Reverberant shear wave phase gradients for elastography

Ormachea, Juvenal; Parker, Kevin J.

doi:10.1088/1361-6560/ac1b37

Cited by 12 publications

(12 citation statements)

References 28 publications

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“…Application of 2 kHz shear waves to the cranium with multiple contact points creates a randomized pattern of shear waves that we classify as a RSW field, with a characteristic 'boiling' pattern shown in figures 6(b) and (e). Estimators then assess the local value of SWS (Parker et al 2017, Ormachea andParker 2021) which are displayed in colors within the 3D scanned volume as shown in figure 6. In the cranial window, major vessels can be resolved and the proximal region surrounding them may appear softer than the more distal parenchyma, see figure 6(c).…”

Section: Resultsmentioning

confidence: 99%

Theory of sleep/wake cycles affecting brain elastography

Ge¹,

Song²,

Nedergaard³

et al. 2022

Phys. Med. Biol.

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As elastography of the brain finds increasing clinical applications, fundamental questions remain about baseline viscoelastic properties of the brain in vivo. Furthermore, the underlying mechanisms of how and why elastographic measures can change over time are still not well understood. To study these issues, reverberant shear wave elastography using an optical coherence tomography scanner is implemented on a mouse model, both under awake conditions and in a sleep state where there are known changes in the glymphatic fluid flow system in the brain. We find that shear wave speed, a measure of stiffness, changes by approximately 12% between the two states, sleep vs awake, in the entire cortical brain imaging volume. Our microchannel flow model of biphasic (fluid plus solid) tissue provides a plausible rheological model based on the fractal branching vascular and perivascular system, plus a second parallel system representing the finer scale glymphatic fluid microchannels. By adjusting the glymphatic system fluid volume proportional to the known wake/sleep changes, we are able to approximately predict the measured shear wave speeds and their change with the state of the glymphatic system. The advantages of this model are that its main parameters are derived from anatomical measures and are linked to other major derivations of branching fluid structures including Murray’s Law. The implications for clinical studies are that elastography of the brain is strongly influenced by the regulation or dysregulation of the vascular, perivascular, and glymphatic systems.

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Section: Resultsmentioning

confidence: 99%

Theory of sleep/wake cycles affecting brain elastography

Ge¹,

Song²,

Nedergaard³

et al. 2022

Phys. Med. Biol.

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“…The general principles of reverberant elastography have been previously described (Ormachea et al 2018 , 2019 , Zvietcovich et al 2019 , Ormachea and Parker 2021 ); therefore, in this section, we provide a summary of the approach. Complex wave fields are produced when plane waves that originate from multiple point sources or reflected from various angles superimpose.…”

Section: Methodsmentioning

confidence: 99%

Reverberant magnetic resonance elastographic imaging using a single mechanical driver

Kabir

Caban-Rivera

Ormachea³

et al. 2023

Phys. Med. Biol.

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Reverberant elastography provides fast and robust estimates of shear modulus; however, its reliance on multiple mechanical drivers hampers clinical utility. In this work, we hypothesize that for constrained organs such as the brain, reverberant elastography can produce accurate magnetic resonance elastograms with a single mechanical driver. To corroborate this hypothesis, we performed studies on healthy volunteers (n=3); and a constrained calibrated brain phantom containing spherical inclusions with diameters ranging from 4-18 mm. In both studies (i.e., phantom and clinical), imaging was performed at frequencies of 50 Hz and 70 Hz. We used the accuracy and contrast-to-noise ratio performance metrics to evaluate reverberant elastograms relative to those computed using the established subzone inversion method. Errors incurred in reverberant elastograms varied from 1.3% to 16.6% when imaging at 50 Hz and 3.1% and 16.8 % when imaging at 70 Hz. In contrast, errors incurred in subzone elastograms ranged from 1.9% to 13% at 50 Hz and 3.6% to 14.9% at 70 Hz. The contrast-to-noise ratio of reverberant elastograms ranged from 63.1 dB to 73 dB compared to 65 dB to 66.2 dB for subzone elastograms. The average global brain stiffness estimated from reverberant and subzone elastograms was 2.36 ± 0.07 kPa and 2.38 ± 0.11 kPa, respectively, when imaging at 50 Hz and 2.70 ± 0.20 kPa and 2.89 ± 0.60 kPa respectively, when imaging at 70 Hz. The results of this investigation demonstrate that reverberant elastography can produce accurate, high-quality elastograms of the brain with a single mechanical driver.

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“…Ormachea et al 10 proposed the Phase Gradient (PG) estimator which is less sensitive to imperfections in the reverberant field and enables smaller window sizes, therefore capable of generating images with better spatial resolution. The PG approach established that is possible to obtain the SWS by the phase distribution of the field.…”

Section: Phase Gradientmentioning

confidence: 99%

“…The filter was used to enhance the image and reduce the variability of the estimations. 10 This filter can be automatic as it is based on frequency and spatial resolution. Initially, this automated value was 51.…”

Section: Phase Gradientmentioning

confidence: 99%

“…8,9 A second estimator based on the phase gradient of the reverberant field was proposed with less sensitivity of non-uniformities in the field, and only requiring a linear fit with less computational cost to its predecessor. 10 The last estimator considered for this comparison is a U-Net-based deep learning algorithm for SWS estimation. 11 A comparison-based study was performed by using the three estimators for tissue characterization with simulations considering a circular inclusion.…”

Section: Introductionmentioning

confidence: 99%

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A simulation study to compare shear wave speed estimators of the reverberant shear wave elastography approach

Romero

Romero²,

Bohorquez³

et al. 2023

18th International Symposium on Medical Information Processing and Analysis

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Reverberant shear wave elastography is quantitative elastography approach that involves the generation of a reverberant field that propagates in all directions within the medium. Based on the generation of the field, the information about tissues stiffness can be obtained by measuring the shear wave speed (SWS). This approach has showed encouraging results for characterization of tissues such as the experiments already carried out in vivo. The aim of this study is to evaluate the quality of SWS estimators for acoustic reverberant fields in heterogeneous media to achieve this purpose, three estimators were tested: Curve fitting, Phase Gradient and a Convolutional Neural Network. Parameters such as time of processing, accuracy, resolution and contrast between background and inclusion were used to determine the best estimator. The results show the inclusion zone a maximum accuracy of 94.75% can be obtained with the deep learning estimator; while, in the background, the maximum accuracy was obtained with the phase gradient estimator and was 96.85%. Even though all three estimators show good results, the execution time, lateral resolution, contrast and CNR have better results with the deep learning estimator.

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Reverberant shear wave phase gradients for elastography

Cited by 12 publications

References 28 publications

Theory of sleep/wake cycles affecting brain elastography

Theory of sleep/wake cycles affecting brain elastography

Reverberant magnetic resonance elastographic imaging using a single mechanical driver

A simulation study to compare shear wave speed estimators of the reverberant shear wave elastography approach

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