title: Prediction of hemodynamic severity of coarctation by magnetic resonance imaging.
abstract: A published formula containing minimal aortic cross-sectional area and the flow deceleration pattern in the descending aorta obtained by cardiovascular magnetic resonance predicts significant coarctation of the aorta (CoA). However, the existing formula is complicated to use in clinical practice and has not been externally validated. Consequently, its clinical utility has been limited. The aim of this study was to derive a simple and clinically practical algorithm to predict severe CoA from data obtained by cardiovascular magnetic resonance. Seventy-nine consecutive patients who underwent cardiovascular magnetic resonance and cardiac catheterization for the evaluation of native or recurrent CoA at Children's Hospital Boston (n = 30) and the University of California, San Francisco (n = 49), were retrospectively reviewed. The published formula derived from data obtained at Children's Hospital Boston was first validated from data obtained at the University of California, San Francisco. Next, pooled data from the 2 institutions were analyzed, and a refined model was created using logistic regression methods. Finally, recursive partitioning was used to develop a clinically practical prediction tree to predict transcatheter systolic pressure gradient ≥ 20 mm Hg. Severe CoA was present in 48 patients (61%). Indexed minimal aortic cross-sectional area and heart rate-corrected flow deceleration time in the descending aorta were independent predictors of CoA gradient ≥ 20 mm Hg (p <0.01 for both). A prediction tree combining these variables reached a sensitivity and specificity of 90% and 76%, respectively. In conclusion, the presented prediction tree on the basis of cutoff values is easy to use and may help guide the management of patients investigated for CoA.
authors.affiliation: Department of Radiology, University Hospital of California, San Francisco, California, USA. stefano.muzzarelli@chuv.ch
authors.forename: Stefano
authors.initials: S
authors.lastname: Muzzarelli
authors.forename: Alison Knauth
authors.initials: AK
authors.lastname: Meadows
authors.forename: Karen Gomes
authors.initials: KG
authors.lastname: Ordovas
authors.forename: Michael Douglas
authors.initials: MD
authors.lastname: Hope
authors.forename: Charles Bernard
authors.initials: CB
authors.lastname: Higgins
authors.forename: James Cordry
authors.initials: JC
authors.lastname: Nielsen
authors.forename: Tal
authors.initials: T
authors.lastname: Geva
authors.forename: Jeffery Joshua
authors.initials: JJ
authors.lastname: Meadows
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001013:Aorta, Thoracic / Q000473:pathology*; D001017:Aortic Coarctation / Q000473:pathology*; D001783:Blood Flow Velocity; D006328:Cardiac Catheterization; D002648:Child; D002675:Child, Preschool; D003097:Collateral Circulation; D003287:Contrast Media; D003430:Cross-Sectional Studies; D006339:Heart Rate; D006801:Humans; D021621:Imaging, Three-Dimensional; D007223:Infant; D016015:Logistic Models; D019028:Magnetic Resonance Imaging, Cine; D008875:Middle Aged; D012039:Regional Blood Flow; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D055815:Young Adult
chemical_list: D003287:Contrast Media