Literature DB >> 10798692

Algorithms and functionality of an intensity modulated radiotherapy optimization system.

Q Wu1, R Mohan.   

Abstract

The main purpose of this paper is to describe formalisms, algorithms, and certain unique features of a system for optimization of intensity modulated radiotherapy (IMRT). The system is coupled to a commercial treatment planning system with an accurate dose calculation engine based on the kernel superposition algorithm. The system was designed for use for research as well as for routine clinical practice. It employs dose- and dose-volume-based objective functions. The system can optimize IMRT plans with multiple target volumes simultaneously. Each target volume may be assigned a different prescription dose with constraints on either underdosing, or overdosing, or both. For organs at risk more than one constraint may be applied. This feature allows simultaneous treatment of primary, regional disease and electively treated nodes. The system allows specification of constraints on logical combinations of anatomic structures, such as a region of overlap between the prostate planning target volume and rectum or the volume of lung excluding the tumor. The optimization may also be performed on plans which, in addition to intensity-modulated beams, include other modalities such as non-IMRT photon and electron beams and brachytherapy sources. The various features of the system are illustrated with one phantom example and two clinical examples: a brain stereotactic radiosurgery case and a nasopharynx case. In the cylindrical phantom example, the use of the system for overlap regions is demonstrated. The brain stereotactic radiosurgery example shows the improvement of IMRT plans over the conventional arcs based plan and the three-dimensional conformal plan with multiple fixed gantry angles and demonstrates the application of our system to cases where small grid sizes are important. The nasopharynx example shows the potential of IMRT to simultaneously treat large and boost fields. It also illustrates the power of IMRT to protect normal anatomic structures for highly complex situations and the efficiency in planning and delivery achievable with IMRT. The overall IMRT planning time is typically less than 2 h on a Sun Ultrasparc workstation, most of which is spent in repeated computation of dose distributions.

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Year:  2000        PMID: 10798692     DOI: 10.1118/1.598932

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  43 in total

1.  Robust optimization of intensity modulated proton therapy.

Authors:  Wei Liu; Xiaodong Zhang; Yupeng Li; Radhe Mohan
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

2.  Influence of robust optimization in intensity-modulated proton therapy with different dose delivery techniques.

Authors:  Wei Liu; Yupeng Li; Xiaoqiang Li; Wenhua Cao; Xiaodong Zhang
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

3.  Toward truly optimal IMRT dose distribution: inverse planning with voxel-specific penalty.

Authors:  Pavel Lougovski; Jordan LeNoach; Lei Zhu; Yunzhi Ma; Yair Censor; Lei Xing
Journal:  Technol Cancer Res Treat       Date:  2010-12

4.  Analytic IMRT dose calculations utilizing Monte Carlo to predict MLC fluence modulation.

Authors:  I B Mihaylov; F A Lerma; Y Wu; J V Siebers
Journal:  Med Phys       Date:  2006-04       Impact factor: 4.071

5.  Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion.

Authors:  J J Gordon; J V Siebers
Journal:  Med Phys       Date:  2009-03       Impact factor: 4.071

6.  A novel reduced-order prioritized optimization method for radiation therapy treatment planning.

Authors:  Georgios Kalantzis; Aditya Apte
Journal:  IEEE Trans Biomed Eng       Date:  2014-04       Impact factor: 4.538

7.  Modeling the dosimetry of organ-at-risk in head and neck IMRT planning: an intertechnique and interinstitutional study.

Authors:  Jun Lian; Lulin Yuan; Yaorong Ge; Bhishamjit S Chera; David P Yoo; Sha Chang; FangFang Yin; Q Jackie Wu
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

8.  Reduced-order constrained optimization (ROCO): clinical application to head-and-neck IMRT.

Authors:  Linda Rivera; Ellen Yorke; Alex Kowalski; Jie Yang; Richard J Radke; Andrew Jackson
Journal:  Med Phys       Date:  2013-02       Impact factor: 4.071

9.  New approach in lung cancer radiotherapy offers better normal tissue sparing.

Authors:  Ivaylo B Mihaylov
Journal:  Radiother Oncol       Date:  2016-09-28       Impact factor: 6.280

10.  Reduced-order constrained optimization in IMRT planning.

Authors:  Renzhi Lu; Richard J Radke; Jie Yang; Laura Happersett; Ellen Yorke; Andrew Jackson
Journal:  Phys Med Biol       Date:  2008-11-07       Impact factor: 3.609

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