
- Optimizing beam arrangement and segment delivery is crucial for improving treatment efficiency and patient comfort.
Purpose of the Study:
- To develop and validate a fully automated, multicriterial treatment planning solution for CyberKnife® with an InCise™ 2 multileaf collimator.
- To integrate automated beam angle optimization (BAO) with multicriterial optimization (MCO) for efficient plan generation.
- To compare the automated planning system's performance against manually generated plans.
Main Methods:
- Developed in-house algorithms for automated prioritized multicriterial optimization (AUTO MCO) and MLC segment generation.
- Implemented noncoplanar beam angle optimization (BAO) within the AUTO MCO framework.
- Validated the automated system (AUTO BAO) on 33 prostate SBRT patients, comparing against manually created reference plans (REF) and auto-optimized beam angle plans (AUTO RB).
Main Results:
- AUTO BAO plans were clinically acceptable and dosimetrically similar to REF plans.
- AUTO BAO significantly reduced the number of beams (49%) and segments (40%), leading to a 23% decrease in delivery time.
- AUTO RB also showed reduced beam usage and delivery times compared to REF, with similar dosimetry across all approaches.
Conclusions:
- A novel, vendor-independent workflow for fully automated CyberKnife® plan generation, including BAO, has been successfully developed.
- The automated system substantially reduces fraction delivery times compared to manual planning.
- This automated approach enhances efficiency in radiation oncology by optimizing beam and segment parameters.
