title: Assessment of the morphological features of degenerative mitral valve disease using 64-slice multi detector computed tomography.
abstract: BACKGROUND
  Patients with severe mitral regurgitation may be screened for coronary artery disease with the use of cardiac computed tomography before valve surgery.
  
  
  OBJECTIVE
  We hypothesized that dual-source multidetector computed tomography (DSCT) could effectively predict the culprit mitral valve scallop identified during surgery among patients with degenerative mitral valve disease undergoing surgical mitral valve repair.
  
  
  METHODS
  Twenty-six patients (7 women) with known severe mitral regurgitation underwent elective mitral valve repair from September 2006 through December 2009 at our institution. An additional 10 patients underwent aortic valve replacement and had no documented history of mitral valve disease. All patients underwent transthoracic echocardiography and had retrospectively gated DSCT performed to evaluate the coronary arteries before surgery. Each mitral scallop was identified as either normal, prolapsed, or flail. CT findings were compared with operative findings, which were guided by intraoperative transesophageal echocardiography (TEE).
  
  
  RESULTS
  In the 26 patients examined, DSCT identified flail in 23 scallops and prolapse in 48. DSCT agreed with operative findings on identification of the culprit scallop in 25 of 26 patients. On a per-patient and per-scallop basis, the observed κ statistic for agreement between DSCT and operative findings was 0.82. Of the 60 scallops in the aortic valve group, all were judged to be normal by both DSCT and TEE.
  
  
  CONCLUSIONS
  In patients with degenerative mitral valve disease undergoing cardiac surgery, DSCT demonstrates excellent agreement with intraoperative findings. DSCT can be used to identify the affected mitral valve scallop and its structure in patients who are candidates for mitral valve repair.
authors.affiliation: Division of Cardiology, University of California, Davis, Sacramento, CA, USA.
authors.forename: Thomas
authors.initials: T
authors.lastname: Smith
authors.forename: Swaminatha
authors.initials: S
authors.lastname: Gurudevan
authors.forename: Victor
authors.initials: V
authors.lastname: Cheng
authors.forename: Alfredo
authors.initials: A
authors.lastname: Trento
authors.forename: Mick
authors.initials: M
authors.lastname: Derobertis
authors.forename: Louise
authors.initials: L
authors.lastname: Thomson
authors.forename: John
authors.initials: J
authors.lastname: Friedman
authors.forename: Sean
authors.initials: S
authors.lastname: Hayes
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Siegel
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Berman
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008943:Mitral Valve / Q000000981:diagnostic imaging*; D008944:Mitral Valve Insufficiency / Q000000981:diagnostic imaging*; D015588:Observer Variation; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*