Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study
書誌事項
- 公開日
- 2017-01-16
- 権利情報
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- https://creativecommons.org/licenses/by/4.0
- https://creativecommons.org/licenses/by/4.0
- DOI
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- 10.1038/srep40683
- 公開者
- Springer Science and Business Media LLC
説明
<jats:title>Abstract</jats:title><jats:p>Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant <jats:italic>vs</jats:italic> benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635–1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient’s anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation.</jats:p>
収録刊行物
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- Scientific Reports
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Scientific Reports 7 (1), 40683-, 2017-01-16
Springer Science and Business Media LLC