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SU‐E‐T‐373: The Comparative Research of Monte Carlo Simulation Based Inhomogeneous Tissue Correction Algorithm
Author(s) -
Li G,
Yan B,
Wu A,
Jing J,
Wang Q
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4735460
Subject(s) - imaging phantom , monte carlo method , approximation error , homogeneous , physics , boundary (topology) , algorithm , mathematics , optics , mathematical analysis , statistics , statistical physics
Purpose : Two kinds of improved Batho method are proposed in this paper, the dose correction results for test example are compared also.Method and Materials:[Method1].The MC simulation model is : a 1cm 3 cavity is placed in the central axis of 30cm 3 water phantom. The center of the cavity is (0,0,0.5),'¦(0,0,29.5). The dose distribution of the cavity is simulated, the relative error with homogeneous water phantom is obtained and pre‐treated by the relative error databases. The corrected dose distribution is got in two steps, the cavity region and boundary point are corrected corresponding to the relative error databases firstly, then, the inhomogeneous tissue outside the cavity is corrected according to the Batho method.[Method2].The density of human tissue is divided into four corresponding intervals in terms of the value of CT. The simulation model is: a 1 cm 3 typical inhomogeneous tissue is placed at the central axis of 30 cm 3 homogeneous tissue phantom. Compared with the PDD of pure homogeneous tissue phantom, the relative error database can be obtained. The program judges the destiny change along the primary ray path. The Batho algorithm is used for dose correction when the destiny of tissue is relatively uniform. In the inhomogeneous interface between different tissues and inside cavity, the program will quickly find the relative error by index according to tissue density changes and depth, read the corresponding data to gain accurate correction results. Results : The method 1 obtain better correction result in the boundary point compared to MC simulation, but, in the cavity, the maximum error correction is 9.661%. Accordingly, the maximum correction error in the cavity region by method2 is 4.73%, in the boundary point is 2.47%, can satisfy the clinical precision requirement of 5%. Conclusions : The method 2 can obtain satisfactory correction Result in inhomogeneous tissue interface and the cavity area. The work is supported by the National Natural Science Foundation of China (60872112 and 10805012), the Natural Science Foundation of Anhui Province (11040606M132) and the Fundamental Research Funds for the Central Universities and the Science Research and Development Fund of Hefei University of Technology (2012HGXJ0062).