Title :
Regional Admittivity Spectra With Tomosynthesis Images for Breast Cancer Detection: Preliminary Patient Study
Author :
Kao, Tzu-Jen ; Boverman, Gregory ; Kim, Bong Seok ; Isaacson, David ; Saulnier, Gary J. ; Newell, Jonathan C. ; Choi, Myoung H. ; Moore, Richard H. ; Kopans, Daniel B.
Author_Institution :
Dept. of Biomed. Eng., Rensselaer Polytech. Inst., Troy, NY
Abstract :
It has been known for some time that many tumors have a significantly different conductivity and permittivity from surrounding normal tissue. This high ldquocontrastrdquo in tissue electrical properties, occurring between a few kilohertz and several megahertz, may permit differentiating malignant from benign tissues. Here we show the ability of electrical impedance spectroscopy (EIS) to roughly localize and clearly distinguish cancers from normal tissues and benign lesions. Localization of these lesions is confirmed by simultaneous, in register digital breast tomosynthesis (DBT) mammography or 3-D mammograms.
Keywords :
biological organs; biomedical measurement; cancer; electric impedance imaging; mammography; tumours; benign lesion; breast cancer detection; conductivity; digital breast tomosynthesis; electrical impedance spectroscopy; electrical impedance tomography; mammography; permittivity; regional admittivity spectra; tissue electrical properties; tumors; Biomedical engineering; Breast cancer; Breast neoplasms; Breast tumors; Cancer detection; Electrochemical impedance spectroscopy; Lesions; Mammography; Surface impedance; Tomography; Breast cancer detection; breast cancer detection; digital breast tomosynthesis (DBT) mammography; digital breast tomosynthesis mammography; electrical impedance spectroscopy; electrical impedance spectroscopy (EIS); electrical impedance tomography; electrical impedance tomography (EIT); Algorithms; Breast Neoplasms; Electric Impedance; Female; Humans; Image Processing, Computer-Assisted; Linear Models; Mammography; Predictive Value of Tests; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Tomography;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2008.926049