Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue

Maarten Grootendorst; Anthony J. Fitzgerald; Susan G.Brouwer De Koning; Aida Santaolalla; Alessia Portieri; Mieke Van Hemelrijck; Matthew R. Young; Julie Owen; Massi Cariati; Michael Pepper; Vincent P. Wallace; Sarah Pinder; Arnie Purushotham; Aida Santaolalla

doi:10.1364/BOE.8.002932

Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue

Maarten Grootendorst, Anthony J. Fitzgerald, Susan G.Brouwer De Koning, Aida Santaolalla, Alessia Portieri, Mieke Van Hemelrijck, Matthew R. Young, Julie Owen, Massi Cariati, Michael Pepper, Vincent P. Wallace, Sarah Pinder, Arnie Purushotham, Aida Santaolalla

Comprehensive Cancer Centre

Research output: Contribution to journal › Article › peer-review

64 Citations (Scopus)

176 Downloads (Pure)

Abstract

Since nearly 20% of breast-conserving surgeries (BCS) require re-operation, there is a clear need for developing new techniques to more accurately assess tumor resection margins intraoperatively. This study evaluates the diagnostic accuracy of a handheld terahertz pulsed imaging (TPI) system to discriminate benign from malignant breast tissue ex vivo. Forty six freshly excised breast cancer samples were scanned with a TPI handheld probe system, and histology was obtained for comparison. The image pixels on TPI were classified using (1) parameters in combination with support vector machine (SVM) and (2) Gaussian wavelet deconvolution in combination with Bayesian classification. The results were an accuracy, sensitivity, specificity of 75%, 86%, 66% for method 1, and 69%, 87%, 54% for method 2 respectively. This demonstrates the probe can discriminate invasive breast cancer from benign breast tissue with an encouraging degree of accuracy, warranting further study.

Original language	English
Article number	#286058
Pages (from-to)	2932-2945
Journal	Biomedical Optics Express
Volume	8
Issue number	6
Early online date	9 May 2017
DOIs	https://doi.org/10.1364/BOE.8.002932
Publication status	Published - 1 Jun 2017

Keywords

Medical and biological imaging
Terahertz imaging
Tissue characterization

UN SDGs

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

Access to Document

10.1364/BOE.8.002932Licence: Other

Use of a handheld terahertz_GROOTENDORST_Publishedonline9May2017_GOLD VoRFinal published version, 3.52 MBLicence: Other

Cite this

Grootendorst, M., Fitzgerald, A. J., De Koning, S. G. B., Santaolalla, A., Portieri, A., Van Hemelrijck, M., Young, M. R., Owen, J., Cariati, M., Pepper, M., Wallace, V. P., Pinder, S., Purushotham, A., & Santaolalla, A. (2017). Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue. Biomedical Optics Express, 8(6), 2932-2945. Article #286058. https://doi.org/10.1364/BOE.8.002932

@article{abc4db0cbfc3449e979d87d7fa6a5679,

title = "Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue",

abstract = "Since nearly 20% of breast-conserving surgeries (BCS) require re-operation, there is a clear need for developing new techniques to more accurately assess tumor resection margins intraoperatively. This study evaluates the diagnostic accuracy of a handheld terahertz pulsed imaging (TPI) system to discriminate benign from malignant breast tissue ex vivo. Forty six freshly excised breast cancer samples were scanned with a TPI handheld probe system, and histology was obtained for comparison. The image pixels on TPI were classified using (1) parameters in combination with support vector machine (SVM) and (2) Gaussian wavelet deconvolution in combination with Bayesian classification. The results were an accuracy, sensitivity, specificity of 75%, 86%, 66% for method 1, and 69%, 87%, 54% for method 2 respectively. This demonstrates the probe can discriminate invasive breast cancer from benign breast tissue with an encouraging degree of accuracy, warranting further study.",

keywords = "Medical and biological imaging, Terahertz imaging, Tissue characterization",

author = "Maarten Grootendorst and Fitzgerald, {Anthony J.} and {De Koning}, {Susan G.Brouwer} and Aida Santaolalla and Alessia Portieri and {Van Hemelrijck}, Mieke and Young, {Matthew R.} and Julie Owen and Massi Cariati and Michael Pepper and Wallace, {Vincent P.} and Sarah Pinder and Arnie Purushotham and Aida Santaolalla",

year = "2017",

month = jun,

day = "1",

doi = "10.1364/BOE.8.002932",

language = "English",

volume = "8",

pages = "2932--2945",

journal = "Biomedical Optics Express",

issn = "2156-7085",

publisher = "The Optical Society",

number = "6",

}

Grootendorst, M, Fitzgerald, AJ, De Koning, SGB, Santaolalla, A, Portieri, A, Van Hemelrijck, M, Young, MR, Owen, J, Cariati, M, Pepper, M, Wallace, VP, Pinder, S , Purushotham, A & Santaolalla, A 2017, 'Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue', Biomedical Optics Express, vol. 8, no. 6, #286058, pp. 2932-2945. https://doi.org/10.1364/BOE.8.002932

TY - JOUR

T1 - Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue

AU - Grootendorst, Maarten

AU - Fitzgerald, Anthony J.

AU - De Koning, Susan G.Brouwer

AU - Santaolalla, Aida

AU - Portieri, Alessia

AU - Van Hemelrijck, Mieke

AU - Young, Matthew R.

AU - Owen, Julie

AU - Cariati, Massi

AU - Pepper, Michael

AU - Wallace, Vincent P.

AU - Pinder, Sarah

AU - Purushotham, Arnie

AU - Santaolalla, Aida

PY - 2017/6/1

Y1 - 2017/6/1

N2 - Since nearly 20% of breast-conserving surgeries (BCS) require re-operation, there is a clear need for developing new techniques to more accurately assess tumor resection margins intraoperatively. This study evaluates the diagnostic accuracy of a handheld terahertz pulsed imaging (TPI) system to discriminate benign from malignant breast tissue ex vivo. Forty six freshly excised breast cancer samples were scanned with a TPI handheld probe system, and histology was obtained for comparison. The image pixels on TPI were classified using (1) parameters in combination with support vector machine (SVM) and (2) Gaussian wavelet deconvolution in combination with Bayesian classification. The results were an accuracy, sensitivity, specificity of 75%, 86%, 66% for method 1, and 69%, 87%, 54% for method 2 respectively. This demonstrates the probe can discriminate invasive breast cancer from benign breast tissue with an encouraging degree of accuracy, warranting further study.

AB - Since nearly 20% of breast-conserving surgeries (BCS) require re-operation, there is a clear need for developing new techniques to more accurately assess tumor resection margins intraoperatively. This study evaluates the diagnostic accuracy of a handheld terahertz pulsed imaging (TPI) system to discriminate benign from malignant breast tissue ex vivo. Forty six freshly excised breast cancer samples were scanned with a TPI handheld probe system, and histology was obtained for comparison. The image pixels on TPI were classified using (1) parameters in combination with support vector machine (SVM) and (2) Gaussian wavelet deconvolution in combination with Bayesian classification. The results were an accuracy, sensitivity, specificity of 75%, 86%, 66% for method 1, and 69%, 87%, 54% for method 2 respectively. This demonstrates the probe can discriminate invasive breast cancer from benign breast tissue with an encouraging degree of accuracy, warranting further study.

KW - Medical and biological imaging

KW - Terahertz imaging

KW - Tissue characterization

UR - http://www.scopus.com/inward/record.url?scp=85020207669&partnerID=8YFLogxK

U2 - 10.1364/BOE.8.002932

DO - 10.1364/BOE.8.002932

M3 - Article

AN - SCOPUS:85020207669

SN - 2156-7085

VL - 8

SP - 2932

EP - 2945

JO - Biomedical Optics Express

JF - Biomedical Optics Express

IS - 6

M1 - #286058

ER -

Use of a handheld terahertz pulsed imaging device to differentiate benign and malignant breast tissue

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this