Reliability and in vivo feasibility of the proposed PWI method were demonstrated in this study. Its simplicity of use and its capability of providing regional PWV render PWI a valuable tool for quantitative assessment of arterial stiffness. The utility of the method in a clinical setting has yet to be established and is part of an ongoing clinical study.

Arterial stiffness is well accepted as a reliable indicator of arterial disease. Increase in carotid arterial stiffness has been associated with carotid arterial disease, e.g., atherosclerotic plaque, thrombosis, stenosis, etc. Several methods for carotid arterial stiffness assessments have been proposed. In this study, in-vivo noninvasive assessment using applanation tonometry and an ultrasound-based motion estimation technique was applied in seven healthy volunteers (age 28 ± 3.6 years old) to determine pressure and wall displacement in the left common carotid artery (CCA), respectively. The carotid pressure was obtained using a calibration method by assuming that the mean and diastolic blood pressures remained constant throughout the arterial tree. The regional carotid arterial wall displacement was estimated using a 1D cross-correlation technique on the ultrasound radio frequency (RF) signals acquired at a frame rate of 505–1010 Hz. Young’s moduli were estimated under two different assumptions: (i) a linear elastic two-parallel spring model and (ii) a two-dimensional, nonlinear, hyperelastic model. The circumferential stress (σθ) and strain (εθ) relationship was then established in humans in vivo. A slope change in the circumferential stress-strain curve was observed and defined as a transition point. The Young’s moduli of the elastic lamellae (E1), elastin-collagen fibers (E2) and collagen fibers (E3) and the incremental Young’s moduli before (E0≤εθ<ε0T) and after the transition point (EεθT≤εθ) were determined from the first and second approach, respectively, to describe the contribution of the complex mechanical interaction of the different arterial wall constituents. The average E1, E2 and E3 from seven healthy volunteers were found to be equal to 0.15 ± 0.04, 0.89 ± 0.27 and 0.75 ± 0.29 MPa, respectively. The average E0≤εθ<εθTInt and EεθT≤εθInt of the intact wall (both the tunica adventitia and tunica media layers) were found to be equal to 0.16 ± 0.04 MPa and 0.90 ± 0.25 MPa, respectively. The average E0≤εθ<εθTAd and EεθT≤εθAd of the tunica adventitia were found to be equal to 0.18 ± 0.05 MPa and 0.84 ± 0.22 MPa, respectively. The average EεθT≤εθMe and EεθT≤εθMe of the tunica media were found to be equal to 0.19 ± 0.05 MPa and 0.90 ± 0.25 MPa, respectively. The stiffness of the carotid artery increased with strain during the systolic phase of cardiac cycle. In conclusion, the feasibility of measuring the regional stress-strain relationship and stiffness of the normal human carotid artery noninvasively was demonstrated in human in vivo.

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.

Magnetic resonance elastography (MRE) is an increasingly used method for non-invasive determination of tissue stiffness. MRE has shown its ability to measure in vivo elasticity or viscoelasticity depending on the chosen rheological model. However, few data exist on quantitative comparison of MRE with reference mechanical measurement techniques. MRE has only been validated on soft homogeneous gels under both Hookean elasticity and linear viscoelasticity assumptions, but comparison studies are lacking concerning viscoelastic properties of complex heterogeneous tissues. In this context, the present study aims at comparing an MRE-based method combined with a wave equation inversion algorithm to rotational rheometry. For this purpose, experiments are performed on in vitro porcine brain tissue. The dynamic behavior of shear storage (G') and loss (G ('')) moduli obtained by both rheometry and MRE at different frequency ranges is similar to that of linear viscoelastic properties of brain tissue found in other studies. This continuity between rheometry and MRE results consolidates the quantitative nature of values found by MRE in terms of viscoelastic parameters of soft heterogeneous tissues. Based on these results, the limits of MRE in terms of frequency range are also discussed.

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Arterial stiffness has been shown to be a good indicator of the arterial wall diseases. However, a single parameter is insufficient to describe the complex stress-strain relationship of a multi-component, non-linear tissue such as the aorta. We therefore propose a new approach to measure the stress-strain relationship locally in vivo and present a noninvasively, clinically relevant parameter describing the mechanical interaction between aortic wall constituents. The slope change of the circumferential stress-strain curve was hypothesized as a contribution of elastin and collagen, which was noninvasively defined in the term of strain using only radial aortic wall acceleration, i.e., transition strain false(εθTfalse). Two-spring parallel was employed as the phenomenological model and three Young's moduli were accordingly evaluated, i.e., corresponding to the: elastic lamellae (E1), elastin-collagen fibers (E2) and collagen fibers (E3). Our study performed on normal and Angiotensin II (AngII)-treated mouse abdominal aortas using aortic pressure from catheterization and local aortic wall diameters from a cross-correlation technique on the radio frequency (RF) ultrasound signal at 30 MHz and frame rate of 8 kHz. Using our technique, transition strain and three Young’s moduli in both normal and pathological aortas were mapped in 2D. In the results, the slope change of the circumferential stress-strain curve was first observed in vivo under physiologic conditions. The transition strain was identified at the lower strain level in the AngII-treated case, i.e., 0.029±0.006 of normal and 0.012±0.004 of AngII-treated aortas. E1, E2 and E3 were 69.7±18.6, 214.5±65.8 and 144.8±55.2 kPa for normal aortas, respectively, and 222.1±114.8, 775.0±586.4 and 552.9±519.1 kPa for AngII-treated aortas, respectively. This is because of the alteration of structures and content of the wall constituents, the degradation of elastic lamella and collagen formation due to AngII treatment. While such values illustrate the alteration of structure and content of the wall constituents related to AngII treatment, limitations regarding physical assumptions (isotropic linear elastic) should be kept in mind. The transition strain, however, was shown to be an aortic pressure waveform independent parameter that can be clinically relevant and noninvasively measured using ultrasound-based motion estimation techniques. In conclusion, our novel methodology can assess the stress-strain relationship of the aortic wall locally in vivo and quantify informative parameters which are related to vascular disease.

Palpation is an established screening procedure for the detection of several superficial cancers including breast, thyroid, prostate, and liver tumors through both self and clinical examinations. This is because solid masses typically have distinct stiffnesses compared to the surrounding normal tissue. In this paper, the application of Harmonic Motion Imaging (HMI) for tumor detection based on its stiffness as well as its relevance in thermal treatment is reviewed. HMI uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI studies have dealt with the measurement of the tissue dynamic motion in response to an oscillatory acoustic force at the same frequency, and have been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animals in vivo. Using an FUS beam, HMI can also be used in an ideal integration setting with thermal ablation using high-intensity focused ultrasound (HIFU), which also leads to an alteration in the tumor stiffness. In this paper, a short review of HMI is provided that encompasses the findings in all the aforementioned areas. The findings presented herein demonstrate that the HMI displacement can accurately depict the underlying tissue stiffness, and the HMI image of the relative stiffness could accurately detect and characterize the tumor or thermal lesion based on its distinct properties. HMI may thus constitute a non-ionizing, cost-efficient and reliable complementary method for noninvasive tumor detection, localization, diagnosis and treatment monitoring.