ESTRO meets Asia 2024 - Abstract Book

S333

Physics – Motion management and adaptive radiotherapy

ESTRO meets Asia 2024

At a patient level, large target displacements and treatment pauses have been automatically identified and investigated alongside acquired radiographs, to establish, for example, that the cause of a shift in prostate position was due to patient gas. The software produces plots of patient-specific target motion data for user interpretation (e.g., Figure 1).

Figure 1. Motion data for initial 10 fractions of an example prostate patient, with pauses in treatment indicated by vertical grey lines.

At a cohort level, histograms of target motion (e.g., Figure 2) have been used locally in the evaluation of margins for both Synchrony and non-Synchrony treatments, by combinations of calculated uncertainties [1] and robust dose calculation approaches.

Figure 2. Histogram of prostate fiducial centre-of-mass displacement across approximately 16000 radiographic images, including 95 th percentile of observed displacements (r 95 ).

Statistical process control charts have been used to establish baselines and tolerance limits for performance measures, such as rigid body difference values describing the deformation of fiducials relative to planning simulation.

Conclusion:

The substantial amount of data provided by the Synchony platform, paired with the in-house data extraction and analysis code enables potential research into questions of margin reduction, investigations of relationships between patient variables and motion characteristics, treatment plan parameters (such as gantry speed) and motion adaptation performance, and other topics. It will support quantitative evaluation of the impact of future