TELKOMNIKA, Vol.14, No.2A, June 2016, pp. 379~387 ISSN: 1693-6930,
accredited A by DIKTI, Decree No: 58DIKTIKep2013 DOI: 10.12928TELKOMNIKA.v14i2A.4356
379
Received February 2, 2016; Revised May 3, 2016; Accepted May 18, 2016
Clinically Relevant Optimization Based on Simulated Annealing Algorithm in IMRT for Prostate Cancer
Caiping Guo
1
, Linhua Zhang
2
1
Electronic Engineering Department, Taiyuan Institute of Technology, Taiyuan, 030008 China
2
Computer Engineering Department, Taiyuan Institute of Technology, Taiyuan, 030008 China Corresponding author, e-mail: guocaipingvip163.com
1
, zhanglinhuazlh163.com
2
Abstract
Given the advantage and trend of the clinically relevant optimization in radiotherapy, a novel optimization method using objective function based on tumor control probability TCP and normal tissue
complication probability NTCP was proposed, which can improve global optimization capacity of simulated annealing optimization algorithm SA by increasing poor solutions acceptance rate. The
effectiveness and superiority of the new method was verified in prostate cancer cases. Experimental results show that the proposed radiotherapy optimization method, not only can improve DVH curve of
organs at risk, reduce the NTCP, and improve the therapeutic gain ration, but also can decrease hot spots and gain better dose distribution uniformity of the target.
Keywords: Simulated annealing; Tumor control probability; Nature tissue control probability Copyright © 2016 Universitas Ahmad Dahlan. All rights reserved.
1. Introduction
Intensity-modulated radiation therapy IMRT is an advanced mode of high-precision radiotherapy that uses computer-controlled linear accelerators to deliver precise radiation doses
to a malignant tumor or specific areas within the tumor. IMRT allows for the radiation dose to conform more precisely to the three-dimensional 3-D shape of the tumor by modulating or
controlling the intensity of the radiation beam in multiple small volumes. IMRT also allows higher radiation doses to be focused to regions within the tumor while minimizing the dose to
surrounding normal critical structures.
Objective function is an important index for the optimization and evaluation of treatment planning. It is not only a tool to evaluate the treatment plan, but also the connection between the
input parameters and the output dose distribution. Now Objective functions used in radiotherapy optimization are based either on physical factors or on biological formulations [1]. The former
employs a physical quadratic dose-based objective function, which, via a combination of weighted terms, penalizes differentially violations of the various dose andor dose-volume
constraints specified with respect to the organs and the targets considered in the optimization process [2-4]. However, this type of physics-based approach is unable, to sufficiently take into
account the nonlinear response of tumors or normal structures to irradiation, especially with arbitrary inhomogeneous dose distribution [5]. In order to be meaningful the optimization
process must be “clinically relevant’’ instead of being simply dose distribution oriented [6]. It is desirable to employ the biological objective function into the inverse planning, as well as
balancing the various normal tissue complication probabilities NTCP with respect to each other and with respect to the tumor control probability TCP.
Mainly three kinds of biological criteria can be applied: generalized equivalent uniform dose gEUD, tumor control probability TCP, and normal tissue complication probability
NTCP[7]. The merits of including the
gEUD concept into an objective function have been widely investigated [5, 8-13]. Based on a volume parameter
a, gEUD corresponds, for a given non- uniform dose distribution, to the uniform dose that induces the same biological effect. And the
NTCP biological criteria has been used in inverse treatment planning optimization [3, 6, 14- 16]and incorporated into some commercial treatment planning software [14, 17]. The advantage
of the TCP criteria, also, was investigated [6, 18-19]. Nevertheless the gEUD model cannot
directly quantify the NTCP and TCP. In contrast, both NTCP and TCP models are more
ISSN: 1693-6930
TELKOMNIKA Vol. 14, No. 2A, June 2016 : 379 – 387
380 clinically relevant. If all constraints of the inverse planning objective function are satisfied, the
NTCP-based and TCP-based treatment plan should be directly implemented, and there is no need to further optimize.
Based on Mohan et al’s research, we did some researches to improve optimized quality. Mohan
et al 1992 used a single score, mixing TCP with NTCP criteria to reduce normal tissue complication rates and increase tumor control. Because both NTCP and TCP
criterias are sigmoidal functions of dose distributions [20-24], and they are thus inherently nonlinear and non-convex in terms of fluence elements in fluence map optimization FMO.The
fast simulated annealing approach was applied to solve this non-convex optimization problem. In their work, calculated TCP was defined as the TCP sub-score, without paying additional
penalty, while piecewise linear penalty was imposed on the computed values of each NTCP, minor importance was paid to small NTCP and only a small penalty to the score is assessed.
We proposed a new objective function based on the NTCP criteria and TCP criteria during the high temperature stage, to improve the global optimization ability of simulated annealing by
increasing poor solutions acceptance rate, while the same objective function proposed by Mohan et al [6] was used for low temperature stage. The effectiveness of the proposed method
was assessed in 10 prostate cancer cases, and compared with optimization method proposed by Mohan et al [6].
2. Methods and Materials 2.1. Simulated Annealing Optimization Algorithm
