Daily imaging during the course of a fractionated radiotherapy treatment has the potential for frequent intervention and therefore effective adaptation of the treatment to the individual patient. The treatment information gained from such images can be analysed and updated daily to obtain a set of patient individualized parameters. However, in many situations, the uncertainty with which these parameters are estimated cannot be neglected. In this work this methodology is applied to the adaptive estimation of setup errors, the derivation of a daily optimal pre-treatment correction strategy, and the daily update of the treatment margins after application of these corrections. For this purpose a dataset of 19 prostate cancer patients was analysed retrospectively. The position of the prostate was measured daily with an optically guided 3D ultrasound localization system. The measurement uncertainty of this system is approximately 2 mm. The algorithm finds the most likely position of the target maximizing an a posteriori probability given the set of measurements. These estimates are used for the optimal corrections applied to the target volume. The results show that the application of the optimal correction strategy allows a reduction in the treatment margins in a systematic way with increasing progression of the treatment. This is not the case using corrections based only on the measured values that do not take the measurement uncertainty into account.
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging