Evaluation of EM Absorption Loss for Continuous Monitoring of Breast Cancer Mohamed M. Elsewe and Deb Chatterjee CSEE Department, University of Missouri - Kansas City (UMKC), 5110 Rockhill Road, Kansas City, MO 64110, USA, mme0f0@umkc.edu Abstract — Continuous monitoring of breast cancer is a vital step in the treatment plan of a breast cancer survivor who has an 11-20% risk of recurrence and a 3x-4x chance of developing breast cancer in a different location within the breast. This study proposes electromagnetic (EM) absorption loss measurements as a cost-effective method which has the potential to replace the rudimentary and inaccurate breast self- examination and complement the traditional X-ray mammography exams, which are cost-prohibitive and carry radiation exposure risk. A breast cancer survivor can continuously monitor the health of her breast by periodically comparing absorption loss measurements to a reference absorption loss measurement taken after a lumpectomy. Results show successful detection of tumors at different locations within the breast with just a 3-element phased array. Index Terms — Breast Cancer, Absorption, Continuous Monitoring, Detection, Tumor, FEM. I. INTRODUCTION Breast cancer infects 1 in 8 women in the United States and an estimated 226,870 women will be diagnosed with breast cancer in the United States in 2012 alone [1]. This makes breast cancer the second leading cause of cancer death among women only after lung cancer [1]. In addition, a breast cancer survivor has a 3x-4x chance of developing breast cancer in a different location within the same breast or in the other breast [1]. Also, a breast cancer survivor has an 11% risk of recurrence within 5 years after treatment and 20% risk of recurrence within 10 years after treatment [2]. All these statistical figures form a strong motivation for early detection of breast cancer and the need for continuous monitoring of breast cancer especially for breast cancer survivors. Existing breast cancer scanning methods such as X-ray mammography and MRI present significant shortcomings which do not make them ideal methods for continuous monitoring of breast cancer. For example, X-ray radiation exposes the patient to ionizing radiation. MRI exams are cost-prohibitive and have a relatively high false alarm rate [3]. Moreover, both tests are only about 70% accurate [4]. This paper builds on research in [5], in which a novel approach in the detection and diagnosis of breast cancer was presented. Briefly, the breast is illuminated by an antenna. The amount of EM power absorbed (absorption loss) by normal breasts of different sizes (masses) is determined. A linear curve is established by which the normal absorption loss value of any breast mass can be determined. Through clinical trials, acceptable ranges would be established as an offset around the linear curve for normal absorption loss. For a patient, if the measured absorption loss value falls outside an acceptable range of normal absorption loss values for her breast mass, the breast will be diagnosed as infected. Moreover, for genetically predisposed patients or surviving breast cancer patients, an absorption loss measurement, immediately after breast tumor removal surgery (lumpectomy), could serve as a reference value with which continuous absorption loss measurements would be compared in lieu of or in combination with the linear curve. This paper focuses on the patient’s own absorption loss measurement after a normal mammography scan or surgery as a reference value. The patient then could continuously monitor the health of her breast by periodically comparing absorption loss measurements to the reference value. This, in turn, would replace the rudimentary and inaccurate breast self-examination patients are asked to perform periodically at their home. In this study, EM simulation experiments are performed to achieve: 1. Detection of tumors by having higher absorption loss contrast in the presence of tumors, and 2. Detection of tumors regardless of their location within breast (particularly deep-seated tumors). Fig. 1. Ansys HFSS 3-D simulation model. 978-1-4673-2932-3/13/$31.00  2013 IEEE RWS 2013 337