A Novel Two Phase Retrieval Mechanism for a Clinical Case Based Reasoning System for Radiotherapy Treatment Planning

Abstract

This paper presents a decision support system for radiotherapy treatment planning for head, neck and brain cancer. The aim of a treatment plan is to apply radiation to kill tumor cells, while minimizing the damage to healthy tissue and critical organs. Since treatment planning is a complex decision making process that relies heavily on the subjective experience of clinicians, we propose the use of case-based reasoning (CBR), in which problems are solved based on the solutions of similar past problems. This paper focuses on the case retrieval process of a CBR system. The attributes, which describe the cases, are selected by assessing their effect on the performance of the CBR system. We have developed a context sensitive local weighting scheme that assigns weights to attributes based on their value and the values of other attributes in the target case. A novel two phase retrieval mechanism is developed, in which each phase is optimized to retrieve a particular part of the solution. We also present an original use of fuzzy logic in order to represent nonlinearity in the similarity measure. Experiments, which evaluate the similarity measure using real brain cancer patient cases, show promising results.

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning

“…Experienced planners often know what configurations are suitable for a cancer patient, even when the underlying theory is not thoroughly understood [7].…”

“…Many knowledge-based methods for radiotherapy planning have been developed to decide upon parameters for treatment plans, including the radiation dose plan, beam configuration, beam weight and wedge configuration [2][3][4][5]7]. Such methods aim at utilising knowledge available in the domain and used by the domain end-user to simulate the natural solving process as much as possible.…”

“…A CBR system for brain cancer RTP was developed by Jagannathan et al [7]. They focused mainly on the retrieval process of the CBR system.…”

“…In this section, a brief description of the CBR system for the RTP of brain cancer developed by Jagannathan et al [7] is given. The case base consists of brain cancer patient cases containing a description of the patient and the plan used for the treatment.…”

“…The research presented in this paper builds on the CBR system for the RTP of brain cancer, which was developed in collaboration with the Nottingham University Hospitals Trust, NHS, Nottingham City Hospital Campus and is described by Jagannathan et al [7]. The experiments showed promising results but suggested that an adaptation of the retrieved solution needs to be performed to better address the requirements of the new case.…”