Quantifying "normalized" regional left ventricular contractile function in XXXX .

@entity1 @entity453 @entity1188 @entity910
OBJECTIVE: When significant coronary lesions are identified by angiography, regional left ventricular (LV) contractile function often plays a role in determining candidacy for revascularization. To improve on current subjective and nonquantitative metrics of regional LV function, we tested a z-score "normalization" of regional strain information quantified from clinically acquired high-resolution LV geometric datasets. METHODS: Test subjects (n  =  120) underwent cardiac MRI with multiple 3-dimensional strain parameters calculated from tissue tag-plane displacement data. Sixty healthy volunteers contributed strain parameter data at each of 15,300 LV grid points, to form a normal @entity1 database. Point-specific database comparisons were made in 60 @entity1 who had documented @entity453 ( @entity453 ), by angiography. @entity1 -specific, color-coded 3-dimensional LV maps of z-score-normalized contractile function were generated. RESULTS: Blinded clinical review indicated that 55% (33 of 60) of the @entity1 with @entity453 had significant regional contractile abnormalities by 1 of 3 "gold-standard" criteria: (1) Q waves on electrocardiography (ECG); (2) @entity1188 on radionuclide single-photon emission computed tomography (SPECT); or (3) @entity910 or @entity910 on echocardiography. Consistency among all gold-standard metrics was found for only 19% (6 of 31) of @entity1 with @entity453 who had >= 2 available metrics. Blinded MRI-based, multiparametric, strain z-score localization of contractile abnormalities was accurate in 89% (ECG), 97% (SPECT), and 95% (echocardiography). CONCLUSIONS: Nonsubjective normalization of regional LV contractile function by z-score calculation from a normal @entity1 database can localize and quantitatively display regional wall motion abnormalities in @entity1 with @entity453 . This high-resolution localization of regional wall motion abnormalities may help improve the accuracy of therapeutic intervention in @entity1 who have @entity453 .
