Special Section on Optical Coherence Tomography and Interferometry: Advanced Engineering and Biomedical Applications

Three-dimensional computational analysis of optical coherence tomography images for the detection of soft tissue sarcomas

[+] Author Affiliations
Shang Wang, Chih-Hao Liu

University of Houston, Department of Biomedical Engineering, 3605 Cullen Boulevard, Houston, Texas 77204-5060

Valery P. Zakharov

Samara State Aerospace University, Department of Radiotechnical Engineering, Moskovskoe shosse 34, Samara, 443086, Russia

Alexander J. Lazar, Raphael E. Pollock

The University of Texas M.D. Anderson Cancer Center, Sarcoma Research Center, 1515 Holcombe Boulevard, Houston, Texas 77030

Kirill V. Larin

University of Houston, Department of Biomedical Engineering, 3605 Cullen Boulevard, Houston, Texas 77204-5060

Baylor College of Medicine, Department of Molecular Physiology and Biophysics, One Baylor Plaza, Houston, Texas 77030

J. Biomed. Opt. 19(2), 021102 (Jun 27, 2013). doi:10.1117/1.JBO.19.2.021102
History: Received April 2, 2013; Revised April 29, 2013; Accepted May 1, 2013
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Abstract.  We present a three-dimensional (3-D) computational method to detect soft tissue sarcomas with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Three parameters are investigated and quantified from OCT images as the indicators for the tissue diagnosis including the signal attenuation (A-line slope), the standard deviation of the signal fluctuations (speckles), and the exponential decay coefficient of its spatial frequency spectrum. The detection of soft tissue sarcomas relies on the combination of these three parameters, which are related to the optical attenuation characteristics and the structural features of the tissue. Pilot experiments were performed on ex vivo human tissue samples with homogeneous pieces (both normal and abnormal) and tumor margins. Our results demonstrate the feasibility of this computational method in the differentiation of soft tissue sarcomas from normal tissues. The features of A-line-based detection and 3-D quantitative analysis yield promise for a computer-aided technique capable of accurately and automatically identifying resection margins of soft tissue sarcomas during surgical treatment.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Shang Wang ; Chih-Hao Liu ; Valery P. Zakharov ; Alexander J. Lazar ; Raphael E. Pollock, et al.
"Three-dimensional computational analysis of optical coherence tomography images for the detection of soft tissue sarcomas", J. Biomed. Opt. 19(2), 021102 (Jun 27, 2013). ; http://dx.doi.org/10.1117/1.JBO.19.2.021102


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