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

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

Authors

Shubham Sumalya

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Dr. Sushma Kumari S.Kumari@hull.ac.uk
Senior Lecturer and Programme Director- MSc Logistics and Supply Chain Management and Education Lead Logistics and Supply Chain Management



Abstract

© 2016, © 2016 Informa UK Limited, trading as Taylor & Francis Group. 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.

Citation

Malekpoor, H., Mishra, N., Sumalya, S., & Kumari, S. (2017). An efficient approach to radiotherapy dose planning problem: a TOPSIS case-based reasoning approach. International Journal of Systems Science: Operations and Logistics, 4(1), 4-12. https://doi.org/10.1080/23302674.2015.1135354

Journal Article Type Article
Acceptance Date Dec 19, 2015
Online Publication Date Mar 3, 2016
Publication Date Jan 2, 2017
Deposit Date Jun 8, 2022
Journal International Journal of Systems Science: Operations and Logistics
Print ISSN 2330-2674
Electronic ISSN 2330-2682
Publisher Taylor and Francis
Peer Reviewed Peer Reviewed
Volume 4
Issue 1
Pages 4-12
DOI https://doi.org/10.1080/23302674.2015.1135354
Keywords Case based reasoning; Prostate cancer; Radiotherapy; Dose planning; TOPSIS
Public URL https://hull-repository.worktribe.com/output/3601750




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