Effect of rt-PA on Shear Wave Mechanical Assessment and Quantitative Ultrasound Properties of Blood Clot Kinetics In Vitro.

OBJECTIVE: The consequences associated with blood clots are numerous and are responsible for many deaths worldwide. The assessment of treatment efficacy is necessary for patient follow-up and to detect treatment-resistant patients. The aim of this study was to characterize the effect of treatment on blood clots in vitro using quantitative ultrasound parameters. METHODS: Blood from 10 pigs was collected to form three clots per pig in gelatin phantoms. Clots were subjected to 1) no treatment, 2) rt-PA (recombinant tissue plasminogen activator) treatment after 20 minutes of clotting, and 3) rt-PA treatment after 60 minutes of clotting. Clots were weighted before and after the experiment to assess the treatment effect by the mass loss. The clot kinetics was studied over 100 minutes using elastography (Young's modulus, shear wave dispersion, and shear wave attenuation). Homodyne K-distribution (HKD) parameters derived from speckle statistics were also studied during clot formation and dissolving (diffuse-to-total signal power ratio and intensity parameters). RESULTS: Treated clots loosed significantly more mass than non-treated ones (P < .005). A significant increase in Young's modulus was observed over time (P < .001), and significant reductions were seen for treated clots at 20 or 60 minutes compared with untreated ones (P < .001). The shear wave dispersion differed for treated clots at 60 minutes versus no treatments (P < .001). The shear wave attenuation decreased over time (P < .001), and was different for clots treated at 20 minutes versus no treatments (P < .031). The HKD intensity parameter varied over time (P < .032), and was lower for clots treated at 20 and 60 minutes than those untreated (P < .001 and P < .02). CONCLUSION: The effect of rt-PA treatment could be confirmed by a decrease in Young's modulus and HKD intensity parameter. The shear wave dispersion and shear wave attenuation were sensitive to late and early treatments, respectively. The Young's modulus, shear wave attenuation, and HKD intensity parameter varied over time despite treatment.

Quantitative ultrasound, elastography, and machine learning for assessment of steatosis, inflammation, and fibrosis in chronic liver disease.

OBJECTIVE: To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. METHODS: This ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed. RESULTS: For classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model. CONCLUSION: Random forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.

Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions.

The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for classification of solid breast lesions at ultrasonography by means of random forests. One hundred and three women with 103 suspicious solid breast lesions (BI-RADS categories 4-5) were enrolled. Before biopsy, additional SWE images and a cine sequence of ultrasound images were obtained. The contours of lesions were delineated, and parametric maps of the homodyned-K distribution were computed on three regions: intra-tumoral, supra-tumoral and infra-tumoral zones. Maximum elasticity and total attenuation coefficient were also extracted. Random forests yielded receiver operating characteristic (ROC) curves for various combinations of features. Adding BI-RADS category improved the classification performance of other features. The best result was an area under the ROC curve of 0.97, with 75.9% specificity at 98% sensitivity.

Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms.

Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide complementary quantitative tissue information, characterization of carotid artery plaques may gain from their combination. Sixty-six patients with symptomatic ( n = 26 ) and asymptomatic ( n = 40 ) carotid atherosclerotic plaques were included in the study. Of these, 31 underwent magnetic resonance imaging (MRI) to characterize plaque vulnerability and quantify plaque components. US radio-frequency data sequence acquisitions were performed on all patients and were used to compute noninvasive vascular US elastography and other QUS features. Additional QUS features were computed from three types of images: homodyned-K (HK) parametric maps, Nakagami parametric maps, and log-compressed B-mode images. The following six classification tasks were performed: detection of 1) a small area of lipid; 2) a large area of lipid; 3) a large area of calcification; 4) the presence of a ruptured fibrous cap; 5) differentiation of MRI-based classification of nonvulnerable carotid plaques from neovascularized or vulnerable ones; and 6) confirmation of symptomatic versus asymptomatic patients. Feature selection was first applied to reduce the number of QUS parameters to a maximum of three per classification task. A random forest machine learning algorithm was then used to perform classifications. Areas under receiver-operating curves (AUCs) were computed with a bootstrap method. For all tasks, statistically significant higher AUCs were achieved with features based on elastography, HK parametric maps, and B-mode gray levels, when compared to elastography alone or other QUS alone ( ). For detection of a large area of lipid, the combination yielding the highest AUC (0.90, 95% CI 0.80-0.92, ) was based on elastography, HK, and B-mode gray-level features. To detect a large area of calcification, the highest AUC (0.95, 95% CI 0.94-0.96, ) was based on HK and B-mode gray level features. For other tasks, AUCs varied between 0.79 and 0.97. None of the best combinations contained Nakagami features. This study shows the added value of combining different features computed from a single US acquisition with machine learning to characterize carotid artery plaques.

Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model.

OBJECTIVES: To develop a machine learning model based on quantitative ultrasound (QUS) parameters to improve classification of steatohepatitis with shear wave elastography in rats by using histopathology scoring as the reference standard. METHODS: This study received approval from the institutional animal care committee. Sixty male Sprague-Dawley rats were either fed a standard chow or a methionine- and choline-deficient diet. Ultrasound-based radiofrequency images were recorded in vivo to generate QUS and elastography maps. Random forests classification models and a bootstrap method were used to identify the QUS parameters that improved the classification accuracy of elastography. Receiver-operating characteristic analyses were performed. RESULTS: For classification of not steatohepatitis vs borderline or steatohepatitis, the area under the receiver-operating characteristic curve (AUC) increased from 0.63 for elastography alone to 0.72 for a model that combined elastography and QUS techniques (p < 0.001). For detection of liver steatosis grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, ≤ 2 vs 3, respectively, the AUCs increased from 0.70, 0.65, and 0.69 to 0.78, 0.78, and 0.75 (p < 0.001). For detection of liver inflammation grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, ≤ 2 vs 3, respectively, the AUCs increased from 0.58, 0.77, and 0.78 to 0.66, 0.84, and 0.87 (p < 0.001). For staging of liver fibrosis grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, and ≤ 2 vs ≥ 3, respectively, the AUCs increased from 0.79, 0.92, and 0.91 to 0.85, 0.98, and 0.97 (p < 0.001). CONCLUSION: QUS parameters improved the classification accuracy of steatohepatitis, liver steatosis, inflammation, and fibrosis compared to shear wave elastography alone. KEY POINTS: • Quantitative ultrasound and shear wave elastography improved classification accuracy of liver steatohepatitis and its histological features (liver steatosis, inflammation, and fibrosis) compared to elastography alone. • A machine learning approach based on random forest models and incorporating local attenuation and homodyned-K tissue modeling shows promise for classification of nonalcoholic steatohepatitis. • Further research should be performed to demonstrate the applicability of this multi-parametric QUS approach in a human cohort and to validate the combinations of parameters providing the highest classification accuracy.

Carotid Plaque Vulnerability Assessment Using Ultrasound Elastography and Echogenicity Analysis.

OBJECTIVE: The purpose of this study was to evaluate ultrasound elastography and echogenicity analysis to discriminate between carotid plaques in patients with symptomatic internal carotid artery (ICA) stenosis versus patients with asymptomatic stenosis. SUBJECTS AND METHODS: Patients with symptomatic and asymptomatic ICA stenosis of more than 50% were recruited for the study. After both carotid arteries were scanned, plaque translation and elastography and echogenicity features were assessed. Parameters of index stenosis (i.e., symptomatic or more severe stenosis) were compared between populations. For further validation, parameters of index stenosis were also compared with those of the contralateral artery for segments with plaque. Segments without plaque on the index side were also evaluated between populations. ROC curve analyses were performed using a cross-validation method with bootstrapping to calculate sensitivity and specificity. RESULTS: Sixty-six patients with symptomatic (n = 26) or asymptomatic (n = 40) carotid stenoses were included. The maximum axial strain (p < 0.001), maximum axial shear strain magnitude (p = 0.03), and percentage of low-intensity of gray level (p = 0.01) of the index ICA were lower for patients with symptoms than for those without symptoms. In both groups, the contralateral ICA had translation and elastography and echogenicity parameters similar to those of the index ICA in patients with asymptomatic stenosis. The ROC curve for the detection of vulnerable plaques in patients with symptomatic stenosis was higher when ultrasound elastography and ultrasound echogenicity were used in combination than when each method was used alone (p < 0.001); a sensitivity of 71.6% and a specificity of 79.3% were obtained. CONCLUSION: This pilot study establishes the usefulness of combining elastography with echogenicity analysis to discriminate plaques in patients with symptomatic ICA stenosis versus asymptomatic stenosis.

Carotid Artery Plaque Vulnerability Assessment Using Noninvasive Ultrasound Elastography: Validation With MRI.

OBJECTIVE: Vulnerable and nonvulnerable carotid artery plaques have different tissue morphology and composition that may affect plaque biomechanics. The objective of this study is to evaluate plaque vulnerability with the use of ultrasound noninvasive vascular elastography (NIVE). MATERIALS AND METHODS: Thirty-one patients (mean [± SD] age, 69 ± 7 years) with stenosis of the internal carotid artery of 50% or greater were enrolled in this cross-sectional study. Elastography parameters quantifying axial strain, shear strain, and translation motion were used to characterize carotid artery plaques as nonvulnerable, neovascularized, and vulnerable. Maximum axial strain, cumulated axial strain, mean shear strain, cumulated shear strain, cumulated axial translation, and cumulated lateral translations were measured. Cumulated measurements were summed over a cardiac cycle. The ratio of cumulated axial strain to cumulated axial translation was also evaluated. The reference method used to characterize plaques was high-resolution MRI. RESULTS: According to MRI, seven plaques were vulnerable, 12 were nonvulnerable without neovascularity, and 12 were nonvulnerable with neovascularity (a precursor of vulnerability). The two parameters cumulated axial translation and the ratio of cumulated axial strain to cumulated axial translation could discriminate between nonvulnerable plaques and vulnerable plaques or determine the presence of neovascularity in nonvulnerable plaques (which was also possible with the mean shear strain parameter). All parameters differed between the non-vulnerable plaque group and the group that combined vulnerable plaques and plaques with neovascularity. The most discriminating parameter for the detection of vulnerable neovascularized plaques was the ratio of cumulated axial strain to cumulated axial translation (expressed as percentage per millimeter) (mean ratio, 39.30%/mm ± 12.80%/mm for nonvulnerable plaques without neovascularity vs 63.79%/mm ± 17.59%/mm for vulnerable plaques and nonvulnerable plaques with neovascularity, p = 0.002), giving an AUC value of 0.886. CONCLUSION: The imaging parameters cumulated axial translation and the ratio of cumulated axial strain to cumulated axial translation, as computed using NIVE, were able to discriminate vulnerable carotid artery plaques characterized by MRI from nonvulnerable carotid artery plaques. Consideration of neovascularized plaques improved the performance of NIVE. NIVE may be a valuable alternative to MRI for carotid artery plaque assessment.

Assessment of Inter-Expert Variability and of an Automated Segmentation Method of 40 and 60 MHz IVUS Images of Coronary Arteries.

The objectives were to compare the performance of a segmentation algorithm, based on the minimization of an uncertainty function, to delineate contours of external elastic membrane and lumen of human coronary arteries imaged with 40 and 60 MHz IVUS, and to use values of this function to delineate portions of contours with highest uncertainty. For 8 patients, 40 and 60 MHz IVUS coronary data acquired pre- and post-interventions were used, for a total of 68,516 images. Manual segmentations of contours (on 2312 images) performed by experts at three core laboratories were the gold-standards. Inter-expert variability was highest on contour points with largest values of the uncertainty function (p < 0.001). Inter-expert variability was lower at 60 than 40 MHz for external elastic membrane (p = 0.013) and lumen (p = 0.024). Average differences in plaque (and atheroma) burden between algorithmic contours and experts' contours were within inter-expert variability (p < 0.001).

Ultrasound viscoelasticity assessment using an adaptive torsional shear wave propagation method.

PURPOSE: Different approaches have been used in dynamic elastography to assess mechanical properties of biological tissues. Most techniques are based on a simple inversion based on the measurement of the shear wave speed to assess elasticity, whereas some recent strategies use more elaborated analytical or finite element method (FEM) models. In this study, a new method is proposed for the quantification of both shear storage and loss moduli of confined lesions, in the context of breast imaging, using adaptive torsional shear waves (ATSWs) generated remotely with radiation pressure. METHODS: A FEM model was developed to solve the inverse wave propagation problem and obtain viscoelastic properties of interrogated media. The inverse problem was formulated and solved in the frequency domain and its robustness to noise and geometric constraints was evaluated. The proposed model was validated in vitro with two independent rheology methods on several homogeneous and heterogeneous breast tissue-mimicking phantoms over a broad range of frequencies (up to 400 Hz). RESULTS: Viscoelastic properties matched benchmark rheology methods with discrepancies of 8%-38% for the shear modulus G' and 9%-67% for the loss modulus G″. The robustness study indicated good estimations of storage and loss moduli (maximum mean errors of 19% on G' and 32% on G″) for signal-to-noise ratios between 19.5 and 8.5 dB. Larger errors were noticed in the case of biases in lesion dimension and position. CONCLUSIONS: The ATSW method revealed that it is possible to estimate the viscoelasticity of biological tissues with torsional shear waves when small biases in lesion geometry exist.

Cost-utility analysis of nonalcoholic steatohepatitis screening.

OBJECTIVES: Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease in Western countries. No studies have examined the cost-effectiveness of screening its advanced form, nonalcoholic steatohepatitis (NASH). METHODS: We performed a cost-utility analysis of annual noninvasive screening strategies using third-party payer perspective in a general population in comparison to screening a high-risk obese or diabetic population. Screening algorithms involved well-studied techniques, including NAFLD fibrosis score, transient elastography (TE), and acoustic radiation force impulse (ARFI) imaging for detecting advanced fibrosis (≥ F3); and plasma cytokeratin (CK)-18 for NASH detection. Liver biopsy and magnetic resonance elastography (MRE) were compared as confirmation methods. Canadian dollar (CAD or C$) costs were adjusted for inflation and discounted at 5%. Incremental cost-effectiveness ratio (ICER) of ≤C$ 50,000 was considered cost-effective. RESULTS: Compared with no screening, screening with NAFLD fibrosis score/TE/CK-18 algorithm with MRE as confirmation for advanced fibrosis had an ICER of C$ 26,143 per quality-adjusted life year (QALY) gained. Screening in high-risk obese or diabetic populations was more cost-effective, with an ICER of C$ 9,051 and C$ 7,991 per quality-adjusted life-year (QALY) gained, respectively. Liver biopsy confirmation was not found to be cost-effective. CONCLUSIONS: Our model suggests that annual NASH screening in high-risk obese or diabetic populations can be cost-effective. KEY POINTS: • This cost-utility analysis suggests that screening for nonalcoholic steatohepatitis may be cost-effective. • In particular, screening of high-risk obese or diabetic populations is more cost-effective. • Magnetic resonance elastography was more cost-effective to confirm disease compared to biopsy. • More studies are needed to determine quality of life in nonalcoholic steatohepatitis. • More management strategies for nonalcoholic steatohepatitis are also needed.

In vivo venous assessment of red blood cell aggregate sizes in diabetic patients with a quantitative cellular ultrasound imaging method: proof of concept.

BACKGROUND: Diabetic patients present higher level of red blood cell (RBC) aggregation contributing to the development of vascular complications. While it has been suggested that this hematology/rheology parameter could bring additional prognostic information for the management of those patients, RBC aggregation screening is not included as a clinical practice. Most medical centers are not equipped to measure properly this parameter, although sedimentation tests can bring some indication. Here, we aimed at evaluating the feasibility of using ultrasound to assess in-vivo hyper-aggregation in type 2 diabetic patients. RESEARCH DESIGN AND METHODS: Seventeen diabetic patients and 15 control subjects underwent ultrasound measurements of RBC aggregation in both cephalic and great saphenous veins. Non-invasive in-vivo ultrasound measurements were performed using a newly developed cellular imaging technique, the structure factor size and attenuation estimator (SFSAE). Comparisons with an ex-vivo gold standard rheometry technique were done, along with measurements of pro-aggregating plasma molecule concentrations. RESULTS: In-vivo RBC aggregation was significantly higher in diabetic patients compared with controls for cephalic vein measurements, while a trend (p = 0.055) was noticed in the great saphenous vein. SFSAE measurements were correlated with gold standard in-vitro measures, fibrinogen and C-reactive protein plasma concentrations. CONCLUSION: RBC aggregation can be measured in-vivo in diabetic patients using ultrasound. Prospective studies are needed to determine whether the SFSAE method could help clinicians in the early management of vascular complications in this patient population.

Rheological assessment of a polymeric spherical structure using a three-dimensional shear wave scattering model in dynamic spectroscopy elastography.

With the purpose of assessing localized rheological behavior of pathological tissues using ultrasound dynamic elastography, an analytical shear wave scattering model was used in an inverse problem framework. The proposed method was adopted to estimate the complex shear modulus of viscoelastic spheres from 200 to 450 Hz. The inverse problem was formulated and solved in the frequency domain, allowing assessment of the complex viscoelastic shear modulus at discrete frequencies. A representative rheological model of the spherical obstacle was determined by comparing storage and loss modulus behaviors with Kelvin-Voigt, Maxwell, Zener, and Jeffrey models. The proposed inversion method was validated by using an external vibrating source and acoustic radiation force. The estimation of viscoelastic properties of three-dimensional spheres made softer or harder than surrounding tissues did not require a priori rheological assumptions. The proposed method is intended to be applied in the context of breast cancer imaging.

Assessment of accuracy of the structure-factor-size-estimator method in determining red blood cell aggregate size from ultrasound spectral backscatter coefficient.

A computer simulation study to produce ultrasonic backscatter coefficients (BSCs) from red blood cell (RBC) clusters is discussed. The simulation algorithm is suitable for generating non-overlapping, isotropic, and fairly identical RBC clusters. RBCs were stacked following the hexagonal close packing (HCP) structure to form a compact spherical aggregate. Such an aggregate was repeated and placed randomly under non-overlapping condition in the three-dimensional space to mimic an aggregated blood sample. BSCs were computed between 750 KHz and 200 MHz for samples of various cluster sizes at different hematocrits. Magnitudes of BSCs increased with mean aggregate sizes at low frequencies (<20 MHz). The accuracy of the structure-factor-size-estimator (SFSE) method in determining mean aggregate size and packing factor was also examined. A good correlation (R(2) ≥ 0.94) between the mean size of aggregates predicted by the SFSE and true size was found for each hematocrit. This study shows that for spherical aggregates there exists a region for each hematocrit where SFSE works most accurately. Typically, error of SFSE in estimating mean cluster size was <20% for dimensions between 14 and 17 µm at 40% hematocrit. This study suggests that the theoretical framework of SFSE is valid under the assumption of isotropic aggregates.

Monte Carlo study on ultrasound backscattering by three-dimensional distributions of red blood cells.

A Monte Carlo study on ultrasound backscattering by red blood cells (RBCs) is presented for three-dimensional (3D) distributions of particles. The cells were treated as classical spherical particles and accordingly, the Boltzmann distribution was considered to describe probability distribution of energy states of a system composed of such particles. The well-known Metropolis algorithm can generate configurations according to that probability distribution and therefore, was employed in this study to simulate some realizations of both nonaggregating and aggregating RBCs. The study of nonaggregating particles was motivated to compare simulations with existing experimental results and consequently, to validate the model. In the case of aggregating RBCs, the interaction potential between cells was modeled with the Morse potential and the frequency-dependent backscattering coefficient (BSC) was investigated at different hematocrits (H, particle volume fractions). The impact of aggregation potential on the spectral slope (SS) was also evaluated. It is shown that BSC increased as the magnitude of aggregating potential was raised and the effect was more pronounced at higher hematocrits. Moreover, spectral slopes at nonaggregating and low aggregating conditions were found to be around 4, which is consistent with the Rayleigh scattering theory. However, it had diminished significantly, particularly at higher hematocrits as the magnitude of the attractive potential energy was raised. For instance, at H=40% SS dropped from 4.04 for nonaggregating particles to 3.62 at the highest aggregating potential considered in this study. Our results suggest that this 3D model is capable of reflecting the effects of RBC aggregation on BSC and SS.

Assessment by transient elastography of the viscoelastic properties of blood during clotting.

Blood clotting is a natural process that can be both beneficial and life-threatening for the human body. It allows the maintenance of hemostasis after vascular injury, but it can also cause deep vein thrombosis and heart stroke. This study aimed better to understand the clotting process from a biomechanical point of view by using an acoustic method. The long-term objective is the staging of the age of clots in deep veins for therapy planning. The transient elastography method using a shear elasticity probe served to evaluate the shear wave velocity (V(S)) and shear wave attenuation (alpha(S)) of porcine whole blood during in vitro clot formation. By solving an inverse problem, it was then possible to provide images of the elasticity (mu(B)) and of the viscosity (eta(B)) from clotting blood. The time-varying elasticity and viscosity were very similar to what has been observed for the sol-gel transition of polymers. The mechanical properties of blood clot, which were modified by varying the hematocrit and by adding heparin or fibrinogen, were clearly assessed by the transient elastography technique. It is concluded that the shear elasticity probe is an appropriate tool to quantify and follow the sol-gel transition of blood during clotting.

Effect of red cell clustering and anisotropy on ultrasound blood backscatter: a Monte Carlo study.

When flowing at a low shear rate, blood appears hyperechogenic on ultrasound B-scans. The formation of red blood cell (RBC) aggregates that also alters blood viscosity is the microscopic mechanism explaining this acoustical phenomenon. In this study, Monte Carlo simulations were performed to predict how RBC clustering increases ultrasound scattering by blood. A bidimensional Gibbs-Markov random point process parameterized by the adhesion energy epsilon and an anisotropy index nu was used to describe RBC positions for a hematocrit H = 40%. The frequency dependence of the backscattering coefficient chi(f) was computed using Born approximation. The backscattering coefficient chi0 at 5 MHz and the spectral slopes n(x) and n(y) (chi alpha f(nx) or f(ny)) measured, respectively, when the insonification is parallel and perpendicular with the RBC cluster axis were then extracted. Under isotropic conditions, chi0 increased up to 7 dB with epsilon and n(x) = n(y) decreased from 4.2 to 3.4. Under anisotropic conditions, the backscattering was stronger perpendicularly to aggregate axis, resulting in n(x) < n(y). The anisotropy in scattering appeared more pronounced when epsilon or nu increased. These two dimensional results generally predict that low-frequency blood backscatter is related to cluster dimension, and higher-frequency properties are affected by finer morphological features as anisotropy. This numerically establishes that ultrasound backscatter spectroscopy on a large frequency range is pertinent to characterize in situ hemorheology.