AN ITERATIVE FILTERED BACKPROJECTION INVERSE TREATMENT PLANNING ALGORITHM FOR TOMOTHERAPY

Purpose: An inverse treatment planning algorithm for tomotherapy is de scribed.Methods and Materials: The algorithm iteratively computes a se t of nonnegative beam intensity profiles that minimizes the least-squa res residual dose defined in the target and selected normal tissue reg ions of interest, At each iteration the residual dose distribution is transformed into a set of residual beam profiles using an inversion me thod derived from filtered backprojection image reconstruction theory, These ''residual'' profiles are used to correct the current beam prof ile estimates resulting in new profile estimates, Adaptive filtering i s incorporated into the inversion model so that the gross structure of the dose distribution is optimized during initial iterations of the a lgorithm, and the fine structure corresponding to edges is obtained at later iterations, A three dimensional, kernel based, convolution/supe rposition dose model is used to compute dose during each iteration. Re sults: Two clinically relevant treatment planning examples are present ed illustrating the use of the algorithm for planning conformal radiot herapy of the breast and the prostate. Solutions are generally achieve d in 10-20 iterations requiring about 20 h of CPU time using a midrang e workstation, The majority of the calculation time is spent on the th ree-dimensional dose calculation. Conclusions: The inverse treatment p lanning algorithm is a useful research tool for exploring the potentia l of tomotherapy for conformal radiotherapy, Further work is needed to (a) achieve clinically acceptable computation times; (b) verify the a lgorithm using multileaf collimator technology; and (c) extend the met hod to biological objectives.