Ultrasound-based Elasticity Imaging Research Articles

The impact of amplitude modulation frequency in harmonic motion imaging on inclusion characterization.

Ultrasound elasticity imaging techniques aim to provide a non-invasive characterization of tissue mechanical properties to detect pathological changes and monitor disease progression. Harmonic motion imaging (HMI) is an ultrasound-based elasticity imaging technique that utilizes an oscillatory acoustic radiation force to induce localized displacements and estimate relative tissue stiffness. Previous studies have applied a low amplitude modulation (AM) frequency of 25 or 50 Hz in HMI to assess the mechanical properties of different tissue types. In this study, we investigate the dependence of AM frequency in HMI and whether the frequency can be adjusted based on the size and mechanical properties of the underlying medium for enhanced image contrast and inclusion detection. A tissue-mimicking phantom with embedded inclusions at different sizes and stiffnesses was imaged within a range of AM frequencies from 25 to 250 Hz at 25-Hz step size. The AM frequency at which the maximum contrast and CNR are achieved depends on the size and stiffness of the inclusions. A general trend shows that contrast and CNR peak at higher frequencies for smaller inclusions. In addition, for some inclusions with the same size but different stiffnesses, the optimized AM frequency increases with the stiffness of the inclusion. Nevertheless, there is a shift between the frequencies at which the contrast peaks and those with maximum CNR. Finally, in agreement with the phantom findings, imaging an ex-vivo human specimen with a 2.7-cm breast tumor at a range of AM frequencies showed that the highest contrast and CNR are achieved at the AM frequency of 50 Hz. These findings indicate that the AM frequency can be optimized in different applications of HMI, especially in the clinic, for improved detection and characterization of tumors with different geometries and mechanical properties.

An Efficient and Multi-Focal Focused Ultrasound Technique for Harmonic Motion Imaging.

Harmonic motion imaging (HMI) is an ultrasound-based elasticity imaging technique that utilizes oscillatory acoustic radiation force to estimate the mechanical properties of tissues, as well as monitor high-intensity focused ultrasound (HIFU) treatment. Conventionally, in HMI, a focused ultrasound (FUS) transducer generates oscillatory tissue displacements, and an imaging transducer acquires channel data for displacement estimation, with each transducer being driven with a separate system. The fixed position of the FUS focal spot requires mechanical translation of the transducers, which can be a time-consuming and challenging procedure. In this study, we developed and characterized a new HMI system with a multi-element FUS transducer with the capability of electronic focal steering of ±5 mm and ±2 mm from the geometric focus in the axial and lateral directions, respectively. A pulse sequence was developed to drive both the FUS and imaging transducers using a single ultrasound data acquisition (DAQ) system. The setup was validated on a tissue-mimicking phantom with embedded inclusions. Integrating beam steering with the mechanical translation of the transducers resulted in a consistent high contrast-to-noise ratio (CNR) for the inclusions with Young's moduli of 22 and 44 kPa within a 5-kPa background while the data acquisition speed is increased by 4.5-5.2-fold compared to the case when only mechanical movements were applied. The feasibility of simultaneous generation of multiple foci and tracking the induced displacements is demonstrated in phantoms for applications where imaging or treatment of a larger region is needed. Moreover, preliminary feasibility is shown in a human subject with a breast tumor, where the mean HMI displacement within the tumor was about 4 times lower than that within perilesional tissues. The proposed HMI system facilitates data acquisition in terms of flexibility and speed and can be potentially used in the clinic for breast cancer imaging and treatment.

Fast lesion mapping during HIFU treatment using harmonic motion imaging guided focused ultrasound (HMIgFUS) in vitro and in vivo

The successful clinical application of high intensity focused ultrasound (HIFU) ablation depends on reliable monitoring of the lesion formation. Harmonic motion imaging guided focused ultrasound (HMIgFUS) is an ultrasound-based elasticity imaging technique, which monitors HIFU ablation based on the stiffness change of the tissue instead of the echo intensity change in conventional B-mode monitoring, rendering it potentially more sensitive to lesion development. Our group has shown that predicting the lesion location based on the radiation force-excited region is feasible during HMIgFUS. In this study, the feasibility of a fast lesion mapping method is explored to directly monitor the lesion map during HIFU. The harmonic motion imaging (HMI) lesion map was generated by subtracting the reference HMI image from the present HMI peak-to-peak displacement map, as streamed on the computer display. The dimensions of the HMIgFUS lesions were compared against gross pathology. Excellent agreement was found between the lesion depth (r2 = 0.81, slope = 0.90), width (r2 = 0.85, slope = 1.12) and area (r2 = 0.58, slope = 0.75). In vivo feasibility was assessed in a mouse with a pancreatic tumor. These findings demonstrate that HMIgFUS can successfully map thermal lesions and monitor lesion development in real time in vitro and in vivo. The HMIgFUS technique may therefore constitute a novel clinical tool for HIFU treatment monitoring.

Noninvasive In-Vivo Quantification of Mechanical Heterogeneity of Invasive Breast Carcinomas.

Heterogeneity is a hallmark of cancer whether one considers the genotype of cancerous cells, the composition of their microenvironment, the distribution of blood and lymphatic microvasculature, or the spatial distribution of the desmoplastic reaction. It is logical to expect that this heterogeneity in tumor microenvironment will lead to spatial heterogeneity in its mechanical properties. In this study we seek to quantify the mechanical heterogeneity within malignant and benign tumors using ultrasound based elasticity imaging. By creating in-vivo elastic modulus images for ten human subjects with breast tumors, we show that Young’s modulus distribution in cancerous breast tumors is more heterogeneous when compared with tumors that are not malignant, and that this signature may be used to distinguish malignant breast tumors. Our results complement the view of cancer as a heterogeneous disease on multiple length scales by demonstrating that mechanical properties within cancerous tumors are also spatially heterogeneous.

Quantifying mechanical heterogeneity of breast tumors using quantitative ultrasound elastography

Heterogeneity is a hallmark of cancer whether one considers the genotype of cancerous cells, the composition of their microenvironment, the distribution of blood and lymphatic microvasculature, or the spatial distribution of the desmoplastic reaction. It is logical to expect that this heterogeneity in tumor microenvironment will lead to spatial heterogeneity in its mechanical properties. In this study we seek to quantify the mechanical heterogeneity within malignant and benign tumors using ultrasound based elasticity imaging. By creating in-vivo elastic modulus images for ten human subjects with breast tumors, we show that Young’s modulus distribution in cancerous breast tumors is more heterogeneous when compared with tumors that are not malignant, and that this signature may be used to distinguish malignant breast tumors. Our results complement the view of cancer as a heterogeneous disease by demonstrating that mechanical properties within cancerous tumors are also spatially heterogeneous. [Work supported by NIH, NSF.]

Harmonic tracking of acoustic radiation force-induced displacements

Ultrasound-based elasticity imaging methods rely upon accurate estimates of tissue deformation to characterize the mechanical properties of soft tissues. These methods are corrupted by clutter, which can bias and/or increase variance in displacement estimates. Harmonic imaging methods are routinely used for clutter suppression and improved image quality in conventional B-mode ultrasound, but have not been utilized in ultrasound-based elasticity imaging methods. We introduce a novel, fully-sampled pulse-inversion harmonic method for tracking tissue displacements that corrects the loss in temporal sampling frequency associated with conventional pulse-inversion techniques. The method is implemented with acoustic radiation force impulse (ARFI) imaging to monitor the displacements induced by an impulsive acoustic radiation force excitation. Custom pulse sequences were implemented on a diagnostic ultrasound scanner to collect spatially-matched fundamental and harmonic information within a single acquisition. B-mode and ARFI images created from fundamental data collected at 4 MHz and 8 MHz are compared with 8-MHz harmonic images created using a band-pass filter approach and the fully sampled pulse-inversion method. In homogeneous, tissue-mimicking phantoms, where no visible clutter was observed, there was little difference in the axial displacements, estimated jitter, and normalized cross-correlation among the fundamental and harmonic tracking methods. The similarity of the lower- and higher-frequency methods suggests that any improvement resulting from the increased frequency of the harmonic components is negligible. The harmonic tracking methods demonstrated a marked improvement in B-mode and ARFI image quality of in vivo carotid arteries. Improved feature detection and decreased variance in estimated displacements were observed in the arterial walls of harmonic ARFI images, especially in the pulse-inversion harmonic ARFI images. Within the lumen, the harmonic tracking methods improved the discrimination of the blood–vessel interface, making it easier to visualize plaque boundaries. Improvements in harmonic ARFI images in vivo were consistent with suppressed clutter supported by improved contrast and contrast-to-noise ratio (CNR) in the matched harmonic B-mode images compared with the fundamental B-mode images. These results suggest that harmonic tracking methods can improve the clinical utility and diagnostic accuracy of ultrasound-based elasticity imaging methods.

Discrepancies in Reporting Tissue Material Properties

Discrepancies in Reporting Tissue Material Properties

Acoustic radiation force elasticity imaging in diagnostic ultrasound

The development of ultrasound-based elasticity imaging methods has been the focus of intense research activity since the mid-1990s. In characterizing the mechanical properties of soft tissues, these techniques image an entirely new subset of tissue properties that cannot be derived with conventional ultrasound techniques. Clinically, tissue elasticity is known to be associated with pathological condition and with the ability to image these features in vivo; elasticity imaging methods may prove to be invaluable tools for the diagnosis and/or monitoring of disease. This review focuses on ultrasound-based elasticity imaging methods that generate an acoustic radiation force to induce tissue displacements. These methods can be performed noninvasively during routine exams to provide either qualitative or quantitative metrics of tissue elasticity. A brief overview of soft tissue mechanics relevant to elasticity imaging is provided, including a derivation of acoustic radiation force, and an overview of the various acoustic radiation force elasticity imaging methods.

Acoustic radiation force impulse imaging of vulnerable plaques: a finite element method parametric analysis

Plaque rupture is the most common cause of complications such as stroke and coronary heart failure. Recent histopathological evidence suggests that several plaque features, including a large lipid core and a thin fibrous cap, are associated with plaques most at risk for rupture. Acoustic Radiation Force Impulse (ARFI) imaging, a recently developed ultrasound-based elasticity imaging technique, shows promise for imaging these features noninvasively. Clinically, this could be used to distinguish vulnerable plaques, for which surgical intervention may be required, from those less prone to rupture. In this study, a parametric analysis using Finite Element Method (FEM) models was performed to simulate ARFI imaging of five different carotid artery plaques across a wide range of material properties. It was demonstrated that ARFI imaging could resolve the softer lipid pool from the surrounding, stiffer media and fibrous cap and was most dependent upon the stiffness of the lipid pool component. Stress concentrations due to an ARFI excitation were located in the media and fibrous cap components. In all cases, the maximum Von Mises stress was<1.2kPa. In comparing these results with others investigating plaque rupture, it is concluded that while the mechanisms may be different, the Von Mises stresses imposed by ARFI imaging are orders of magnitude lower than the stresses associated with blood pressure.

OpenITGLinkMUSiiC: A Standard Communications Protocol for Advanced Ultrasound Research

Ultrasound imaging is the most popular and safe diagnostic medical imaging modality. Over the past years, a considerable number of studies have been conducted on new medical ultrasound imaging modalities such as ultrasound-based elasticity imaging, photoacoustic imaging, thermal imaging, etc. Moreover, results of such advanced ultrasound research are readily integrated with Image Guided Therapy (IGT) systems due to the advantages of ultrasound imaging such as mobility and real-time data acquisition. For integrating two systems, a communication method between systems has to be devised. OpenIGTLink is a standardized TCP/IP-based protocol for the integration of medical imaging and IGT systems. However, OpenIGTLink is not sufficient for communicating between IGT and advanced ultrasound research systems, because OpenIGTLink does not define any message type for general ultrasound data and some results of ultrasound researching. In this paper, we propose an extension to OpenIGTLink, called OpenIGTLinkMUSiiC, by adding new message types and new network classes. Our new message types are designed for containing raw ultrasound data, advanced ultrasound modalities, and text-based control parameters. The network classes of OpenIGTLinkMUSiiC improve upon the performance of existing network classes by implementing a multithread architecture. Finally, we present two ultrasound research applications using OpenIGTLink-MUSiiC.

Quantitative viscoelastic parameters measured by harmonic motion imaging

Quantifying the mechanical properties of soft tissues remains a challenging objective in the field of elasticity imaging. In this work, we propose an ultrasound-based method for quantitatively estimating viscoelastic properties, using the amplitude-modulated harmonic motion imaging (HMI) technique. In HMI, an oscillating acoustic radiation force is generated inside the medium by using focused ultrasound and the resulting displacements are measured using an imaging transducer. The proposed approach is a two-step method that uses both the properties of the propagating shear wave and the phase shift between the applied stress and the measured strain in order to infer to the shear storage (G′) and shear loss modulus (G″), which refer to the underlying tissue elasticity and viscosity, respectively. The proposed method was first evaluated on numerical phantoms generated by finite-element simulations, where a very good agreement was found between the input and the measured values of G′ and G″. Experiments were then performed on three soft tissue-mimicking gel phantoms. HMI measurements were compared to rotational rheometry (dynamic mechanical analysis), and very good agreement was found at the only overlapping frequency (10 Hz) in the estimate of the shear storage modulus G′ (14% relative error, averaged p-value of 0.34), whereas poorer agreement was found in G″ (55% relative error, averaged p-value of 0.0007), most likely due to the significantly lower values of G″ of the gel phantoms, posing thus a greater challenge in the sensitivity of the method. Nevertheless, this work proposes an original model-independent ultrasound-based elasticity imaging method that allows for direct, quantitative estimation of tissue viscoelastic properties, together with a validation against mechanical testing.

Real‐time sonoelastography of hepatic thermal lesions in a swine model

Sonoelastography has been developed as an ultrasound-based elasticity imaging technique. In this technique, external vibration is induced into the target tissue. In general, tissue stiffness is inversely proportional to the amplitude of tissue vibration. Imaging tissue vibration will provide the elasticity distribution in the target region. This study investigated the feasibility of using real-time sonoelastography to detect and estimate the volume of thermal lesions in porcine livers in vivo. A total of 32 thermal lesions with volumes ranging from 0.2 to 5.3 cm3 were created using radiofrequency ablation (RFA) or high-intensity focused ultrasound (HIFU) technique. Lesions were imaged using sonoelastography and coregistered B-mode ultrasound. Volumes were reconstructed from a sequence of two-dimensional scans. The comparison of sonoelastographic measurements and pathology findings showed good correlation with respect to the area of the lesions (r2 = 0.8823 for RFA lesions, r2 = 0.9543 for HIFU lesions). In addition, good correspondence was found between three-dimensional sonoelastography and gross pathology (3.6% underestimate), demonstrating the feasibility of sonoelastography for volume estimation of thermal lesions. These results support that sonoelastography outperforms conventional B-mode ultrasound and could potentially be used for assessment of thermal therapies.

Sonographic elasticity imaging of acute and chronic deep venous thrombosis in humans

Conclusion: Ultrasound-based elasticity imaging may help distinguish chronic from acute thrombosis and thus be useful in the clinical evaluation of patients with post-thrombotic syndrome. Summary: Distinguishing acute from chronic venous thrombosis is difficult with ultrasound B-mode imaging alone but may be important in a patient with a history of venous thrombosis and new symptoms in the leg. Under such circumstances, determining the age of the thrombus has significant clinical implications. One method of potentially aging venous thrombus is sonographic elasticity imaging. This technique allows direct assessment of tissue hardness. Because deep vein thrombi harden as they age, the technique may be possible to use in distinguishing acute from chronic venous thrombus. The authors of this study analyzed data in 46 patients: 23 had acute venous thrombi (mean age, 5.7 days) and 23 had chronic venous thrombi (>8 months). A 5-MHz linear array transducer was used to subject each thrombus to free-hand external deformation. Strains in the thrombi were normalized to average strain between the skin surface and the back wall of the vein. Thrombus echogenicity was measuring by comparing the adjacent arterial lumen with the echogenicity of the thrombus. The acute cases had a median normalized strain magnitude of 2.75 (interquartile range, 2.4 to 3.71). In chronic cases, the mean normalized strain magnitude was 0.94 (interquartile range, 0.48 1.36, P < 10−7). Echogenicity differences between the populations were also highly significant (P < 10−5). Comment: Reliably determining the age of a venous thrombus is one of the Holy Grails of noninvasive vascular testing. The population studied here, however, was somewhat artificial compared with the clinical situation. The current population consisted of patients with known acute vs known chronic thrombi. Sonographic elastic imaging needs to be evaluated in patients with a combination of acute and chronic venous thrombi to more mimic the clinical question of determining thrombus age in a patient with acute symptoms and known previous venous thrombosis.