Near-IR imaging of atheromas in living arterial tissue

• Published in: Analytical chemistry (Washington) 1993-05, Vol.65 (9), p.1247-1256
• Main Authors: Cassis, Lisa A, Lodder, Robert A
• Format: Article
• Language: English
• Subjects: Apolipoproteins - metabolism; Arteries - metabolism; Arteries - pathology; Arteriosclerosis - metabolism; Arteriosclerosis - pathology; Biochemistry; Biological and medical sciences; Cardiovascular system; Circulatory system; Humans; Image Processing, Computer-Assisted; Investigative techniques, diagnostic techniques (general aspects); Lipoproteins - metabolism; Medical research; Medical sciences; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Scientific imaging; Spectrophotometry, Infrared
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/ac00057a023

A near-IR imaging system and parallel vector supercomputer are used with a fiber-optic probe to produce chemical maps of the intimal surface of living arteries. Spectrometric information collected at hundreds of near-IR wavelengths is assembled into color pictures of the lipoprotein and apolipoprotein composition of atheromas using a vectorized 3-D cellular automaton-based algorithm that operates in parallel. The nonparametric mathematics developed to identify and quantify the constituents of each voxel in the artery wall avoid the matrix factorizations that generate excess error in other pattern recognition methods and permit analysis in a wavelength space of over 1000 dimensions using fewer than 100 calibration samples. A surface feature resolution of 5.5 microns and depth resolution of 6.5 microns are achieved with the system. Data from the fiber optics confirm the injury hypothesis of lesion formation and the differing roles of HDL and LDL in cholesterol transport. In clinical studies, approximately 1/2 of human arterial lesions appear fibrous and contain little or no lipid. As such, these lesions would not be expected to regress in response to cholesterol-lowering agents such as lovastatin. Identification of lesion types in vivo will enhance the efficacy of treatment programs.