Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study.
prospective_cohort · Level II
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Abstract
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.
Medical subject headings
- Artificial Intelligence
- Image Interpretation, Computer-Assisted
- Imaging, Three-Dimensional
- Magnetic Resonance Imaging
- Myocardial Infarction
- Pattern Recognition, Automated
- Ventricular Dysfunction, Left