Improving left ventricular segmentation in four-dimensional flow MRI using intramodality image registration for cardiac blood flow analysis.

PURPOSE: Assessment of blood flow in the left ventricle using four-dimensional flow MRI requires accurate left ventricle segmentation that is often hampered by the low contrast between blood and the myocardium. The purpose of this work is to improve left-ventricular segmentation in four-dimensional flow MRI for reliable blood flow analysis.
METHOD: The left ventricle segmentations are first obtained using morphological cine-MRI with better in-plane resolution and contrast, and then aligned to four-dimensional flow MRI data. This alignment is, however, not trivial due to inter-slice misalignment errors caused by patient motion and respiratory drift during breath-hold based cine-MRI acquisition. A robust image registration based framework is proposed to mitigate such errors automatically. Data from 20 subjects, including healthy volunteers and patients, was used to evaluate its geometric accuracy and impact on blood flow analysis.
RESULTS: High spatial correspondence was observed between manually and automatically aligned segmentations, and the improvements in alignment compared to uncorrected segmentations were significant (P < 0.01). Blood flow analysis from manual and automatically corrected segmentations did not differ significantly (P > 0.05).
CONCLUSION: Our results demonstrate the efficacy of the proposed approach in improving left-ventricular segmentation in four-dimensional flow MRI, and its potential for reliable blood flow analysis. Magn Reson Med 79:554-560, 2018.