Evaluation and simulation of breast cancer imaging devices using multi-criteria decision theory

Breast cancer is the most common type of cancer seen in women. The incidence of breast cancer increases with age. The most important factor in breast cancer is that it is diagnosed before spreading to other organs by the blood or lymph circulation. When cancer is diagnosed at an early stage, the success rate of breast cancer treatment is over 90%. For this reason, breast cancer imaging devices should be used for early diagnosis of breast cancer. The main aim of this study is to shed more light on the parameters that affect the different imaging device alternatives for breast cancer and how these parameters affect the preference ranking of each imaging technique. In this study, the most commonly used imaging devices for breast cancer are analysed based on various parameters that are likely to affect the outcome of the imaging methods. These parameters are the cost per scan, cost of the device, radiation dose, specificity, sensitivity, total scan time, spatial resolution, comparison with the natural radiation exposure, real 3D, compression and claustrophobia. According to this study, positron emission mammography and breast computed tomography are the best breast cancer imaging techniques for both patients and hospitals. The analysis and ranking were evaluated and compared using fuzzy PROMETHEE, a multi-criteria decision-making technique.