Literature DB >> 2912950

Semi-automated radiotherapy treatment planning with a mathematical model to satisfy treatment goals.

W D Powlis1, M D Altschuler, Y Censor, E L Buhle.   

Abstract

Iterative algorithms can provide a feasible solution, if any exists, to specified treatment goals. Our model subdivides both the patient's cross section into a fine grid of points and the radiation beam into a set of "pencil" rays. The anatomy, treatment machine parameters, dose limits and homogeneity, are all defined. This process of subdivision leads to a large system of linear inequalities with a solution that provides a radiation intensity distribution that will deliver a prescribed dose distribution. The clinical results from two different algorithms will be presented and contrasted. Once the anatomy, treatment, and machine parameters have been entered, the computerized algorithms yield an answer in several minutes. The Cimmino algorithm also allows "weights" or priority assignments of the treatment goals. The resulting solution is biased towards fulfilling the specified doses for the anatomic regions which were given greater weight. It is desirable to have a systematic search of possible treatment alternatives in complex clinical situations, including 3-dimensional radiation therapy treatment planning (RTTP). Our method has been applied to 2-D RTTP, but is equally applicable to 3-D RTTP with minor modifications.

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Year:  1989        PMID: 2912950     DOI: 10.1016/0360-3016(89)90042-4

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  11 in total

1.  Designing radiotherapy plans with elastic constraints and interior point methods.

Authors:  Allen Holder
Journal:  Health Care Manag Sci       Date:  2003-02

2.  Dose gradient based algorithm for beam weights selection in 3D-CRT plans.

Authors:  Marta Krystyna Giżyńska; Paweł F Kukołowicz
Journal:  Rep Pract Oncol Radiother       Date:  2014-05-13

3.  A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT.

Authors:  Timothy C Zhu; Martin D Altschuler; Yida Hu; Ken Wang; Jarod C Finlay; Andreea Dimofte; Keith Cengel; Stephen M Hahn
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2010-01

Review 4.  From analytic inversion to contemporary IMRT optimization: radiation therapy planning revisited from a mathematical perspective.

Authors:  Yair Censor; Jan Unkelbach
Journal:  Phys Med       Date:  2011-05-25       Impact factor: 2.685

5.  Implementation of a dose gradient method into optimization of dose distribution in prostate cancer 3D-CRT plans.

Authors:  Marta K Giżyńska; Paweł F Kukołowicz; Paweł Kordowski
Journal:  Rep Pract Oncol Radiother       Date:  2014-05-03

6.  Optimization of light sources for prostate photodynamic therapy.

Authors:  Martin D Altschuler; Timothy C Zhu; Jun Li; Stephen M Hahn
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2005-04-22

7.  A heterogeneous algorithm for PDT dose optimization for prostate.

Authors:  Martin D Altschuler; Timothy C Zhu; Yida Hu; Jarod C Finlay; Andreea Dimofte; Ken Wang; Jun Li; Keith Cengel; S B Malkowicz; Stephen M Hahn
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2009-02-18

8.  Performance evaluation of an algorithm for fast optimization of beam weights in anatomy-based intensity modulated radiotherapy.

Authors:  Vaitheeswaran Ranganathan; V K Sathiya Narayanan; Janhavi R Bhangle; Kamlesh K Gupta; Sumit Basu; Vikram Maiya; Jolly Joseph; Amit Nirhali
Journal:  J Med Phys       Date:  2010-04

9.  Optimization of light source parameters in the photodynamic therapy of heterogeneous prostate.

Authors:  Jun Li; Martin D Altschuler; Stephen M Hahn; Timothy C Zhu
Journal:  Phys Med Biol       Date:  2008-07-08       Impact factor: 3.609

10.  Optimized interstitial PDT prostate treatment planning with the Cimmino feasibility algorithm.

Authors:  Martin D Altschuler; Timothy C Zhu; Jun Li; Stephen M Hahn
Journal:  Med Phys       Date:  2005-12       Impact factor: 4.071

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