Advanced Techniques for Liver Fibrosis Detection: Spectral Photoacoustic Imaging and Superpixel Photoacoustic Unmixing Analysis for Collagen Tracking.

Liver fibrosis, a major global health issue, is marked by excessive collagen deposition that impairs liver function. Noninvasive methods for the direct visualization of collagen content are crucial for the early detection and monitoring of fibrosis progression. This study investigates the potential of spectral photoacoustic imaging (sPAI) to monitor collagen development in liver fibrosis. Utilizing a novel data-driven superpixel photoacoustic unmixing (SPAX) framework, we aimed to distinguish collagen presence and evaluate its correlation with fibrosis progression. We employed an established diethylnitrosamine (DEN) model in rats to study liver fibrosis over various time points. Our results revealed a significant correlation between increased collagen photoacoustic signal intensity and advanced fibrosis stages. Collagen abundance maps displayed dynamic changes throughout fibrosis progression. These findings underscore the potential of sPAI for the noninvasive monitoring of collagen dynamics and fibrosis severity assessment. This research advances the development of noninvasive diagnostic tools and personalized management strategies for liver fibrosis.

In Vivo Photoacoustic Ultrasound (PAUS) Assay for Monitoring Tendon Collagen Compositional Changes during Injury and Healing.

Tendon injury and healing involve significant changes to tissue biology and composition. Current techniques often require animal sacrifice or tissue destruction, limiting assessment of dynamic changes in tendons, including treatment response, disease development, rupture risk, and healing progression. Changes in tendon composition, such as altered collagen content, can significantly impact tendon mechanics and function. Analyses of compositional changes typically require ex vivo techniques with animal sacrifice or destruction of the tissue. In vivo evaluation of tendons is critical for longitudinal assessment. We hypothesize that photoacoustic ultrasound detects differences in collagen concentration throughout healing. We utilized photoacoustic ultrasound, a hybrid imaging modality that combines ultrasound and laser-induced photoacoustic signals to create detailed and high-resolution images of tendons, to identify its endogenous collagen composition. We correlated the photoacoustic signal to picrosirius red staining. The results show that the photoacoustic ultrasound-estimated collagen content in tendons correlates well with picrosirius red staining. This study demonstrates that photoacoustic ultrasound can assess injury-induced compositional changes within tendons and is the first study to image these targets in rat Achilles tendon in vivo.

Can Artificial Intelligence Aid Diagnosis by Teleguided Point-of-Care Ultrasound? A Pilot Study for Evaluating a Novel Computer Algorithm for COVID-19 Diagnosis Using Lung Ultrasound.

With the 2019 coronavirus disease (COVID-19) pandemic, there is an increasing demand for remote monitoring technologies to reduce patient and provider exposure. One field that has an increasing potential is teleguided ultrasound, where telemedicine and point-of-care ultrasound (POCUS) merge to create this new scope. Teleguided POCUS can minimize staff exposure while preserving patient safety and oversight during bedside procedures. In this paper, we propose the use of teleguided POCUS supported by AI technologies for the remote monitoring of COVID-19 patients by non-experienced personnel including self-monitoring by the patients themselves. Our hypothesis is that AI technologies can facilitate the remote monitoring of COVID-19 patients through the utilization of POCUS devices, even when operated by individuals without formal medical training. In pursuit of this goal, we performed a pilot analysis to evaluate the performance of users with different clinical backgrounds using a computer-based system for COVID-19 detection using lung ultrasound. The purpose of the analysis was to emphasize the potential of the proposed AI technology for improving diagnostic performance, especially for users with less experience.

Hydralazine-augmented contrast ultrasound imaging improves the detection of hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) detection with B-mode and contrast-enhanced ultrasound (CUS) imaging often varies between subjects, especially in patients with background cirrhosis. Various factors contribute to this variability, including the tumor blood flow, tumor size, internal echoes, and its location in livers with diffuse fibro-cirrhotic changes. OBJECTIVE: Towards improving lesion detection, this study evaluates a vasodilator, hydralazine, to enhance the visibility of HCC by reducing its blood flow relative to the surrounding liver tissue. METHODS: HCC were analyzed for tumor visibility measured for B-mode, CUS, and hydralazine-augmented-contrast ultrasound (HyCUS) in an autochthonous HCC rat model. 21 tumors from 12 rats were studied. B-mode and CUS images were acquired before hydralazine injection. Rats received an intravenous hydralazine injection of 5 mg/kg, then images were acquired 20 min later. Four rats were used as controls. The difference in echo intensity of the lesion and the surrounding tissue was used to determine the visibility index (VI). RESULTS: The visibility index for HCC was found to be significantly improved with the use of HyCUS imaging compared to traditional B-mode and CUS imaging. The visibility index for HCC was 16.5 ± 2.8 for HyCUS, compared to 5.3 ± 4.8 for B-mode and 4.1 ± 3.8 for CUS. The differences between HyCUS and the other imaging modalities were statistically significant, with p-values of 0.001 and 0.02, respectively. Additionally, when compared to control cases, HyCUS showed higher discrimination of HCC (VI = 6.4 ± 1.2) with a p-value of 0.003, while B-mode (VI = 6.7 ± 1.4, p = 0.5) and CUS (VI = 6.4 ± 1.2, p = 0.3) showed lower discrimination. CONCLUSION: Vascular blood flow modulation by hydralazine enhances the visibility of HCC. HyCUS offers a potential problem-solving method for detecting HCC when B-mode and CUS are unsuccessful, especially with background fibro-cirrhotic liver disease. Future evaluation of the approach in humans will determine its translatability for clinical applications.

Sonothrombolysis: State-of-the-Art and Potential Applications in Children.

In recent years, advances in ultrasound therapeutics have been implemented into treatment algorithms for the adult population; however, the use of therapeutic ultrasound in the pediatric population still needs to be further elucidated. In order to better characterize the utilization and practicality of sonothrombolysis in the juvenile population, the authors conducted a literature review of current pediatric research in therapeutic ultrasound. The PubMed database was used to search for all clinical and preclinical studies detailing the use and applications of sonothrombolysis, with a focus on the pediatric population. As illustrated by various review articles, case studies, and original research, sonothrombolysis demonstrates efficacy and safety in clot dissolution in vitro and in animal studies, particularly when combined with microbubbles, with potential applications in conditions such as deep venous thrombosis, peripheral vascular disease, ischemic stroke, myocardial infarction, and pulmonary embolism. Although there is limited literature on the use of therapeutic ultrasound in children, mainly due to the lower prevalence of thrombotic events, sonothrombolysis shows potential as a noninvasive thrombolytic treatment. However, more pediatric sonothrombolysis research needs to be conducted to quantify the safety and ethical considerations specific to this vulnerable population.

Ultrasound Radiomics for the Detection of Early-Stage Liver Fibrosis.

Objective: The study evaluates quantitative ultrasound (QUS) texture features with machine learning (ML) to enhance the sensitivity of B-mode ultrasound (US) for the detection of fibrosis at an early stage and distinguish it from advanced fibrosis. Different ML methods were evaluated to determine the best diagnostic model. Methods: 233 B-mode images of liver lobes with early and advanced-stage fibrosis induced in a rat model were analyzed. Sixteen features describing liver texture were measured from regions of interest (ROIs) drawn on B-mode images. The texture features included a first-order statistics run length (RL) and gray-level co-occurrence matrix (GLCM). The features discriminating between early and advanced fibrosis were used to build diagnostic models with logistic regression (LR), naïve Bayes (nB), and multi-class perceptron (MLP). The diagnostic performances of the models were compared by ROC analysis using different train-test sampling approaches, including leave-one-out, 10-fold cross-validation, and varying percentage splits. METAVIR scoring was used for histological fibrosis staging of the liver. Results: 15 features showed a significant difference between the advanced and early liver fibrosis groups, p < 0.05. Among the individual features, first-order statics features led to the best classification with a sensitivity of 82.1−90.5% and a specificity of 87.1−89.8%. For the features combined, the diagnostic performances of nB and MLP were high, with the area under the ROC curve (AUC) approaching 0.95−0.96. LR also yielded high diagnostic performance (AUC = 0.91−0.92) but was lower than nB and MLP. The diagnostic variability between test-train trials, measured by the coefficient-of-variation (CV), was higher for LR (3−5%) than nB and MLP (1−2%). Conclusion: Quantitative ultrasound with machine learning differentiated early and advanced fibrosis. Ultrasound B-mode images contain a high level of information to enable accurate diagnosis with relatively straightforward machine learning methods like naïve Bayes and logistic regression. Implementing simple ML approaches with QUS features in clinical settings could reduce the user-dependent limitation of ultrasound in detecting early-stage liver fibrosis.

Contrast-Enhanced Ultrasound Tumor Therapy With Abdominal Imaging Transducer.

A diagnostic ultrasound machine add-on module (AOM) was created to enable an off-the-shelf abdominal imaging transducer to perform contrast-enhanced therapeutic ultrasound. The AOM creates plane-wave ultrasound through an abdominal imaging transducer targeting intravascular microbubbles within tumors. This therapeutic antivascular ultrasound (AVUS) causes heating and cavitation effects that destroy tumor vasculature and starves it of nutrients. The AOM can switch between therapeutic and imaging modes for monitoring AVUS treatment. The therapeutic capability of the AOM was validated in murine hepatocellular carcinomas (HCC) grown in adult mice. Contrast-enhanced ultrasound imaging performed before and after the therapeutic treatment evaluated the AVUS response to the treatment. The peak enhancement (PE), perfusion index (PI), and area under the curve (AUC) were measured for the control and AOM treatment groups. The AOM group showed a substantial decrease in these parameters compared to the control group. The difference between the pre- and post-therapy was significant, (p < 0.001) for the AOM group and not significant (p > 0.5) for the control group. Tumor temperatures increased markedly for the AOM group with a thermal dose (CEM43) of 124.8 (±2.5). Histochemical analysis of the excised HCC samples revealed several hemorrhagic pools in tumors from the AOM group, absent in the tumors of the control group. These results demonstrate the theranostic potential of the AOM to induce and monitor vascular disruption within murine tumors.

Dynamic contrast-enhanced MRI and Doppler sonography in patients with squamous cell carcinoma of head and neck treated with induction chemotherapy.

In view of the inherent limitations associated with performing dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in clinical settings, current study was designed to provide a proof of principle that Doppler sonography and DCE-MRI derived perfusion parameters yield similar hemodynamic information from metastatic lymph nodes in squamous cell carcinomas of head and neck (HNSCCs). Strong positive correlations between volume fraction of plasma space in tissues (Vp ) and blood volume (r = 0.72, p = 0.02) and between Vp and %area perfused (r = 0.65, p = 0.04) were observed. Additionally, a moderate positive correlation trending towards significance was obtained between volume transfer constant (Ktrans ) and %area perfused (r = 0.49, p = 0.09).

Can Sequential Images from the Same Object Be Used for Training Machine Learning Models? A Case Study for Detecting Liver Disease by Ultrasound Radiomics.

Machine learning for medical imaging not only requires sufficient amounts of data for training and testing but also that the data be independent. It is common to see highly interdependent data whenever there are inherent correlations between observations. This is especially to be expected for sequential imaging data taken from time series. In this study, we evaluate the use of statistical measures to test the independence of sequential ultrasound image data taken from the same case. A total of 1180 B-mode liver ultrasound images with 5903 regions of interests were analyzed. The ultrasound images were taken from two liver disease groups, fibrosis and steatosis, as well as normal cases. Computer-extracted texture features were then used to train a machine learning (ML) model for computer-aided diagnosis. The experiment resulted in high two-category diagnosis using logistic regression, with AUC of 0.928 and high performance of multicategory classification, using random forest ML, with AUC of 0.917. To evaluate the image region independence for machine learning, Jenson-Shannon (JS) divergence was used. JS distributions showed that images of normal liver were independent from each other, while the images from the two disease pathologies were not independent. To guarantee the generalizability of machine learning models, and to prevent data leakage, multiple frames of image data acquired of the same object should be tested for independence before machine learning. Such tests can be applied to real-world medical image problems to determine if images from the same subject can be used for training.

Increasing Vascular Response to Injury Improves Tendon Early Healing Outcome in Aged Rats.

Tendon injuries positively correlate with patient age, as aging has significant effects on tendon homeostatic maintenance and healing potential after injury. Vascularity is also influenced by age, with both clinical and animal studies demonstrating reduced blood flow in aged tissues. However, it is unknown how aging effects vascularity following tendon injury, and if this vascular response can be modulated through the delivery of angiogenic factors. Therefore, the objective of this study is to evaluate the vascular response following Achilles tendon injury in adult and aged rats, and to define the alterations to tendon healing in an aged model following injection of angiogenic factors. It was determined that aged rat Achilles tendons have a reduced angiogenesis following injury. Further, the delivery of vascular endothelial growth factor, VEGF, caused an increase in vascular response to tendon injury and improved mechanical outcome in this aged population. This work suggests that reduced angiogenic potential with aging may be contributing to impaired tendon healing response and that the delivery of angiogenic factors can rescue this impaired response. This study was also the first to relate changes in vascular response in an aged model using in vivo measures of blood perfusion to alterations in healing properties.

Hyperechoic Renal Masses: Differentiation of Angiomyolipomas from Renal Cell Carcinomas using Tumor Size and Ultrasound Radiomics.

A retrospective single-center study was performed to assess the performance of ultrasound image-based texture analysis in differentiating angiomyolipoma (AML) from renal cell carcinoma (RCC) on incidental hyperechoic renal lesions. Ultrasound reports of patients from 2012 to 2017 were queried, and those with a hyperechoic renal mass <5 cm in diameter with further imaging characterization and/or pathological correlation were included. Quantitative texture analysis was performed using a model including 18 texture features. Univariate logistic regression was used to identify texture variables differing significantly between AML and RCC, and the performance of the model was measured using the area under the receiver operating characteristic (ROC) curve. One hundred thirty hyperechoic renal masses in 127 patients characterized as RCCs (25 [19%]) and AMLs (105 [81%]) were included. Size (odds ratio [OR] = 0.12, 95% confidence interval [CI]: 0.04-0.43, p < 0.001) and 4 of 18 texture features, including entropy (OR = 0.09, 95% CI: 0.01-0.81, p = 0.03), gray-level non-uniformity (OR = 0.12, 95% CI: 0.02-0.72, p = 0.02), long-run emphasis (OR = 0.49, 95% CI: 0.27-0.91, p = 0.02) and run-length non-uniformity (OR = 2.18, 95% CI: 1.14-4.16, p = 0.02) were able to differentiate AMLs from RCCs. The area under the ROC curve for the performance of the model, including texture features and size, was 0.945 (p < 0.001). Ultrasound image-based textural analysis enables differentiation of hyperechoic RCCs from AMLs with high accuracy, which improves further when combined with tumor size.

A comparison of ultrasound echo intensity to magnetic resonance imaging as a metric for tongue fat evaluation.

STUDY OBJECTIVES: Tongue fat is associated with obstructive sleep apnea (OSA). Magnetic resonance imaging (MRI) is the standard for quantifying tongue fat. Ultrasound echo intensity has been shown to correlate to the fat content in skeletal muscles but has yet to be studied in the tongue. The objective of this study is to evaluate the relationship between ultrasound echo intensity and tongue fat. METHODS: Ultrasound coronal cross-sections of ex-vivo cow tongues were recorded at baseline and following three 1 mL serial injections of fat into the tongue. In humans, adults with and without OSA had submental ultrasound coronal cross-sections of their posterior tongue. The average echo intensity of the tongues (cow/human) was calculated in ImageJ software. Head and neck MRIs were obtained on human subjects to quantify tongue fat volume. Echo intensity was compared to injected fat volume or MRI-derived tongue fat percentage. RESULTS: Echo intensity in cow tongues showed a positive correlation to injected fat volume (rho = 0.93, p < .001). In human subjects, echo intensity of the tongue base strongly correlated with MRI-calculated fat percentage for both the posterior tongue (rho = 0.95, p < .001) and entire tongue (rho = 0.62, p < .001). Larger tongue fat percentages (rho = 0.38, p = .001) and higher echo intensity (rho = 0.27, p = .024) were associated with more severe apnea-hypopnea index, adjusted for age, body mass index, sex, and race. CONCLUSIONS: Ultrasound echo intensity is a viable surrogate measure for tongue fat volume and may provide a convenient modality to characterize tongue fat in OSA.

Machine learning improves early detection of liver fibrosis by quantitative ultrasound radiomics.

Progression of liver fibrosis to cirrhosis, a severe non-reversible process, is one of the most critical risk factors in developing hepatocellular carcinoma and liver failure. Detection of liver fibrosis at an early stage is therefore essential for better patient management. Ultrasound (US) imaging can provide a noninvasive alternative to biopsies. This study evaluates quantitative US texture features to improve early-stage versus advanced liver fibrosis detection. 157 B-mode US images of different liver lobes acquired from early and advanced fibrosis rat cases were used for analysis. 5-6 regions of interest were placed on each image. Twelve quantitative features that describe liver texture changes were extracted from the images, including first-order histogram, run length (RL), and gray level co-occurrence matrix (GLCM). The diagnostic performance of individual features was high with AUC ranging from 0.80 to 0.94. Logistic regression with leave-one-out cross-validation was used to evaluate the performance of the combined features. All features combined showed a slight improvement in performance with AUC = 0.95, sensitivity = 96.8%, and specificity = 93.7%. Quantitative US texture features characterize liver fibrosis changes with high accuracy and can differentiate early from advanced disease. Quantitative ultrasound, if validated in future clinical studies, can have a potential role in identifying fibrosis changes that are not easily detected by visual US image assessments.

Contrast-enhanced ultrasound for assessing blood flow modulation of hepatocellular carcinoma by hydralazine.

Modulating aberrant tumor microvasculature provides unique opportunities for enhancing ultrasound imaging of hepatocellular carcinoma (HCC). This study aims to use contrast-enhanced ultrasound to evaluate the potential of a potent vasodilator, hydralazine, to attenuate blood flow in HCC while enhancing it in the surrounding liver tissue. The "steel effect," where blood flow is diverted from the lesion to the surrounding tissue aims to enhance lesion-tissue contrast. Methods: HCC was induced in six rats by oral ingestion of diethylnitrosamine for 12 weeks. 10 tumors were studied to assess the enhancement in HCC tumors and surrounding tissue. Contrast-enhanced ultrasound images (CEUS) of each tumor were acquired before and after hydralazine injection. The enhancement of images was analyzed for the qualitative and quantitative assessment of HCC enhancement. Peak enhancement (PE) was calculated, representing the maximum signal intensity reached during the transit of the contrast bolus for both the tumor and the surrounding tissue. Intravenous administration of hydralazine significantly reduced CEUS signals in HCC tumors. The visual examination of images showed that the enhancement of tumors dramatically decreased after hydralazine injection. On the other hand, the surrounding tissue showed an increased enhancement. PE for the HCC changed from (71.8 ± 5) pre hydralazine to (28.7± 4.9), a 61.7% reduction after hydralazine injection, p=0.01. Future studies validating the technique in clinical settings for enhancing lesion-tissue contrast may allow physicians greater precision and accuracy in HCC surveillance for early detection of small tumors.

Hydralazine augmented ultrasound hyperthermia for the treatment of hepatocellular carcinoma.

This study investigates the use of hydralazine to enhance ultrasound hyperthermia for the treatment of hepatocellular carcinoma (HCC) by minimizing flow-mediated heat loss from the tumor. Murine HCC tumors were treated with a continuous mode ultrasound with or without an intravenous administration of hydralazine (5 mg/kg). Tumor blood flow and blood vessels were evaluated by contrast-enhanced ultrasound (CEUS) imaging and histology, respectively. Hydralazine markedly enhanced ultrasound hyperthermia through the disruption of tumor blood flow in HCC. Ultrasound treatment with hydralazine significantly reduced peak enhancement (PE), perfusion index (PI), and area under the curve (AUC) of the CEUS time-intensity curves by 91.9 ± 0.9%, 95.7 ± 0.7%, and 96.6 ± 0.5%, compared to 71.4 ± 1.9%, 84.7 ± 1.1%, and 85.6 ± 0.7% respectively without hydralazine. Tumor temperature measurements showed that the cumulative thermal dose delivered by ultrasound treatment with hydralazine (170.8 ± 11.8 min) was significantly higher than that without hydralazine (137.7 ± 10.7 min). Histological assessment of the ultrasound-treated tumors showed that hydralazine injection formed larger hemorrhagic pools and increased tumor vessel dilation consistent with CEUS observations illustrating the augmentation of hyperthermic effects by hydralazine. In conclusion, we demonstrated that ultrasound hyperthermia can be enhanced significantly by hydralazine in murine HCC tumors by modulating tumor blood flow. Future studies demonstrating the safety of the combined use of ultrasound and hydralazine would enable the clinical translation of the proposed technique.

Multivariable Dependence of Acoustic Contrast of Fluorocarbon and Xenon Microbubbles under Flow.

Microbubbles (MBs) are 1 to 10 µm gas particles stabilized by an amphiphilic shell capable of responding to biomedical ultrasound with strong acoustic signals, allowing them to be commonly used in ultrasound imaging and therapy. The composition of both the shell and the core determines their stability and acoustic properties. While there has been extensive characterization of the dissolution, oscillation, cavitation, collapse and therefore, ultrasound contrast of MBs under static conditions, few reports have examined such behavior under hydrodynamic flow. In this study, we evaluate the interplay of ultrasound parameters (five different mechanical indices [MIs]), MB shell parameter (shell stiffness), type of gas (perfluorocarbon for diagnostic imaging and xenon as a therapeutic gas), and a flow parameter (flow rate) on the ultrasound signal of phospholipid-stabilized MBs flowing through a latex tube embedded in a tissue-mimicking phantom. We find that the contrast gradient (CG), a metric of the rate of decay of contrast along the length of the tube, and the contrast peak (CP), the location where the maximum contrast is reached, depend on the conditions of flow, imaging, and MB material. For instance, while the contrast near the flow inlet of the field of view is highest for a softer shell (dipalmitoylphosphatidylcholine [DPPC], C16) than for stiffer shells (distearoylphosphatidylcholine [DSPC], C18, and dibehenoylphosphatidylcholine [DBPC], C22), the contrast decay is also faster; stiffer shells provide more resistance and hence lead to slower MB dissolution/destruction. At higher flow rates, the CG is low for a fixed length of time because each MB is exposed to ultrasound for a shorter period. The CG becomes high for low flow rates, especially at high incident pressures (high MI), causing more MB destruction closer to the inlet of the field of view. Also, the CP shifts toward the inlet at low flow rates, high MIs, and low shell stiffness. We also report the first demonstration of sustained ultrasound flow imaging of a water-soluble, therapeutic gas MB (xenon). We find that an increased MB concentration is necessary for obtaining the same signal magnitude for xenon MBs. In summary, this study builds a framework depicting how multiple variables simultaneously affect the evolution of MB ultrasound contrast under flow. Depending on the MB composition, imaging conditions, transducer positioning, and image processing, building on such a framework could potentially allow for extraction of additional diagnostic information than is commonly analyzed for physiological flow.

Quantitative colour Doppler and greyscale ultrasound for evaluating prostate cancer.

INTRODUCTION: Although transrectal ultrasound is routinely performed for imaging prostate lesions, colour Doppler imaging visualizing vascularity is not commonly used for diagnosis. The goal of this study was to measure vascular and echogenic differences between malignant and benign lesions of the prostate by quantitative colour Doppler and greyscale transrectal ultrasound. METHODS: Greyscale and colour Doppler ultrasound images of the prostate were acquired in 16 subjects with biopsy-proven malignant or benign lesions. Echogenicity and microvascular flow velocity of each lesion were measured by quantitative image analysis. Flow velocity was measured over several cardiac cycles and the velocity-time waveform was used to determine microvascular pulsatility index and microvascular resistivity index. The Wilcoxon rank sum test was used to compare the malignant and benign groups. RESULTS: Median microvascular flow velocity of the malignant lesions was 1.25 cm/s compared to 0.36 cm/s for the benign lesions. Median pulsatility and resistive indices of the malignant lesions were 1.55 and 0.68, respectively versus 6.38 and 1.0 for the benign lesions. Malignant lesions were more hypoechoic relative to the surrounding tissue, with median echogenicity of 0.24 compared to 0.76 for the benign lesions. The differences between the malignant and benign groups for each measurement were significant (p < 0.01). CONCLUSION: Marked differences were observed in flow velocity, microvascular pulsatility, microvascular resistance, and echogenicity of prostate cancer measured with quantitative colour Doppler and greyscale ultrasound imaging. Vascular differences measured together with echogenicity have the combined potential to characterize malignant and benign prostate lesions.

Quantitative pleural line characterization outperforms traditional lung texture ultrasound features in detection of COVID-19.

BACKGROUND AND OBJECTIVE: Lung ultrasound is an inherently user-dependent modality that could benefit from quantitative image analysis. In this pilot study we evaluate the use of computer-based pleural line (p-line) ultrasound features in comparison to traditional lung texture (TLT) features to test the hypothesis that p-line thickening and irregularity are highly suggestive of coronavirus disease 2019 (COVID-19) and can be used to improve the disease diagnosis on lung ultrasound. METHODS: Twenty lung ultrasound images, including normal and COVID-19 cases, were used for quantitative analysis. P-lines were detected by a semiautomated segmentation method. Seven quantitative features describing thickness, margin morphology, and echo intensity were extracted. TLT lines were outlined, and texture features based on run-length and gray-level co-occurrence matrix were extracted. The diagnostic performance of the 2 feature sets was measured and compared using receiver operating characteristics curve analysis. Observer agreements were evaluated by measuring interclass correlation coefficients (ICC) for each feature. RESULTS: Six of 7 p-line features showed a significant difference between normal and COVID-19 cases. Thickness of p-lines was larger in COVID-19 cases (6.27 ± 1.45 mm) compared to normal (1.00 ± 0.19 mm), P < 0.001. Among features describing p-line margin morphology, projected intensity deviation showed the largest difference between COVID-19 cases (4.08 ± 0.32) and normal (0.43 ± 0.06), P < 0.001. From the TLT line features, only 2 features, gray-level non-uniformity and run-length non-uniformity, showed a significant difference between normal cases (0.32 ± 0.06, 0.59 ± 0.06) and COVID-19 (0.22 ± 0.02, 0.39 ± 0.05), P = 0.04, respectively. All features together for p-line showed perfect sensitivity and specificity of 100; whereas, TLT features had a sensitivity of 90 and specificity of 70. Observer agreement for p-lines (ICC = 0.65-0.85) was higher than for TLT features (ICC = 0.42-0.72). CONCLUSION: P-line features characterize COVID-19 changes with high accuracy and outperform TLT features. Quantitative p-line features are promising diagnostic tools in the interpretation of lung ultrasound images in the context of COVID-19.

Photoacoustic monitoring of oxygenation changes induced by therapeutic ultrasound in murine hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly vascular solid tumor. We have previously shown that ultrasound (US) therapy significantly reduces tumor vascularity. This study monitors US-induced changes in tumor oxygenation on murine HCC by photoacoustic imaging (PAI). Oxygen saturation and total hemoglobin were assessed by PAI before and after US treatments performed at different intensities of continuous wave (CW) bursts and pulsed wave (PW) bursts US. PAI revealed significant reduction both in HCC oxygen saturation and in total hemoglobin, proportional to the US intensity. Both CW bursts US (1.6 W/cm2) and the PW bursts US (0.8 W/cm2) significantly reduced HCC oxygen saturation and total hemoglobin which continued to diminish with time following the US treatment. The effects of US therapy were confirmed by power Doppler and histological examination of the hemorrhage in tumors. By each measure, the changes observed in US-treated HCC were more prevalent than those in sham-treated tumors and were statistically significant. In conclusion, the results show that US is an effective vascular-targeting therapy for HCC. The changes in oxygenation induced by the US treatment can be noninvasively monitored longitudinally by PAI without the use of exogenous image-enhancing agents. The combined use of PAI and the therapeutic US has potential for image-guided vascular therapy for HCC.

Subsequent Ultrasound Vascular Targeting Therapy of Hepatocellular Carcinoma Improves the Treatment Efficacy.

The response of hepatocellular carcinoma (HCC) to anti-vascular ultrasound therapy (AVUS) can be affected by the inherent differences in tumor vascular structure, and the functionality of tumor vessels at the time of treatment. In this study, we evaluate the hypothesis that repeated subsequent AVUS therapies are a possible approach to overcome these factors and improve the therapeutic efficacy of AVUS. HCC was induced in 30 Wistar rats by oral ingestion of diethylnitrosamine (DEN) for 12 weeks. A total of 24 rats received treatment with low intensity, 2.8 MHz ultrasound with an intravenous injection of microbubbles. Treated rats were divided into three groups: single therapy group (ST), 2-days subsequent therapy group (2DST), and 7-days subsequent therapy group (7DST). A sham control group did not receive ultrasound therapy. Tumor perfusion was measured by quantitative contrast-enhanced ultrasound (CEUS) nonlinear and power-Doppler imaging. Tumors were harvested for histologic evaluation of ultrasound-induced vascular changes. ANOVA was used to compare the percent change of perfusion parameters between the four treatment arms. HCC tumors treated with 2DST showed the largest reduction in tumor perfusion, with 75.3% reduction on average for all perfusion parameters. The ST group showed an average decrease in perfusion of 54.3%. The difference between the two groups was significant p < 0.001. The 7DST group showed a reduction in tumor perfusion of 45.3%, which was significant compared to the 2DST group (p < 0.001) but not different from the ST group (p = 0.2). The use of subsequent targeted AVUS therapies applied shortly (two days) after the first treatment enhanced the anti-vascular effect of ultrasound. This gain, however, was lost for a longer interval (1 week) between the therapies, possibly due to tumor necrosis and loss of tumor viability. These findings suggest that complex interplay between neovascularization and tumor viability plays a critical role in treatment and, therefore, must be actively monitored following treatment by CEUS for optimizing sequential treatment.