Blood flow imaging using singular value decomposition filter during high-intensity focused ultrasound exposure

Ikeda, Hayato; Yoshizawa, Shin; Maeda, Moe; Umemura, Shin‐ichiro; Saijo, Yoshifumi

doi:10.7567/1347-4065/ab1a2e

Cited by 11 publications

(11 citation statements)

References 27 publications

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“…Other studies have applied SVD filtering in ultrasound studies like blood flow imaging [50]. However, the optimization of the cutoff value of SVD filtering for SWEI has not been widely studied.…”

Section: Discussionmentioning

confidence: 99%

Shear Wave Dispersion as a Potential Biomarker for Cervical Remodeling During Pregnancy: Evidence From a Non-Human Primate Model

et al. 2021

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Shear wave dispersion (variation of phase velocity with frequency) occurs in tissues with layered and anisotropic microstructure and viscous components, such as the uterine cervix. This phenomenon, mostly overlooked in previous applications of cervical Shear Wave Elasticity Imaging (SWEI) for preterm birth risk assessment, is expected to change drastically during pregnancy due to cervical remodeling. Here we demonstrate the potential of SWEI-based descriptors of dispersion as potential biomarkers for cervical remodeling during pregnancy. First, we performed a simulation-based pre-selection of two SWEI-based dispersion descriptors: the ratio R of group velocities computed with particle-velocity and particle-displacement, and the slope S of the phase velocity vs. frequency. The pre-selection consisted of comparing the contrast-to-noise ratio (CNR) of dispersion descriptors in materials with different degrees of dispersion with respect to a low-dispersive medium. Shear waves induced in these media by SWEI were simulated with a finite-element model of Zener viscoelastic solids. The pre-selection also considered two denoising strategies to improve CNR: a low-pass filter with automatic frequency cutoff determination, and singular value decomposition of shear wave displacements. After pre-selection, the descriptor-denoising combination that produced the largest CNR was applied to SWEI cervix data from 18 pregnant Rhesus macaques acquired at weeks 10 (mid-pregnancy stage) and 23 (late pregnancy stage) of the 24.5-weeks full pregnancy. A maximum likelihood linear mixed-effects model (LME) was used to evaluate the dependence of the dispersion descriptor on pregnancy stage, maternal age, parity and other experimental factors. The pre-selection study showed that descriptor S combined with singular value decomposition produced a CNR 11.6 times larger than the other descriptor and denoising strategy combinations. In the Non-Human Primates (NHP) study, the LME model showed that descriptor S significantly decreased from mid to late pregnancy (−0.37 ± 0.07 m/s-kHz per week, p< 0.00001) with respect to the base value of 15.5 ± 1.9 m/s-kHz. This change was more significant than changes in other SWEI features such as the group velocity previously reported. Also, S varied significantly between the anterior and posterior portions of the cervix (p= 0.02) and with maternal age (p= 0.008). Given the potential of shear wave dispersion to track cervical remodeling, we will extend its application to ongoing longitudinal human studies.

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Section: Discussionmentioning

confidence: 99%

Shear Wave Dispersion as a Potential Biomarker for Cervical Remodeling During Pregnancy: Evidence From a Non-Human Primate Model

et al. 2021

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“…SVD is widely applied in signal processing to analyze real or complex matrices [ 14 ]. The SVD of an m × n matrix S can be formulated as…”

Section: Methodsmentioning

confidence: 99%

“…However, their approach is less applicable when long, continuous HIFU treatment is required. More recently, singular value decomposition (SVD)–based blood flow imaging during HIFU exposure was suggested [ 14 ], which showed promising potential for eliminating HIFU artifacts from Doppler sequences.…”

Section: Introductionmentioning

confidence: 99%

“…This approach relies on SVD, which decomposes individual scanline data into several components, making it possible to extract interference-free ultrasound images by adaptively tracking the HIFU center frequencies [ 15 , 16 ]. Compared to the previous approach [ 14 ], decomposing two-dimensional (2-D) image data to select the desired components excluding HIFU signals, this approach relies on one-dimensional (1-D) scanline data to generate a sufficient number of decomposed components. In addition, harmonic imaging is used as a baseline imaging method to improve the contrast resolution of guidance images for effective lesion localization [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive singular value decomposition filtering of high-intensity focused ultrasound interference enables real-time ultrasound-guided therapy

et al. 2023

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High-intensity focused ultrasound (HIFU) is an emerging therapeutic tool for effective thermal ablation of pathological tissue. For accurate localization of the target, and safe control of the HIFU dosage, real-time image guidance is desired during the HIFU exposure. Ultrasound imaging has a capability to guide the lesions in real-time, but is not an ideal option, as the HIFU application causes a strong interference, and thus, distorts the guidance image substantially. Thus, this study introduces singular value decomposition (SVD)-based filtering capable of restoring ultrasound harmonic images from the HIFU interferences without undesirable spectral distortion. The results experimentally validated with a custom-made phantom indicate that our approach eliminates HIFU-induced artifacts effectively, which is essential for real-time monitoring of therapeutic process.

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“…SVD has been widely used in medical ultrasound, especially in the field of blood flow imaging. [28][29][30][31][32][33][34][35][36] When SVD is used to identify artifacts or blood flow components from the acquired signal, [37][38][39] the spatial information of the signal and the temporal information in the frame direction are separated. In the present study, because the purpose is to improve the axial resolution of medical ultrasound images, only the information of the signal in the beam (depth) direction for a single frame is used for SVD.…”

Section: Introductionmentioning

confidence: 99%

Improving axial resolution of medical ultrasound images by using noise-robust broadband filter based on singular value decomposition

Kawamata

Mori

Arakawa

et al. 2022

Jpn. J. Appl. Phys.

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Improving spatial resolution is a crucial issue in medical ultrasound. One of the improving methods is the post-processing of the received ultrasound RF signal. In the present paper, we propose a design method for a noise-robust broadband filter based on the singular value decomposition of the received RF signal. To design a noise-robust filter, we propose a logical method to determine the optimal truncated order of singular values, which was validated by applying the filter to noise-contaminated signals. Furthermore, the proposed filter applied to the wire phantom resulted in a better axial resolution than that obtained without the filter and with our previously designed Wiener filter.

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Blood flow imaging using singular value decomposition filter during high-intensity focused ultrasound exposure

Cited by 11 publications

References 27 publications

Shear Wave Dispersion as a Potential Biomarker for Cervical Remodeling During Pregnancy: Evidence From a Non-Human Primate Model

Shear Wave Dispersion as a Potential Biomarker for Cervical Remodeling During Pregnancy: Evidence From a Non-Human Primate Model

Adaptive singular value decomposition filtering of high-intensity focused ultrasound interference enables real-time ultrasound-guided therapy

Improving axial resolution of medical ultrasound images by using noise-robust broadband filter based on singular value decomposition

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