Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions

Skin changes associated with alterations in the interstitial matrix and lymph system might provide significant and measurable effects due to the presence of breast cancer. This study aimed to determine if skin electrical resistance changes could serve as a diagnostic and therapeutic biomarker associ...

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Autores principales:	Natasha Andreasen, Henry Crandall, Owen Brimhall, Brittny Miller, Jose Perez-Tamayo, Orjan G. Martinsen, Steven K. Kauwe, Benjamin Sanchez
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Breast cancer bioimpedance skin resistance machine learning Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/0bd5f958d3bd444dbbd235f135098dd3
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spelling	oai:doaj.org-article:0bd5f958d3bd444dbbd235f135098dd32021-11-20T00:02:14ZSkin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions2169-353610.1109/ACCESS.2021.3123569https://doaj.org/article/0bd5f958d3bd444dbbd235f135098dd32021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9591616/https://doaj.org/toc/2169-3536Skin changes associated with alterations in the interstitial matrix and lymph system might provide significant and measurable effects due to the presence of breast cancer. This study aimed to determine if skin electrical resistance changes could serve as a diagnostic and therapeutic biomarker associated with physiological changes in patients with malignant versus benign breast cancer lesions. Forty-eight women (24 with malignant cancer, 23 with benign lesions) were enrolled in this study. Repeated skin resistance measurements were performed within the same session and 1 week after the first measurement in the breast lymphatic region and non-breast lymphathic regions. Intraclass correlation coefficients were calculated to determine the technique’s intrasession and intersession reproducibility. Data were then normalized as a mean of comparing cross-sectional differences between malignant and benign lesions of the breast. Six months longitudinal data from six patients that received therapy were analyzed to detect the effect of therapy. Standard descriptive statistics were used to compare ratiometric differences between groups. Skin resistance data were used to train a machine learning random forest classification algorithm to diagnose breast cancer lesions. Significant differences between malignant and benign breast lesions were obtained (p<0.01), also pre- and post-treatment (p<0.05). The diagnostic algorithm demonstrated the capability to classify breast cancer with an area under the curve of 0.68, sensitivity of 66.3%, specificity of 78.5%, positive predictive value 70.7% and negative predictive value 75.1%. Measurement of skin resistance in patients with breast cancer may serve as a convenient screening tool for breast cancer and evaluation of therapy. Further work is warranted to improve our approach and further investigate the biophysical mechanisms leading to the observed changes.Natasha AndreasenHenry CrandallOwen BrimhallBrittny MillerJose Perez-TamayoOrjan G. MartinsenSteven K. KauweBenjamin SanchezIEEEarticleBreast cancerbioimpedanceskin resistancemachine learningElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 152322-152332 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Breast cancer bioimpedance skin resistance machine learning Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Breast cancer bioimpedance skin resistance machine learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Natasha Andreasen Henry Crandall Owen Brimhall Brittny Miller Jose Perez-Tamayo Orjan G. Martinsen Steven K. Kauwe Benjamin Sanchez Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions
description	Skin changes associated with alterations in the interstitial matrix and lymph system might provide significant and measurable effects due to the presence of breast cancer. This study aimed to determine if skin electrical resistance changes could serve as a diagnostic and therapeutic biomarker associated with physiological changes in patients with malignant versus benign breast cancer lesions. Forty-eight women (24 with malignant cancer, 23 with benign lesions) were enrolled in this study. Repeated skin resistance measurements were performed within the same session and 1 week after the first measurement in the breast lymphatic region and non-breast lymphathic regions. Intraclass correlation coefficients were calculated to determine the technique’s intrasession and intersession reproducibility. Data were then normalized as a mean of comparing cross-sectional differences between malignant and benign lesions of the breast. Six months longitudinal data from six patients that received therapy were analyzed to detect the effect of therapy. Standard descriptive statistics were used to compare ratiometric differences between groups. Skin resistance data were used to train a machine learning random forest classification algorithm to diagnose breast cancer lesions. Significant differences between malignant and benign breast lesions were obtained (p<0.01), also pre- and post-treatment (p<0.05). The diagnostic algorithm demonstrated the capability to classify breast cancer with an area under the curve of 0.68, sensitivity of 66.3%, specificity of 78.5%, positive predictive value 70.7% and negative predictive value 75.1%. Measurement of skin resistance in patients with breast cancer may serve as a convenient screening tool for breast cancer and evaluation of therapy. Further work is warranted to improve our approach and further investigate the biophysical mechanisms leading to the observed changes.
format	article
author	Natasha Andreasen Henry Crandall Owen Brimhall Brittny Miller Jose Perez-Tamayo Orjan G. Martinsen Steven K. Kauwe Benjamin Sanchez
author_facet	Natasha Andreasen Henry Crandall Owen Brimhall Brittny Miller Jose Perez-Tamayo Orjan G. Martinsen Steven K. Kauwe Benjamin Sanchez
author_sort	Natasha Andreasen
title	Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions
title_short	Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions
title_full	Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions
title_fullStr	Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions
title_full_unstemmed	Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions
title_sort	skin electrical resistance as a diagnostic and therapeutic biomarker of breast cancer measuring lymphatic regions
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/0bd5f958d3bd444dbbd235f135098dd3
work_keys_str_mv	AT natashaandreasen skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT henrycrandall skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT owenbrimhall skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT brittnymiller skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT josepereztamayo skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT orjangmartinsen skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT stevenkkauwe skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions AT benjaminsanchez skinelectricalresistanceasadiagnosticandtherapeuticbiomarkerofbreastcancermeasuringlymphaticregions
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Skin Electrical Resistance as a Diagnostic and Therapeutic Biomarker of Breast Cancer Measuring Lymphatic Regions

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