Intensity modulated radiotherapy using Monte Carlo for routine postmastectomy radiotherapy

Radiotherapy given after mastectomy (PMRT) will reduce the risk of local recurrence by about two-thirds. Clinical and dosimetric trials were carried out using various techniques to optimize the treatments by maximizing the dose to the tumour and minimizing it to the healthy tissues at proximity. Different conventional techniques which have been studied suffer from important dose inhomogeneities due to the complex anatomy of the chest, which reduces the benefits from such treatments. Moreover, due to the heterogeneity of breast cancer, the response to therapy and a systematic approach to treatment cannot be derived and treatment regimens must be determined on a patient-by-patient basis. This is only possible if accurate and fast treatment planning systems are available. Intensity Modulated Radiotherapy (IMRT) allows delivering higher doses to the target volume and limits the doses to the surrounding tissues. The objective of this study is to test the feasibility of applying a Monte Carlo-based treatment planning system, Hyperion accurately in routine Intensity Modulated Radiotherapy (IMRT) postmastectomy. In order to use a treatment planning system for routine work it should prove to provide optimized dose delivery in a suitable time. Treatment planning for IMRT application to PMRT was performed using Hyperion. Constraints were set to deliver the prescribed dose to the target and minimize the dose to the organs at risk. Dose Volume Histograms (DVH) were used to evaluate the set up plans. Time taken to optimize the plan was measured. The target coverage was within the accepted values. Approximately 90% of the breast and 80% of the PTV received 45 Gy or above. The volume of the lung that received 40Gy was less than 10% and the volume that received 20Gy (V20) was less than 25%. The volume of the heart receiving 30 Gy (V30) or above was negligible. This indicates low NTCP of these organs. The time taken for optimization, showed it possible to apply Monte Carlo-based treatment-planning systems for patient-to-patient PMRT.