Tailored 3D breast models for development of microwave based breast tumor screening

Authors

• Mariella Särestöniemi Research Unit of Health Sciences and Technology, Faculty of Medicine & Centre for Wireless Communications, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu
• Daljeet Singh Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu
• Jarmo Reponen Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu
• Teemu Myllylä Research Unit of Health Sciences and Technology, Faculty of Medicine; Optoelectronics and Measurements, Faculty of Information Technology and Electrical Engineering & Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu

DOI: https://doi.org/10.23996/fjhw.140947

Keywords:

breast cancer, breast density, breast self-examination, early detection of cancer, rural nursing, telemedicine

Abstract

Portable breast monitoring devices, which could be used outside the hospital and even for self-monitoring of risk groups, are considered as promising eHealth applications for future telemedicine. Microwave technique is one of the most promising emerging techniques for portable monitoring devices since it enables low-cost, high accuracy, and user-friendly devices. The technique is based on detecting differences in radio channel responses since tumors have different dielectric properties than the breast glandular or fat tissues. Breast density categories affect the detectability of the tumors with also microwave technique. This paper presents a study on breast tumor detectability with different simulation and measurement models tailored to correspond different breast types. The simulations are carried out using electromagnetic simulation software with human voxel models as well as developed breast models. The evaluation results show that even small-sized breast tumors can be detected with microwave technique within all the breast density categories. Differences in channel responses caused by tumors are breast-type dependent. The results highlight the importance of developing extensive reference databank covering all the breast density categories for microwave-based breast tumor detection applications.