title: Automated characterisation of lipid core plaques in vivo by quantitative optical coherence tomography tissue type imaging.
abstract: OBJECTIVE
  Qualitative criteria for plaque tissue characterisation by OCT are well established, but quantitative methods lack systematic validation in vivo. High optical attenuation coefficient µt has been associated with unstable plaque features, such as lipid core. The purpose of this study was to validate optical coherence tomography (OCT) attenuation imaging for tissue characterisation in vivo, specifically to detect lipid core in coronary atherosclerotic plaques, and to evaluate quantitatively the ability of OCT attenuation imaging to differentiate thin-cap (TCFA) and thick-cap fibroatheroma (FA).
  
  
  RESULTS
  We prospectively enrolled 85 patients undergoing imaging of a native coronary segment by both OCT and near-infrared spectroscopy and intravascular ultrasound (NIRS-IVUS). Ninety-eight NIRS-positive 4 mm plaque segments were selected and matched to the OCT data. Two experienced OCT readers classified the plaque type using OCT criteria. A cap thickness of 65 μm was used to differentiate TCFA and FA. We computed an index of plaque attenuation (IPA) in the 4 mm blocks, and assessed the association of this index with plaque type. IPA differentiated between TCFA and FA (AUC=0.82 in ROC analysis; p<0.0001). LCBI was numerically, but not significantly, higher in TCFA compared to FA (p=0.097).
  
  
  CONCLUSIONS
  IPA is an unbiased reproducible measure of tissue optical properties. The fraction of pixels with attenuation coefficient ≥11 mm-1 can identify TCFA.
authors.affiliation: Thoraxcenter, Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: Muthukaruppan
authors.initials: M
authors.lastname: Gnanadesigan
authors.forename: Takeyoshi
authors.initials: T
authors.lastname: Kameyama
authors.forename: Antonios
authors.initials: A
authors.lastname: Karanasos
authors.forename: Nienke S
authors.initials: NS
authors.lastname: van Ditzhuijzen
authors.forename: Johannes N
authors.initials: JN
authors.lastname: van der Sijde
authors.forename: Robert-Jan
authors.initials: RJ
authors.lastname: van Geuns
authors.forename: Jurgen
authors.initials: J
authors.lastname: Ligthart
authors.forename: Karen
authors.initials: K
authors.lastname: Witberg
authors.forename: Giovanni J
authors.initials: GJ
authors.lastname: Ughi
authors.forename: Antonius F
authors.initials: AF
authors.lastname: van der Steen
authors.forename: Evelyn
authors.initials: E
authors.lastname: Regar
authors.forename: Gijs
authors.initials: G
authors.lastname: van Soest
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001331:Automation; D017023:Coronary Angiography / Q000379:methods; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000601:surgery; D005260:Female; D006801:Humans; D008055:Lipids / Q000032:analysis*; D008297:Male; D008875:Middle Aged; D058226:Plaque, Atherosclerotic / Q000175:diagnosis* / Q000601:surgery*; D041623:Tomography, Optical Coherence / Q000379:methods; D018084:Ultrasonography, Interventional / Q000379:methods
chemical_list: D008055:Lipids