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Applications of signal processing to conformal radiation therapy dose optimization

The delivery of the proper dose of radiation to a tumor volume without causing irreparable damage to healthy tissue and critical organs is paramount in radiation therapy. With the development of the multi-leaf collimator (MLC) a new type of conformal radiation therapy, known as intensity modulated radiation therapy (IMRT), was developed and deployed in a number of clinics around the world. The inverse optimization parallelism to the solution is the approach taken in IMRT and in this paper, where the optimality is based on the minimization of a cost function depending on the difference between the prescribed and the delivered dose. Until recently, Bayesian techniques have been used to solve this problem. Here we investigate and implement two new cost functions frequently used in signal processing community as part of the dose optimization. A simulation model was developed and tested using both phantom data and CT scan results from two patients with encouraging results.