eXaSkin: A novel high-density bolus for 6MV X-rays radiotherapy

RIS ID

146083

Publication Details

Al-sudani, T., Biasi, G., Wilkinson, D., Davis, J., Kearnan, R., Matar, F., Cutajar, D., Metcalfe, P. & Rozenfeld, A. (2020). eXaSkin: A novel high-density bolus for 6MV X-rays radiotherapy. Physica Medica, 80 42-46.

Abstract

© 2020 Associazione Italiana di Fisica Medica Purpose: To evaluate eXaSkin, a novel high-density bolus alternative to commercial tissue-equivalent Superflab, for 6MV photon-beam radiotherapy. Materials and methods: We delivered a 10 × 10 cm2 open field at 90° and head-and-neck clinical plan, generated with the volumetric modulated arc therapy (VMAT) technique, to an anthropomorphic phantom in three scenarios: with no bolus on the phantom's surface, with Superflab, and with eXaSkin. In each scenario, we measured dose to a central planning target volume (PTV) in the nasopharynx region with an ionization chamber, and we measured dose to the skin, at three different positions within the vicinity of a neck lymph node PTV, with MOSkin™, a semiconductor dosimeter. Measurements were compared against calculations with the treatment planning system (TPS). Results: For the static field, MOSkin results underneath the eXaSkin were in agreement with calculations to within 1.22%; for VMAT, to within 5.68%. Underneath Superflab, those values were 3.36% and 11.66%. The inferior agreement can be explained by suboptimal adherence of Superflab to the phantom's surface as well as difficulties in accurately reproducing its placement between imaging and treatment session. In all scenarios, dose measured at the central target agreed to within 1% with calculations. Conclusions: eXaSkin was shown to have superior adaptation to the phantom's surface, producing minimal air gaps between the skin surface and bolus, allowing for accurate positioning and reproducibility of set-up conditions. eXaSkin with its high density material provides sufficient build-up to achieve full skin dose with less material thickness than Superflab.

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Link to publisher version (DOI)

http://dx.doi.org/10.1016/j.ejmp.2020.09.002