Huang, Chengwu

Objective: This study aims to develop a contrast-free, high-sensitivity ultrasound method, denoted as Radon transform-based flow measurement (R-Flow), for in vivo mapping of microvascular flow vectors and for establishing R-Flow-derived vector-field metrics to noninvasively quantify microcirculatory patterns in liver cirrhosis. Impact Statement: R-Flow enables robust, contrast-free imaging of microvascular dynamics and demonstrates translational feasibility in the human liver. Its direction-aware indices offer pilot in vivo quantification of flow redistribution and remodeling, providing unique insights into hepatic flow dynamics. Introduction: Microvascular dysfunction is a hallmark of many diseases, yet noninvasive visualization and quantitative assessment of abnormal microcirculation remain limited. Methods: R-Flow leverages Radon transform to decode red blood cell dynamics from the spatiotemporal domain of ultrasound flow signals, reconstructing velocity vectors at microvascular scale. From these vector maps, unique direction-aware indices are further derived to characterize flow distribution and heterogeneity. Results: Validated across simulations, phantoms, and in vivo studies, R-Flow provides robust velocity estimation across a wide range (1 to 60 mm/s). Notably, it enables high-sensitivity microvascular flow vector mapping of human liver, showing strong agreement with references ( r > 0.9). In a rat model, these direction-aware indices revealed a shift from healthy multipath perfusion in control livers to directionally biased vascular pattern in cirrhotic livers, demonstrating significant correlation with pathological indicators. Conclusion: R-Flow enables noninvasive, contrast-free mapping of microvascular blood flow velocity and offers a promising approach for high-resolution assessment of microvascular flow characteristics.

Key Points The kidney microvasculature was quantified reliably in human autosomal dominant polycystic kidney disease early on, using super-resolution ultrasound localization microscopy. Microvascular parameters correlated with structural and functional indices, constituting promising biomarkers to evaluate noncystic parenchyma. Microvascular parameters may serve to assess disease severity and monitor progression from the early stages of the disease. Background In vitro studies in individuals with autosomal dominant polycystic kidney disease (ADPKD) have shown extensive intrarenal microvascular remodeling. However, analyses have been limited to the time of kidney failure because of the invasive nature of current methodologies to assess the intrarenal microvasculature. We hypothesized that super-resolution ultrasound microvascular imaging, known as ultrasound localization microscopy, enabled by high-framerate ultrasound imaging and microbubble localization and tracking postprocessing techniques, would safely, reliably, and reproducibly assess the intrarenal microvasculature in individuals with ADPKD at an early stage of the disease. Methods We prospectively enrolled young (<40 years of age), well-characterized, early-stage (eGFR >90 ml/min per 1.73 m 2 ) individuals with ADPKD, and sex–age 1:1 matched controls ( n =17 each) and assessed the intrarenal microvasculature using ultrasound localization microscopy. We determined the intersonographer reliability, intraobserver repeatability, and interobserver reproducibility of microvascular parameters in both groups, and the day-to-day variability in the control group. Microvascular parameters were correlated with structural (total kidney volume) and functional (eGFR) markers in individuals with ADPKD. Results Ultrasound localization microscopy provided a super-resolved map of the intrarenal microvasculature in ADPKD and matched controls. Intrarenal microvascular parameters ( e.g ., vessel density) were quantified in a safe, reliable (intraclass correlation coefficients, 0.96; 95% confidence interval, 0.91 to 0.98), reproducible (intraclass correlation coefficient, 0.96; 95% confidence interval, 0.93 to 0.98), and repeatable (coefficient of variations, 3.6%) manner. In control individuals, the day-to-day variability of most parameters was low, with coefficient of variation ranging from 1.8% to 10.7%. Microvascular parameters differed in individuals with ADPKD compared with controls, despite preserved eGFR. Interestingly, cortical vessel density and its derived perfusion correlated directly with eGFR, whereas tortuosity indices presented an inverse correlation. Conclusions Ultrasound localization microscopy provided a safe and reliable in vivo assessment of the human intrarenal microvasculature.

ObjectivesMetabolic dysfunction‐associated steatotic liver disease (MASLD) is the most prevalent liver disorder in Western countries, with approximately 20%–30% of the MASLD patients progressing to severe stages. There is an urgent need for noninvasive, cost‐effective, widely accessible, and precise biomarkers to evaluate liver steatosis. This study aims to assess and compare the diagnostic performance of a novel reference frequency method‐based ultrasound attenuation coefficient estimation (ACE) in both fundamental (RFM‐ACE‐FI) and harmonic (RFM‐ACE‐HI) imaging for detecting and grading liver steatosis.MethodsAn Institutional Review Board‐approved prospective study was carried out between December 2018 and October 2022. A total number of 130 subjects were enrolled in the study. The correlation between RFM‐ACE‐HI values and magnetic resonance imaging proton density fat fraction (MRI‐PDFF), as well as between RFM‐ACE‐FI values and MRI‐PDFF were calculated. The diagnostic performance of RFM‐ACE‐FI and RFM‐ACE‐HI was evaluated using receiver operating characteristic (ROC) curve analysis, as compared to MRI‐PDFF. The reproducibility of RFM‐ACE‐HI was assessed by interobserver agreement between two sonographers.ResultsA strong correlation was observed between RFM‐ACE‐HI and MRI‐PDFF, with R = 0.88 (95% confidence interval [CI]: 0.83–0.92; P < .001), while the correlation between RFM‐ACE‐FI and MRI‐PDFF was R = 0.65 (95% CI: 0.50–0.76; P < .001). The area under the ROC (AUROC) curve for RFM‐ACE‐HI in staging liver steatosis grades of S ≥ 1 and S ≥ 2 was 0.97 (95% CI: 0.91–0.99; P < .001) and 0.98 (95% CI: 0.93–1.00; P < .001), respectively, and 0.76 (95% CI: 0.65–0.85) and 0.80 (95% CI: 0.70–0.88) for RFM‐ACE‐FI, respectively. Great reproducibility was achieved for RFM‐ACE‐HI, with an interobserver agreement of R = 0.97 (95% CI: 0.94–0.99; P < .001).ConclusionsThe novel RFM‐ACE‐HI method offered high liver steatosis diagnostic accuracy and reproducibility, which has important clinical implications for early disease intervention and treatment evaluation.

Recent advancements in ultrasound technologies, such as ultrasound localization microscopy and ultrafast ultrasound Doppler, have enabled high-definition imaging of microvasculature. However, detecting weak microbubble or blood flow signals amid strong background noise remains a challenge, particularly in deep tissues. This study aims to enhance the signal contrast of microbubble and blood flow by leveraging their distinct spatial-temporal coherence in comparison to undesired noise for robust microbubble detection and microvascular imaging. We propose to quantify the signal coherence based on similarity analysis of beamformed ultrasound microbubble/blood flow data within the plane wave imaging framework. A spatial pixel is considered more likely to be a true microbubble/blood flow signal with a higher level of similarity, which can be measured by either of the following methods: 1) spatially block-wise normalized cross-correlation between two compounded frames; 2) temporally normalized autocorrelation across multiple compounded frames; 3) normalized cross-correlation between two subsets of post-compounded frames; 4) normalized autocorrelation of the pre-compounded data across angular direction. The original microbubble/blood flow signal is then weighted by the similarity measurement on a pixel-by-pixel basis to generate images with an improved signal contrast. The robustness of the proposed methods was first demonstrated in both phantom experiments and in vivo microbubble data from kidney transplant. We further validated their feasibility in blood flow imaging without the use of microbubbles based on in vivo data of human liver and kidney. Significant contrast improvement was observed, facilitating better visualization and detection of both microbubble and noncontrast microflow signals, which indicates a great potential of the methods for improved microvascular imaging and widespread clinical translation.

Abstract Objective . Ultrasound attenuation coefficient estimation (ACE) has diagnostic potential for clinical applications such as quantifying fat content in the liver. Previously, we have proposed a system-independent ACE technique based on spectral normalization of different frequencies, called the reference frequency method (RFM). This technique does not require a well-calibrated reference phantom for normalization. However, this method may be vulnerable to severe reverberation clutter introduced by the body wall. The clutter superimposed on liver echoes may bias the estimation. Approach . We proposed to use robust principal component analysis, combined with wavelet-based sparsity promotion, to suppress the severe reverberation clutters. The capability to mitigate the reverberation clutters was validated through phantom and in vivo studies. Main Results . In the phantom studies with added reverberation clutters, higher normalized cross-correlation and smaller mean absolute errors were attained as compared to RFM results without the proposed method, demonstrating the capability to reconstruct tissue signals from reverberations. In a pilot patient study, the correlation between ACE and proton density fat fraction (PDFF), a measurement of liver fat by MRI as a reference standard, was investigated. The proposed method showed an improvement of the correlation (coefficient of determination, R = 0.82) as compared with the counterpart without the proposed method ( R = 0.69). Significance : The proposed method showed the feasibility of suppressing the reverberation clutters, providing an important basis for the development of a robust ACE with large reverberation clutters.

Abstract Photoacoustic tomography (PAT), a hybrid imaging modality that acoustically detects the optical absorption contrast, is a promising technology for imaging hemodynamic functions in deep tissues. Particularly, PAT is capable of measuring the blood oxygenation level using hemoglobin as the endogenous contrast. However, the most clinically compatible PAT configuration usually employs a linear ultrasound transducer array and often suffers from the poor image fidelity, mostly due to the limited detection view of the transducer array. PAT can be improved by employing highly-absorbing contrast agents such as droplets and nanoparticles, which, however, have low clinical translation potential due to safety concerns and regulatory hurdles. Moreover, unlike hemoglobin, these exogenous contrast agents cannot report the functional hemodynamic information. In this work, we have developed a new methodology that can improve PAT’s image fidelity without hampering its functional capability or clinical translation potential. By using clinically-approved microbubbles as virtual point sources that strongly scatter the local pressure waves generated by surrounding hemoglobin, we can overcome the limited-detection-view problem and achieve high-fidelity functional PAT in deep tissues, a technology referred to as virtual-point-source PAT (VPS-PAT). We have thoroughly investigated the working principle of VPS-PAT by numerical simulations and phantom validations, showing the acoustic origin of signal enhancement and the superiority over traditional PAT. We have also demonstrated proof-of-concept applications of functional VPT-PAT for in vivo small-animal studies with physiological challenges. We expect that VPS-PAT can find broad applications in biomedical research and accelerated translation to clinical impact.