title: Manual versus Automated Carotid Artery Plaque Component Segmentation in High and Lower Quality 3.0 Tesla MRI Scans.
abstract: OBJECTIVE
  To study the interscan reproducibility of manual versus automated segmentation of carotid artery plaque components, and the agreement between both methods, in high and lower quality MRI scans.
  
  
  METHODS
  24 patients with 30-70% carotid artery stenosis were planned for 3T carotid MRI, followed by a rescan within 1 month. A multicontrast protocol (T1w,T2w, PDw and TOF sequences) was used. After co-registration and delineation of the lumen and outer wall, segmentation of plaque components (lipid-rich necrotic cores (LRNC) and calcifications) was performed both manually and automated. Scan quality was assessed using a visual quality scale.
  
  
  RESULTS
  Agreement for the detection of LRNC (Cohen's kappa (k) is 0.04) and calcification (k = 0.41) between both manual and automated segmentation methods was poor. In the high-quality scans (visual quality score ≥ 3), the agreement between manual and automated segmentation increased to k = 0.55 and k = 0.58 for, respectively, the detection of LRNC and calcification larger than 1 mm2. Both manual and automated analysis showed good interscan reproducibility for the quantification of LRNC (intraclass correlation coefficient (ICC) of 0.94 and 0.80 respectively) and calcified plaque area (ICC of 0.95 and 0.77, respectively).
  
  
  CONCLUSIONS
  Agreement between manual and automated segmentation of LRNC and calcifications was poor, despite a good interscan reproducibility of both methods. The agreement between both methods increased to moderate in high quality scans. These findings indicate that image quality is a critical determinant of the performance of both manual and automated segmentation of carotid artery plaque components.
authors.affiliation: Department of Vascular Medicine, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Loek P
authors.initials: LP
authors.lastname: Smits
authors.affiliation: Department of Vascular Medicine, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Diederik F
authors.initials: DF
authors.lastname: van Wijk
authors.affiliation: Department of Vascular Medicine, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Raphael
authors.initials: R
authors.lastname: Duivenvoorden
authors.affiliation: Department of Radiology, University of Washington, Seattle, United States of America.
authors.forename: Dongxiang
authors.initials: D
authors.lastname: Xu
authors.affiliation: Department of Radiology, University of Washington, Seattle, United States of America.
authors.forename: Chun
authors.initials: C
authors.lastname: Yuan
authors.affiliation: Department of Vascular Medicine, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Erik S
authors.initials: ES
authors.lastname: Stroes
authors.affiliation: Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Aart J
authors.initials: AJ
authors.lastname: Nederveen
mesh_terms: D000368:Aged; D001331:Automation; D002114:Calcinosis / Q000000981:diagnostic imaging; D002339:Carotid Arteries / Q000000981:diagnostic imaging / Q000473:pathology; D016893:Carotid Stenosis / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009336:Necrosis; D015203:Reproducibility of Results