A cardiac motion model to evaluate intra-fraction dosimetric variations in radiotherapy treatments

Purpose: A cardiac cycle model was implemented to simulate cardiac motion during radiotherapy to evaluate the intra-fraction dosimetric impact on cardiac sub-structures comparing different planning techniques. Methods: Cardiac sub-structures were automatically contoured in 10 CTs acquired in deep inspiration breath hold (DIBH) by using a recently developed hierarchical-clustering atlas-based algorithm. A deformable image registration algorithm was used to simulate the cardiac motion cycle based on volume variations available in the literature. Two synthetic CTs were created and contoured simulating contraction and expansion during the cardiac cycle. Ninety radiotherapy plans were calculated using three radiotherapy paradigms: tangential fields planned as Linac-3D-CRT with a steep linear dose gradient toward the heart-modulated therapy with an intermediately steep concave gradient of intermediate-to-high doses toward the heart, planned as Linac-VMAT; modulated therapy with a steep concave gradient of intermediate-to-high doses toward the heart, planned as helical tomotherapy. Python scripts were developed for autocontouring, automatic creation of synthetic CTs and data extraction. Results: Comparison between paradigms shows that different constraints (maximal gradient toward heart/lung versus maximal sparing of contralateral breast/axilla) do not necessarily result in preferred or reduced heart sparing, but this depends more on individual anatomy. A planning paradigm with an intermediate-steepness dose gradient showed the best robustness against intra-fraction organ motion. Conclusions: Patient-specific organ motion models may reduce differences between planned and delivered RT and may thus help to refine dose-volume-toxicity models for cardiac sub-structures and, as a consequence, clinical constraints. Automatized plan recalculation on synthetic image sets might be used for robustness optimization and evaluation.