Literature DB >> 15798337

Quantitation of the a priori dosimetric capabilities of spatial points in inverse planning and its significant implication in defining IMRT solution space.

Z Shou1, Y Yang, C Cotrutz, D Levy, Lei Xing.   

Abstract

In inverse planning, the likelihood for the points in a target or sensitive structure to meet their dosimetric goals is generally heterogeneous and represents the a priori knowledge of the system once the patient and beam configuration are chosen. Because of this intrinsic heterogeneity, in some extreme cases, a region in a target may never meet the prescribed dose without seriously deteriorating the doses in other areas. Conversely, the prescription in a region may be easily met without violating the tolerance of any sensitive structure. In this work, we introduce the concept of dosimetric capability to quantify the a priori information and develop a strategy to integrate the data into the inverse planning process. An iterative algorithm is implemented to numerically compute the capability distribution on a case specific basis. A method of incorporating the capability data into inverse planning is developed by heuristically modulating the importance of the individual voxels according to the a priori capability distribution. The formalism is applied to a few specific examples to illustrate the technical details of the new inverse planning technique. Our study indicates that the dosimetric capability is a useful concept to better understand the complex inverse planning problem and an effective use of the information allows us to construct a clinically more meaningful objective function to improve IMRT dose optimization techniques.

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Year:  2005        PMID: 15798337     DOI: 10.1088/0031-9155/50/7/010

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  4 in total

1.  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

2.  Automated population-based planning for whole brain radiation therapy.

Authors:  Eduard Schreibmann; Tim Fox; Walter Curran; Hui-Kuo Shu; Ian Crocker
Journal:  J Appl Clin Med Phys       Date:  2015-09-08       Impact factor: 2.102

3.  Prior-knowledge treatment planning for volumetric arc therapy using feature-based database mining.

Authors:  Eduard Schreibmann; Tim Fox
Journal:  J Appl Clin Med Phys       Date:  2014-03-06       Impact factor: 2.102

4.  Physically constrained voxel-based penalty adaptation for ultra-fast IMRT planning.

Authors:  Niklas Wahl; Mark Bangert; Cornelis P Kamerling; Peter Ziegenhein; Gijsbert H Bol; Bas W Raaymakers; Uwe Oelfke
Journal:  J Appl Clin Med Phys       Date:  2016-07-08       Impact factor: 2.102

  4 in total

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