Potential of hybrid computational phantoms for retrospective heart dosimetry after breast radiation therapy A feasibility study

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Moignier, A. | Derreumaux, S. | Broggio, David | Beurrier, J. | Chea, M. | Boisserie, G. | Franck, D. | Aubert, B. | Mazeron, J.-J.

Edité par CCSD ; Elsevier -

International audience. Purpose Current retrospective cardiovascular dosimetry studies are based on a representative patient or simple mathematic phantoms. Here, a process of patient modeling was developed to personalize the anatomy of the thorax and to include a heart model with coronary arteries. Methods and Materials The patient models were hybrid computational phantoms (HCPs) with an inserted detailed heart model. A computed tomography (CT) acquisition (pseudo-CT) was derived from HCP and imported into a treatment planning system where treatment conditions were reproduced. Six current patients were selected 3 were modeled from their CT images (A patients) and the others were modelled from 2 orthogonal radiographs (B patients). The method performance and limitation were investigated by quantitative comparison between the initial CT and the pseudo-CT, namely, the morphology and the dose calculation were compared. For the B patients, a comparison with 2 kinds of representative patients was also conducted. Finally, dose assessment was focused on the whole coronary artery tree and the left anterior descending coronary. Results When 3-dimensional anatomic information was available, the dose calculations performed on the initial CT and the pseudo-CT were in good agreement. For the B patients, comparison of doses derived from HCP and representative patients showed that the HCP doses were either better or equivalent. In the left breast radiation therapy context and for the studied cases, coronary mean doses were at least 5-fold higher than heart mean doses. Conclusions For retrospective dose studies, it is suggested that HCP offers a better surrogate, in terms of dose accuracy, than representative patients. The use of a detailed heart model eliminates the problem of identifying the coronaries on the patient's CT. © 2013 Elsevier Inc. All rights reserved.

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