Key result
A phase-based registration method using an anatomical deformation model achieved better accuracy on longitudinal strain and significantly smaller tracking errors compared to regularized HARP tracking.
Why the study?
Does a phase-based registration method improve the accuracy of cardiac motion and strain quantification from tagged MR images compared to point-wise HARP tracking?
Does a phase-based registration method improve the accuracy of cardiac motion and strain quantification from tagged MR images compared to point-wise HARP tracking?
The proposed phase-based registration method improves the accuracy of longitudinal strain and reduces tracking errors in cardiac tagged MR images compared to existing HARP tracking methods.
May enhance tagged MRI strain accuracy in research; leaves open patient validation before clinical adoption.
We developed a phase-based registration method applied to cardiac motion and strain quantification from tagged MR images. A parametric deformation model defined in an anatomical space of the heart was incorporated into the registration framework. The model parameters were optimized by minimizing phase-based similarity criteria. The proposed method was compared to a previously developed algorithm where point-wise HARP tracking results were regularized a posteriori by the same parametric deformation model. On synthetic data, the two methods achieved similar results on motion and circumferential strain accuracies. However, our method achieved better accuracy on longitudinal strain. On volunteer data, our method gave smaller median and variance values on tracking errors with statistical significance.
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Zhou et al. (2016) studied Cardiac motion and strain quantification. Phase-based registration method with anatomical deformation model vs. Point-wise HARP tracking regularized a posteriori was evaluated on Motion and strain accuracies and tracking errors. A phase-based registration method using an anatomical deformation model achieved better accuracy on longitudinal strain and significantly smaller tracking errors compared to regularized HARP tracking.
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