Aperture-based inverse planning (ABIP) for intensity modulated radiation therapy (IMRT) treatment planning starts with external radiation fields (beams) that fully conform to the target(s) and then superimposes sub-fields called segments to achieve complex shaping of 3D dose distributions. The segments' intensities are determined by solving a feasibility problem. The least-intensity feasible (LIF) solution, proposed and studied here, seeks a feasible solution closest to the origin, thus being of least intensity or least energy. We present a new iterative, primal-dual, algorithm for finding the LIF solution and explain our experimental observation that Cimmino's algorithm for feasibility actually converges to a close approximation of the LIF solution. Comparison with linear programming shows that Cimmino's algorithm has the additional advantage of generating much smoother solutions.
Bibliographical noteFunding Information:
We are indebted to two anonymous referees whose comments and suggestions helped us to improve the first version of this paper. The results presented here were announced at the 43rd Annual Meeting of the American Association of Physicists in Medicine (AAPM), July 2001, Salt Lake City, Utah, USA. This work was supported in part by Elekta Oncology Systems Inc. The work of Y. Censor was supported by research grant 592/00 from the Israel Science Foundation founded by the Israel Academy of Sciences and Humanities.
ASJC Scopus subject areas
- Decision Sciences (all)
- Management Science and Operations Research