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  • Title: Cardiac MR imaging in constrictive pericarditis: multiparametric assessment in patients with surgically proven constriction.
    Author: Bolen MA, Rajiah P, Kusunose K, Collier P, Klein A, Popović ZB, Flamm SD.
    Journal: Int J Cardiovasc Imaging; 2015 Apr; 31(4):859-66. PubMed ID: 25672267.
    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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