title: Clinical Feasibility of 3D Automated Coronary Atherosclerotic Plaque Quantification Algorithm on Coronary Computed Tomography Angiography: Comparison with Intravascular Ultrasound.
abstract: OBJECTIVE
  To evaluate the diagnostic performance of automated coronary atherosclerotic plaque quantification (QCT) by different users (expert/non-expert/automatic).
  
  
  METHODS
  One hundred fifty coronary artery segments from 142 patients who underwent coronary computed tomography angiography (CCTA) and intravascular ultrasound (IVUS) were analyzed. Minimal lumen area (MLA), maximal lumen area stenosis percentage (%AS), mean plaque burden percentage (%PB), and plaque volume were measured semi-automatically by expert, non-expert, and fully automatic QCT analyses, and then compared to IVUS.
  
  
  RESULTS
  Between IVUS and expert QCT analysis, the correlation coefficients (r) for the MLA, %AS, %PB, and plaque volume were excellent: 0.89 (p < 0.001), 0.84 (p < 0.001), 0.91 (p < 0.001), and 0.94 (p < 0.001), respectively. There were no significant differences in the mean parameters (all p values >0.05) except %AS (p = 0.01). The automatic QCT analysis showed comparable performance to non-expert QCT analysis, showing correlation coefficients (r) of the MLA (0.80 vs. 0.82), %AS (0.82 vs. 0.80), %PB (0.84 vs. 0.73), and plaque volume (0.84 vs. 0.79) when they were compared to IVUS, respectively.
  
  
  CONCLUSIONS
  Fully automatic QCT analysis showed clinical utility compared with IVUS, as well as a compelling performance when compared with semiautomatic analyses.
  
  
  CONCLUSIONS
  • Coronary CTA enables the assessment of coronary atherosclerotic plaque. • High-risk plaque characteristics and overall plaque burden can predict future cardiac events. • Coronary atherosclerotic plaque quantification is currently unfeasible in practice. • Quantitative computed tomography coronary plaque analysis software (QCT) enables feasible plaque quantification. • Fully automatic QCT analysis shows excellent performance.
authors.affiliation: Yonsei-Cedar Sinai Integrative Cardiovascular Imaging Research Center, Yonsei University Health System, Seoul, South Korea.
authors.forename: Hyung-Bok
authors.initials: HB
authors.lastname: Park
authors.forename: Byoung Kwon
authors.initials: BK
authors.lastname: Lee
authors.forename: Sanghoon
authors.initials: S
authors.lastname: Shin
authors.forename: Ran
authors.initials: R
authors.lastname: Heo
authors.forename: Reza
authors.initials: R
authors.lastname: Arsanjani
authors.forename: Pieter H
authors.initials: PH
authors.lastname: Kitslaar
authors.forename: Alexander
authors.initials: A
authors.lastname: Broersen
authors.forename: Jouke
authors.initials: J
authors.lastname: Dijkstra
authors.forename: Sung Gyun
authors.initials: SG
authors.lastname: Ahn
authors.forename: James K
authors.initials: JK
authors.lastname: Min
authors.forename: Hyuk-Jae
authors.initials: HJ
authors.lastname: Chang
authors.forename: Myeong-Ki
authors.initials: MK
authors.lastname: Hong
authors.forename: Yangsoo
authors.initials: Y
authors.lastname: Jang
authors.forename: Namsik
authors.initials: N
authors.lastname: Chung
mesh_terms: D000368:Aged; D000465:Algorithms; D017023:Coronary Angiography / Q000379:methods; D003324:Coronary Artery Disease / Q000473:pathology*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D058226:Plaque, Atherosclerotic / Q000000981:diagnostic imaging / Q000473:pathology*; D014057:Tomography, X-Ray Computed / Q000379:methods; D018084:Ultrasonography, Interventional / Q000379:methods