title: Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy.
abstract: Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.
authors.affiliation: Korea Advanced Institute of Science and Technology, Department of Bio and Brain Engineering, Daejeon 34141, Korea.
authors.forename: Jihye
authors.initials: J
authors.lastname: Seo
authors.affiliation: Korea Advanced Institute of Science and Technology, Department of Bio and Brain Engineering, Daejeon 34141, KoreabKorea Advanced Institute of Science and Technology, KI for the BioCentury, Daejeon 34141, Korea.
authors.forename: Yuri
authors.initials: Y
authors.lastname: An
authors.affiliation: Korea Advanced Institute of Science and Technology, Department of Bio and Brain Engineering, Daejeon 34141, KoreabKorea Advanced Institute of Science and Technology, KI for the BioCentury, Daejeon 34141, Korea.
authors.forename: Jungsul
authors.initials: J
authors.lastname: Lee
authors.affiliation: Korea Advanced Institute of Science and Technology, Department of Bio and Brain Engineering, Daejeon 34141, Korea.
authors.forename: Taeyun
authors.initials: T
authors.lastname: Ku
authors.affiliation: Vieworks Co., R&D Center, Gyeonggi-do 14055, Korea.
authors.forename: Yujung
authors.initials: Y
authors.lastname: Kang
authors.affiliation: Yonsei University College of Medicine, Department of Internal Medicine, Seoul 03722, Korea.
authors.forename: Chulwoo
authors.initials: C
authors.lastname: Ahn
authors.affiliation: Korea Advanced Institute of Science and Technology, Department of Bio and Brain Engineering, Daejeon 34141, KoreabKorea Advanced Institute of Science and Technology, KI for the BioCentury, Daejeon 34141, Korea.
authors.forename: Chulhee
authors.initials: C
authors.lastname: Choi
mesh_terms: D017719:Diabetic Foot / Q000000981:diagnostic imaging*; D005260:Female; D005456:Fluorescent Dyes / Q000737:chemistry / Q000493:pharmacokinetics; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007208:Indocyanine Green / Q000737:chemistry / Q000493:pharmacokinetics; D008297:Male; D008875:Middle Aged; D061848:Optical Imaging / Q000379:methods*; D025341:Principal Component Analysis
chemical_list: D005456:Fluorescent Dyes; D007208:Indocyanine Green