title: How to quantify infarct size on delayed-enhancement MR images: a comparison between visual and quantitative approach.
abstract: OBJECTIVE
  Our aim was to evaluate the reliability of visual quantification of infarct extent on delayed enhanced magnetic resonance images.
  
  
  METHODS
  Eighty patients with previous myocardial infarction underwent cine and contrast-enhanced cardiac magnetic resonance imaging. The gadolinium-enhanced images were evaluated using a segmental model with two different methods: a visual score on a 5-point scale (0 no hyperenhancement, 4 hyperenhancement>76% of myocardial wall) and a quantitative analysis based on the manual tracing of infarct contours with automatic threshold analysis. Each segment was also assigned a wall-motion score ranging from 0 (normokinesia) to 4 (dyskinesia). Statistical evaluation was performed.
  
  
  RESULTS
  Out of 1,280 segments, 322 (25.1%) showed wall-motion abnormalities with enhancement in 327 (25.5%) evaluated with visual score and in 414 (32.3%) quantitatively. Among segments with normal or mild hypokinesia, 89.2% had a delayed-enhancement score<or=1, whereas 80.2% of akinetic or dyskinetic segments had a score>or=3. Mean time required for the visual and quantitative approach was 7+/-3 and 18+/-9 min, respectively. There was strong agreement between the visual and quantitative method (k=0.92; p<0.01).
  
  
  CONCLUSIONS
  Visual analysis of delayed enhancement is a timesaving approach that is sufficient to assess the transmural extent of infarction. Moreover, it has high correlation with wall-motion abnormalities.
authors.affiliation: Cattedra e Servizio di Radiologia I, Dipartimento Integrato dei Servizi Diagnostici e per Immagini, Università degli Studi di Modena e Reggio Emilia, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy. ligabue.guido@unimore.it
authors.forename: G
authors.initials: G
authors.lastname: Ligabue
authors.forename: F
authors.initials: F
authors.lastname: Fiocchi
authors.forename: S
authors.initials: S
authors.lastname: Ferraresi
authors.forename: A
authors.initials: A
authors.lastname: Barbieri
authors.forename: R
authors.initials: R
authors.lastname: Romagnoli
authors.forename: P
authors.initials: P
authors.lastname: Torricelli
mesh_terms: D000368:Aged; D000465:Algorithms; D003287:Contrast Media; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis*; D013997:Time Factors; D018754:Ventricular Dysfunction / Q000175:diagnosis
chemical_list: D003287:Contrast Media