Assessment of infarct‐specific cardiac motion dysfunction using modeling and multimodal magnetic resonance merging

Purpose To propose a cardiac motion tracking model that evaluates wall motion abnormality in postmyocardial infarction patients. Correlation between the motion parameter of the model and left ventricle (LV) function was also determined. Materials and Methods Twelve male patients with post‐ST elevati...

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Veröffentlicht in:Journal of magnetic resonance imaging 2017-02, Vol.45 (2), p.525-534
Hauptverfasser: Leong, Chen Onn, Liew, Yih Miin, Bilgen, Mehmet, Abdul Aziz, Yang Faridah, Chee, Kok Han, Chiam, Yin Kia, Lim, Einly
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Sprache:eng
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Zusammenfassung:Purpose To propose a cardiac motion tracking model that evaluates wall motion abnormality in postmyocardial infarction patients. Correlation between the motion parameter of the model and left ventricle (LV) function was also determined. Materials and Methods Twelve male patients with post‐ST elevation myocardial infarction (post‐STEMI) and 10 healthy controls of the same gender were recruited to undergo cardiac magnetic resonance imaging (MRI) using a 1.5T scanner. Using an infarct‐specific LV division approach, the late gadolinium enhancement (LGE) MRI images were used to divide the LV on the tagged MRI images into infarct, adjacent, and remote sectors. Motion tracking was performed using the infarct‐specific two‐parameter empirical deformable model (TPEDM). The match quality was defined as the position error computed using root‐mean‐square (RMS) distance between the estimated and expert‐verified tag intersections. The position errors were compared with the ones from our previously published fixed‐sector TPEDM. Cine MRI images were used to calculate regional ejection fraction (REF). Correlation between the end‐systolic contraction parameter (αES) with REF was determined. Results The position errors in the proposed model were significantly lower than the fixed‐sector model (P < 0.01). The median position errors were 0.82 mm versus 1.23 mm. The αES correlates significantly with REF (r = 0.91, P < 0.01). Conclusion The infarct‐specific TPEDM combines the morphological and functional information from LGE and tagged MRI images. It was shown to outperform the fixed‐sector model in assessing regional LV dysfunction. The significant correlation between αES and REF added prognostic value because it indicated an impairment of cardiac function with the increase of infarct transmurality. Level of Evidence: 3 J. Magn. Reson. Imaging 2017;45:525–534.
ISSN:1053-1807
1522-2586
DOI:10.1002/jmri.25390