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  • >New Algorithms and Software for Treatment Planning Problems in Intensity Modulated Radiation Therapy

New Algorithms and Software for Treatment Planning Problems in Intensity Modulated Radiation Therapy

March 9, 2004

Date: Tuesday, March 9th, 2004
Time: 11am-12:15pm
Location: Woodward 149

Shuang (Sean) Luan, <sluan@cse.nd.edu>
Department of Computer Science and Engineering University of Notre Dame

Abstract: Computer-assisted radiotherapy is an emerging interdisciplinary area that applies the state-of-the-art computing technologies to help the diagnosis, design, optimization, and operation of modern radiation therapy. In this talk, we present some interesting problems and their solutions in this exciting area. Intensity-modulated radiation therapy (IMRT) is a modern cancer treatment technique, aiming to deliver a highly conformal dose to a target tumor while sparing the surrounding normal tissues and critical structures. A key to performing IMRT is the accurate and efficient delivery of discrete dose distributions using the linear accelerator and the multileaf collimator. The leaf sequencing problems arise in such scenarios, whose goal is to compute a treatment plan that delivers the given dose distributions in the minimum amount of time. Existing leaf sequencing algorithms, both in commercial planning systems and in medical literature are all heuristics and do not guarantee any good quality of the computed treatment plans, which in many cases result in prolonged delivery time and compromised treatment quality. In this talk, we present some new MLC leaf sequencing algorithms and software. Our new algorithms, based on a novel unified approach and geometric optimization techniques, are very efficient and guarantee the optimal quality of the output treatment plans. Our ideas include formulating the leaf sequencing problems as computing shortest paths in a weighted directed acyclic graph and building the graph by computing optimal bipartite matchings on various geometric objects. Our new IMRT algorithms run very fast on real medical data (in only few minutes). Comparisons between our software with commercial planning systems and the current most well known leaf sequencing algorithm in medical literature showed substantial improvement. The treatment plan computed by our software not only takes much less delivery times (up to 75% less) but also has much better treatment quality. Our software has already been used for treating cancer patients at a couple of medical centers.