A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment

David Gur; Bin Zheng; Dror Lederman; Sreeram Dhurjaty; Jules Sumkin; Margarita Zuley

doi:10.1117/12.844452

A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment

David Gur, Bin Zheng, Dror Lederman, Sreeram Dhurjaty, Jules Sumkin, Margarita Zuley

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

A new resonance-frequency based electronic impedance spectroscopy (REIS) system with multi-probes, including one central probe and six external probes that are designed to contact the breast skin in a circular form with a radius of 60 millimeters to the central ("nipple") probe, has been assembled and installed in our breast imaging facility. We are conducting a prospective clinical study to test the performance of this REIS system in identifying younger women (< 50 years old) at higher risk for having or developing breast cancer. In this preliminary analysis, we selected a subset of 100 examinations. Among these, 50 examinations were recommended for a biopsy due to detection of a highly suspicious breast lesion and 50 were determined negative during mammography screening. REIS output signal sweeps that we used to compute an initial feature included both amplitude and phase information representing differences between corresponding (matched) EIS signal values acquired from the left and right breasts. A genetic algorithm was applied to reduce the feature set and optimize a support vector machine (SVM) to classify the REIS examinations into "biopsy recommended" and "non-biopsy" recommended groups. Using the leave-one-case-out testing method, the classification performance as measured by the area under the receiver operating characteristic (ROC) curve was 0.816 ± 0.042. This pilot analysis suggests that the new multi-probe-based REIS system could potentially be used as a risk stratification tool to identify pre-screened young women who are at higher risk of having or developing breast cancer.

Original language	English
Title of host publication	Medical Imaging 2010
Subtitle of host publication	Image Perception, Observer Performance, and Technology Assessment
DOIs	https://doi.org/10.1117/12.844452
State	Published - 1 Dec 2010
Externally published	Yes
Event	Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment - San Diego, CA, United States Duration: 17 Feb 2010 → 18 Feb 2010

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	7627
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment
Country/Territory	United States
City	San Diego, CA
Period	17/02/10 → 18/02/10

Keywords

Electrical impedance spectroscopy (EIS)
breast cancer
resonance frequency
risk stratification
support vector machine
technology assessment

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Biomaterials
Radiology Nuclear Medicine and imaging

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1117/12.844452

Cite this

Gur, D., Zheng, B., Lederman, D., Dhurjaty, S., Sumkin, J., & Zuley, M. (2010). A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment. In Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment Article 76271B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7627). https://doi.org/10.1117/12.844452

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title = "A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment",

abstract = "A new resonance-frequency based electronic impedance spectroscopy (REIS) system with multi-probes, including one central probe and six external probes that are designed to contact the breast skin in a circular form with a radius of 60 millimeters to the central ({"}nipple{"}) probe, has been assembled and installed in our breast imaging facility. We are conducting a prospective clinical study to test the performance of this REIS system in identifying younger women (< 50 years old) at higher risk for having or developing breast cancer. In this preliminary analysis, we selected a subset of 100 examinations. Among these, 50 examinations were recommended for a biopsy due to detection of a highly suspicious breast lesion and 50 were determined negative during mammography screening. REIS output signal sweeps that we used to compute an initial feature included both amplitude and phase information representing differences between corresponding (matched) EIS signal values acquired from the left and right breasts. A genetic algorithm was applied to reduce the feature set and optimize a support vector machine (SVM) to classify the REIS examinations into {"}biopsy recommended{"} and {"}non-biopsy{"} recommended groups. Using the leave-one-case-out testing method, the classification performance as measured by the area under the receiver operating characteristic (ROC) curve was 0.816 ± 0.042. This pilot analysis suggests that the new multi-probe-based REIS system could potentially be used as a risk stratification tool to identify pre-screened young women who are at higher risk of having or developing breast cancer.",

keywords = "Electrical impedance spectroscopy (EIS), breast cancer, resonance frequency, risk stratification, support vector machine, technology assessment",

author = "David Gur and Bin Zheng and Dror Lederman and Sreeram Dhurjaty and Jules Sumkin and Margarita Zuley",

year = "2010",

month = dec,

day = "1",

doi = "10.1117/12.844452",

language = "English",

isbn = "9780819480286",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

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note = "Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment ; Conference date: 17-02-2010 Through 18-02-2010",

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Gur, D, Zheng, B, Lederman, D, Dhurjaty, S, Sumkin, J & Zuley, M 2010, A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment. in Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment., 76271B, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, San Diego, CA, United States, 17/02/10. https://doi.org/10.1117/12.844452

A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment. / Gur, David; Zheng, Bin; Lederman, Dror et al.
Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment. 2010. 76271B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7627).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T2 - Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment

AU - Gur, David

AU - Zheng, Bin

AU - Lederman, Dror

AU - Dhurjaty, Sreeram

AU - Sumkin, Jules

AU - Zuley, Margarita

PY - 2010/12/1

Y1 - 2010/12/1

N2 - A new resonance-frequency based electronic impedance spectroscopy (REIS) system with multi-probes, including one central probe and six external probes that are designed to contact the breast skin in a circular form with a radius of 60 millimeters to the central ("nipple") probe, has been assembled and installed in our breast imaging facility. We are conducting a prospective clinical study to test the performance of this REIS system in identifying younger women (< 50 years old) at higher risk for having or developing breast cancer. In this preliminary analysis, we selected a subset of 100 examinations. Among these, 50 examinations were recommended for a biopsy due to detection of a highly suspicious breast lesion and 50 were determined negative during mammography screening. REIS output signal sweeps that we used to compute an initial feature included both amplitude and phase information representing differences between corresponding (matched) EIS signal values acquired from the left and right breasts. A genetic algorithm was applied to reduce the feature set and optimize a support vector machine (SVM) to classify the REIS examinations into "biopsy recommended" and "non-biopsy" recommended groups. Using the leave-one-case-out testing method, the classification performance as measured by the area under the receiver operating characteristic (ROC) curve was 0.816 ± 0.042. This pilot analysis suggests that the new multi-probe-based REIS system could potentially be used as a risk stratification tool to identify pre-screened young women who are at higher risk of having or developing breast cancer.

AB - A new resonance-frequency based electronic impedance spectroscopy (REIS) system with multi-probes, including one central probe and six external probes that are designed to contact the breast skin in a circular form with a radius of 60 millimeters to the central ("nipple") probe, has been assembled and installed in our breast imaging facility. We are conducting a prospective clinical study to test the performance of this REIS system in identifying younger women (< 50 years old) at higher risk for having or developing breast cancer. In this preliminary analysis, we selected a subset of 100 examinations. Among these, 50 examinations were recommended for a biopsy due to detection of a highly suspicious breast lesion and 50 were determined negative during mammography screening. REIS output signal sweeps that we used to compute an initial feature included both amplitude and phase information representing differences between corresponding (matched) EIS signal values acquired from the left and right breasts. A genetic algorithm was applied to reduce the feature set and optimize a support vector machine (SVM) to classify the REIS examinations into "biopsy recommended" and "non-biopsy" recommended groups. Using the leave-one-case-out testing method, the classification performance as measured by the area under the receiver operating characteristic (ROC) curve was 0.816 ± 0.042. This pilot analysis suggests that the new multi-probe-based REIS system could potentially be used as a risk stratification tool to identify pre-screened young women who are at higher risk of having or developing breast cancer.

KW - Electrical impedance spectroscopy (EIS)

KW - breast cancer

KW - resonance frequency

KW - risk stratification

KW - support vector machine

KW - technology assessment

UR - https://www.scopus.com/pages/publications/79551715832

U2 - 10.1117/12.844452

DO - 10.1117/12.844452

M3 - Conference contribution

AN - SCOPUS:79551715832

SN - 9780819480286

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2010

Y2 - 17 February 2010 through 18 February 2010

ER -

Gur D, Zheng B, Lederman D, Dhurjaty S, Sumkin J, Zuley M. A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment. In Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment. 2010. 76271B. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.844452

A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: A preliminary assessment

Abstract

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Keywords

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UN SDGs

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