A novel case based reasoning approach to radiotherapy planning

  • Authors:

  • Sanja Petrovic;Nishikant Mishra;Santhanam Sundar

  • Affiliations:

  • Automated Scheduling, Optimization and Planning Research Group, School of Computer Science and IT, University of Nottingham, Nottingham, UK;Automated Scheduling, Optimization and Planning Research Group, School of Computer Science and IT, University of Nottingham, Nottingham, UK;Department of Oncology, Nottingham University Hospital NHS Trust Nottingham, UK

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

Quantified Score

Hi-index 12.06

Visualization

Abstract

Radiotherapy planning is a complex problem which requires both expertise and experience of an oncologist. A case based reasoning (CBR) system is developed to generate dose plans for prostate cancer patients. The proposed approach captures the expertise and experience of oncologists in treating previous patients and recommends a dose in phase I and phase II of the treatment of a new patient considering also the success rate of the treatment. The proposed CBR system employs a modified Dempster-Shafer theory to fuse dose plans suggested by the most similar cases retrieved from the case base. In order to mimic the continuous learning characteristic of oncologists, the weights corresponding to each feature used in the retrieval process are updated automatically each time after generating a treatment plan for a new patient. The efficiency of the proposed methodology has been validated using real data sets collected from the Nottingham University Hospitals NHS, City Hospital Campus, UK. Experiments demonstrated that for most of the patients, the dose plan generated by our approach is coherent with the dose plan suggested by an experienced oncologist. This methodology can assist both new and experienced oncologists in the treatment planning.