IMRT Optimization with Both Fractionation and Cumulative Constraints

Radiation therapy plans are optimized as a single treatment plan, but delivered over 30 - 50 treatment sessions (known as fractions). This paper proposes a new mixed-integer linear programming model to simultaneously incorporate fractionation and cumulative constraints in Intensity Modulated Radiation Therapy (IMRT) planning optimization used in cancer treatment. The method is compared against a standard practice of posing only cumulative limits in the optimization. In a prostate case, incorporating both forms of limits into planning converted an undeliverable plan obtained by considering only the cumulative limits into a deliverable one within 3% of the value obtained by ignoring the fraction size limits. A two-phase boosting strategy is studied as well, where the first phase aims to radiate primary and secondary targets simultaneously, and the second phase aims to escalate the tumor dose. Using of the simultaneous strategy on both phases, the dose difference between the primary and secondary targets was enhanced, with better sparing of the rectum and bladder.

[1]  S. Webb Optimization by simulated annealing of three-dimensional conformal treatment planning for radiation fields defined by a multileaf collimator. , 1991, Physics in medicine and biology.

[2]  R Mohan,et al.  Algorithms and functionality of an intensity modulated radiotherapy optimization system. , 2000, Medical physics.

[3]  Jian Z. Wang,et al.  Dosimetric advantages of IMRT simultaneous integrated boost for high-risk prostate cancer. , 2005, International journal of radiation oncology, biology, physics.

[4]  B. Erickson,et al.  Simultaneous integrated intensity-modulated radiotherapy boost for locally advanced gynecological cancer: radiobiological and dosimetric considerations. , 2005, International journal of radiation oncology, biology, physics.

[5]  S. Sutlief,et al.  Optimization of intensity modulated beams with volume constraints using two methods: cost function minimization and projections onto convex sets. , 1998, Medical physics.

[6]  Arvind Kumar,et al.  A New Linear Programming Approach to Radiation Therapy Treatment Planning Problems , 2006, Oper. Res..

[7]  Eva K. Lee,et al.  Integer Programming Applied to Intensity-Modulated Radiation Therapy Treatment Planning , 2003, Ann. Oper. Res..

[8]  R. Lane,et al.  A comparison of mixed integer programming and fast simulated annealing for optimizing beam weights in radiation therapy. , 1996, Medical physics.

[9]  R. Lane,et al.  A generic genetic algorithm for generating beam weights. , 1996, Medical physics.

[10]  I I Rosen,et al.  Dose-volume considerations with linear programming optimization. , 1991, Medical physics.

[11]  Arvind Kumar,et al.  A Column Generation Approach to Radiation Therapy Treatment Planning Using Aperture Modulation , 2005, SIAM J. Optim..

[12]  Ronald L. Rardin,et al.  Column generation for IMRT cancer therapy optimization with implementable segments , 2006, Ann. Oper. Res..

[13]  G A Ezzell,et al.  Genetic and geometric optimization of three-dimensional radiation therapy treatment planning. , 1996, Medical physics.

[14]  I. Rosen,et al.  The influence of dose constraint point placement on optimized radiation therapy treatment planning. , 1990, International journal of radiation oncology, biology, physics.

[15]  G. Sanguineti,et al.  IMRT to Escalate the Dose to the Prostate while Treating the Pelvic Nodes , 2005, Strahlentherapie und Onkologie.

[16]  Jun Duan,et al.  Simultaneous optimization of sequential IMRT plans. , 2005, Medical physics.

[17]  S. Spirou,et al.  A gradient inverse planning algorithm with dose-volume constraints. , 1998, Medical physics.

[18]  Eva K. Lee,et al.  Operations research applied to radiotherapy, an NCI-NSF-sponsored workshop February 7-9, 2002. , 2003, International journal of radiation oncology, biology, physics.

[19]  P Kijewski,et al.  The effect on minimum tumor dose of restricting target-dose inhomogeneity in optimized three-dimensional treatment of lung cancer. , 1991, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[20]  Eva K. Lee,et al.  Simultaneous beam geometry and intensity map optimization in intensity-modulated radiation therapy. , 2006, International journal of radiation oncology, biology, physics.

[21]  A. Niemierko,et al.  Random sampling for evaluating treatment plans. , 1990, Medical physics.

[22]  J Dai,et al.  Selection and determination of beam weights based on genetic algorithms for conformal radiotherapy treatment planning. , 2000, Physics in medicine and biology.

[23]  Bill J. Salter,et al.  Radiotherapy optimAl Design: An Academic Radiotherapy Treatment Design System , 2009 .

[24]  I I Rosen,et al.  Constrained simulated annealing for optimized radiation therapy treatment planning. , 1990, Computer methods and programs in biomedicine.

[25]  R Mohan,et al.  The potential for sparing of parotids and escalation of biologically effective dose with intensity-modulated radiation treatments of head and neck cancers: a treatment design study. , 2000, International journal of radiation oncology, biology, physics.

[26]  J. Shapiro,et al.  Large scale optimization of beam weights under dose-volume restrictions. , 1990, International journal of radiation oncology, biology, physics.

[27]  B G Fallone,et al.  A continuous penalty function method for inverse treatment planning. , 1998, Medical physics.

[28]  D Andrew Loblaw,et al.  Individualized planning target volumes for intrafraction motion during hypofractionated intensity-modulated radiotherapy boost for prostate cancer. , 2005, International journal of radiation oncology, biology, physics.

[29]  R Mohan,et al.  Application of fast simulated annealing to optimization of conformal radiation treatments. , 1993, Medical physics.

[30]  Ronald L. Rardin,et al.  A coupled column generation, mixed integer approach to optimal planning of intensity modulated radiation therapy for cancer , 2004, Math. Program..

[31]  M Goitein,et al.  Comments on "Sampling techniques for the evaluation of treatment plans" [Med. Phys. 20, 151-161 (1993)]. , 1993, Medical physics.

[32]  H. Romeijn,et al.  A novel linear programming approach to fluence map optimization for intensity modulated radiation therapy treatment planning. , 2003, Physics in medicine and biology.