ArticleInternational journal of computer assisted radiology and surgery2019
Analysis and optimization of the robot setup for robotic-ultrasound-guided radiation therapy.
Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- AI-based optimization for US-guided radiation therapy of the prostate.International journal of computer assisted radiology and surgery · 2022Article
- Systematic analysis of volumetric ultrasound parameters for markerless 4D motion tracking.International journal of computer assisted radiology and surgery · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
purposeRobotic ultrasound promises continuous, volumetric, and non-ionizing tracking of organ motion during radiation therapy. However, placement of the robot is critical because it is radio-opaque and might severely influence the achievable dose distribution.
methodsWe propose two heuristic optimization strategies for automatic placement of an ultrasound robot around a patient. Considering a kinematically redundant robot arm, we compare a generic approach based on stochastic search and a more problem-specific segmentwise construction approach. The former allows for multiple elbow configurations while the latter is deterministic. Additionally, we study different objective functions guiding the search. Our evaluation is based on data for ten actual prostate cancer cases and we compare the resulting plan quality for both methods to manually chosen robot configurations previously proposed.
resultsThe mean improvements in the treatment planning objective value with respect to the best manually selected robot position and a single elbow configuration range from 8.2 to 32.8% and 8.5 to 15.5% for segmentwise construction and stochastic search, respectively. Considering three different elbow configurations, the stochastic search results in better objective values in 80% of the cases, with 30% being significantly better. The optimization strategies are robust with respect to beam sampling and transducer orientation and using previous optimization results as starting point for stochastic search typically results in better solutions compared to random starting points.
conclusionWe propose a robust and generic optimization scheme, which can be used to optimize the robot placement for robotic ultrasound guidance in radiation therapy. The automatic optimization further mitigates the impact of robotic ultrasound on the treatment plan quality.
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