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Adaptive Postprocessing Techniques for Myocardial Tissue Tracking with Displacement-encoded MR Imaging¹

¹ From the National Heart, Lung and Blood Institute, National Institutes of Health, Bldg 10, B1D416, 10 Center Dr, Bethesda, MD 20892 (H.W., E.E.B., R.P.L., N.D.E.); Department of Computer Science and Engineering, Ohio State University, Columbus, Ohio (K.A.M.); Division of Cardiology, George Washington University School of Medicine, Washington, DC (J.F.P.); Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY (K.S.K.); Department of Biomedical Engineering, Tulane University, New Orleans, La (D.B.L.); and Department of Radiology, Hôpital Cardiologique et Pneumologique, L. Pradel, Lyon, France (P.C.). Received January 9, 2007; revision requested March 2; revision received March 28; accepted May 2; final version accepted July 2. Supported by the National Heart, Lung, and Blood Institute, National Institutes of Health. Address correspondence to H.W. (e-mail: wenh{at}nhlbi.nih.gov).

The purpose of this study was to prospectively assess the effects of two adaptive postprocessing techniques on the evaluation of myocardial function with displacement-encoded magnetic resonance (MR) imaging, including sensitivity for abnormal wall motion, with two-dimensional echocardiography as the reference standard. Sixteen patients (11 men, five women; age range, 26–74 years) and 12 volunteers (six men, six women; age range, 29–53 years) underwent breath-hold MR imaging. Institutional review board approval and informed consent were obtained. Adaptive phase-unwrapping and spatial filtering techniques were compared with conventional phase-unwrapping and spatial filtering techniques. Use of the adaptive techniques led to a reduced rate of failure with the phase-unwrapping technique from 18.9% to 0.6% (P < .001), resulted in lower variability of segmental strain measurements among healthy volunteers (P < .001 to P = .02), and increased the sensitivity of quantitative detection of abnormal segments in patients from 82.5% to 87.7% (P = .034). The adaptive techniques improved the semiautomated postprocessing of displacement-encoded cardiac images and increased the sensitivity of detection of abnormal wall motion in patients.

Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/246/1/229/DC1

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