Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.4636
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  
Hofmann, Theresa 
Fürweger, Christoph 
Schlaefer, Alexander 
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 
Projekt DEAL 
License: CC BY 4.0 (Attribution) CC BY 4.0 (Attribution)
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