Cardiac MR imaging in constrictive pericarditis: multiparametric assessment in patients with surgically proven constriction
- PMID: 25672267
- DOI: 10.1007/s10554-015-0616-z
Cardiac MR imaging in constrictive pericarditis: multiparametric assessment in patients with surgically proven constriction
Abstract
To assess the utility of cardiac magnetic resonance (MR) imaging in the diagnosis of constrictive pericarditis (CP). This study was approved by the institutional review board, with a waiver of informed consent. A total of 42 consecutive patients (mean age, 55 ± 16 years; 3 women, 39 men) with CP treated with pericardiectomy who had undergone cardiac MR before surgery were evaluated retrospectively. An additional 21 patients were evaluated as a control group; of these, 10 consecutive patients received cardiac MR for reasons other than suspected pericardial disease, and 11 consecutive patients had a history of pericarditis but no clinical suspicion of pericardial constriction. MR imaging parameters were analyzed independently and with a decision tree algorithm for usefulness in the prediction of CP. Catheterization data were also reviewed when available. A model combining pericardial thickness and relative interventricular septal (IVS) excursion provided the best overall performance in prediction of CP (C statistic, 0.98, 100% sensitivity, 90% specificity). Several individual parameters also showed strong predictive value in the assessment of constriction, including relative IVS excursion (sensitivity, 93%; specificity, 95%), pericardial thickness (sensitivity, 83%; specificity, 100%), qualitative assessment of pathologic coupling (sensitivity, 88%; specificity, 100%), diastolic IVS bounce (sensitivity, 90%; specificity, 85%), left ventricle area change (sensitivity, 86%; specificity, 100%), and eccentricity index (sensitivity, 86%; specificity, 90%; all P < 0.001). Strong agreement was observed between catheterization and surgical findings of constriction (97%). Cardiac MR provides robust quantitative and qualitative analysis for the diagnosis of CP.
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