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Journal of Biomedical Optics

Elastic scattering spectroscopy for detection of cancer risk in Barrett's esophagus: experimental and clinical validation of error removal by orthogonal subtraction for increasing accuracy
Author(s): Ying Zhu; Thomas Fearn; Gary D. Mackenzie; Benjamin R. Clark; Jason M. Dunn; Irving J. Bigio; Stephen G. Bown; Laurence B. Lovat
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Paper Abstract

Elastic scattering spectroscopy (ESS) may be used to detect high-grade dysplasia (HGD) or cancer in Barrett's esophagus (BE). When spectra are measured in vivo by a hand-held optical probe, variability among replicated spectra from the same site can hinder the development of a diagnostic model for cancer risk. An experiment was carried out on excised tissue to investigate how two potential sources of this variability, pressure and angle, influence spectral variability, and the results were compared with the variations observed in spectra collected in vivo from patients with Barrett's esophagus. A statistical method called error removal by orthogonal subtraction (EROS) was applied to model and remove this measurement variability, which accounted for 96.6% of the variation in the spectra, from the in vivo data. Its removal allowed the construction of a diagnostic model with specificity improved from 67% to 82% (with sensitivity fixed at 90%). The improvement was maintained in predictions on an independent in vivo data set. EROS works well as an effective pretreatment for Barrett's in vivo data by identifying measurement variability and ameliorating its effect. The procedure reduces the complexity and increases the accuracy and interpretability of the model for classification and detection of cancer risk in Barrett's esophagus.

Paper Details

Date Published: 1 July 2009
PDF: 7 pages
J. Biomed. Opt. 14(4) 044022 doi: 10.1117/1.3194291
Published in: Journal of Biomedical Optics Volume 14, Issue 4
Show Author Affiliations
Ying Zhu, Univ. College London (United Kingdom)
Thomas Fearn, Univ. College London (United Kingdom)
Gary D. Mackenzie, Univ. College London (United Kingdom)
Benjamin R. Clark, Univ. College London (United Kingdom)
Jason M. Dunn, Univ. College London (United Kingdom)
Irving J. Bigio, Boston Univ. (United States)
Stephen G. Bown, Univ. College London (United Kingdom)
Laurence B. Lovat, Univ. College London (United Kingdom)

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