An efficient approach to radiotherapy dose planning problem: a TOPSIS case-based reasoning approach

Hanif Malekpoor, Nishikant Mishra*, Shubham Sumalya, Sushma Kumari

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (SciVal)

Abstract

Dose planning of prostate cancer is a complex and time-consuming process. Usually, oncologists use past experience and spend a large amount of time to determine the optimal combination of dose in phase I and II of treatment. In this article, a novel TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) case-based reasoning (CBR) approach is proposed to capture the past experience and expertise of oncologists. Initially, cases that resemble new case are extracted from database. Thereafter, inferred cases are evaluated using TOPSIS, a multi-criteria decision-making approach to prescribe an optimal dose plan. Robustness of the proposed method is validated on data sets collected from the City Hospital Campus, Nottingham University Hospitals, NHS, UK, using leave-one-out strategy. In experiment, the proposed methodology outperformed CBR approach. It also endorses the suitability of multi-criteria decision-making approach. This method will help oncologists to make a better trade-off between similarity measures, success rate and side effects of treatment. The methodology is generic in nature and can help oncologists both new and experienced in dose planning process.

Original languageEnglish
Pages (from-to)4-12
Number of pages9
JournalInternational Journal of Systems Science: Operations and Logistics
Volume4
Issue number1
DOIs
Publication statusPublished - 02 Jan 2017

Keywords

  • Case based reasoning
  • dose planning
  • prostate cancer
  • radiotherapy
  • TOPSIS

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