The proposed automatic left ventricle segmentation algorithm achieved accuracy comparable to inter-observer variability, with a mean difference in end-diastolic volume of -2.4±12.8 ml compared to manual delineation.
Does an automatic algorithm for time-resolved segmentation of the left ventricle in MRI provide comparable accuracy to manual delineation?
The new automatic LV segmentation algorithm achieved accuracy comparable to interobserver variability for manual delineation, facilitating its potential use in clinical routine.
Effect estimate: Mean difference -2.4 ml
INTRODUCTION: Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axis motion. Therefore, the aim of this study was to develop and validate an automatic algorithm for time-resolved segmentation covering the whole left ventricle, including basal slices affected by long-axis motion. METHODS: Ninety subjects imaged with a cine balanced steady state free precession sequence were included in the study (training set n = 40, test set n = 50). Manual delineation was reference standard and second observer analysis was performed in a subset (n = 25). The automatic algorithm uses deformable model with expectation-maximization, followed by automatic removal of papillary muscles and detection of the outflow tract. RESULTS: The mean differences between automatic segmentation and manual delineation were EDV -11 mL, ESV 1 mL, EF -3%, and LVM 4 g in the test set. CONCLUSIONS: The automatic LV segmentation algorithm reached accuracy comparable to interobserver for manual delineation, thereby bringing automatic segmentation one step closer to clinical routine. The algorithm and all images with manual delineations are available for benchmarking.
Tufvesson et al. (Sun,) conducted a other in Cardiovascular magnetic resonance imaging (n=90). Automatic algorithm for time-resolved segmentation of the left ventricle vs. Manual delineation was evaluated on Difference in end-diastolic volume (EDV) between automatic segmentation and reference manual delineation (Mean difference -2.4 ml). The proposed automatic left ventricle segmentation algorithm achieved accuracy comparable to inter-observer variability, with a mean difference in end-diastolic volume of -2.4±12.8 ml compared to manual delineation.