title: Detection of breast abnormalities using a prototype resonance electrical impedance spectroscopy system: a preliminary study.
abstract: Electrical impedance spectroscopy has been investigated with but limited success as an adjunct procedure to mammography and as a possible pre-screening tool to stratify risk for having or developing breast cancer in younger women. In this study, the authors explored a new resonance frequency based [resonance electrical impedance spectroscopy (REIS)] approach to identify breasts that may have highly suspicious abnormalities that had been recommended for biopsies. The authors assembled a prototype REIS system generating multifrequency electrical sweeps ranging from 100 to 4100 kHz every 12 s. Using only two probes, one in contact with the nipple and the other with the outer breast skin surface 60 mm away, a paired transmission signal detection system is generated. The authors recruited 150 women between 30 and 50 years old to participate in this study. REIS measurements were performed on both breasts. Of these women 58 had been scheduled for a breast biopsy and 13 had been recalled for additional imaging procedures due to suspicious findings. The remaining 79 women had negative screening examinations. Eight REIS output signals at and around the resonance frequency were computed for each breast and the subtracted signals between the left and right breasts were used in a simple jackknifing method to select an optimal feature set to be inputted into a multi-feature based artificial neural network (ANN) that aims to predict whether a woman's breast had been determined as abnormal (warranting a biopsy) or not. The classification performance was evaluated using a leave-one-case-out method and receiver operating characteristics (ROC) analysis. The study shows that REIS examination is easy to perform, short in duration, and acceptable to all participants in terms of comfort level and there is no indication of sensation of an electrical current during the measurements. Six REIS difference features were selected as input signals to the ANN. The area under the ROC curve (A(z)) was 0.707 +/- 0.033 for classifying between biopsy cases and non-biopsy (including recalled and screening negative) and the performance (A(z)) increased to 0.746 +/- 0.033 after excluding recalled but negative cases. At 95% specificity, the sensitivity levels were approximately 20.5% and 30.4% in the two data sets tested. The results suggest that differences in REIS signals between two breasts measured in and around the tissue resonance frequency can be used to identify at least some of the women with suspicious abnormalities warranting biopsy with high specificity.
authors.affiliation: Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA. zhengb@upmc.edu
authors.forename: Bin
authors.initials: B
authors.lastname: Zheng
authors.forename: Margarita L
authors.initials: ML
authors.lastname: Zuley
authors.forename: Jules H
authors.initials: JH
authors.lastname: Sumkin
authors.forename: Victor J
authors.initials: VJ
authors.lastname: Catullo
authors.forename: Gordon S
authors.initials: GS
authors.lastname: Abrams
authors.forename: Grace Y
authors.initials: GY
authors.lastname: Rathfon
authors.forename: Denise M
authors.initials: DM
authors.lastname: Chough
authors.forename: Michelle Z
authors.initials: MZ
authors.lastname: Gruss
authors.forename: David
authors.initials: D
authors.lastname: Gur
mesh_terms: D000328:Adult; D001706:Biopsy; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D017097:Electric Impedance; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods; D008495:Medical Oncology / Q000379:methods; D008875:Middle Aged; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012372:ROC Curve; D012306:Risk; D013057:Spectrum Analysis / Q000379:methods*