A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy

Mishra, Nishikant, Petrovic, Sanja and Sundar, Santhanam (2011) A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy. Medical Physics, 38 (12). pp. 6528-6538. ISSN 0094-2405

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Purpose: Prostate cancer is the most common cancer in the male population. Radiotherapy is often used in the treatment for prostate cancer. In radiotherapytreatment, the oncologist makes a trade-off between the risk and benefit of the radiation, i.e., the task is to deliver a high dose to the prostate cancer cells and minimize side effects of the treatment. The aim of our research is to develop a software system that will assist the oncologist in planning new treatments. Methods: A nonlinear case-based reasoning system is developed to capture the expertise and experience of oncologists in treating previous patients. Importance (weights) of different clinical parameters in the dose planning is determined by the oncologist based on their past experience, and is highly subjective. The weights are usually fixed in the system. In this research, the weights are updated automatically each time after generating a treatment plan for a new patient using a group based simulated annealing approach. Results: The developed approach is analyzed on the real data set collected from the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. Extensive experiments show that the dose plan suggested by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Conclusions: The developed case-based reasoning system enables the use of knowledge and experience gained by the oncologist in treating new patients. This system may play a vital role to assist the oncologist in making a better decision in less computational time; it utilizes the success rate of the previously treated patients and it can also be used in teaching and training processes.

Item Type: Article
Uncontrolled Keywords: sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School: Faculty of Social Sciences > Norwich Business School
Depositing User: Pure Connector
Date Deposited: 06 Nov 2015 12:00
Last Modified: 21 Nov 2022 10:31
URI: https://ueaeprints.uea.ac.uk/id/eprint/55026
DOI: 10.1118/1.3660517

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