Citations

ObjectivesFetal growth restriction (FGR) is commonly associated with placental dysfunction, increasing perinatal morbidity and mortality. Visualizing placental vessels in utero would be advantageous for identifying functional FGR cause and determining proper management strategies. We aimed to utilize high‐sensitivity ultrasound microvessel imaging (HUMI) for quantifying placental vessel density (VD) in pregnancies diagnosed with FGR.MethodsThis pilot case–control study enrolled subjects in the third trimester with a diagnosis of FGR (n = 40) and gestational age‐matched controls with normal fetal growth (n = 20) at a 2:1 ratio, respectively. The Verasonics Vantage ultrasound system was used to perform HUMI on each participant at one timepoint. Scanning involved randomized singular value decomposition‐based clutter filtering to identify the villous tree, followed by step‐by‐step scanning to acquire 3‐dimensional‐like data. Mean VD was calculated from three ultrasound measurements per subject. Additional clinical and pathology data were also collected and compared.ResultsSixteen participants were utilized to establish the scanning protocol and 2 met exclusion criteria at delivery. Thus, VD was successfully measured on 42 pregnancies scanned at 35 weeks 5 days on average. In FGR (n = 24), placental VD was significantly reduced compared to controls (P < .01). VD measures were as good at predicting FGR as systolic/diastolic (S/D) ratios (area under the curve 0.86 versus 0.80). In a smaller cohort, VD in placentas with a diagnosis of inflammatory villitis (n = 10) by histology showed an increase in VD compared to those without inflammation (P = .01). Low VD was correlated with increased S/D ratios (P = .03).ConclusionsHUMI is useful for identifying altered placental vascularization in utero for FGR. VD may be a valuable indicator for placental health and could lead to improved risk stratification methods considering underlying biology.

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.

Abstract Background No human rabies post-exposure prophylaxis (PEP) failure has been documented in the United States using modern cell culture–based vaccines. In January 2021, an 84-year-old male died from rabies 6 months after being bitten by a rabid bat despite receiving timely rabies PEP. We investigated the cause of breakthrough infection. Methods We reviewed medical records, laboratory results, and autopsy findings and performed whole-genome sequencing (WGS) to compare patient and bat virus sequences. Storage, administration, and integrity of PEP biologics administered to the patient were assessed; samples from leftover rabies immunoglobulin were evaluated for potency. We conducted risk assessments for persons potentially exposed to the bat and for close patient contacts. Results Rabies virus antibodies present in serum and cerebrospinal fluid were nonneutralizing. Antemortem blood testing revealed that the patient had unrecognized monoclonal gammopathy of unknown significance. Autopsy findings showed rabies meningoencephalitis and metastatic prostatic adenocarcinoma. Rabies virus sequences from the patient and the offending bat were identical by WGS. No deviations were identified in potency, quality control, administration, or storage of administered PEP. Of 332 persons assessed for potential rabies exposure to the case patient, 3 (0.9%) warranted PEP. Conclusions This is the first reported failure of rabies PEP in the Western Hemisphere using a cell culture–based vaccine. Host-mediated primary vaccine failure attributed to previously unrecognized impaired immunity is the most likely explanation for this breakthrough infection. Clinicians should consider measuring rabies neutralizing antibody titers after completion of PEP if there is any suspicion for immunocompromise.

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.

ObjectiveTo use probe oscillation shear wave elastography (PROSE) with two vibration sources to generate two shear waves in the imaging plane to quantitatively assess the shear wave speeds (SWSs) of muscles with and without the diagnosis of taut bands (TB) and/or myofascial trigger points (MTrPs).MethodsThirty‐three patients were scanned with the PROSE technique. Shear waves were generated through continuous vibration of the ultrasound probe, while the shear wave motions were detected using the same probe. SWSs for the sides with and without TBs and/or MTrPs were computed and compared. The pressure pain thresholds (PPTs) were measured as an indicator of maximum pain tolerance of patients. The statistical differences between the SWSs with and without TBs and/or MTrPs with different PPT values were analyzed using the nonparametric Wilcoxon rank‐sum test.ResultsThe mean SWSs for the sides with TBs and/or MTrPs are faster than that of the contralateral side without TBs and/or MTrPs. A significant difference was observed between mean SWSs with and without TBs and/or MTrPs without any information of PPT, with rank‐sum test P < .005. Additionally, with the information of PPT, a significant difference was observed between mean SWSs for the sides with and without TBs and/or MTrPs, for PPT values between 0 and 50 N/cm2 (P < .005), but for PPT values between 50 and 90 N/cm2, it was difficult to differentiate mean SWSs with and without TBs and/or MTrPs.ConclusionOur preliminary results show that SWSs measured from patients had a significant difference between the mean SWSs with and without TBs and/or MTrPs.

Abstract Non-invasive detection of microvascular alterations in deep tissues in vivo provides critical information for clinical diagnosis and evaluation of a broad-spectrum of pathologies. Recently, the emergence of super-resolution ultrasound localization microscopy (ULM) offers new possibilities for clinical imaging of microvasculature at capillary level. Currently, the clinical utility of ULM on clinical ultrasound scanners is hindered by the technical limitations, such as long data acquisition time, high microbubble (MB) concentration, and compromised tracking performance associated with low imaging frame-rate. Here we present a robust in-human ULM on a high frame-rate (HFR) clinical ultrasound scanner to achieve super-resolution microvessel imaging using a short acquisition time (<10 s). Ultrasound MB data were acquired from different human tissues, including a healthy liver and a diseased liver with acute-on-chronic liver failure, a kidney, a pancreatic tumor, and a breast mass using an HFR clinical scanner. By leveraging the HFR and advanced processing techniques including sub-pixel motion registration, MB signal separation, and Kalman filter-based tracking, MBs can be robustly localized and tracked for ULM under the circumstances of relatively high MB concentration associated with standard clinical MB administration and limited data acquisition time in humans. Subtle morphological and hemodynamic information in microvasculature were shown based on data acquired with single breath-hold and free-hand scanning. Compared with contrast-enhanced power Doppler generated based on the same MB dataset, ULM showed a 5.7-fold resolution improvement in a vessel based on a linear transducer, and provided a wide-range blood flow speed measurement that is Doppler angle-independent. Microvasculatures with complex hemodynamics can be well-differentiated at super-resolution in both normal and pathological tissues. This preliminary study implemented the ultrafast in-human ULM in various human tissues based on a clinical scanner that supports HFR imaging, indicating the potentials of the technique for various clinical applications. However, rigorous validation of the technique in imaging human microvasculature (especially for those tiny vessel structure), preferably with a gold standard, is still required.

Abstract Ultrasound localization microscopy (ULM) has been proposed to image microvasculature beyond the ultrasound diffraction limit. Although ULM can attain microvascular images with a sub-diffraction resolution, long data acquisition time and processing time are the critical limitations. Deep learning-based ULM (deep-ULM) has been proposed to mitigate these limitations. However, microbubble (MB) localization used in deep-ULMs is currently based on spatial information without the use of temporal information. The highly spatiotemporally coherent MB signals provide a strong feature that can be used to differentiate MB signals from background artifacts. In this study, a deep neural network was employed and trained with spatiotemporal ultrasound datasets to better identify the MB signals by leveraging both the spatial and temporal information of the MB signals. Training, validation and testing datasets were acquired from MB suspension to mimic the realistic intensity-varying and moving MB signals. The performance of the proposed network was first demonstrated in the chicken embryo chorioallantoic membrane dataset with an optical microscopic image as the reference standard. Substantial improvement in spatial resolution was shown for the reconstructed super-resolved images compared with power Doppler images. The full-width-half-maximum (FWHM) of a microvessel was improved from 133 μ m to 35 μ m, which is smaller than the ultrasound wavelength (73 μ m). The proposed method was further tested in an in vivo human liver data. Results showed the reconstructed super-resolved images could resolve a microvessel of nearly 170 μ m (FWHM). Adjacent microvessels with a distance of 670 μ m, which cannot be resolved with power Doppler imaging, can be well-separated with the proposed method. Improved contrast ratios using the proposed method were shown compared with that of the conventional deep-ULM method. Additionally, the processing time to reconstruct a high-resolution ultrasound frame with an image size of 1024 × 512 pixels was around 16 ms, comparable to state-of-the-art deep-ULMs.