Open Access
24 July 2013 Automatic characterization of neointimal tissue by intravascular optical coherence tomography
Giovanni J. Ughi, Kristin Steigerwald, Tom Adriaenssens, Walter Desmet, Giulio Guagliumi, Michael Joner, Jan D'Hooge
Author Affiliations +
Abstract
Intravascular optical coherence tomography (IVOCT) is rapidly becoming the method of choice for assessing vessel healing after stent implantation due to its unique axial resolution <20  μm . The amount of neointimal coverage is an important parameter. In addition, the characterization of neointimal tissue maturity is also of importance for an accurate analysis, especially in the case of drug-eluting and bioresorbable stent devices. Previous studies indicated that well-organized mature neointimal tissue appears as a high-intensity, smooth, and homogeneous region in IVOCT images, while lower-intensity signal areas might correspond to immature tissue mainly composed of acellular material. A new method for automatic neointimal tissue characterization, based on statistical texture analysis and a supervised classification technique, is presented. Algorithm training and validation were obtained through the use of 53 IVOCT images supported by histology data from atherosclerotic New Zealand White rabbits. A pixel-wise classification accuracy of 87% and a two-dimensional region–based analysis accuracy of 92% (with sensitivity and specificity of 91% and 93%, respectively) were found, suggesting that a reliable automatic characterization of neointimal tissue was achieved. This may potentially expand the clinical value of IVOCT in assessing the completeness of stent healing and speed up the current analysis methodologies (which are, due to their time- and energy-consuming character, not suitable for application in large clinical trials and clinical practice), potentially allowing for a wider use of IVOCT technology.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
Giovanni J. Ughi, Kristin Steigerwald, Tom Adriaenssens, Walter Desmet, Giulio Guagliumi, Michael Joner, and Jan D'Hooge "Automatic characterization of neointimal tissue by intravascular optical coherence tomography," Journal of Biomedical Optics 19(2), 021104 (24 July 2013). https://doi.org/10.1117/1.JBO.19.2.021104
Published: 24 July 2013
Lens.org Logo
CITATIONS
Cited by 23 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Tissues

Tissue optics

Image classification

Statistical analysis

Optical coherence tomography

Analytical research

Algorithm development

Back to Top