A novel semiautomatic segmentation method for myocardial tissue phase mapping significantly reduces processing time while maintaining data quality and improving interobserver agreement.
PURPOSE: To develop a semiautomatic method for rapid segmentation of myocardial tissue phase mapping (TPM) data. METHODS: Manual segmentation of the myocardium was performed at end-diastole and end-systole. The points in both user-defined masks were then automatically tracked over the entire cardiac cycle using temporal integration of the velocity field. Paths that failed to visit both masks at the expected times were excluded, after which masks for all time points were generated automatically from the accepted paths. Midventricular and basal phase contrast TPM slices from 12 rats were segmented using the proposed method and fully manual segmentation. The results were compared using Dice's metric and Bland-Altman analysis, and interobserver variability was assessed. RESULTS: The semiautomatic method reduced the average user input time from 21 min to 1 min per slice. The Dice metrics between the methods were 0.88 ± 0.03 (midventricular) and 0.83 ± 0.06 (basal), and Bland-Altman limits of agreement of peak systolic and diastolic regional velocities were: midventricular: 0.05 ± 0.65 cm/s, -0.02 ± 0.42 cm/s, and -0.03 ± 0.40 cm/s (radial, tangential, longitudinal); basal: -0.04 ± 0.73 cm/s, 0.03 ± 0.60 cm/s, and -0.04 ± 0.48 cm/s (radial, tangential, longitudinal). Interobserver variability following semiautomatic segmentation was lower than for manual segmentation. CONCLUSION: The proposed method reduced the segmentation time substantially and exhibited well-preserved data quality and excellent interobserver limits of agreement. Magn Reson Med 78:1199-1207, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Espe et al. (Mon,) studied this question.