TY - JOUR
T1 - Three-dimensional computational analysis of optical coherence tomography images for the detection of soft tissue sarcomas
AU - Wang, Shang
AU - Liu, Chih Hao
AU - Zakharov, Valery P.
AU - Lazar, Alexander J.
AU - Pollock, Raphael E.
AU - Larin, Kirill V.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Optical coherence tomography
KW - computational image analysis
KW - soft tissue sarcomas
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U2 - 10.1117/1.JBO.19.2.021102
DO - 10.1117/1.JBO.19.2.021102
M3 - Article
C2 - 23807552
AN - SCOPUS:84887849977
SN - 1083-3668
VL - 19
JO - Journal of Biomedical Optics
JF - Journal of Biomedical Optics
IS - 2
M1 - 021102
ER -