Poster Poster Program Therapy Physics

BLUE RIBBON POSTER MULTI-DISCIPLINARY: Develop and Evaluate a Fast 5D Dosimetry Estimation Algorithm for Stereotactic Arrhythmia Radioablation Treatments

Abstract
Purpose

It was critical yet impossible to quantitatively assess the impact of patient-specific cardiorespiratory motion on dose plans for stereotactic arrhythmia radioablation (STAR) treatments. To fill the gap, a fast algorithm, SPM (spatial probability map), was developed for assessing 5D motion (3D + cardiac + respiration) effects for STAR treatment targets at the treatment planning stage.

Methods

The 5D dosimetry procedure used the treatment planning CT, structures, dose volume, respiratory 4DCTs (r4DCT), and breath-hold cardiac 4DCTs (c4DCT) of the patient: 1) remove ICD metal artifacts in r4DCT and c4DCT using in-house AI models; 2) compute cardiac and respiratory 4D motions separately in r4DCTs and c4DCTs using deformable image registration, and joining two 4D motions into 5D; 3) (the new SPM algorithm) compute the 5D dose directly using the treatment plan dose volume and the 5D motion field. For evaluating SPM, we also implemented the traditional 5D dosimetry method, which recomputed the treatment plan doses on 100 5DCT phases (10 cardiac × 10 respiratory phases) and averaged them in the planning anatomy.

Results

5D dosimetry was computed for three patient cases. The necessity of 5D dosimetry was confirmed as 5D dosimetry metrics (Dmax, Dmean, Dmin, D95, V35Gy) for STAR targets being significantly different (2% to 14%) from the treatment planning. SPM results were statistically no different from the traditional 5D dosimetry results (4 hours with the traditional method using Eclipse TPS for each case.

Conclusion

Compared to the traditional 5D dosimetry procedure, the SPM algorithm skips 5DCT generation and dose calculation on every 5DCT phase, saving hours of manual effort while retaining calculation accuracy. While clinical treatment plans are optimized on static planning CTs, SPM makes it feasible to estimate how patient-specific cardiorespiratory motion affects treatment delivery.

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