title: Evaluation of carotid artery wall volume measurement using novel semiautomated analysis software.
abstract: OBJECTIVE
  To evaluate semiautomated analysis software for measuring the total carotid arterial wall volume (TWV) as a measure of atheroma burden.
  
  
  METHODS
  Semiautomated-software and manual analyses of TWV measured by cardiovascular magnetic resonance (CMR) were compared in two phantom models, 10 subjects with no known carotid artery disease, and eight subjects with known carotid disease. The subjects were scanned twice for reproducibility.
  
  
  RESULTS
  In subjects with no known carotid disease, semiautomated analysis of 98% of slices showed an improved interstudy coefficient of variation (COV) compared to manual analysis of 50% of slices (4.0% vs. 6.2%, P = 0.02). The proportion of matched cross-sectional slices usable for TWV measurement was superior (99% vs. 49%, P = 0.005) and the median analysis time was shorter (31 minutes vs. 90 minutes, P < 0.001) using the semiautomated software. In subjects with known carotid disease, semiautomated (99% of slices) and manual (56% of slices) analyses had comparable interstudy COVs (4.1% vs. 3.9%, P = 0.01). However, the proportion of matched cross-sectional slices usable for TWV measurement was greater using semiautomated contouring (96% vs. 56%, P = 0.01).
  
  
  CONCLUSIONS
  Carotid CMR measurement of TWV using novel semiautomated analysis software shows good reproducibility, enables greater coverage of arterial vessel wall length, and is considerably faster compared to manual contouring.
authors.affiliation: Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, United Kingdom.
authors.forename: Anitha
authors.initials: A
authors.lastname: Varghese
authors.forename: Robert D
authors.initials: RD
authors.lastname: Merrifield
authors.forename: Lindsey A
authors.initials: LA
authors.lastname: Crowe
authors.forename: Steven A
authors.initials: SA
authors.lastname: Collins
authors.forename: Niall G J
authors.initials: NG
authors.lastname: Keenan
authors.forename: David N
authors.initials: DN
authors.lastname: Firmin
authors.forename: Guang Zhong
authors.initials: GZ
authors.lastname: Yang
authors.forename: Dudley J
authors.initials: DJ
authors.lastname: Pennell
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D002339:Carotid Arteries / Q000473:pathology*; D002340:Carotid Artery Diseases / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D012986:Software Validation