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Automated Quantification of Myocardial Infarction from MR Images by Accounting for Partial Volume Effects: Animal, Phantom, and Human Study¹

¹ From the Departments of Radiology and Clinical Physiology (E.H., M.U., H.E., H.A.) and Cardiology (M.G., G.K.O., D.E.), Lund University Hospital, SE-221 85 Lund, Sweden. Received December 20, 2006; revision requested February 19, 2007; revision received March 12; accepted April 20; final version acepted June 6. Supported in part by the Swedish Research Council, the Swedish Heart and Lung Foundation, the Faculty of Medicine at Lund University, and the Region of Scania. Address correspondence to H.A. (e-mail: hakan.arheden{at}med.lu.se).

Ethics committees approved human and animal study components; informed written consent was provided (prospective human study [20 men; mean age, 62 years]) or waived (retrospective human study [16 men, four women; mean age, 59 years]). The purpose of this study was to prospectively evaluate a clinically applicable method, accounting for the partial volume effect, to automatically quantify myocardial infarction from delayed contrast material–enhanced magnetic resonance images. Pixels were weighted according to signal intensity to calculate infarct fraction for each pixel. Mean bias ± variability (or standard deviation), expressed as percentage left ventricular myocardium (%LVM), were –0.3 ± 1.3 (animals), –1.2 ± 1.7 (phantoms), and 0.3 ± 2.7 (patients), respectively. Algorithm had lower variability than dichotomous approach (2.7 vs 7.7 %LVM, P < .01) and did not differ from interobserver variability for bias (P = .31) or variability (P = .38). The weighted approach provides automatic quantification of myocardial infarction with higher accuracy and lower variability than a dichotomous algorithm.

Supplemental material: radiology.rsnajnls.org/cgi/content/full/2461062164/DC1

© RSNA, 2007