Automated Motion Estimation for 2-D Cine DENSE MRI

Abstract

Cine displacement encoding with stimulated echoes (DENSE) is a magnetic resonance (MR) method that directly encodes tissue displacement into MR phase images. This technique has successfully interrogated many forms of tissue motion, but is most commonly used to evaluate cardiac mechanics. Currently, motion analysis from cine DENSE images requires manually delineated anatomical structures. An automated analysis would improve measurement throughput, simplify data interpretation, and potentially access important physiological information during the MR exam. In this article, we present the first fully automated solution for the estimation of tissue motion and strain from 2D cine DENSE data. Results using both simulated and human cardiac cine DENSE data indicate good agreement between the automated algorithm and the standard semi-manual analysis method.

Accurate High-Resolution Measurements of 3-D Tissue Dynamics With Registration-Enhanced Displacement Encoded MRI

“…In recent studies on cardiac mechanics [3], [29], [44], first-order approximations of velocity were used to estimate small deformations in intermediate DENSE scan time points. The deformation fields were then incorporated in the DENSE reconstruction to improve the accuracy tracking and phase offset determination [27].…”

“…In recent studies on cardiac mechanics [3], [29], [44], first-order approximations of velocity were used to estimate small deformations in intermediate DENSE scan time points. The deformation fields were then incorporated in the DENSE reconstruction to improve the accuracy tracking and phase offset determination [27]. Although a direct comparison may yield comparable performances, as noted above, the current direct registration-based reconstruction can be advantageous since it does not require 1) additional high temporal-resolution scans, or 2) the condition that the local deformations between frames to be small enough to be approximated by a first order velocity integration.…”

“…Consequently, a major part of displacement measurement via DENSE is the postprocessing of phase wrapped images, which involves two critical steps: first, the phase is unwrapped to eliminate discontinuities in phase images, and second, the resulting continuous phase maps is matched to true displacements by correcting for the phase offsets at selected pixels (known as “seed,” “true phase,” or “reference” points). Although phase unwrapping has been well studied from its association with other fields like radar interferometry [46], [47] and geophysics [48], [49], matching the results to underlying displacements is more unique to DENSE reconstruction, which continues as an active area of research [29], [45], [50]. …”

“…For example, because healthy left-ventricular (LV) motion in a 2-D slice is mostly radially symmetric, it has been assumed that in-plane displacements should average to zero [26]. Offset vectors can also be estimated assuming small displacements in between frames [29], [45]. To date, means to objectively correct for arbitrarily fast or large displacements in between temporal frames remains lacking.…”

“…These benefits have fueled the analysis of deformation predominantly in the heart. But practical utility of DENSE has largely been limited by the lack of a generalized approach for relating phase image information to physical displacements, though some recent progress appears promising [27]. The key challenge is to avoid potential problems arising from the angular nature of phase images, like phase wrapping and displacement offsets, which ultimately determine the overall accuracy of the measurements [28], [29].…”