{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T22:00:47Z","timestamp":1781820047452,"version":"3.54.5"},"reference-count":28,"publisher":"IOP Publishing","issue":"6","license":[{"start":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T00:00:00Z","timestamp":1726704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/page\/copyright"},{"start":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T00:00:00Z","timestamp":1726704000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Biomed. Phys. Eng. Express"],"published-print":{"date-parts":[[2024,11,1]]},"abstract":"Abstract<\/jats:title>\n Breast cancer detection and differentiation of breast tissues are critical for accurate diagnosis and treatment planning. This study addresses the challenge of distinguishing between invasive ductal carcinoma (IDC), normal glandular breast tissues (nGBT), and adipose tissue using electrical impedance spectroscopy combined with Gaussian relaxation-time distribution (EIS-GRTD). The primary objective is to investigate the relaxation-time characteristics of these tissues and their potential to differentiate between normal and abnormal breast tissues. We applied a single-point EIS-GRTD measurement to ten mastectomy specimens across a frequency range f<\/jats:italic> = 4 Hz to 5 MHz. The method calculates the differential ratio of the relaxation-time distribution function \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \u03b3<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> between IDC and nGBT, which is denoted by \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n IDC<\/mml:mi>\n \u2212<\/mml:mo>\n nGBT<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n ,<\/mml:mo>\n <\/mml:math>\n <\/jats:inline-formula> and \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \u03b3<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> between IDC and adipose tissues, which is denoted by \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n IDC<\/mml:mi>\n \u2212<\/mml:mo>\n adipose<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n .<\/mml:mo>\n <\/mml:math>\n <\/jats:inline-formula> As a result, the differential ratio of \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \u03b3<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> between IDC and nGBT \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n IDC<\/mml:mi>\n \u2212<\/mml:mo>\n nGBT<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n <\/mml:math>\n <\/jats:inline-formula> is 0.36, and between IDC and adipose \n \n\n<\/jats:tex-math>\n \n \u0394<\/mml:mi>\n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n IDC<\/mml:mi>\n \u2212<\/mml:mo>\n adipose<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n <\/mml:math>\n <\/jats:inline-formula> is 0.27, which included in the \n \n\n<\/jats:tex-math>\n \n \u03b1<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula>-dispersion at \n \n\n<\/jats:tex-math>\n \n \n \n \u03c4<\/mml:mi>\n <\/mml:mrow>\n \n peak<\/mml:mi>\n 1<\/mml:mn>\n <\/mml:mrow>\n <\/mml:msup>\n =<\/mml:mo>\n 0.033<\/mml:mn>\n \u00b1<\/mml:mo>\n 0.001<\/mml:mn>\n \n s<\/mml:mi>\n .<\/mml:mo>\n <\/mml:math>\n <\/jats:inline-formula> In all specimens, the relaxation-time distribution function \n \n\n<\/jats:tex-math>\n \n \u03b3<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> of IDC \n \n\n<\/jats:tex-math>\n \n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n IDC<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n <\/mml:math>\n <\/jats:inline-formula> is higher, and there is no intersection with \n \n\n<\/jats:tex-math>\n \n \u03b3<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> of nGBT \n \n\n<\/jats:tex-math>\n \n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n nGBT<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n <\/mml:math>\n <\/jats:inline-formula> and adipose \n \n\n<\/jats:tex-math>\n \n \n \n \u03b3<\/mml:mi>\n <\/mml:mrow>\n \n adipose<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msup>\n .<\/mml:mo>\n <\/mml:math>\n <\/jats:inline-formula> The difference in \n \n\n<\/jats:tex-math>\n \n \u03b3<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> suggests potential variations in relaxation properties at the molecular or structural level within each breast tissue that contribute to the overall relaxation response. The average mean percentage error \n \n\n<\/jats:tex-math>\n \n \u03b4<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula> for IDC, nGBT, and adipose tissues are 5.90%, 6.33%, and 8.07%, respectively, demonstrating the model\u2019s accuracy and reliability. This study provides novel insights into the use of relaxation-time characteristic for differentiating breast tissue types, offering potential advancements in diagnosis methods. Future research will focus on correlating EIS-GRTD finding with pathological results from the same test sites to further validate the method\u2019s efficacy.<\/jats:p>","DOI":"10.1088\/2057-1976\/ad795f","type":"journal-article","created":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T22:48:31Z","timestamp":1726094911000},"page":"065022","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Detection of invasive ductal carcinoma by electrical impedance spectroscopy implementing gaussian relaxation-time distribution (EIS-GRTD)"],"prefix":"10.1088","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8023-6950","authenticated-orcid":true,"given":"Galih","family":"Setyawan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6015-9422","authenticated-orcid":true,"given":"Kiagus Aufa","family":"Ibrahim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryoma","family":"Ogawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0509-841X","authenticated-orcid":true,"given":"Prima Asmara","family":"Sejati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroshi","family":"Fujimoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroto","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masahiro","family":"Takei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2024,9,19]]},"reference":[{"key":"bpexad795fbib1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2024-06-07","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2024-09-11","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2024-09-19","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}