RT for Patients with Compressed Air Tissue Expanders: Treatment Planning Solutions and Limitations

Document Type

Conference Proceeding

Publication Date


Publication Title

Int J Radiat Oncol Biol Phys


Purpose/Objective(s): Compressed air tissue expanders (CATEs) consist of a silicon shell containing a metallic CO2 reservoir, surgically placed in the chest wall post-mastectomy. CATEs pose significant challenges for RT: The high density reservoir causes artifacts on the planning CT, which encumber structure definition and cause misrepresentation of density information, in turn affecting dose calculation. This study describes a method to model the CATE in a commercial treatment planning system (TPS), and discusses the limitations of different dose calculation algorithms (DCAs) in and around the device. An understanding of DCA accuracy near the CATE is critical for assessing individual plan quality, appropriateness of DCA and planning technique, and even the decision to use a CATE in an RT setting. Materials/Methods: A CATE model was created in a commercial TPS. The CATE was imaged using optimal CT geometry and technique. Individual components were contoured and dimensions were verified against manufacturer specifications. The model was available for registration with a patient CT in the TPS. Assigned densities of the model were optimized by comparing measured and calculated transmission through the CATE. Transmission was measured with radiochromic film in various geometries. Dose was calculated using two commercially available DCAs: a convolution-based algorithm (CBA) and an explicit linear Boltzman transport equation solver algorithm (LBTEA). Doses were compared using profile and gamma analyses. Clinical impact was evaluated using CT data from 3 patients with CATEs. The CATE model was registered to each patient CT, and 3DRT plans were calculated using both DCAs. Clinically significant DVHs were analyzed. Results: For direct transmission through the CATE, both DCAs achieved greater than 99% gamma pass rate. However, for the region 0-1 cm adjacent to the CATE, gamma pass rate was greater than 98% for the LBTEA, but near 0% for the CBA. Compared to the LBTEA, the CBA overestimated mean dose in the CO2 reservoir and the air cavity by 5-7% and 10-13%, respectively. The CBA underestimated mean dose in the reservoir’s dose shadow and the adjacent chest wall by 0.5-5%. Changes in max dose were more variable and patient-specific. Conclusion: Approaching a CATE in an RT setting, clinicians must first obtain accurate patient density information. The CATE model described here is one practical method. Second, clinicians must understand the accuracy of their DCA near the CATE to evaluate plan quality. This work suggests that both the CBA and LBTEA accurately predicted beam transmission through the CATE, but the CBA overestimates dose within 1 cm lateral of the CATE. Finally, clinicians must decide if and how an acceptable plan can be delivered with the CATE in place. The decrease in target coverage due to attenuation by the CATE may require optimization techniques (such as field-in-field). These techniques should be used with careful consideration of the DCA’s uncertainty.





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