High-Frequency (30 MHz–6 GHz) Breast Tissue Characterization Stabilized by Suction Force for Intraoperative Tumor Margin Assessment
Hadi Mokhtari Dowlatabad,
Amir Mamdouh,
Narges Yousefpour,
Reihane Mahdavi,
Ashkan Zandi,
Parisa Hoseinpour,
Seyed Mohammad Sadegh Moosavi-Kiasari,
Fereshte Abbasvandi,
Yasin Kordehlachin,
Mohammad Parniani,
Karim Mohammadpour-Aghdam,
Pooya Faranoush,
Mohammad Reza Foroughi-Gilvaee,
Mohammad Abdolahad
Affiliations
Hadi Mokhtari Dowlatabad
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Amir Mamdouh
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Narges Yousefpour
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Reihane Mahdavi
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Ashkan Zandi
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Parisa Hoseinpour
Department of Pathology, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 15179-64311, Iran
Seyed Mohammad Sadegh Moosavi-Kiasari
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Fereshte Abbasvandi
ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 15179-64311, Iran
Yasin Kordehlachin
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Mohammad Parniani
Pathology Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 15179-64311, Iran
Karim Mohammadpour-Aghdam
Center of Excellence for Applied Electromagnetic Systems, University of Tehran, Tehran 14399-57131, Iran
Pooya Faranoush
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Mohammad Reza Foroughi-Gilvaee
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
Mohammad Abdolahad
Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran
A gigahertz (GHz) range antenna formed by a coaxial probe has been applied for sensing cancerous breast lesions in the scanning platform with the assistance of a suction tube. The sensor structure was a planar central layer and a metallic sheath of size of 3 cm2 connected to a network analyzer (keySight FieldFox N9918A) with operational bandwidth up to 26.5 GHz. Cancer tumor cells have significantly higher water content (as a dipolar molecule) than normal breast cells, changing their polarization responses and dielectric losses to incoming GHz-based stimulation. Principal component analysis named S11, related to the dispersion ratio of the input signal, is used as a parameter to identify malignant tumor cells in a mouse model (in vivo) and tumor specimens of breast cancer patients (in vitro) (both central and marginal parts). The results showed that S11 values in the frequency range from 5 to 6 GHz were significantly higher in cancer-involved breast lesions. Histopathological analysis was the gold standard for achieving the S11 calibration to distinguish normal from cancerous lesions. Our calibration on tumor specimens presented 82% positive predictive value (PPV), 100% negative predictive value (NPV), and 86% accuracy. Our goal is to apply this system as an in vivo non-invasive tumor margin scanner after further investigations in the future.
