Custom-made flow phantoms for quantitative ultrasound microvessel imaging.

Morphologically realistic flow phantoms are essential experimental tools for quantitative ultrasound-based microvessel imaging. As new quantitative flow imaging tools are developed, the need for more complex vessel-mimicking phantoms is indisputable. In this article, we propose a method for fabricating phantoms with sub-millimeter channels consisting of branches and curvatures in various shapes and sizes suitable for quantifying vessel morphological features. We used different tissue-mimicking materials (TMMs) compatible with ultrasound imaging as the base and metal wires of different diameters (0.15-1.25 mm) to create wall-less channels. The TMMs used are silicone rubber, plastisol, conventional gelatin, and medical gelatin. Mother channels in these phantoms were made in diameters of 1.25 mm or 0.3 mm and the daughter channels in diameters 0.3 mm or 0.15 mm. Bifurcations were created by soldering wires together at branch points. Quantitative parameters were assessed, and accuracy of measurements from the ground truth were determined. Channel diameters were seen to have increased (76-270%) compared to the initial state in the power Doppler images, partly due to blood mimicking fluid pressure. Amongst the microflow phantoms made from the different TMMs, the medical gelatin phantom was selected as the best option for microflow imaging, fulfilling the objective of being easy to fabricate with high transmittance while having a speed of sound and acoustic attenuation close to human tissue. A flow velocity of 0.85 ± 0.01 mm/s, comparable to physiological flow velocity was observed in the smallest diameter phantom (medical gelatin branch) presented here. We successfully constructed more complex geometries, including tortuous and multibranch channels using the medical gelatin as the TMM. We anticipate this will create new avenues for validating quantitative ultrasound microvessel imaging techniques.

Morphometric analysis of tumor microvessels for detection of hepatocellular carcinoma using contrast-free ultrasound imaging: A feasibility study.

Introduction: A contrast-free ultrasound microvasculature imaging technique was evaluated in this study to determine whether extracting morphological features of the vascular networks in hepatic lesions can be beneficial in differentiating benign and malignant tumors (hepatocellular carcinoma (HCC) in particular). Methods: A total of 29 lesions from 22 patients were included in this work. A post-processing algorithm consisting of clutter filtering, denoising, and vessel enhancement steps was implemented on ultrasound data to visualize microvessel structures. These structures were then further characterized and quantified through additional image processing. A total of nine morphological metrics were examined to compare different groups of lesions. A two-sided Wilcoxon rank sum test was used for statistical analysis. Results: In the malignant versus benign comparison, six of the metrics manifested statistical significance. Comparing only HCC cases with the benign, only three of the metrics were significantly different. No statistically significant distinction was observed between different malignancies (HCC versus cholangiocarcinoma and metastatic adenocarcinoma) for any of the metrics. Discussion: Obtained results suggest that designing predictive models based on such morphological characteristics on a larger sample size may prove helpful in differentiating benign from malignant liver masses.

Volumetric imaging and morphometric analysis of breast tumor angiogenesis using a new contrast-free ultrasound technique: a feasibility study.

BACKGROUND: There is a strong correlation between the morphological features of new tumor vessels and malignancy. However, angiogenic heterogeneity necessitates 3D microvascular data of tumor microvessels for more reliable quantification. To provide more accurate information regarding vessel morphological features and improve breast lesion characterization, we introduced a quantitative 3D high-definition microvasculature imaging (q3D-HDMI) as a new easily applicable and robust tool to morphologically characterize microvasculature networks in breast tumors using a contrast-free ultrasound-based imaging approach. METHODS: In this prospective study, from January 2020 through December 2021, a newly developed q3D-HDMI technique was evaluated on participants with ultrasound-identified suspicious breast lesions recommended for core needle biopsy. The morphological features of breast tumor microvessels were extracted from the q3D-HDMI. Leave-one-out cross-validation (LOOCV) was applied to test the combined diagnostic performance of multiple morphological parameters of breast tumor microvessels. Receiver operating characteristic (ROC) curves were used to evaluate the prediction performance of the generated pooled model. RESULTS: Ninety-three participants (mean age 52 ± 17 years, 91 women) with 93 breast lesions were studied. The area under the ROC curve (AUC) generated with q3D-HDMI was 95.8% (95% CI 0.901-1.000), yielding a sensitivity of 91.7% and a specificity of 98.2%, that was significantly higher than the AUC generated with the q2D-HDMI (p = 0.02). When compared to q2D-HDMI, the tumor microvessel morphological parameters obtained from q3D-HDMI provides distinctive information that increases accuracy in differentiating breast tumors. CONCLUSIONS: The proposed quantitative volumetric imaging technique augments conventional breast ultrasound evaluation by increasing specificity in differentiating malignant from benign breast masses.

Ultrasound high-definition microvasculature imaging with novel quantitative biomarkers improves breast cancer detection accuracy.

OBJECTIVES: To overcome the limitations of power Doppler in imaging angiogenesis, we sought to develop and investigate new quantitative biomarkers of a contrast-free ultrasound microvasculature imaging technique for differentiation of benign from malignant pathologies of breast lesion. METHODS: In this prospective study, a new high-definition microvasculature imaging (HDMI) was tested on 521 patients with 527 ultrasound-identified suspicious breast masses indicated for biopsy. Four new morphological features of tumor microvessels, microvessel fractal dimension (mvFD), Murray's deviation (MD), bifurcation angle (BA), and spatial vascularity pattern (SVP) as well as initial biomarkers were extracted and analyzed, and the results correlated with pathology. Multivariable logistic regression analysis was used to study the performance of different prediction models, initial biomarkers, new biomarkers, and combined new and initial biomarkers in differentiating benign from malignant lesions. RESULTS: The new HDMI biomarkers, mvFD, BA, MD, and SVP, were statistically significantly different in malignant and benign lesions, regardless of tumor size. Sensitivity and specificity of the new biomarkers in lesions > 20 mm were 95.6% and 100%, respectively. Combining the new and initial biomarkers together showed an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively, for all lesions regardless of mass size. The classification was further improved by adding the Breast Imaging Reporting and Data System (BI-RADS) score to the prediction model, showing an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively. CONCLUSION: The addition of new quantitative HDMI biomarkers significantly improved the accuracy in breast lesion characterization when used as a complementary imaging tool to the conventional ultrasound. KEY POINTS: • Novel quantitative biomarkers extracted from tumor microvessel images increase the sensitivity and specificity in discriminating malignant from benign breast masses. • New HDMI biomarkers Murray's deviation, bifurcation angles, microvessel fractal dimension, and spatial vascularity pattern outperformed the initial biomarkers. • The addition of BI-RADS scores based on US descriptors to the multivariable analysis using all biomarkers remarkably increased the sensitivity, specificity, and AUC in all size groups.

Hybrid high-definition microvessel imaging/shear wave elastography improves breast lesion characterization.

BACKGROUND: Low specificity in current breast imaging modalities leads to increased unnecessary follow-ups and biopsies. The purpose of this study is to evaluate the efficacy of combining the quantitative parameters of high-definition microvasculature imaging (HDMI) and 2D shear wave elastography (SWE) with clinical factors (lesion depth and age) for improving breast lesion differentiation. METHODS: In this prospective study, from June 2016 through April 2021, patients with breast lesions identified on diagnostic ultrasound and recommended for core needle biopsy were recruited. HDMI and SWE were conducted prior to biopsies. Two new HDMI parameters, Murray's deviation and bifurcation angle, and a new SWE parameter, mass characteristic frequency, were included for quantitative analysis. Lesion malignancy prediction models based on HDMI only, SWE only, the combination of HDMI and SWE, and the combination of HDMI, SWE and clinical factors were trained via elastic net logistic regression with 70% (360/514) randomly selected data and validated with the remaining 30% (154/514) data. Prediction performances in the validation test set were compared across models with respect to area under the ROC curve as well as sensitivity and specificity based on optimized threshold selection. RESULTS: A total of 508 participants (mean age, 54 years ± 15), including 507 female participants and 1 male participant, with 514 suspicious breast lesions (range, 4-72 mm, median size, 13 mm) were included. Of the lesions, 204 were malignant. The SWE-HDMI prediction model, combining quantitative parameters from SWE and HDMI, with AUC of 0.973 (95% CI 0.95-0.99), was significantly higher than the result predicted with the SWE model or HDMI model alone. With an optimal cutoff of 0.25 for the malignancy probability, the sensitivity and specificity were 95.5% and 89.7%, respectively. The specificity was further improved with the addition of clinical factors. The corresponding model defined as the SWE-HDMI-C prediction model had an AUC of 0.981 (95% CI 0.96-1.00). CONCLUSIONS: The SWE-HDMI-C detection model, a combination of SWE estimates, HDMI quantitative biomarkers and clinical factors, greatly improved the accuracy in breast lesion characterization.

Improved Ultrasound Attenuation Measurement Method for the Non-invasive Evaluation of Hepatic Steatosis Using FibroScan.

Controlled attenuation parameter (CAP) is a measurement of ultrasound attenuation used to assess liver steatosis non-invasively. However, the standard method has some limitations. This study assessed the performance of a new CAP method by ex vivo and in vivo assessments. The major difference with the new method is that it uses ultrasound data continuously acquired during the imaging phase of the FibroScan examination. Seven reference tissue-mimicking phantoms were used to test the performance. In vivo performance was assessed in two cohorts (in total 195 patients) of patients using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as a reference. The precision of CAP was improved by more than 50% on tissue-mimicking phantoms and 22%-41% in the in vivo cohort studies. The agreement between both methods was excellent, and the correlation between CAP and MRI-PDFF improved in both studies (0.71 to 0.74; 0.70 to 0.76). Using MRI-PDFF as a reference, the diagnostic performance of the new method was at least equal or superior (area under the receiver operating curve 0.889-0.900, 0.835-0.873). This study suggests that the new continuous CAP method can significantly improve the precision of CAP measurements ex vivo and in vivo.

Quantitative Biomarkers for Cancer Detection Using Contrast-Free Ultrasound High-Definition Microvessel Imaging: Fractal Dimension, Murray's Deviation, Bifurcation Angle & Spatial Vascularity Pattern.

A growing body of evidence indicates that there is a strong correlation between microvascular morphological features and malignant tumors. Therefore, quantification of these features might allow more accurate differentiation of benign and malignant tumors. The main objective of this research project is to improve the quantification of microvascular networks depicted in contrast-free ultrasound microvessel images. To achieve this goal, a new series of quantitative microvessel morphological parameters are introduced for differentiation of breast masses using contrast-free ultrasound-based high-definition microvessel imaging (HDMI). Using HDMI, we quantified and analyzed four new parameters: 1) microvessel fractal dimension (mvFD), a marker of tumor microvascular complexity; 2) Murray's deviation (MD), the diameter mismatch, defined as the deviation from Murray's law; 3) bifurcation angle (BA), abnormally decreased angle; and 4) spatial vascular pattern (SVP), indicating tumor vascular distribution pattern, either intratumoral or peritumoral. The new biomarkers have been tested on 60 patients with breast masses. Validation of the feature's extraction algorithm was performed using a synthetic data set. All the proposed parameters had the power to discriminate the breast lesion malignancy (p < 0.05), displaying BA as the most sensitive test, with a sensitivity of 90.6%, and mvFD as the most specific test, with a specificity of 92%. The results of all four new biomarkers showed an AUC = 0.889, sensitivity of 80% and specificity of 91.4% In conclusion, the added value of the proposed quantitative morphological parameters, as new biomarkers of angiogenesis within breast masses, paves the way for more accurate breast cancer detection with higher specificity.

Ultrasound image processing to estimate the structural and functional properties of mouse skeletal muscle.

Noninvasive imaging techniques are increasingly used for monitoring muscle behavior in mice. However, muscle is a complex tissue that exhibits different properties under passive and active conditions. In addition to structural properties, it is also important to analyze functional characteristics. At present, such information can be obtained with ultrasound elastography. However, this technique is poorly used for small rodent models (mice and gerbils). Thus, this study aims at establish referent hindlimb muscle data, and experimental guidelines, for wild-type (WT) control mice as well as the TIEG1 knockout (KO) mouse model that is known to exhibit skeletal muscle defects. Ultrasound was performed with the Aixplorer machine using a SLH 20-6 linear transducer probe (2.8 cm footprint). A region of interest (ROI) was placed around a superficial group of muscles. Subsequently, from the B-mode image, a classification of all the muscles and ultrasound biomarkers such as echo intensity and texture anisotropy have been determined. The influence of the gain setting (from 40% to 70%) was analyzed on these parameters. Moreover, the elasticity (E) was also measured within the ROI. This study provides a suitable methodology for collecting experimental data: 1) the correct range of gain (between 50% and 70%) to apply for the ultrasound measurement of muscle structure, 2) the structural and functional referent data for a group of healthy muscles, 3) the gray scale index, the texture anisotropy and the elasticity (ETIEG1 KO = 36.1 ± 10.3 kPa, EWT = 44.4 ± 13.4 kPa) parameters, which were obtained for a group of muscles as a function of genotype.

Individualized-thresholding Shear Wave Elastography combined with clinical factors improves specificity in discriminating breast masses.

PURPOSE: To investigate the diagnostic role of new metrics, defined as individualized-thresholding of Shear Wave Elastography (SWE) parameters, in association with clinical factors (such as age, mammographic density, lesion size and depth) and the BI-RADS features in differentiating benign from malignant breast lesions. METHODS: Of 644 consecutive patients (median age, 55 years), prospectively referred for evaluation, 659 ultrasound detected breast lesions underwent SWE measurements. Multivariable logistic regression analysis was used to estimate the probability of malignancy. The area under the curve (AUC), optimal cutoff value, and the corresponding sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were determined. RESULTS: 265 of 659 (40.2%) masses were malignant. Using two Emean cutoffs, 69.6 kPa for large superficial lesions (size >10 mm, depth ≤5 mm) and 39.2 kPa for the rest, the overall specificity, sensitivity, PPV and NPV were 92.6%, 86.8%, 88.8% and 91.3%, respectively. Combining multiple factors, including Emean with two cutoffs, age and BI-RADS, the new ROC curve based on the malignancy probability calculation showed the highest AUC (0.954, 95% CI: 0.938-0.969). Using the optimal probability threshold of 0.514, the corresponding specificity, sensitivity, PPV and NPV were 92.9%, 89.1%, 89.4% and 92.7%, respectively. CONCLUSIONS: The false-positive rate can be significantly reduced when applying two Emean cutoffs based on lesion size and depth. Moreover, the combination of age, Emean with two cutoffs and BI-RADS can further reduce the false negatives and false positives. Overall, this multifactorial analysis improves the specificity of ultrasound while maintaining a high sensitivity.

Development of a novel multiphysical approach for the characterization of mechanical properties of musculotendinous tissues.

At present, there is a lack of well-validated protocols that allow for the analysis of the mechanical properties of muscle and tendon tissues. Further, there are no reports regarding characterization of mouse skeletal muscle and tendon mechanical properties in vivo using elastography thereby limiting the ability to monitor changes in these tissues during disease progression or response to therapy. Therefore, we sought to develop novel protocols for the characterization of mechanical properties in musculotendinous tissues using atomic force microscopy (AFM) and ultrasound elastography. Given that TIEG1 knockout (KO) mice exhibit well characterized defects in the mechanical properties of skeletal muscle and tendon tissue, we have chosen to use this model system in the present study. Using TIEG1 knockout and wild-type mice, we have devised an AFM protocol that does not rely on the use of glue or chemical agents for muscle and tendon fiber immobilization during acquisition of transversal cartographies of elasticity and topography. Additionally, since AFM cannot be employed on live animals, we have also developed an ultrasound elastography protocol using a new linear transducer, SLH20-6 (resolution: 38 µm, footprint: 2.38 cm), to characterize the musculotendinous system in vivo. This protocol allows for the identification of changes in muscle and tendon elasticities. Such innovative technological approaches have no equivalent to date, promise to accelerate our understanding of musculotendinous mechanical properties and have numerous research and clinical applications.

Brain Tissue Pulsatility is Increased in Midlife Depression: a Comparative Study Using Ultrasound Tissue Pulsatility Imaging.

Cerebrovascular disease (CVD) is consistently associated with late-life depression but poorly documented in midlife depression. It can be hypothesized that the relatively low sensitivity of conventional neuroimaging techniques does not allow the detection of subtle CVD in midlife depression. We used tissue pulsatility imaging (TPI), a novel ultrasound (US) neuroimaging technique that has demonstrated good sensitivity to detect changes in the pulsatility of small brain volumes, to identify early and subtle changes in brain vascular function in midlife depression. We compared the maximum and mean brain tissue pulsatility (MaxBTP and MeanBTP), as identified by TPI, between three groups of middle-aged females matched for age: patients with depression (n=25), patients with remitted depression (n=24) and community controls (n=25). MRI arterial spin labeling, white matter hyperintensities (WMHs) and transcranial doppler (TCD) were used as control conventional markers for CVD. We found no difference in the MRI and TCD measures among the three groups. In contrast, depressive patients showed an increased BTP related to the mean global brain pulsatility (MeanBTP) and no change related to large vessels (MaxBTP) in comparison with the remitted and control groups. US neuroimaging is a highly accurate method to detect brain pulsatility changes related to cerebrovascular functioning, and TPI identified an increased BTP in midlife depressed patients, suggesting early and subtle vascular impairments in this population at risk for CVD such as stroke or WMHs. Because high pulsatility could represent prodromal cerebrovascular changes that damage the brain over time, this paper provides a potential target for blocking the progression of CVD.

Ultrasound Tissue Pulsatility Imaging Suggests Impairment in Global Brain Pulsatility and Small Vessels in Elderly Patients with Orthostatic Hypotension.

BACKGROUND: Orthostatic hypotension (OH) is highly prevalent in the elderly, and this population can be exposed to serious complications, including falls and cognitive disorders, as well as overall mortality. However, the pathophysiology of OH is still poorly understood, and innovative methods of cerebral blood flow (CBF) assessment have been required to accurately investigate cerebrovascular reactivity in OH. OBJECTIVES: We want to compare brain tissue pulsatility (BTP) changes during an orthostatic challenge in elderly patients over 80 with and without OH. MATERIALS AND METHODS: Forty-two subjects aged 80 and over were recruited from the geriatric unit of the Hospital of Tours, France, and were divided into two groups according to the result of an orthostatic challenge. The noninclusion criteria were any general unstable medical condition incompatible with orthostatic challenge, having no temporal acoustic window, severe cognitive impairment (Mini Mental Status Examination <15), history of stroke, and legal guardianship. We used the novel and highly sensitive ultrasound technique of tissue pulsatility imaging to measure BTP changes in elderly patients with (n = 22) and without OH (n = 17) during an orthostatic challenge. RESULTS: We found that the mean brain tissue pulsatility related to global intracranial pulsatility, but not maximum brain tissue pulsatility related to large arteries pulsatility, decreased significantly in OH patients, with a delay compared with the immediate drop in peripheral blood pressure. CONCLUSION: Global pulsatile CBF changes and small vessels pulsatility, rather than changes in only large arteries, may be key mechanisms in OH to account for the links between OH and cerebrovascular disorders.

Ultrasound measurements of brain tissue pulsatility correlate with the volume of MRI white-matter hyperintensity.

White-matter hyperintensity (WMH) is frequently seen in magnetic resonance imaging (MRI), but the complete physiopathology of WMH remains to be elucidated. In this study, we sought to determine whether there is an association between the maximum brain tissue displacement (maxBTD), as assessed by ultrasound, and the WMH, as observed by MRI. Nine healthy women aged 60 to 85 years underwent ultrasound and MRI assessments. We found a significant negative correlation between maxBTD and WMH (ρ=-0.86, P<0.001), suggesting a link between cerebral hypoperfusion and WMH.