Abstract
BackgroundMonte Carlo simulations were run to estimate the dose variations generated by thedifference arising from the chemical composition of the tissues.MethodsCT datasets of five breast cancer patients were selected. Mammary gland was delineated as clinical target volume CTV, as well as CTV_lob and CTV_fat, being the lobular and fat fractions of the entire mammary gland. Patients were planned for volumetric modulated arc therapy technique, optimized in the Varian Eclipse treatment planning system. CT, structures and plans were imported in PRIMO, based on Monte Carlo code Penelope, to run three simulations: AdiMus, where the adipose and muscle tissues were automatically assigned to fat and lobular fractions of the breast; Adi and Mus, where adipose and muscle, respectively were assigned to the whole mammary gland. The specific tissue density was kept identical from the CT dataset. Differences in mean doses in the CTV_lob and CTV_fat structures were evaluated for the different tissue assignments. Differences generated by the tissue composition and estimated by Acuros dose calculations in Eclipse were also analysed.ResultsFrom Monte Carlo simulations, the dose in the lobular fraction of the breast, when adipose tissue is assigned in place of muscle, is overestimated by 1.25 ± 0.45%; the dose in the fat fraction of the breast with muscle tissue assignment is underestimated by 1.14 ± 0.51%. Acuros showed an overestimation of 0.98 ± 0.06% and an underestimation of 0.21 ± 0.14% in the lobular and fat portions, respectively. Reason of this dissimilarity resides in the fact that the two calculations, Monte Carlo and Acuros, differently manage the range of CT numbers and the material assignments, having Acuros an overlapping range, where two tissues are both present in defined proportions.ConclusionAlthough not clinically significant, the dose deposition difference in the lobular and connective fat fraction of the breast tissue lead to an improved knowledge of the possible dose distribution and homogeneity in the breast radiation treatment.
Highlights
Monte Carlo simulations were run to estimate the dose variations generated by thedifference arising from the chemical composition of the tissues
In 2015, Mak et al [8] in a study on 280 patients reported that the breast tissue treated to more than 105 and 110% of the prescribed doses were found to be predictors of long term breast pain on univariate analysis, with the V110% remaining significant in a multivariate analysis with an odds ratio 1.01 per cm3, p = 0.007
Acuros calculations Concerning the clinical use of tissue differentiation in Acuros, the results showed a dose overestimation of the algorithm for intermediate dose estimation (AAA) in the lobular portion of breast of 0.98 ± 0.06%, and an underestimation of 0.21 ± 0.14% in the fat portion
Summary
Monte Carlo simulations were run to estimate the dose variations generated by thedifference arising from the chemical composition of the tissues. Breast cancer is one of the most spread cancer diseases, treated with different modalities. The radiation treatment might increase the toxicity, cutaneous, cardiac and pulmonary, reducing the quality of life of the patients [2]. The statistical significance of the Vicini et al data, based on only 95 patients, suggested the importance of keeping the dose homogeneity in the breast as good as possible. In 2015, Mak et al [8] in a study on 280 patients reported that the breast tissue treated to more than 105 and 110% of the prescribed doses were found to be predictors of long term breast pain on univariate analysis, with the V110% remaining significant in a multivariate analysis with an odds ratio 1.01 per cm, p = 0.007
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