Browsing by Author "Barnhill, E."

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    Fast robust dejitter and interslice discontinuity removal in MRI phase acquisitions: application to magnetic resonance elastography
    (IEEE, 2019-07) Barnhill, E.; Nikolova, M.; Arıyürek, Cemre; Dittmann, F.; Braun, J.; Sack, I.
    MRI phase contrast imaging methods that assemble slice-wise acquisitions into volumes can contain interslice phase discontinuities (IPDs) over the course of the scan from sources, including unavoidable physiological activity. In magnetic resonance elastography (MRE), this can alter wavelength and tissue stiffness estimates, invalidating the analysis. We first model this behavior as jitter along the z-axis of the phase of 3D complex-valued wave volumes. A two-step image processing pipeline is then proposed that removes IPDs. First, constant slicewise phase shift is removed with a novel, non-convex dejittering algorithm. Then, regional physiological noise artifacts are removed with novel filtering of 3D wavelet coefficients. Calibration of two pipeline coefficients, the dejitter parameter α and the wavelet band high-pass coefficient ωc , was first performed on a finite-element method brain phantom. A comparative investigation was then performed, on a cohort of 48 brain acquisitions, of four approaches to IPDs: 1) the proposed method; 2) a “control” condition of neglect of IPDs; 3) an anisotropic wavelet-based method; and 4) a method of in-plane (2D) processing. The present method showed medians of |G∗|=1873 Pa for a multifrequency wave inversion centered at 40 Hz which was within 6% of methods 3) and 4), while neglect produced |G∗| estimates a mean of 17% lower. The proposed method reduced the value range of the cohort against methods 3) and 4) by 29% and 31%, respectively. Such reduction in variance enhances the ability of brain MRE to predict subtler physiological changes. Our theoretical approach further enables more powerful applications of fundamental findings in noise and denoising to MRE.
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    Heterogeneous multifrequency direct inversion (HMDI) for magnetic resonance elastography with application to a clinical brain exam
    (Elsevier B.V., 2018) Barnhill, E.; Davies, P. J.; Ariyurek, C.; Fehlner, A.; Braun, J.; Sack, I.
    A new viscoelastic wave inversion method for MRE, called Heterogeneous Multifrequency Direct Inversion (HMDI), was developed which accommodates heterogeneous elasticity within a direct inversion (DI) by incorporating first-order gradients and combining results from a narrow band of multiple frequencies. The method is compared with a Helmholtz-type DI, Multifrequency Dual Elasto-Visco inversion (MDEV), both on ground-truth Finite Element Method simulations at varied noise levels and a prospective in vivo brain cohort of 48 subjects ages 18-65. In simulated data, MDEV recovered background material within 5% and HMDI within 1% of prescribed up to SNR of 20 dB. In vivo HMDI and MDEV were then combined with segmentation from SPM to create a fully automated “brain palpation” exam for both whole brain (WB), and brain white matter (WM), measuring two parameters, the complex modulus magnitude |G*|, which measures tissue “stiffness” and the slope of |G*| values across frequencies, a measure of viscous dispersion. |G*| values for MDEV and HMDI were comparable to the literature (for a 3-frequency set centered at 50 Hz, WB means were 2.17 and 2.15 kPa respectively, and WM means were 2.47 and 2.49 kPa respectively). Both methods showed moderate correlation to age in both WB and WM, for both |G*| and |G*| slope, with Pearson's r ≥ 0.4 in the most sensitive frequency sets. In comparison to MDEV, HMDI showed better preservation of recovered target shapes, more noise-robustness, and stabler recovery values in regions with rapid property change, however summary statistics for both methods were quite similar. By eliminating homogeneity assumptions within a fast, fully automatic, regularization-free direct inversion, HMDI appears to be a worthwhile addition to the MRE image reconstruction repertoire. In addition to supporting the literature showing decrease in brain viscoelasticity with age, our work supports a wide range of inter-individual variation in brain MRE results.