The application of tagged MRI to the RV has various difficulties; the thin wall of the normal RV limits the number of tag lines that are required for accurate quantification (17
). Several myocardial tagging studies have been performed on the RV to investigate and characterize mechanical deformation. Klien et al. (18
) used measures of percent segmental shortening of the RV free wall. Zahi et al. (17
) designed a specific breath hold imaging sequence with 1-D tag lines for RV tagging acquisition and, thus, were able to characterize the RV regional deformation. Young et al. (19
) use a finite element model for 3D reconstruction of the in-plane deformations of the RV free wall as a surface. Haber et al. (2
) also use a finite element model to obtain 3D strains in the RV. Using this model, they were able to quantify components of the in-plane strain tensor in the RV free wall. Tustison et. al. (20
) computed biventricular strains using volumetric deformable models with a non-uniform rational B-splines (NURBS) basis. All the 3D methods (2
) feature tag tracking to obtain displacements.
In this paper, an unwrapped phase technique to compute 3D biventricular strain in about three-fourths of the cardiac cycle using tagged cardiac MR images has been described and validated. The BiSUP technique consists of an unwrapped phase technique to compute the 1D displacements followed by a discrete model-free reconstruction method to obtain 3D strain measurements.
A major problem in computing strain in the RV is that the RV wall is relatively thin. To compensate for the thinness of the RV wall, RV contours were drawn so that the RV wall is slightly thicker than it actually is. An example can be seen in where RV wall contours define a thicker wall than one would expect from a physiological standpoint. The bandpass filtering used in the HARP computation smooths the phase so that the phase is extrapolated to a slightly larger region than the RV wall actually occupies. This effect can be seen in the HARP images in . Any phase errors from adjacent tissues or blood or air show up as phase inconsistencies, which are corrected with branch cuts. Also, strain tensors were computed only at grid points where the entire 3 × 3 × 3 neighborhood was present. This approach reduced the partial volume effect, but strain could only be computed at the mid wall.
We demonstrated on human subjects of different pathologies that displacement measurements, as well as circumferential, longitudinal and minimum principal strains measured using BiSUP are similar to those obtained from a feature-based method that uses tag tracking to obtain the displacement measurements.
The mean differences between BiSUP and FB displacement measurements were a few hundredths of pixel, which means there is no bias toward under or over estimation of displacement. The difference standard deviation was around 1/2 of pixel, which is close to the tag line tracking accuracy (8
). A small number of differences (<1%) were in the range of 2–5 pixels. Most of these were near the apex in both the LV and RV where partial volume effects, diminished the contrast-to-noise ratio (CNR). However, these measurements were small in number and isolated and had little effect on the resulting strain map due to the smoothness constraints used in the reconstruction.
In the comparison of 3D end-systolic strains computed by the BiSUP and FB methods in , the correlation between the methods was strongest in longitudinal strain. Six long-axis images were acquired, allowing more comparisons so the correlation in longitudinal strain (Ell) and torsion was higher, but the other strains measured showed a high correlation as well. The tangential strain in the RV was found to be significantly different between the BiSUP and FB methods, but this could be because of the increased number of short-axis measurements with BiSUP, which would have larger effect on the relatively sparsely-sampled RV.
The time required for the BiSUP measured strains in the entire LV and RV combined over 20 timeframes is less than 1.5 hours per study with less than an hour of manual intervention. While 1.5 hours is still too long for clinical feasibility, the same analysis using the feature-based method would require approximately 3 hours with significantly higher manual intervention. In addition, methods for reducing the analysis time through automated branch cut placement, algorithmic improvements, and implementation on graphics processing units (GPUs) are currently being explored. Compared to methods based on tracking tag lines (2
), displacement measurements from the BiSUP method are dense, potentially resulting in more accurate estimates of strain.
The strains from the BiSUP method were also compared to the strains from HARP. BiSUP-HARP agreement was not as strong as BiSUP-FB agreement because the BiSUP computes 3D strain while HARP computes 2D strain. Also, the tag line CNR decreases through the cycle due to T1 decay of the tag pattern, so early diastolic correlations are lower than correlations for peak strain and systolic strain rate.
It was observed that HARP in general measured lower minimum principal strains as compared to the BiSUP method. This could be attributed to the improved accuracy of tracking using the BiSUP method as a result of removal of inconsistencies in the HARP image using branch cuts. Also, HARP analysis does not correct for motion through the stationary basal and apical image planes, whereas BiSUP reconstructs 3D deformation and strain in each timeframe, which corrects for through-plane motion. With HARP, torsion is computed with HARP tracking, and large deformations between timeframes can cause errors. The unwrapped phase technique used in BiSUP is potentially more robust than HARP to large interframe deformations (6
). With unwrapped phase, points can be tracked through an image sequence as long as the average inter-frame deformation over the entire myocardium is less than one-half tag spacing.
The DMF method has advantages that are utilized for the reconstruction of strain in the RV, and in the LV in patients with pulmonary hypertension. The DMF method does not need a specific coordinate system to do the LV reconstruction and uses relatively lesser amount of smoothing than other reconstruction methods (13
). Therefore, the lack of a consistent geometry does not affect the performance of the DMF method as opposed to finite-element methods and prolate-spheroidal methods.
While the tagged imaging protocol used in this paper is commercially available and is widely used clinically, advanced tagged imaging techniques such as Complementary SPAMM (22
), can yield a higher tag CNR throughout the cardiac cycle. Higher CNR images will result in fewer phase inconsistencies and less user interaction will be required to correct them. The BiSUP technique reconstructs full 3D strain maps from tagged MR images through the cardiac cycle, and takes into account the through-plane motion of the heart. Slice-following DENSE (10
), zHARP (23
) and HARP-SENC (24
) can account for through-plane motion, but these techniques require two breath-holds per slice. In contrast, tagged images can be acquired with multiple slices per breath hold which allows the entire LV and RV to be imaged in significantly less time.
In the tests performed to study inter-user and intra-user variability, variance of the BiSUP method was introduced by the differences in branch-cuts manually placed by users for resolving the inconsistencies in the unwrapped phase of each study. The differences in the 3D strains, including Ecc, Ell, E3 in both LV and RV, and Torsion, between each user were computed. No significant differences were found in these strains among users, which indicated the uniform reproducibility of the method. The differences in the strains between each trial from each user were also computed. No significant differences were found among trials, suggestive of the acceptable repeatability of the method. In conclusion, these results suggest that BiSUP method is reproducible and repeatable for cardiac tagged image analysis.
In conclusion, the BiSUP method can compute accurate 3D biventricular strains through the cardiac cycle in a reasonable amount of time and user interaction compared to other 3D analysis methods.