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

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Assessing pulsatile blood flow through the left ventricle (LV) of the heart is vital for understanding the cardiovascular function in health and disease. Four‐dimensional (4D) flow MRI has been developed and successfully used for such an assessment 1. However, it requires accurate geometric identification of underlying cardiac or vascular anatomy that is often poorly visible even to an experienced clinician, mainly due to low resolution and poor contrast between blood and the myocardium. One of the commonly used solutions to obtain reliable segmentations is the utilization of higher in‐plane resolution and better contrast in routinely acquired multislice cine balanced steady‐state free precession (cine‐bSSFP) MR images 2. The desired segmentation is first delineated on the cine‐bSSFP images and then manually aligned to the corresponding 4D flow MRI data. Although such a procedure provides a close estimate of the required anatomical geometry, it is quite tedious, slow, and prone to interobserver and intraobserver bias. Moreover, alignment errors may also be introduced due to suboptimal breath‐holding 3 leading to respiratory drift during the acquisition of multiple slices of the cine‐bSSFP image 4. The respiratory‐induced motion of the heart was studied in detail by McLeish et al. 3 and the application of image registration was suggested to mitigate such misalignment errors. Inaccuracies in the segmentation used for the analysis of blood flow can affect the results significantly, and could be ground for the exclusion of data 6.
Image registration methods have been successfully used to solve motion correction problems in a multitude of applications 8. Typically, these methods receive a pair of images as input, usually referred to as “reference” and “target,” and generate as output a transformation that brings them into a common spatial alignment 8. Long‐axis (LAX) cine‐bSSFP images have often been used as reference for this purpose 9, but with the assumption that they are free of motion artifacts. Several other methods exist for motion correction in cine‐bSSFP images 12, but lack a suitable reference image for reliable alignment. In contrast to cine‐bSSFP images, 4D Flow MR images are acquired with navigator gating, hence, no breath‐holds are required during their acquisition. They are, consequently, less prone to respiration induced motion, and can be an effective reference for image registration.
The purpose of this study is to investigate the feasibility of robust and automatic image registration between breath‐hold acquired morphological cine‐bSSFP and respiratory‐gated 4D flow MRI to improve the accuracy of left‐ventricular segmentation, and hence, the subsequent blood flow analysis.

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