Novel Uses of Ultrasound to Assess Kidney Mechanical Properties : Kidney360

Journal Logo

Review Articles

Novel Uses of Ultrasound to Assess Kidney Mechanical Properties

Urban, Matthew W.1; Rule, Andrew D.2; Atwell, Thomas D.1; Chen, Shigao1

Author Information
Kidney360 2(9):p 1531-1539, September 2021. | DOI: 10.34067/KID.0002942021
  • Open



Palpation has been an essential tool in medical practice for centuries because of its utility in detecting abnormalities within an organ using the sense of touch. However, not all organs are superficial, nor is the sense of touch sensitive enough to detect subtle changes in the mechanical properties of the tissue under investigation. The native kidney and, in some patients, the transplanted kidney, are not easy to evaluate with palpation due to their depth from the skin surface.

Different imaging modalities, such as x-ray computed tomography, magnetic resonance imaging, and ultrasound, can provide information about the morphology and vasculature of the kidney (1–3). Ultrasound, due to its low cost and widespread availability, is commonly used for imaging of the kidney (1). Laboratory-based renal function tests can provide a glimpse into kidney health (4,5). However, microscopic changes in the kidney due to processes such as inflammation and fibrosis can cause loss of nephron function and thereby decrease the overall GFR (6–9). The remaining nephrons can compensate through hyperfiltration, but as disease progresses, the availability of healthy nephrons may be insufficient to compensate, and hyperfiltration can also lead to further nephron loss and eventual kidney failure (10).

These same morphologic changes can cause an alteration in the proportion of tissue constituents, such as the increased presence of inflammatory cells and edema in the interstitium, or replacement of parenchyma with increased collagen content from global glomerulosclerosis and interstitial fibrosis with tubular atrophy. Further, nephrons can hypertrophy with both glomerulomegaly and tubular hypertrophy. With new proportions of tissue constituents and changes in the tissue organization and structure, the mechanical properties at the microscopic and macroscopic scale levels will change.

In addition to changes in tissue composition, the structure may be altered. The measurement of mechanical properties of the kidney may benefit from distinguishing nephrons with glomeruli in the superficial cortex from those in the deep cortex that extend their loop of Henle into the medulla. Indeed, the structural pathology with different processes may vary by kidney tissue depth (e.g., glomerulosclerosis of aging occurs primarily in the superficial cortex) (9). Although current imaging techniques can distinguish cortex from medulla, they are insufficient to resolve the components (glomeruli and tubular segments) of individual nephrons. Additionally, the macroscopic structure of the kidney, that is, the nephrons and vessels, are organized in a radial fashion. As a result, we can consider the anisotropic mechanical properties when evaluating nephrons because the directionality will be important in interpreting the result.

Another important factor to consider is the perfusion of the kidney. The kidney receives 20–25% of the cardiac output (11), and the pressure in the kidney can affect the mechanical properties measured in the renal parenchyma. As a result, the pathology of the parenchyma and the perfusion conditions will both contribute to the mechanical stiffness of the kidney, and results must be interpreted with this mind. With some pathologic processes, this may make interpretation of stiffness difficult. For example, arteriosclerosis may decrease kidney stiffness from decreased perfusion, whereas the associated glomerulosclerosis, tubular atrophy, and interstitial fibrosis with arteriosclerosis may increase kidney stiffness.

Overview of Ultrasound-based Elastography Methods

As previously mentioned, different imaging modalities can provide morphologic and functional (e.g., perfusion) information, but they do not provide quantitative information about the mechanical properties of soft tissues. Over the last two decades, multiple elastography approaches for measuring the mechanical properties of different organs have been developed and subsequently commercialized for use in clinical practice (12–14).

There are two commonalities among these different elastography approaches, which include applying stress to the tissue and measuring the response to that stress (15). The applied stress can be external mechanical actuation, external compression, an internally applied acoustic radiation force (ARF), or endogenous motion, such as motion due to the cardiac pressure pulse. In this paper, we will focus primarily on the excitation (applying stress) using a focused ultrasound beam to generate an ARF in the renal tissue (16). The motion from that applied stress can be measured using sensitive high frame-rate ultrasound measurements, which can detect micron-level displacements, and the mechanical properties can be assessed.

Ultrasound array transducers can focus the ultrasound “push” beam to specific locations within the imaging field of view (17,18). To generate a force that will perturb the tissue to the level that the motion can be measured, long tonebursts are used, in the order of 100–1000 μs, resulting in hundreds to thousands of ultrasound cycles (16). As a comparison point, pulses used for B-mode imaging or Doppler measurements may be in the order of 1–10 cycles, or bursts of only a few microseconds.

The push is applied and the transfer of momentum of the ultrasound waves to the absorbing tissue causes the tissue to be pushed in the direction of the ultrasound propagation (17,19). When the pushing toneburst ceases, the tissue may still undergo motion in the direction of the ultrasound, but will eventually start to return to its equilibrium position. The motion within the push beam region of excitation (ROE) can be analyzed to evaluate the tissue, including the level of peak displacement and other features of the time-dependent behavior of the response (17). Multiple ARF pushes can be used in time to interrogate the response, such as in one method called viscoelastic response (VisR) imaging (20,21). These motion features are determined by the elastic or viscoelastic properties of the tissue. Figure 1 shows the intensity produced by a curvilinear transducer and measurements of motion inside and outside the ROE.

Figure 1.:
Uses of acoustic radiation force (ARF) to displace tissue and measurement in the region-of-excitation (ROE) with one acoustic radiation force impulse (ARFI) excitation or two ARF excitations for viscoelastic response (VisR). ARF excitations are shown by the orange rectangles. Shear waves are measured outside of the ROE at numerous locations starting at x = 1.5 mm and each curve is extracted in 2.0 mm steps. All data are from simulations described by methods in Palmeri et al (28). SW, shear waves.

An elastic material will deform immediately due to an applied force. After the force ceases, the material will return to its original position. In a viscoelastic material, the material’s response to a force will have some delay or time dependence (22). Additionally, when the force is taken away, the material will take some time to relax back to its original position. An everyday example is the behavior of a spring mattress and a memory foam mattress. A spring mattress will respond quickly to a depressing force and return to its original position almost immediately when the force is removed, whereas the memory foam mattress will take some time to deform and return to its original shape.

In many works related to characterizing the viscoelastic mechanical properties of soft tissues, various rheological models have been used and are modeled as different configurations of springs (elastic component) and dashpots (viscous component) (23). In the example above, a spring mattress may be modeled using only spring components, and the memory foam may be modeled using springs and dashpots arranged in series or in parallel. These different rheological models allow for simplified explanations of mechanical behavior of tissues. Common models include the Kelvin–Voigt, Maxwell, and Generalized Maxwell models (20,24–31). The most appropriate model may vary among tissues and the time scale used for fitting the measured behavior.

By virtue of the tissue being a mechanical continuum, when the tissue deforms and returns to its original position, it causes motion outside of the ROE and generates shear, or transverse, waves (18,19). In this case, the particle displacement is parallel to the ultrasound propagation direction (z-direction, Figure 1), but the wave propagates perpendicular to the direction of the ultrasound propagation. The shear wave velocity (SWV) of the propagating wave is related to the elastic and viscoelastic properties of the tissue, by using specific equations, the shear or Young’s modulus can be estimated. Measurement of the SWV is encompassed by the general term of shear wave elastography (SWE). It should be noted that in the clinical implementations of SWE that the following relationships are used:(1)E=3μ=c2where E is the Young’s modulus, μ is the shear modulus, ρ is the mass density assumed to be 1000 kg/m3, and c is the SWV. For this equation, the tissue is assumed to be linear, elastic, isotropic, homogeneous, and nearly incompressible (Poisson’s ratio, v=0.5). To interpret between studies, Equation 1 can be used to convert the measurements to consistent units (32–35). It should be noted that this conversion can be performed on individual data values, but for cutoff thresholds derived from receiver operating characteristic curve analysis, all values may need to be converted and the analysis performed again to obtain the proper threshold due to the nonlinear relationship in Equation 1.

Seminal Studies in Renal Elastography

ARF-based methods have been used in many studies in the kidney to evaluate physiologic and pathologic states. We highlight a few early seminal studies in the kidney. Gennisson et al. performed a fundamental study in a porcine model exploring the anisotropy of the in vivo kidney and the effects of renal artery flow, venous outflow, and urinary blockage on the mechanical properties (36). Shear wave measurements were made where the waves were propagating transverse to the renal structures in the middle of a longitudinal plane and parallel to the renal structures in one of the poles of the kidney as conceptualized in Figure 2. The transverse, μ, and parallel, μǁ, shear modulus changes and the anisotropic ratio, AR = μǁ, are listed in Table 1 for cases of the normal kidney, and when the renal vein or artery was occluded. The venous occlusion leads to a 4–5-fold increase in the modulus, whereas occlusion of the renal artery decreases the modulus. The anisotropic effects change markedly in the outer cortex and medulla with these variations in perfusion of the kidney.

Figure 2.:
Direction of shear wave propagation with ARF applied in different locations demonstrated on porcine kidney cross-section. The shear waves propagate transverse to the tubules/vessels in the middle (yellow) of the longitudinal section. The shear waves propagate parallel to the tubules/vessels in the pole (white) of the longitudinal section.
Table 1. - Shear modulus measurements in pigs under different physiologic conditions (36)
Measurement Transverse (μ), kPa Parallel (μǁ), kPa Anisotropy Ratio (μǁ)
 Outer cortex 6.9±1.4 7.7±2.3 1.12
 Inner cortex 8.1±1.9 8.7±2.5 1.07
 Medulla 6.6±2.3 7.7±2.3 1.17
Vein occlusion
 Outer cortex 32.6±10.7 33.7±20.6 1.03
 Inner cortex 43.5±15.1 43.2±16.8 0.99
 Medulla 36.6±12.5 47.9±14.4 1.30
Artery occlusion
 Outer cortex 3.4±0.8 4.6±2.1 1.35
 Inner cortex 4.6±1.2 5.1±2.4 1.10
 Medulla 4.8±1.2 5.6±2.9 1.17

Amador et al. reported measurements in ex vivo porcine kidneys to evaluate the role of anisotropy and other factors on the viscoelastic properties of the cortical tissue (37). The viscoelasticity was characterized using analysis of the shear wave motion in the frequency domain. The wave velocity at each frequency, phase velocity, is evaluated and the variation of the phase velocity, or dispersion, is fit to a parametric model involving springs and dashpots, which characterize the elastic and viscous components of the tissue, respectively. Using a Kelvin–Voigt rheological model, the mean shear elasticity (spring), μ1, and shear viscosity (dashpot), μ2, was 1.89 kPa and 1.61 Pa⋅s, averaged across four kidneys. It was found that the viscoelastic parameters were larger when the shear wave propagated parallel with the nephron structures compared with transversely (Figure 2).

Amador et al. explored an acute renal artery stenosis (RAS) model and evaluated the viscoelastic properties of the kidney as renal blood flow was reduced. As renal blood flow decreased, the shear elasticity and viscosity immediately decreased (100% to 75% flow), then decreased slightly (μ1) or held constant (μ2) (38). Warner et al. investigated porcine models of acute and chronic RAS with magnetic resonance elastography (39). In patients with acute RAS, the modulus of the affected kidney decreased, whereas the contralateral kidney exhibited a higher modulus, and the mean arterial pressure and renal blood flow to the contralateral kidney increased in pigs. In the chronic RAS study, the stenotic kidney had similar stiffness compared with control, but was lower than the contralateral kidney. Fibrosis was substantial in the stenotic kidney, but the authors concluded that renal fibrosis may have been masked by the reduced perfusion of the stenotic kidney. Additional ex vivo and in vivo studies have addressed the aspects of increased and decreased renal internal pressure (40–42).

Clinical Studies with Renal Elastography

ARF impulse imaging and VisR imaging utilize motion that is captured in the ROE for analysis. The ARF impulse method typically measures the peak displacement with an underlying assumption that stiffer tissue will deform less than softer tissue (17). The VisR method uses two ARF pushes applied in a precisely timed fashion at the same location to examine the time-dependent recovery of the tissue to evaluate viscoelastic properties of the tissue, such as the time constant (τ = μ21) relative elasticity and viscosity (20,21). The parameters were mapped in renal transplants and a region of interest analysis was performed (43). The τ ratios calculated from different regions of interest could differentiate transplants with vascular disease, tubular/interstitial scarring, chronic allograft nephropathy, and glomerulonephritis from control allografts.

Ultrasound SWE has been utilized in many different studies to evaluate different regions of the kidney for different diseases that affect the kidney. These evaluations are typically paired with measurements of kidney morphology (length, cortical thickness) from B-mode, Doppler measurements to determine resistive index. An example in a kidney allograft is shown in Figure 3. We summarize some findings in native and transplant kidneys, although more thorough overviews may be found in the other review articles (44–49).

Figure 3.:
Examples of B-mode, Doppler, and shear wave elastography (SWE) images in a transplanted kidney in a 52-year-old male patient 5 years post-transplant with a General Electric Logiq E9 scanner (General Electric Healthcare, Wauwatosa, WI). The SWE images shows the color-coded overlay for shear wave velocity. Data were acquired under a protocol approved by the Mayo Clinic Institutional Board with written informed consent.

Native kidneys have been assessed in patients with CKD and diabetic kidney disease. In many of these studies, patients have been categorized using eGFR measurements. There are conflicting findings with respect to mechanical properties and eGFR values. In some papers, the mechanical properties increased with progressive disease stages or decreased eGFR (i.e., negative correlation with eGFR) (50–56). However, other studies showed no correlation (57,58) or a positive correlation with eGFR (59,60). The prevailing conclusion related to the negative correlation between mechanical properties and eGFR could be explained that more advanced CKD is associated with fibrosis, which can increase the stiffness of the parenchymal tissue. The role of perfusion may also be a factor because the perfusion could be reduced with mild levels of fibrosis.

Asano et al. studied patients with glomerulonephritis (n=129), diabetic nephropathy (n=107), and nephrosclerosis (n=83) (61). They found positive correlations between SWV and eGFR in each of the cohorts, although the correlation coefficients ranged between r=0.216 and r=0.320 (P<0.01). In the report by Leong et al. 106 patients with CKD were studied and compared with 203 control subjects (52). In this study, it was found that Young’s modulus increased in patients with CKD compared with controls, having a moderate correlation coefficient of r=−0.576 (P<0.0001).

More work has been reported in renal transplants and measurements are compared with Banff biopsy scores and renal function outcomes. Two early, small studies compared SWV and Banff biopsy scores for measurements made in transplanted kidneys (62,63). The study by Syversveen et al. examined 30 patients and did not find a significant correlation of SWV with fibrosis (62). Stock et al. studied 18 patients and found positive correlations between SWV and level of fibrosis (Spearman correlation coefficient = 0.47, P=0.026) (63). He et al. reported higher values of SWV in dysfunctional allografts and a negative correlation between SWV and eGFR (64).

These various studies measuring elastic mechanical properties, either SWV or Young’s modulus, unfortunately demonstrate some inconsistencies and raise questions about how renal mechanical properties relate to renal structure and function in a comprehensive manner. Different studies found positive (63–69) and no (62,70,71) correlation with interstitial fibrosis. Several studies noted a negative correlation of SWV with eGFR (64,68,72,73). The dual roles of fibrosis and perfusion need to be studied in more detail to elucidate their contributions to the renal mechanical properties, for example, studying kidneys with moderate or severe fibrosis compared with mild fibrosis.

Another aspect of using SWE in renal allografts is that applied transducer force can alter the SWV measurements because the allograft is placed at a shallow depth (74). In normal scanning, applying significant pressure by the transducer should be avoided (45), but if used intentionally, it could yield information about the nonlinear mechanical properties of the renal tissue (75).

Current Challenges for Ultrasound Elastography Measurements

Although ultrasound-based methods have been used in transplant and native kidneys, ARF-based methods are limited to depths from the skin surface to about 7 cm. At increasing depth, ultrasound waves will attenuate and the ARF will be weak. Second, the ultrasound motion detection becomes more difficult due to a lower signal-to-noise ratio and poorer spatial resolution. The ultrasound amplitude used for the push pulse is limited due to regulatory limits, such as those mandated for diagnostic ultrasound by the US Food and Drug Administration (76). These limits are meant to prevent tissue damage due to the thermal and mechanical bioeffects of ultrasound. Efforts are being directed toward examining the safety under conditions related to using ultrasound with higher values of acoustic output (77–80).

Another challenge is the effects of anisotropy on measurements of renal mechanical properties. The shape of the push beam and the direction of the propagating shear waves with respect to the directionality of the nephrons and vessels can affect the consistency of the measurements. The measured responses with ARF beams of different shapes can help to discern the anisotropy of the tissue (81). For SWE measurements, the effects of anisotropy can be accounted for by making measurements in a consistent location such as in the middle of the cortex (away from the poles) in a longitudinal plane.

Another limitation of renal elastography research studies is that, typically, the mechanical properties are the primary focus, but the individual contributions to these properties from nephron size, nephron number, interstitial inflammation and edema, fibrosis, and blood flow characteristics are not provided. Methods that can achieve higher spatial resolution and extract more details about the macroscopic and microscopic features will be important to understand the state of the kidney. For example, in recent years, ultrasound methods have progressed to the point that microvessels can be observed without any contrast agents (Figure 4) and super-resolution imaging of microvessels on the scale of tens to hundreds of microns is possible with the use of ultrasound microbubble contrast agents (82–87). The efficacy of identifying specific diseases and CKD severity may depend on more holistic characterization of the kidney.

Figure 4.:
Examples of B-mode image and microvasculature imaging in a native kidney in a healthy 31-year-old male subject with a Verasonics Vantage research ultrasound scanner (Verasonics, Inc., Kirkland, WA). Vessels can be differentiated much better than those in the Doppler image in Figure 3. Data were acquired under a protocol approved by the Mayo Clinic Institutional Board with written informed consent.

Future Opportunities for Renal Elastography Investigation

Considering the current renal elastography literature, there is no complete consensus on mechanical property trends with different conditions. Consistency among different studies still need to be established, such that these elastographic tools could be used and trusted more widely by nephrologists. Validation of mechanical properties against specific microstructural findings on histology and prognostic utility beyond common clinical tests (eGFR and proteinuria) are also necessary steps for establishing clinical utility. Reconciling the results from ultrasound-based methods implemented by different vendors is an important step as is exploring the role of evaluating the viscoelastic properties of the renal tissue (88).

Although renal elastography has been explored in porcine and rabbit models (36,38,39,42), it may be useful in other preclinical models involving rats and mice. Research ultrasound devices such as those produced by Verasonics Inc. and Sonovol Inc. may make this possible. Integration of renal elastography ROE or shear wave measurements could provide more information on disease progression and the effects on the mechanical properties. Figure 5 shows results from a SonoVol Vega system for measuring SWV in a mouse using a high frequency ultrasound transducer. Measurements that integrate morphology, blood flow, and mechanical properties could be quite revelatory to understanding pathophysiology.

Figure 5.:
Long-axis view of kidney in a mouse using B-mode with overlaid shear wave velocity (SWV). B-Mode of a female C57BK6j mouse (5 mo) kidney is shown. The B-mode was acquired at 24 MHz and shear wave velocity overlay acquired with 17 MHz excitation and tracking pulses. Images acquired with the Vega robotic ultrasound system (SonoVol, Inc., Durham, NC, USA). Images courtesy of Dr. Michael F. Romero (Mayo Clinic) and Dr. Christopher Moore (SonoVol, Inc.). Data were acquired under a protocol approved by the Mayo Clinic Institutional Animal Care and Use Committee. SWEI, shear wave elasticity imaging.

As with many diseases, it is imperative but challenging to understand how changes of the tissue composition and structure alter the properties observed at the macroscopic scale. This can be done both with improved abilities to conduct preclinical and human studies and model wave propagation in complex tissues from the microscopic scale to observe the effects at the macroscopic scale. Advances in blood flow imaging may also provide information to interpret how perfusion of the kidney affects mechanical property measurements.

Current Outlook

Ultrasound-based elastography techniques have allowed clinicians and scientists to obtain new insight into pathophysiology of multiple organs. Renal elastography has similar potential, but the kidney presents unique challenges that require special care to interpret measurements in light of the multiple factors that affect the measured mechanical properties within the kidney.


The Mayo Clinic and two of the authors (M.W. Urban and S. Chen) have a potential financial interest related to the technology referenced in this paper. M.W. Urban reports having consultancy agreements with Michigan State University; reports receiving research funding from Computerized Imaging Reference Systems, Inc. (CIRS, Inc.), Incorporated and the National Institutes of Health (R01 DK092255 and R01 HL145268); and reports patents and inventions with General Electric Healthcare. S. Chen reports having patents and inventions with Alpinion, General Electric Healthcare, Samsung, Sonoscape. All remaining authors have nothing to disclose.


This work was supported in part by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) award R01 DK092255.


The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIDDK or the National Institutes of Health.

Author Contributions

M.W. Urban conceptualized the study, was responsible for funding acquisition, and wrote the original draft; and all authors reviewed and edited the manuscript.


1. Grenier N, Merville P, Combe C: Radiologic imaging of the renal parenchyma structure and function. Nat Rev Nephrol 12: 348–359, 2016
2. Thölking G, Schuette-Nuetgen K, Kentrup D, Pawelski H, Reuter S: Imaging-based diagnosis of acute renal allograft rejection. World J Transplant 6: 174–182, 2016
3. Caroli A, Remuzzi A, Lerman LO: Basic principles and new advances in kidney imaging [published online ahead of print, May 11, 2021]. Kidney Int 2021
4. Bagshaw SM, Gibney RTN: Conventional markers of kidney function. Crit Care Med 36[Suppl]: S152–S158, 2008
5. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration): A new equation to estimate glomerular filtration rate. Ann Intern Med 150: 604–612, 2009
6. Sis B, Mengel M, Haas M, Colvin RB, Halloran PF, Racusen LC, Solez K, Baldwin WM 3rd, Bracamonte ER, Broecker V, Cosio F, Demetris AJ, Drachenberg C, Einecke G, Gloor J, Glotz D, Kraus E, Legendre C, Liapis H, Mannon RB, Nankivell BJ, Nickeleit V, Papadimitriou JC, Randhawa P, Regele H, Renaudin K, Rodriguez ER, Seron D, Seshan S, Suthanthiran M, Wasowska BA, Zachary A, Zeevi A: Banff ’09 meeting report: Antibody mediated graft deterioration and implementation of Banff working groups. Am J Transplant 10: 464–471, 2010
7. Haas M, Loupy A, Lefaucheur C, Roufosse C, Glotz D, Seron D, Nankivell BJ, Halloran PF, Colvin RB, Akalin E, Alachkar N, Bagnasco S, Bouatou Y, Becker JU, Cornell LD, Duong van Huyen JP, Gibson IW, Kraus ES, Mannon RB, Naesens M, Nickeleit V, Nickerson P, Segev DL, Singh HK, Stegall M, Randhawa P, Racusen L, Solez K, Mengel M: The Banff 2017 Kidney Meeting Report: Revised diagnostic criteria for chronic active T cell-mediated rejection, antibody-mediated rejection, and prospects for integrative endpoints for next-generation clinical trials. Am J Transplant 18: 293–307, 2018
8. Denic A, Glassock RJ, Rule AD: Structural and functional changes with the aging kidney. Adv Chronic Kidney Dis 23: 19–28, 2016
9. Denic A, Ricaurte L, Lopez CL, Narasimhan R, Lerman LO, Lieske JC, Thompson RH, Kremers WK, Rule AD: Glomerular volume and glomerulosclerosis at different depths within the human kidney. J Am Soc Nephrol 30: 1471–1480, 2019
10. Chagnac A, Zingerman B, Rozen-Zvi B, Herman-Edelstein M: Consequences of glomerular hyperfiltration: The role of physical forces in the pathogenesis of chronic kidney disease in diabetes and obesity. Nephron 143: 38–42, 2019
11. Guyton AC, Hall JE: Textbook of Medical Physiology, 3rd Ed., Philadelphia, PA, W. B. Saunders Company, 2000
12. Sarvazyan A, Hall TJ, Urban MW, Fatemi M, Aglyamov SR, Garra B: An overview of elastography: An emerging branch of medical imaging. Curr Med Imaging Rev 7: 255–282, 2011
13. Nenadic IZ, Urban MW, Greenleaf JF, Bernal M, Gennisson JL, Tanter M, Ultrasound Elastography for Biomedical Applications and Medicine, Elsevier and Wiley Publishing, Hoboken, NJ, 2016
14. Urban MW: Production of acoustic radiation force using ultrasound: Methods and applications. Expert Rev Med Devices 15: 819–834, 2018
15. Li G-Y, Cao Y: Mechanics of ultrasound elastography. Proc Math Phys Eng Sci 473: 20160841, 2017
16. Doherty JR, Trahey GE, Nightingale KR, Palmeri ML: Acoustic radiation force elasticity imaging in diagnostic ultrasound. IEEE Trans Ultrason Ferroelectr Freq Control 60: 685–701, 2013
17. Nightingale KR, Palmeri ML, Nightingale RW, Trahey GE: On the feasibility of remote palpation using acoustic radiation force. J Acoust Soc Am 110: 625–634, 2001
18. Nightingale K, McAleavey S, Trahey G: Shear-wave generation using acoustic radiation force: in vivo and ex vivo results. Ultrasound Med Biol 29: 1715–1723, 2003
19. Sarvazyan AP, Rudenko OV, Swanson SD, Fowlkes JB, Emelianov SY: Shear wave elasticity imaging: A new ultrasonic technology of medical diagnostics. Ultrasound Med Biol 24: 1419–1435, 1998
20. Selzo MR, Gallippi CM: Viscoelastic response (VisR) imaging for assessment of viscoelasticity in Voigt materials. IEEE Trans Ultrason Ferroelectr Freq Control 60: 2488–2500, 2013
21. Selzo MR, Moore CJ, Hossain MM, Palmeri ML, Gallippi CM: On the quantitative potential of viscoelastic response (VisR) ultrasound using the one-dimensional mass-spring-damper model. IEEE Trans Ultrason Ferroelectr Freq Control 63: 1276–1287, 2016
22. Fung YC: Biomechanics: Mechanical Properties of Living Tissues, 2nd Ed., New York, NY, Springer-Verlag, 1993
23. Loret B, Simoes FMF: Biomechanical Aspects of Soft Tissues, Boca Raton, FL, CRC Press, 2017
24. Chen S, Urban MW, Pislaru C, Kinnick R, Zheng Y, Yao A, Greenleaf JF: Shearwave dispersion ultrasound vibrometry (SDUV) for measuring tissue elasticity and viscosity. IEEE Trans Ultrason Ferroelectr Freq Control 56: 55–62, 2009
25. Urban MW, Chen S, Fatemi M: A review of shearwave dispersion ultrasound vibrometry (SDUV) and its applications. Curr Med Imaging Rev 8: 27–36, 2012
26. Catheline S, Gennisson JL, Delon G, Fink M, Sinkus R, Abouelkaram S, Culioli J: Measuring of viscoelastic properties of homogeneous soft solid using transient elastography: An inverse problem approach. J Acoust Soc Am 116: 3734–3741, 2004
27. Nightingale KR, Rouze NC, Rosenzweig SJ, Wang MH, Abdelmalek MF, Guy CD, Palmeri ML: Derivation and analysis of viscoelastic properties in human liver: Impact of frequency on fibrosis and steatosis staging. IEEE Trans Ultrason Ferroelectr Freq Control 62: 165–175, 2015
28. Palmeri ML, Qiang B, Chen S, Urban MW: Guidelines for finite-element modeling of acoustic radiation force-induced shear wave propagation in tissue-mimicking media. IEEE Trans Ultrason Ferroelectr Freq Control 64: 78–92, 2017
29. Chen S, Sanchez W, Callstrom MR, Gorman B, Lewis JT, Sanderson SO, Greenleaf JF, Xie H, Shi Y, Pashley M, Shamdasani V, Lachman M, Metz S: Assessment of liver viscoelasticity by using shear waves induced by ultrasound radiation force. Radiology 266: 964–970, 2013
30. Urban MW, Nenadic IZ, Mitchell SA, Chen S, Greenleaf JF: Generalized response of a sphere embedded in a viscoelastic medium excited by an ultrasonic radiation force. J Acoust Soc Am 130: 1133–1141, 2011
31. Mauldin FW Jr, Haider MA, Loboa EG, Behler RH, Euliss LE, Pfeiler TW, Gallippi CM: Monitored steady-state excitation and recovery (MSSER) radiation force imaging using viscoelastic models. IEEE Trans Ultrason Ferroelectr Freq Control 55: 1597–1610, 2008
32. Urban MW, Nenadic IZ, Chen S, Greenleaf JF: Discrepancies in reporting tissue material properties. J Ultrasound Med 32: 886–888, 2013
33. Shiina T, Nightingale KR, Palmeri ML, Hall TJ, Bamber JC, Barr RG, Castera L, Choi BI, Chou Y-H, Cosgrove D, Dietrich CF, Ding H, Amy D, Farrokh A, Ferraioli G, Filice C, Friedrich-Rust M, Nakashima K, Schafer F, Sporea I, Suzuki S, Wilson S, Kudo M: WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 1: basic principles and terminology. Ultrasound Med Biol 41: 1126–1147, 2015
34. Bamber J, Cosgrove D, Dietrich CF, Fromageau J, Bojunga J, Calliada F, Cantisani V, Correas JM, D’Onofrio M, Drakonaki EE, Fink M, Friedrich-Rust M, Gilja OH, Havre RF, Jenssen C, Klauser AS, Ohlinger R, Saftoiu A, Schaefer F, Sporea I, Piscaglia F: EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 1: Basic principles and technology. Ultraschall Med 34: 169–184, 2013
35. Cosgrove D, Piscaglia F, Bamber J, Bojunga J, Correas JM, Gilja OH, Klauser AS, Sporea I, Calliada F, Cantisani V, D’Onofrio M, Drakonaki EE, Fink M, Friedrich-Rust M, Fromageau J, Havre RF, Jenssen C, Ohlinger R, Săftoiu A, Schaefer F, Dietrich CF; EFSUMB: EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 2: Clinical applications. Ultraschall Med 34: 238–253, 2013
36. Gennisson J-L, Grenier N, Combe C, Tanter M: Supersonic shear wave elastography of in vivo pig kidney: influence of blood pressure, urinary pressure and tissue anisotropy. Ultrasound Med Biol 38: 1559–1567, 2012
37. Amador C, Urban MW, Chen S, Greenleaf JF: Shearwave dispersion ultrasound vibrometry (SDUV) on swine kidney. IEEE Trans Ultrason Ferroelectr Freq Control 58: 2608–2619, 2011
38. Amador C, Urban M, Kinnick R, Chen S, Greenleaf JF: In vivo swine kidney viscoelasticity during acute gradual decrease in renal blood flow: Pilot study. Rev Ing Biomed 7: 68–78, 2013
39. Warner L, Yin M, Glaser KJ, Woollard JA, Carrascal CA, Korsmo MJ, Crane JA, Ehman RL, Lerman LO: Noninvasive in vivo assessment of renal tissue elasticity during graded renal ischemia using MR elastography. Invest Radiol 46: 509–514, 2011
40. Helfenstein C, Gennisson JL, Tanter M, Beillas P: Effects of pressure on the shear modulus, mass and thickness of the perfused porcine kidney. J Biomech 48: 30–37, 2015
41. Helfenstein-Didier C, Tanter M, Gennisson JL, Beillas P: Observation of the internal response of the kidney during compressive loading using ultrafast ultrasonography. J Biomech 48: 1852–1859, 2015
42. Liu X, Li N, Xu T, Sun F, Li R, Gao Q, Chen L, Wen C: Effect of renal perfusion and structural heterogeneity on shear wave elastography of the kidney: An in vivo and ex vivo study. BMC Nephrol 18: 265, 2017
43. Hossain MM, Selzo MR, Hinson RM, Baggesen LM, Detwiler RK, Chong WK, Burke LM, Caughey MC, Fisher MW, Whitehead SB, Gallippi CM: Evaluating renal transplant status using viscoelastic response (VisR) ultrasound. Ultrasound Med Biol 44: 1573–1584, 2018
44. Wang Z, Yang H, Suo C, Wei J, Tan R, Gu M: Application of ultrasound elastography for chronic allograft dysfunction in kidney transplantation. J Ultrasound Med 36: 1759–1769, 2017
45. Early H, Aguilera J, Cheang E, McGahan J: Challenges and considerations when using shear wave elastography to evaluate the transplanted kidney, with pictorial review. J Ultrasound Med 36: 1771–1782, 2017
46. Hwang J, Kim HW, Kim PH, Suh CH, Yoon HM: Technical performance of acoustic radiation force impulse imaging for measuring renal parenchymal stiffness: A systematic review and meta-analysis [published online ahead of print, February 18, 2021]. J Ultrasound Med 2021
47. Grenier N, Gennisson JL, Cornelis F, Le Bras Y, Couzi L: Renal ultrasound elastography. Diagn Interv Imaging 94: 545–550, 2013
48. Correas J-M, Anglicheau D, Joly D, Gennisson J-L, Tanter M, Hélénon O: Ultrasound-based imaging methods of the kidney-recent developments. Kidney Int 90: 1199–1210, 2016
49. Lim WTH, Ooi EH, Foo JJ, Ng KH, Wong JHD, Leong SS: Shear wave elastography: A review on the confounding factors and their potential mitigation in detecting chronic kidney disease. Ultrasound Med Biol 47: 2033–2047, 2021
50. Lin HY-H, Lee Y-L, Lin K-D, Chiu Y-W, Shin S-J, Hwang S-J, Chen H-C, Hung C-C: Association of renal elasticity and renal function progression in patients with chronic kidney disease evaluated by real-time ultrasound elastography. Sci Rep 7: 43303, 2017
51. Samir AE, Allegretti AS, Zhu Q, Dhyani M, Anvari A, Sullivan DA, Trottier CA, Dougherty S, Williams WW, Babitt JL, Wenger J, Thadhani RI, Lin HY: Shear wave elastography in chronic kidney disease: A pilot experience in native kidneys. BMC Nephrol 16: 119, 2015
52. Leong SS, Wong JHD, Md Shah MN, Vijayananthan A, Jalalonmuhali M, Ng KH: Shear wave elastography in the evaluation of renal parenchymal stiffness in patients with chronic kidney disease. Br J Radiol 91: 20180235, 2018
53. Radulescu D, Peride I, Petcu LC, Niculae A, Checherita IA: Supersonic shear wave ultrasonography for assessing tissue stiffness in native kidney. Ultrasound Med Biol 44: 2556–2568, 2018
54. Goya C, Kilinc F, Hamidi C, Yavuz A, Yildirim Y, Cetincakmak MG, Hattapoglu S: Acoustic radiation force impulse imaging for evaluation of renal parenchyma elasticity in diabetic nephropathy. AJR Am J Roentgenol 204: 324–329, 2015
55. Shi L-Q, Sun J-W, Miao H-H, Zhou X-L: Comparison of supersonic shear wave imaging–derived renal parenchyma stiffness between diabetes mellitus patients with and without diabetic kidney disease. Ultrasound Med Biol 46: 1630–1640, 2020
56. Hassan K, Loberant N, Abbas N, Fadi H, Shadia H, Khazim K: Shear wave elastography imaging for assessing the chronic pathologic changes in advanced diabetic kidney disease. Ther Clin Risk Manag 12: 1615–1622, 2016
57. Bob F, Grosu I, Sporea I, Timar R, Lighezan D, Popescu A, Sirli R, Buzas R, Petrica L, Munteanu M, Schiller A: Is kidney stiffness measured using elastography influenced mainly by vascular factors in patients with diabetic kidney disease? Ultrason Imaging 40: 300–309, 2018
58. Bob F, Grosu I, Sporea I, Bota S, Popescu A, Sirli R, Petrica L, Schiller A: Is there a correlation between kidney shear wave velocity measured with VTQ and histological parameters in patients with chronic glomerulonephritis? A pilot study. Med Ultrason 1: 27–31, 2018
59. Bob F, Bota S, Sporea I, Sirli R, Petrica L, Schiller A: Kidney shear wave speed values in subjects with and without renal pathology and inter-operator reproducibility of acoustic radiation force impulse elastography (ARFI): Preliminary results. PLoS One 9: e113761, 2014
60. Bob F, Grosu I, Sporea I, Bota S, Popescu A, Sima A, Şirli R, Petrica L, Timar R, Schiller A: Ultrasound-based shear wave elastography in the assessment of patients with diabetic kidney disease. Ultrasound Med Biol 43: 2159–2166, 2017
61. Asano K, Ogata A, Tanaka K, Ide Y, Sankoda A, Kawakita C, Nishikawa M, Ohmori K, Kinomura M, Shimada N, Fukushima M: Acoustic radiation force impulse elastography of the kidneys: is shear wave velocity affected by tissue fibrosis or renal blood flow? J Ultrasound Med 33: 793–801, 2014
62. Syversveen T, Brabrand K, Midtvedt K, Strøm EH, Hartmann A, Jakobsen JA, Berstad AE: Assessment of renal allograft fibrosis by acoustic radiation force impulse quantification: A pilot study. Transpl Int 24: 100–105, 2011
63. Stock KF, Klein BS, Vo Cong MT, Sarkar O, Römisch M, Regenbogen C, Büttner M, Schuster T, Matevossian E, Amann K, Clevert DA, Heemann U, Küchle C: ARFI-based tissue elasticity quantification in comparison to histology for the diagnosis of renal transplant fibrosis. Clin Hemorheol Microcirc 46: 139–148, 2010
64. He W-Y, Jin Y-J, Wang W-P, Li C-L, Ji Z-B, Yang C: Tissue elasticity quantification by acoustic radiation force impulse for the assessment of renal allograft function. Ultrasound Med Biol 40: 322–329, 2014
65. Yang C, Jin Y, Wu S, Li L, Hu M, Xu M, Rong R, Zhu T, He W: Prediction of renal allograft acute rejection using a novel non-invasive model based on acoustic radiation force impulse. Ultrasound Med Biol 42: 2167–2179, 2016
66. Chiocchini ALC, Sportoletti C, Comai G, Brocchi S, Capelli I, Baraldi O, Bruno P, Conti F, Serra C, Meola M, Zompatori M, La Manna G: Correlation between renal cortical stiffness and histological determinants by point shear-wave elastography in patients with kidney transplantation. Prog Transplant 27: 346–353, 2017
67. Ma MKM, Law HKW, Tse KS, Chan KW, Chan GCW, Yap DYH, Mok MMY, Kwan LPY, Tang SCW, Choy BY, Chan TM: Non-invasive assessment of kidney allograft fibrosis with shear wave elastography: A radiological-pathological correlation analysis. Int J Urol 25: 450–455, 2018
68. Ghonge NP, Mohan M, Kashyap V, Jasuja S: Renal allograft dysfunction: Evaluation with shear-wave sonoelastography. Radiology 288: 146–152, 2018
69. Yang JR, La Q, Ding XM, Song Y, Wang YY: Using real-time sound touch elastography to monitor changes in transplant kidney elasticity. Clin Radiol 75: 963.e1–963.e6, 2020
70. Lee J, Oh YT, Joo DJ, Ma BG, Lee AL, Lee JG, Song SH, Kim SU, Jung DC, Chung YE, Kim YS: Acoustic radiation force impulse measurement in renal transplantation: A prospective, longitudinal study with protocol biopsies. Medicine (Baltimore) 94: e1590, 2015
71. Grenier N, Poulain S, Lepreux S, Gennisson J-L, Dallaudière B, Lebras Y, Bavu E, Servais A, Meas-Yedid V, Piccoli M, Bachelet T, Tanter M, Merville P, Couzi L: Quantitative elastography of renal transplants using supersonic shear imaging: A pilot study. Eur Radiol 22: 2138–2146, 2012
72. Kim BJ, Kim CK, Park JJ: Noninvasive evaluation of stable renal allograft function using point shear-wave elastography. Br J Radiol 91: 20170372, 2017
73. Bolboacă SD, Elec FI, Elec AD, Muntean AM, Socaciu MA, Iacob G, Zaro R, Andrieș AI, Bădulescu RM, Ignat RM, Iancu M, Badea RI: Shear-wave elastography variability analysis and relation with kidney allograft dysfunction: A single-center study. Diagnostics (Basel) 10: 41, 2020
74. Syversveen T, Midtvedt K, Berstad AE, Brabrand K, Strøm EH, Abildgaard A: Tissue elasticity estimated by acoustic radiation force impulse quantification depends on the applied transducer force: An experimental study in kidney transplant patients. Eur Radiol 22: 2130–2137, 2012
75. Aristizabal S, Amador Carrascal C, Nenadic IZ, Greenleaf JF, Urban MW: Application of acoustoelasticity to evaluate nonlinear modulus in ex vivo kidneys. IEEE Trans Ultrason Ferroelectr Freq Control 65: 188–200, 2018
76. Herman BA, Harris GR: Models and regulatory considerations for transient temperature rise during diagnostic ultrasound pulses. Ultrasound Med Biol 28: 1217–1224, 2002
77. Deng Y, Palmeri ML, Rouze NC, Haystead CM, Nightingale KR: Evaluating the benefit of elevated acoustic output in harmonic motion estimation in ultrasonic shear wave elasticity imaging. Ultrasound Med Biol 44: 303–310, 2018
78. Deng Y, Palmeri ML, Rouze NC, Rosenzweig SJ, Abdelmalek MF, Nightingale KR: Analyzing the impact of increasing mechanical index and energy deposition on shear wave speed reconstruction in human liver. Ultrasound Med Biol 41: 1948–1957, 2015
79. Nightingale KR, Church CC, Harris G, Wear KA, Bailey MR, Carson PL, Jiang H, Sandstrom KL, Szabo TL, Ziskin MC: Conditionally increased acoustic pressures in nonfetal diagnostic ultrasound examinations without contrast agents: A preliminary assessment. J Ultrasound Med 34: 1–41, 2015
80. Deng Y, Palmeri ML, Rouze NC, Trahey GE, Haystead CM, Nightingale KR: Quantifying image quality improvement using elevated acoustic output in B-Mode harmonic imaging. Ultrasound Med Biol 43: 2416–2425, 2017
81. Hossain MM, Moore CJ, Gallippi CM: Acoustic radiation force impulse (ARFI)-induced peak displacements reflect degree of anisotropy in transversely isotropic elastic materials. IEEE Trans Ultrason Ferroelectr Freq Control 64: 989–1001, 2017
82. Demené C, Deffieux T, Pernot M, Osmanski BF, Biran V, Gennisson JL, Sieu LA, Bergel A, Franqui S, Correas JM, Cohen I, Baud O, Tanter M: Spatiotemporal clutter filtering of ultrafast ultrasound data highly increases Doppler and fultrasound sensitivity. IEEE Trans Med Imaging 34: 2271–2285, 2015
83. Song P, Manduca A, Trzasko JD, Chen S: Ultrasound small vessel imaging with block-wise adaptive local clutter filtering. IEEE Trans Med Imaging 36: 251–262, 2017
84. Huang C, Song P, Gong P, Trzasko JD, Manduca A, Chen S: Debiasing-based noise suppression for ultrafast ultrasound microvessel imaging. IEEE Trans Ultrason Ferroelectr Freq Control 66: 1281–1291, 2019
85. Huang C, Song P, Trzasko JD, Gong P, Lok UW, Tang S, Manduca A, Chen S: Simultaneous noise suppression and incoherent artifact reduction in ultrafast ultrasound vascular imaging. IEEE Trans Ultrason Ferroelectr Freq Control 68: 2075–2085, 2021
86. Huang C, Zhang W, Gong P, Lok UW, Tang S, Yin T, Zhang X, Zhu L, Sang M, Song P, Zheng R, Chen S: Super-resolution ultrasound localization microscopy based on a high frame-rate clinical ultrasound scanner: An in-human feasibility study. Phys Med Biol 66: 08NT01, 2021
87. Errico C, Pierre J, Pezet S, Desailly Y, Lenkei Z, Couture O, Tanter M: Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging. Nature 527: 499–502, 2015
88. Palmeri ML, Milkowski A, Barr R, Carson P, Couade M, Chen J, Chen S, Dhyani M, Ehman R, Garra B, Gee A, Guenette G, Hah Z, Lynch T, Macdonald M, Managuli R, Miette V, Nightingale KR, Obuchowski N, Rouze NC, Morris DC, Fielding S, Deng Y, Chan D, Choudhury K, Yang S, Samir AE, Shamdasani V, Urban M, Wear K, Xie H, Ozturk A, Qiang B, Song P, McAleavey S, Rosenzweig S, Wang M, Okamura Y, McLaughlin G, Chen Y, Napolitano D, Carlson L, Erpelding T, Hall TJ: Radiological Society of North America/quantitative imaging biomarker alliance shear wave speed bias quantification in elastic and viscoelastic phantoms. J Ultrasound Med 40: 569–581, 2021

transplantation; basic science; elasticity; shear wave; ultrasound; viscoelasticity

Copyright © 2021 by the American Society of Nephrology