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High-Frequency (30 MHz-6 GHz) Breast Tissue Characterization Stabilized by Suction Force for Intraoperative Tumor Margin Assessment.
Mokhtari Dowlatabad, Hadi; Mamdouh, Amir; Yousefpour, Narges; Mahdavi, Reihane; Zandi, Ashkan; Hoseinpour, Parisa; Moosavi-Kiasari, Seyed Mohammad Sadegh; Abbasvandi, Fereshte; Kordehlachin, Yasin; Parniani, Mohammad; Mohammadpour-Aghdam, Karim; Faranoush, Pooya; Foroughi-Gilvaee, Mohammad Reza; Abdolahad, Mohammad.
Afiliação
  • Mokhtari Dowlatabad H; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Mamdouh A; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Yousefpour N; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Mahdavi R; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Zandi A; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Hoseinpour P; Department of Pathology, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 15179-64311, Iran.
  • Moosavi-Kiasari SMS; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Abbasvandi F; ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 15179-64311, Iran.
  • Kordehlachin Y; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Parniani M; Pathology Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 15179-64311, Iran.
  • Mohammadpour-Aghdam K; Center of Excellence for Applied Electromagnetic Systems, University of Tehran, Tehran 14399-57131, Iran.
  • Faranoush P; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
  • Foroughi-Gilvaee MR; Pediatric Growth and Development Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran 14496-14535, Iran.
  • Abdolahad M; Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran 14399-57131, Iran.
Diagnostics (Basel) ; 13(2)2023 Jan 04.
Article em En | MEDLINE | ID: mdl-36672989
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Irã

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Irã