Multiobjective approach in plans for treatment of cancer by radiotherapy

Abstract

Nowadays the technique of radiotherapy has been one of the main alternatives for the treatment of several types of cancer today. With technological development, especially in the case of 3D conformal radiotherapy, applications involving mathematical techniques and algorithms have been proposed to help the development a good treatment plan. This paper aims at present a model for multiobjective linear programming problem of dose intensity. The focus of the model is to determine the best dose distribution of radiation field, so that the dose delivered to the tumor to be prescribed and that affects the minimum the noble and healthy tissues. A test case of prostate cancer was used as an example of the numerical model and the Pareto-Optimal Frontier was generated using the method of weighted function.

Operational research techniques applied throughout cancer care services: a review

“…The authors present promising model results (Obal et al, 2013;Petrovic, Mishra, & Sundar, 2011;Petrovic et al, 2016). For most patients, the dose plans produced by Petrovic, Mishra, et al (2011) were at least as good as those generated by oncologists, in that they met dose constraints and the total dose was at least as high.…”

“…Here we discuss some 3D conformal radiotherapy planning models (Obal, Volpi, & Miloca, 2013;Petrovic, Khussainova, & Jagannathan, 2016;Petrovic, Mishra, & Sundar, 2011). Petrovic, Mishra, et al (2011) andObal et al (2013) model prostate cancer treatment, while Petrovic et al (2016) apply their approach to brain cancer treatment.…”

“…Petrovic, Mishra, et al (2011) andObal et al (2013) model prostate cancer treatment, while Petrovic et al (2016) apply their approach to brain cancer treatment. The decision variables are different in each paper.…”

“…Petrovic, Mishra, et al (2011) andObal et al (2013) aim to determine the appropriate dose. For Obal et al (2013), this is the dose intensity that each beam should deliver over the whole treatment course, but for Petrovic, Mishra, et al (2011) this is the total dose that should be delivered during phase 1, when both the prostate and surrounding area are targeted, and the total dose in phase 2, when only the prostate is targeted. Petrovic et al (2016) decide on the appropriate number of beams and the beam angles.…”

“…Petrovic et al (2016) present methods to adapt previous cases without needing expert knowledge: neural networks, naïve Bayes classifier and adaptation-guided retrieval. On the other hand, Obal et al (2013) formulate their model as a multi-objective linear program and use the weighted sum method to find the set of efficient solutions.…”