Accuracy and Time-Efficiency of an Automated Software Tool to Assess Left Ventricular Parameters in Cardiac Magnetic Resonance Imaging

Purpose: Routine manual tracing of cardiac contours is time-consuming and subject to variability. A fully automated software tool may improve reading efficiency.

This study was performed to assess the accuracy, reliability, and time-efficiency of a fully automated left ventricular (LV) segmentation software tool to calculate LV volumes and function compared with conventional manual contouring.

Materials and methods: Sixty-seven consecutive patients (53 male, mean age 62.5±10.9 y) underwent adenosine stress/rest perfusion cardiac magnetic resonance examination to rule out myocardial ischemia.

Double-oblique short-axis 6-mm slice thickness steady-state free precession cine images were acquired to assess LV ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), and stroke volume (SV) using manual contour tracing and a recently developed fully automated software tool. The length of time needed to obtain LV volumes with each segmentation method was also compared.

Results: Compared with manual contouring, the fully automated software tool minimally underestimated LV-EF (mean difference of 2.9%±3.9%) and SV (mean difference of 4.4±8.5 mL) and slightly overestimated ESV (mean difference of -6.4±10.8 mL) and LV mass (mean difference of -14±20.4 g).

EDV quantification did not statistically differ. Reliability for EF (concordance correlation coefficient [CCC]=0.92, 95% confidence interval [CI], 0.88-0.95), EDV (CCC=0.98, 95% CI, 0.97-0.99), ESV (CCC=0.96, 95% CI, 0.94-0.97), SV (CCC=0.93, 95% CI, 0.89-0.95), and LV mass (CCC=0.84, 95% CI, 0.76-0.89) was very good. The evaluated software allowed to quantify LV parameters with a 79% reduction in the time required for manual contouring (414.7±91 s vs. 85±16.1 s, respectively, P<0.001).

Conclusion: Quantification of LV volumes using the evaluated fully automated segmentation software is accurate and time-efficient.

CITA DEL ARTÍCULO  J Thorac Imaging. 2020 Jan;35(1):64-70.  doi: 10.1097/RTI.0000000000000459