An inverse planning simulated annealing algorithm with adaptive weight adjustment for LDR pancreatic brachytherapy

The inverse planning simulated annealing (IPSA) algorithm has shown good results in cancer surgical treatment planning. However, an adaptive approach has not well been proposed for different shapes and sizes of tumors. The purpose of this study was to propose an adaptive, efficient and safe algorithm to get high-quality treatment dose planning, which is presented for pancreatic cancer.

An algorithm employs an optimized IPSA and an adaptive process for adjusting the weight of organs at risk (OAR) and tumor. The algorithm, which was combined with ant colony optimization, was further optimized to reduce the number of needles. It could meet the clinical dose objectives within the tumors, reduce the dose distribution within the OAR and minimize the number of needles. Ten clinical cases were chosen randomly from patients, previously successfully treated in clinic to test our method. The algorithm was validated against clinical cases, using clinically relevant dose parameters.

The results were compared with clinical results in ten cases, indicating that the dose distribution within the tumor meets the clinical dose objectives. The dose received by OAR had been greatly reduced, and the number of needles could be reduced by about 50%. It was a significant improvement over the clinical treatment planning.

In this paper, we have devised an algorithm to optimize the treatment planning in brachytherapy. The method in this paper could meet the clinical dose objectives and reduce the difficulty of operation. The results were clinically acceptable. This algorithm is also applicable to other cancers such as lung cancer.