2d cpa mr

The LV volumes, LVEF, and GLS measurements on CMR images were performed using the CMR feature tracking software (2D CPA MR; TomTec Imaging Systems, Unterschleissheim, Germany), which is a vector-based analysis tool based on a hierarchical algorithm. For each of the three apical long-axis SSFP images, the LV endocardial border at the end-systolic frame was semi-automatically determined by a 3-point click (both sides of the mitral annulus and the apex). The software then automatically propagated the contour and followed its features throughout the cardiac cycle to generate LV volume curves from which LVEDV, LVESV, and LVEF were determined. The software also provided segmental peak LS values on the bull’s eye map as well as the GLS.

CMR imaging was performed using a 3-T scanner (Discovery 750 W; GE Healthcare, Milwaukee, WI) with a phased-array cardiovascular coil. Retrospective electrocardiography-gated localizing spin-echo sequences were used to identify the long axis of the heart. Steady-state free precision (SSFP) dynamic gradient-echo cine loops were acquired by retrospective electrocardiographic gating and parallel imaging techniques during 10- to 15-s breath-holds with the following general parameters: 8-mm slice thickness of the imaging planes, 40 × 40-cm field of view, 200 × 160-scan matrix, 50° flip angle, 3.8/1.7-ms repetition/echo times, and 20 reconstructed cardiac phases. Eight to 16 short-axis slices from the base of the heart to the apex, and three standard long-axis views were recorded in each patient.
CMR LV volumes and LVEF were measured by the same operator (the expert that visited each hospital for training intervention) via feature tracking analysis (2D CPA MR; TomTec Imaging Systems, Unterschleissheim, Germany). In three apical long-axis SSFP images, the LV endocardial border was manually traced at the end-diastolic frame. Then, the feature tracking software propagates the endocardial contour and follows its tissue features throughout a cardiac cycle to generate LV volume curves from which LVEDV, LVESV, and LVEF were determined automatically.

CMR images were analyzed using commercial FT software (2D CPA MR; TomTec Imaging Systems, Unterschleissheim, Germany), which is a vector-based analysis tool based on a hierarchical algorithm [13 –15 ]. Using three apical long-axis cine SSFP images, the LV endocardial border at end-systole was semi-automatically drawn after 3-point clicking. Manual adjustment of endocardial border was performed when required. Subsequently, the software automatically propagates the contour and follows its features throughout the cardiac cycle to generate LV volume curve, from which the software provided LVEDV, LVESV and LVEF.