ESTRO 2024 - Abstract Book

S4314

Physics - Intra-fraction motion management and real-time adaptive radiotherapy

ESTRO 2024

Keywords: Organ-at-risk, Deep learning, Markerless tracking

References:

1. Toshiyuki T et al. Explainability and controllability of patient-specific deep learning with attention-based augmentation for markerless image-guided radiotherapy , Medical Physics, 2022, 480-494, DOI: 10.1002/mp.16095

2. Phillip I et al. Image-to-Image Translation with Conditional Adversarial Networks , arXiv Computer Vision and Pattern Recognition, 2016. DOI: https://doi.org/10.48550/arXiv.1611.07004

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Sensitivity and imaging dose of two intrafraction prostate motion monitoring approaches

Sankar Arumugam

Liverpool Hospital, Cancer Therapy Centre, Sydney, Australia. Ingham Institute, Department of Medical Physics, Sydney, Australia. University of New South Wales, Clinical Scholl, Sydney, Australia

Purpose/Objective:

Prostate motion during radiotherapy can compromise treatment accuracy, potentially reducing the tumour dose and increasing the dose to critical structures. Elekta linear accelerators, equipped with the XVI imaging system and intrafraction Cone Beam Computed Tomography (IFCBCT), offer the potential to correct intrafraction motion and improve the accuracy of treatment plans with multiple VMAT arcs. We have developed SeedTracker 1,2 , a real-time position monitoring system that works in conjunction with the XVI system, enabling real-time monitoring of prostate motion using intraprostatic fiducials. This study aims to investigate the sensitivity of IFCBCT and SeedTracker-based strategies for detecting intrafraction prostate motion and compare the resulting imaging dose from both approaches.

Material/Methods:

An in-house-developed phantom implanted with three gold fiducial markers was utilized for this study. Static and dynamic intrafraction motion occurring at different time points during treatment delivery was introduced to the phantom using a programmable robotic arm. The type, magnitude, and timing of the position offsets introduced to the phantom during treatment delivery are detailed in Table 1. The IFCBCT images acquired during treatment were registered to the reference planning CT data using the Seed auto-registration feature available in XVI. Projection images obtained during IFCBCT acquisition were monitored in real-time by SeedTracker to detect the occurrence of intrafraction motion.

Table1: Static and Dynamic offsets introduced to the phantom.