|Publisher DOI:||10.1007/s11548-022-02664-6||Title:||AI-based optimization for US-guided radiation therapy of the prostate||Language:||English||Authors:||Gerlach, Stefan
|Keywords:||Convolutional neural network; Heuristic optimization; Robotic ultrasound; Simulated annealing; Treatment planning||Issue Date:||20-May-2022||Publisher:||Springer||Source:||International Journal of Computer Assisted Radiology and Surgery 17 (11): 2023-2032 (2022-11)||Abstract (english):||
Objectives: Fast volumetric ultrasound presents an interesting modality for continuous and real-time intra-fractional target tracking in radiation therapy of lesions in the abdomen. However, the placement of the ultrasound probe close to the target structures leads to blocking some beam directions.
Methods: To handle the combinatorial complexity of searching for the ultrasound-robot pose and the subset of optimal treatment beams, we combine CNN-based candidate beam selection with simulated annealing for setup optimization of the ultrasound robot, and linear optimization for treatment plan optimization into an AI-based approach. For 50 prostate cases previously treated with the CyberKnife, we study setup and treatment plan optimization when including robotic ultrasound guidance.
Results: The CNN-based search substantially outperforms previous randomized heuristics, increasing coverage from 93.66 to 97.20% on average. Moreover, in some cases the total MU was also reduced, particularly for smaller target volumes. Results after AI-based optimization are similar for treatment plans with and without beam blocking due to ultrasound guidance.
Conclusions: AI-based optimization allows for fast and effective search for configurations for robotic ultrasound-guided radiation therapy. The negative impact of the ultrasound robot on the plan quality can successfully be mitigated resulting only in minor differences.
|URI:||http://hdl.handle.net/11420/12765||DOI:||10.15480/882.4636||ISSN:||1861-6429||Journal:||Institute:||Medizintechnische und Intelligente Systeme E-1||Document Type:||Article||Project:||Robotisierte Ultraschall-gestützte Bildgebung zur Echtzeit-Bewegungskompensation in der Strahlentherapie (RobUST), Phase II
|License:||CC BY 4.0 (Attribution)|
|Appears in Collections:||Publications with fulltext|
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