TU‐G‐BRB‐08: IMRT Optimization with Fixed Point Iteration

Z. Tian, X. Jia, A. Uribe‐sanchez, Q. Gautier, Y. Graves, N. li, S. Jiang

Research output: Contribution to journalArticle

Abstract

Purpose: In IMRT optimization, dose‐deposition coefficient (DDC) matrix is needed to parameterize the contribution of each beamlet to each dose voxel. However, due to the limitation of computer memory and the requirement on computational efficiency, small matrix elements are usually truncated, compromising the resulting plan's quality. Besides, the practice of ignoring multileaf collimator (MLC) transmission in IMRT planning also introduces inaccuracy into the resulting plan. Therefore an IMRT optimization algorithm with fixed point iteration is developed. Methods: For truncation problem, IMRT optimization is implemented as the inner‐loop with truncated DDC matrix. Fixed point iteration, as the outer‐loop, is to recalculate the actual dose with complete DDC matrix and use the difference between the optimized dose and the actual dose as the input for the optimization at the next iteration. MLC transmission can also be incorporated into IMRT planning, by adding this fixed point iteration to optimize the intensity of the already optimized apertures. The convergence and feasibility of this algorithm are mathematically studied using a simplified model. Results: Two head‐and‐neck IMRT cases are used to test our algorithm. It is mathematically proven and experimentally validated on the simplified model that with proper DDC matrix splitting, the fixed point iteration converges, although not to the solution obtained using the complete DDC matrix, but to a solution much closer to it than that from the truncated DDC matrix, in terms of the resulting dose distribution. The experimental results on the patient cases also demonstrate that our algorithm could handle both DDC matrix truncation and MLC transmission problems and give us good plans with comparable dose‐volume histograms and dose distributions. Conclusions: This fixed point iteration scheme can effectively take the DDC matrix truncation and MLC transmission into account during IMRT optimization, and thus solve the efficiency and memory issue while maintaining a reasonable accuracy. This work is supported by Varian Medical Systems through a Master Research Agreement.

Original languageEnglish (US)
Pages (from-to)3921
Number of pages1
JournalMedical Physics
Volume39
Issue number6
DOIs
StatePublished - 2012

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ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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TU‐G‐BRB‐08 : IMRT Optimization with Fixed Point Iteration. / Tian, Z.; Jia, X.; Uribe‐sanchez, A.; Gautier, Q.; Graves, Y.; li, N.; Jiang, S.

In: Medical Physics, Vol. 39, No. 6, 2012, p. 3921.

Research output: Contribution to journalArticle

Tian, Z, Jia, X, Uribe‐sanchez, A, Gautier, Q, Graves, Y, li, N & Jiang, S 2012, 'TU‐G‐BRB‐08: IMRT Optimization with Fixed Point Iteration', Medical Physics, vol. 39, no. 6, pp. 3921. https://doi.org/10.1118/1.4736003
Tian Z, Jia X, Uribe‐sanchez A, Gautier Q, Graves Y, li N et al. TU‐G‐BRB‐08: IMRT Optimization with Fixed Point Iteration. Medical Physics. 2012;39(6):3921. https://doi.org/10.1118/1.4736003
Tian, Z. ; Jia, X. ; Uribe‐sanchez, A. ; Gautier, Q. ; Graves, Y. ; li, N. ; Jiang, S. / TU‐G‐BRB‐08 : IMRT Optimization with Fixed Point Iteration. In: Medical Physics. 2012 ; Vol. 39, No. 6. pp. 3921.
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