Ming Qian

Surface Roughness Detection of Arteries via Texture Analysis of Ultrasound Images for Early Diagnosis of Atherosclerosis

There is a strong research interest in identifying the surface roughness of the carotid arterial inner wall via texture analysis for early diagnosis of atherosclerosis. The purpose of this study is to assess the efficacy of texture analysis methods for identifying arterial roughness in the early stage of atherosclerosis. Ultrasound images of common carotid arteries of 15 normal mice fed a normal diet and 28 apoE−/− mice fed a high-fat diet were recorded by a high-frequency ultrasound system (Vevo 2100, frequency: 40 MHz). Six different texture feature sets were extracted based on the following methods: first-order statistics, fractal dimension texture analysis, spatial gray level dependence matrix, gray level difference statistics, the neighborhood gray tone difference matrix, and the statistical feature matrix. Statistical analysis indicates that 11 of 19 texture features can be used to distinguish between normal and abnormal groups (p<0.05). When the 11 optimal features were used as inputs to a support vector machine classifier, we achieved over 89% accuracy, 87% sensitivity and 93% specificity. The accuracy, sensitivity and specificity for the k-nearest neighbor classifier were 73%, 75% and 70%, respectively. The results show that it is feasible to identify arterial surface roughness based on texture features extracted from ultrasound images of the carotid arterial wall. This method is shown to be useful for early detection and diagnosis of atherosclerosis.

Measurement of flow velocity fields in small vessel-mimic phantoms and vessels of small animals using micro ultrasonic particle image velocimetry (micro-EPIV).

Determining a multidimensional velocity field within microscale opaque fluid flows is needed in areas such as microfluidic devices, biofluid mechanics and hemodynamics research in animal studies. The ultrasonic particle image velocimetry (EchoPIV) technique is appropriate for measuring opaque flows by taking advantage of PIV and B-mode ultrasound contrast imaging. However, the use of clinical ultrasound systems for imaging flows in small structures or animals has limitations associated with spatial resolution. This paper reports on the development of a high-resolution EchoPIV technique (termed as micro-EPIV) and its application in measuring flows in small vessel-mimic phantoms and vessels of small animals. Phantom experiments demonstrate the validity of the technique, providing velocity estimates within 4.1% of the analytically derived values with regard to the flows in a small straight vessel-mimic phantom, and velocity estimates within 5.9% of the computationally simulated values with regard to the flows in a small stenotic vessel-mimic phantom. Animal studies concerning arterial and venous flows of living rats and rabbits show that the micro-EPIV-measured peak velocities within several cardiac cycles are about 25% below the values measured by the ultrasonic spectral Doppler technique. The micro-EPIV technique is able to effectively measure the flow fields within microscale opaque fluid flows.

REAL-TIME TEXTURE ANALYSIS FOR IDENTIFYING OPTIMUM MICROBUBBLE CONCENTRATION IN 2-D ULTRASONIC PARTICLE IMAGE VELOCIMETRY

Many recent studies on ultrasonic particle image velocimetry (Echo PIV) showed that the accuracy of two-dimensional (2-D) flow velocity measured depends largely on the concentration of ultrasound contrast agents (UCAs) during imaging. This article presents a texture-based method for identifying the optimum microbubble concentration for Echo PIV measurements in real-time. The texture features, standard deviation of gray level, and contrast, energy and homogeneity of gray level co-occurrence matrix were extracted from ultrasound contrast images of rotational and pulsatile flow (10 MHz) in vitro and in vivo mouse common carotid arterial flow (40 MHz) with UCAs at various concentrations. The results showed that, at concentration of 0.8∼2 × 10³ bubbles/mL in vitro and 1∼5 × 10⁵ bubbles/mL in vivo, image texture features had a peak value or trough value, and velocity vectors with high accuracy can be obtained. Otherwise, poor quality velocity vectors were obtained. When the texture features were used as a feature set, the accuracy of K-nearest neighbor classifier can reach 86.4% in vitro and 87.5% in vivo, respectively. The texture-based method is shown to be able to quickly identify the optimum microbubble concentration and improve the accuracy for Echo PIV imaging.

Computer-assisted assessment of ultrasound real-time elastography: Initial experience in 145 breast lesions

PURPOSE To develop and evaluate a computer-assisted method of quantifying five-point elasticity scoring system based on ultrasound real-time elastography (RTE), for classifying benign and malignant breast lesions, with pathologic results as the reference standard. MATERIALS AND METHODS Conventional ultrasonography (US) and RTE images of 145 breast lesions (67 malignant, 78 benign) were performed in this study. Each lesion was automatically contoured on the B-mode image by the level set method and mapped on the RTE image. The relative elasticity value of each pixel was reconstructed and classified into hard or soft by the fuzzy c-means clustering method. According to the hardness degree inside lesion and its surrounding tissue, the elasticity score of the RTE image was computed in an automatic way. Visual assessments of the radiologists were used for comparing the diagnostic performance. Histopathologic examination was used as the reference standard. The Students t test and receiver operating characteristic (ROC) curve analysis were performed for statistical analysis. RESULTS Considering score 4 or higher as test positive for malignancy, the diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 93.8% (136/145), 92.5% (62/67), 94.9% (74/78), 93.9% (62/66), and 93.7% (74/79) for the computer-assisted scheme, and 89.7% (130/145), 85.1% (57/67), 93.6% (73/78), 92.0% (57/62), and 88.0% (73/83) for manual assessment. Area under ROC curve (Az value) for the proposed method was higher than the Az value for visual assessment (0.96 vs. 0.93). CONCLUSION Computer-assisted quantification of classical five-point scoring system can significantly eliminate the interobserver variability and thereby improve the diagnostic confidence of classifying the breast lesions to avoid unnecessary biopsy.

A 2D non-invasive ultrasonic method for simultaneous measurement of arterial strain and flow pattern

Many cardiovascular diseases are closely associated with the mechanical properties of arterial wall and hemodynamic parameters. Simultaneous measurements of the arterial strain and flow pattern may aid diagnosis of cardiovascular diseases and may be useful to study fluid‐structure interaction between blood and vessel. This paper proposes a 2D non‐invasive ultrasonic method to simultaneously measure arterial strain and flow pattern with sub‐pixel accuracy.

Investigation on utilizing laser speckle velocimetry to measure the velocities of nanoparticles in nanofluids.

Laser speckle velocimetry (LSV) is presented to measure the velocities of nanoparticles in nanofluids and its feasibility is verified in this paper. An optical scattering model of a single nanoparticle is developed and numerical computations are done to simulate the formation of the speckles by the addition of the complex amplitudes of the scattering lights from multiple nanoparticles. Then relative experiments are done to form speckles when nanofluids are illuminated by a laser beam. The results of the experiments are in agreement with the numerical results, which verify the feasibility of utilizing LSV to measure the velocities of nanoparticles in nanofluids.

A Novel Modulated Excitation Imaging System for Microultrasound

Microultrasound (micro-US), also known as ultrasound biomicroscope, is able to delineate small structures with fine spatial resolution. However, micro-US suffers limited depth of penetration due to significantly large attenuation at high frequencies. Modulated excitation imaging has displayed the capability to improve the penetration depth, while maintaining the spatial resolution. But the effectiveness of this technique in micro-US has not been fully demonstrated. In addition, the current modulated excitation imaging systems for micro-US are designed for specific excitation method, therefore, lack of flexibility, and are typically bulky and expensive. This paper presents the development of a novel system to achieve modulated excitation imaging with high programmability and flexibility to satisfy various micro-US studies. It incorporates a high-voltage arbitrary waveform generator for producing desired excitation waveform, and a programmable imaging receiver implemented by the state-of-the-art electronics and field-programmable gate array. Test results show that the proposed modulated excitation imaging system can acquire up to 20 dB signal-to-noise ratio improvement and 83% increase of penetration depth in contrast to traditional short-pulse imaging method. In vivo experiment on the dorsal skin of a human hand demonstrates good performance of the programmable modulated excitation imaging system.

Quantitative analysis of peri-tumor tissue elasticity based on shear-wave elastography for breast tumor classification

For shear-wave elastography (SWE) images, the most common site of tumor-associated stiffness is generally in the surrounding stroma rather than the tumor itself. The aim of this study is to assess the value of the peri-tumor tissue elasticity in the classification of breast tumors. SWE images of 106 breast tumors (65 benign, 41 malignant) were collected from 82 consecutive patients. By applying the image processing method, 5 elastographic features of the peri-tumor area (elasticity modulus mean, maximum, standard deviation, hardness degree and elasticity ratio) were computed to represent peri-tumor tissue elasticity. B-mode Breast Imaging Reporting and Data System (BI-RADS) were used for comparing the diagnostic performances between the grayscale US and color SWE images. Histopathologic results were used as the reference standard. The t-test, point biserial correlation coefficient and receiver operating characteristic (ROC) curve analysis were performed for statistical analysis. As a result, the Az values (area under ROC curve) were 0.92, 0.95, 0.94, 0.91, and 0.98 for the classifiers using the five elastographic features respectively, and 0.91 for BI-RADS assessment. The results showed that the peri-tumor tissue elasticity could provide valuable information for breast tumor classification.

Impact of Multiple Cardiovascular Risk Factors on Carotid Intima-Media Thickness and Elasticity

Background Carotid intima-media thickness (IMT) and elasticity have been shown to be independent predictors of cardiovascular disease (CVD). Cardiovascular risk factors (CVRFs) includes hypertension, dyslipidemia, diabetes, overweight and smoking. The objective was to investigate whether the clustering of three or more components of CVRFs has a greater impact on carotid IMT and elasticity than individual components of CVRFs. Methods One hundred and seventy-three participants without clinical CVD were classified as the multiple CVRFs patients with three or more CVRFs (n  = 55) and control group with two or less CVRFs (n  = 118). Carotid IMT and elastic modulus were measured by B-mode ultrasound and vessel texture matching method (VTMM), respectively. Results The multiple CVRFs conferred a disproportionate increase in carotid IMT (43%, p<0.0001) and elastic modulus (60%, p<0.0001), compared with control group. Multiple regression models, which included age, gender, as well as each individual component of CVRFs as continuous variables, showed that multiple CVRFs was an independent determinant of both IMT (p  = 0.042) and elasticity (p  = 0.008). In the analysis of variance adjusted with age, subjects with single, double, and multiple CVRFs, increased by 8.1%, 42.2%, and 66% for IMT, 54.6%, 94.3%, and 125.2% for elastic modulus, respectively, compared to subjects without CVRFs. Conclusions The clustering of multiple CVRFs has a greater impact on carotid IMT and elasticity than individual components of CVRFs. This suggests that the components of CVRFs interact to synergistically impact carotid IMT and elasticity.

A Texture Matching Method Considering Geometric Transformations in Noninvasive Ultrasonic Measurement of Arterial Elasticity

Measurement of arterial elasticity can provide an important reference for understanding arterial wall changes that may occur in the early stages of atherosclerosis. Conventional correlation-based methods for evaluating arterial wall movements consider only the translation, ignoring the rotation and deformation, which limits the accuracy of measurement of arterial displacement and its biomechanical properties. This article proposes a novel texture matching method based on ultrasonic B-mode image considering geometric transformations to accurately measure arterial displacement and acquire arterial elasticity noninvasively. The method was validated by simulated images with rotation and deformation and further by measurements in vitro arterial phantom and in vivo common carotid arteries of 20 healthy volunteers. Simulation results demonstrate that the method can improve the accuracy of measurement of arterial displacement. Experimental results show that the elastic modulus of the arterial phantom agrees well with the results obtained from mechanical tests, deviating only 4.1%. The mean elastic modulus of the common carotid arteries is 361.7 ± 93.5 kPa. The texture matching method was shown to be able to measure the displacement and elasticity of the arterial wall with complex geometric transformations and may be clinically useful for early detecting and monitoring atherosclerosis.