Optical Coherence Tomography, Near-Infrared Spectroscopy, and Near-Infrared Fluorescence Molecular Imaging

2016 ◽  
pp. 91-106
Author(s):  
Ismail Dogu Kilic ◽  
Roberta Serdoz ◽  
Enrico Fabris ◽  
Farouc Amin Jaffer ◽  
Carlo Di Mario
Keyword(s):  
Optical Coherence Tomography ◽  
Infrared Spectroscopy ◽  
Molecular Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Optical Coherence ◽  
Near Infrared Fluorescence ◽  
Fluorescence Molecular Imaging

scholarly journals Optical coherence tomography – near infrared spectroscopy system and catheter for intravascular imaging

2013 ◽  
Vol 21 (25) ◽  
pp. 30849 ◽  
Author(s):  
Ali M. Fard ◽  
Paulino Vacas-Jacques ◽  
Ehsan Hamidi ◽  
Hao Wang ◽  
Robert W. Carruth ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Intravascular Imaging ◽  
Optical Coherence ◽  
Spectroscopy System

Near Infrared Spectroscopy in Optical Coherence Tomography

2012 ◽  
Vol 20 (1) ◽  
pp. 237-247 ◽  
Author(s):  
Chenyu Wang ◽  
Jinman Kim ◽  
Craig T. Jin ◽  
Philip H.W. Leong ◽  
Alistair McEwan
Keyword(s):  
Optical Coherence Tomography ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Optical Coherence

In vivo relationship between near-infrared spectroscopy-detected lipid-rich plaques and morphological plaque characteristics by optical coherence tomography and intravascular ultrasound: a multimodality intravascular imaging study

2020 ◽  
Author(s):  
Christian Zanchin ◽  
Yasushi Ueki ◽  
Sylvain Losdat ◽  
Gregor Fahrni ◽  
Joost Daemen ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Infrared Spectroscopy ◽  
Intravascular Ultrasound ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multimodality Imaging ◽  
Plaque Burden ◽  
Optical Coherence ◽  
Coronary Syndrome ◽  
Automated Method

Abstract Aims We assessed morphological features of near-infrared spectroscopy (NIRS)-detected lipid-rich plaques (LRPs) by using optical coherence tomography (OCT) and intravascular ultrasound (IVUS). Methods and results IVUS-NIRS and OCT were performed in the two non-infarct-related arteries (non-IRAs) in patients undergoing percutaneous coronary intervention for treatment of an acute coronary syndrome. A lesion was defined as the 4 mm segment with the maximum amount of lipid core burden index (maxLCBI4mm) of each LRP detected by NIRS. We divided the lesions into three groups based on the maxLCBI4mm value: <250, 250–399, and ≥400. OCT analysis and IVUS analysis were performed blinded for NIRS. We measured fibrous cap thickness (FCT) by using a semi-automated method. A total of 104 patients underwent multimodality imaging of 209 non-IRAs. NIRS detected 299 LRPs. Of those, 41% showed a maxLCBI4mm <250, 39% a maxLCBI4mm 251–399, and 19% a maxLCBI4mm ≥400. LRPs with a maxLCBI4mm ≥400, as compared with LRPs with a maxLCBI4mm 250–399 and <250, were more frequently thin-cap fibroatheroma (TCFA) (42.1% vs. 5.1% and 0.8%; P < 0.001) with a smaller minimum FCT (80 μm vs. 110 μm and 120 μm; P < 0.001); a higher IVUS-derived percent atheroma volume (53% vs. 53% and 44%; P < 0.001) and a higher remodelling index (1.08 vs. 1.02 and 1.01; P < 0.001). MaxLCBI4mm correlated with OCT-derived FCT (r = 0.404; P < 0.001) and was the best predictor for TCFA with an optimal cut-off value of 401 (area under the curve = 0.882; P < 0.001). Conclusion LRPs with increasing maxLCBI4mm exhibit OCT and IVUS features of presumed plaque vulnerability including TCFA morphology, increased plaque burden, and positive remodelling.

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