title: Validation of sub-segmental visual scoring for the quantification of ischemic and nonischemic myocardial fibrosis using late gadolinium enhancement MRI.
abstract: OBJECTIVE
  To determine the accuracy and reproducibility of late gadolinium enhancement (LGE) MRI scar quantification using visual sub-segmental analysis (VSSA) versus signal threshold-based analysis in ischemic and nonischemic cardiomyopathy.
  
  
  METHODS
  One-hundred sixty-one patients with abnormal LGE imaging underwent VSSA and signal threshold-based analysis. VSSA was performed using a 68 sub-segmental model. Signal threshold-based analysis was performed using cutoffs of ≥2, ≥3, and ≥5 standard deviations (SD) above the mean signal of normal myocardium. Comparison of VSSA and signal threshold-based analysis was performed by linear regression and Bland Altman plots.
  
  
  RESULTS
  Seventy (44%) patients had ischemic scar, 76 (47%) had nonischemic scar, and 15 (9%) had a combined pattern. Correlation coefficients for VSSA versus signal threshold-based analysis at ≥2, ≥3, and ≥5SD thresholds were r = 0.63, r = 0.79, r = 0.81 (P < 0.001) for all patients, r = 0.74, r = 0.81, r = 0.81 (P < 0.001) in those with ischemic scar, and r = 0.46, r = 0.69, r = 0.72 (P < 0.001) in those with nonischemic scar. Bland Altman analysis revealed no significant bias in total scar volume among all patients (-4.3 ± 7.9%), those with ischemic scar (-4.8 ± 7.8%), or those with nonischemic scar (-2.6 ± 7.6%). Intra-observer and inter-observer variability of the VSSA technique was excellent with a mean difference in total percent scar of 0.3% (-8.3-8.9%) and -0.4% (-9.5-8.5%), respectively.
  
  
  CONCLUSIONS
  A VSSA-based model of myocardial scar quantification is accurate and reproducible in ischemic and nonischemic cardiomyopathy.
authors.affiliation: Division of Cardiology, Department of Medicine, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.
authors.forename: Nowell M
authors.initials: NM
authors.lastname: Fine
authors.forename: Shruti
authors.initials: S
authors.lastname: Tandon
authors.forename: Han W
authors.initials: HW
authors.lastname: Kim
authors.forename: Dipan J
authors.initials: DJ
authors.lastname: Shah
authors.forename: Terry
authors.initials: T
authors.lastname: Thompson
authors.forename: Maria
authors.initials: M
authors.lastname: Drangova
authors.forename: James A
authors.initials: JA
authors.lastname: White
mesh_terms: D009202:Cardiomyopathies / Q000150:complications* / Q000473:pathology*; D003287:Contrast Media / Q000008:administration & dosage; D005260:Female; D005355:Fibrosis; D005682:Gadolinium / Q000008:administration & dosage; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008297:Male; D008875:Middle Aged; D017202:Myocardial Ischemia / Q000150:complications* / Q000473:pathology*; D009206:Myocardium / Q000473:pathology*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D005682:Gadolinium
keywords: late gadolinium enhancement; magnetic resonance imaging; quantitative analysis; visual quantification