Effects of axial resolution improvement on optical coherence tomography (OCT) imaging of gastrointestinal tissues.
Optical coherence tomography (OCT) is an emerging medical imaging technology which generates high resolution, cross-sectional images in situ, without the need for excisional biopsy. Previous clinical studies using endoscopic OCT with standard 10-15 microm axial resolution have demonstrated its capability in diagnosing Barrett's esophagus (BE) and high-grade dysplasia (HGD). Quantitative OCT image analysis has shown promise for detecting HGD in Barrett's esophagus patients. We recently developed an endoscopic OCT system with an improved axial resolution of approximately 5 microm. The goal in this manuscript is to compare standard resolution OCT and ultrahigh resolution OCT (UHR-OCT) for image quality and computer-aided detection using normal and Barrett's esophagus. OCT images of gastrointestinal (GI) tissues were obtained using UHR-OCT (5.5 microm) and standard resolution OCT (13 microm). Image quality including the speckle size and sharpness was compared. Texture features of endoscopic OCT images from normal and Barrett's esophagus were extracted using quantitative metrics including spatial frequency analysis and statistical texture analysis. These features were analyzed using principal component analysis (PCA) to reduce the vector dimension and increase the discriminative power, followed by linear discrimination analysis (LDA). UHR-OCT images of GI tissues improved visualization of fine architectural features compared to standard resolution OCT. In addition, the quantitative image feature analysis showed enhanced discrimination of normal and Barrett's esophagus with UHR-OCT. The ability of UHR-OCT to resolve tissue morphology at improved resolution enables visualization of subtle features in OCT images, which may be useful in disease diagnosis. Enhanced classification of image features using UHR-OCT promises to help in the computer-aided diagnosis of GI diseases.
Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Yu
Y
Chen
Aaron D
AD
Aguirre
Pei-Lin
PL
Hsiung
Shu-Wei
SW
Huang
Hiroshi
H
Mashimo
Joseph M
JM
Schmitt
James G
JG
Fujimoto
D001471:Barrett Esophagus / Q000473:pathology*; D004945:Esophagoscopy; D004947:Esophagus / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D041623:Tomography, Optical Coherence / Q000379:methods*