AI-based optimization for US-guided radiation therapy of the prostate

Link:
Autor/in:
Verlag/Körperschaft:
Hamburg University of Technology
Erscheinungsjahr:
2022
Medientyp:
Text
Schlagworte:
  • Convolutional neural network
  • Heuristic optimization
  • Robotic ultrasound
  • Simulated annealing
  • Treatment planning
  • 004: Informatik
  • 600: Technik
  • 610: Medizin
Beschreibung:
  • 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.
Beziehungen:
DOI 10.1007/s11548-022-02664-6
Lizenzen:
  • info:eu-repo/semantics/openAccess
  • https://creativecommons.org/licenses/by/4.0/
Quellsystem:
TUHH Open Research

Interne Metadaten
Quelldatensatz
oai:tore.tuhh.de:11420/12765