Ultrasound surface wave elastography for assessing scleroderma

Abstract

Scleroderma, or systemic sclerosis (SSc), is a multi-organ connective tissue disease characterized by immune dysregulation and tissue fibrosis. Skin disease is both a disabling feature of SSc and a predictor of visceral involvement and increased mortality. The Modified Rodnan Skin Score (MRSS) is currently the most common clinical method for assessing skin. We developed ultrasound surface wave elastography (USWE) techniques to measure skin surface wave speeds and analyze skin viscoelasticity. The objective of this research was to determine the correlations of skin surface wave speed, skin viscoelasticity with MRSS. Twenty-six SSc patients were studied using USWE and the MRSS. The subject was tested in a sitting position while his/her left or right forearm and upper arm were placed horizontally on a pillow in a relaxed state. The skin of both left and right forearms and upper arms of subjects was tested using USWE. Surface wave speeds are positively correlated with the MRSS. Skin elasticity is also positively correlated with the MRSS. However, there is no correlation between skin viscosity and the MRSS for these SSc patients. We will further study if skin viscosity is sensitive enough to detect early edema from inflammation changes of SSc.

INTRODUCTION

Scleroderma, also termed systemic sclerosis (SSc), (Steen and Medsger 2000) is a multi-organ connective tissue disease characterized by immune dysregulation and tissue fibrosis. Fibrosis is caused by abnormal remodeling of the extracellular matrix (Yamaguchi, et al. 2013) stemming from discrepant deposition and degradation of protein (excessive deposition), but the precise mechanism is still unclear. However, vascular injury and abnormal repair have a role in this complex pathway as do autoimmune defects that result in cytokine activation and molecular signaling (Fauci 2010, Verrecchia, et al. 2007). A recent epidemiologic study reported that the incidence of SSc is increasing, partly because of greater disease awareness and improved diagnosis (Nikpour, et al. 2010).

Skin disease is both a disabling feature of SSc and a predictor of visceral involvement and increased mortality (Clements, et al. 2000). It has been shown that improvement in skin disease with treatment correlates with improved survival (Steen and Medsger 2001). The degree of skin involvement is an important measure and a predictor of mortality (Clements, et al. 1990). The American College of Rheumatology (1980) developed classification criteria for SSc. The diagnosis requires either 1) the major criterion of proximal scleroderma, as judged by palpating or simply observing the skin; or 2) two minor criteria such as sclerodactyly, digital pitting scars or loss of substance from the finger pad, and bibasilar pulmonary fibrosis.

The Modified Rodnan Skin Score (MRSS) (Furst, et al. 1998, Rodnan, et al. 1979), currently the most common clinical method of assessment, is obtained by palpating 17 designated sites and scoring the level of skin thickening from 0 to 3 (where, 0: uninvolved; 1: mild thickening; 2: moderate thickening; and 3: severe thickening) at each site. The sum yields a score that ranges from 0 to 51 for the 17 sites. The severity of skin sclerosis, as assessed by the MRSS, is predictive of disease outcome: patients with an improved skin score (relative to baseline) after two years of treatment had improved survival outcomes (Steen and Medsger 2001). The MRSS is a surrogate marker of SSc severity and is commonly used as an outcome measure in clinical trials. However, the MRSS has a high intrarater and interrater user variability (12% and 25%, respectively) (Clements, et al. 1995). It is affected by examiner experience, and it has low sensitivity for assessing disease progression or response to treatment over a short time period (Czirjak, et al. 2007, Furst, et al. 1998, Postlethwaite, et al. 2008). Objective methods such as skin thickness by ultrasonography (Hesselstrand, et al. 2008, Scheja and Akesson 1997) have been proposed to measure skin disease progression in SSc.

We developed surface wave elastography (SWE) techniques to measure viscoelastic properties of skin. One advantage of SWE over other elastography methods is that the wave can be safely and easily generated and measured on the skin. The wave speed measurement is a relative measurement among several detection positions, and is therefore, independent of the source location. This contrasts with other techniques, such as durometry (Kissin, et al. 2006, Merkel, et al. 2008) or the suction method (Hendriks, et al. 2006), where measurements are dependent on the detector and its application to the tissue. Skin viscoelasticity was tested using an optical-based SWE technique for 30 healthy volunteers and 10 patients with SSc (Zhang 2011). An ultrasound-based SWE technique was used to measure both skin and lung stiffness for patients with SSc and interstitial lung disease (ILD) (Zhang, et al. 2018). The ultrasound-based technique can measure both skin and subcutaneous tissue at the same time (Zhang, et al. 2017, Zhang, et al. 2018, Zhou, et al. 2019). The objective of this research was to determine the correlations of skin surface wave speed, skin viscoelasticity with the MRSS.

MATERIALS AND METHODS

Ultrasound surface wave elastography

USWE was developed to measure the surface wave speed of tissue noninvasively. In USWE, a local, gentle harmonic vibration signal of 0.1 s duration is generated on the skin using a function generator (Model 33120A, Agilent, Santa Clara, CA). The excitation signal is amplified by an audio amplifier (Model D150A, Crown Audio Inc., Elkhart, IN) and then applied to a handheld shaker (Model: FG-142, Labworks Inc., Costa Mesa, CA 92626). The generated tissue motion amplitude is typically less than 10 μm. The excitation of the shaker on the skin is typically less than 1N and does not cause the patient any discomfort. An ultrasound system (Vantage 1, Verasonics, Kirkland, WA) with an L11–4 ultrasound transducer with a central frequency of 6.4 MHz is used for detecting surface wave propagation on the skin. The ultrasound probe is aligned with the indenter of the handheld shaker and is situated 5 mm away. The measured surface wave speed is only dependent on the local elastic properties of skin and independent of the location of wave generation.

Radio-frequency data of ultrasound echo from the tissues are obtained. By demodulating the RF data using quadrature detection, the in-phase/quadrature data of ultrasound signals are processed. Tissue motion at a location is calculated from in-phase/quadrature data of consecutive frames using a one-dimensional autocorrelation method (Kasai, et al. 1985, Zhang, et al. 2018). Images of the skin were acquired by compounding 11 successive angles at a pulse repetition frequency (PRF) of 2 kHz.

Let s₁(t) and s₂(t) represent displacement responses at two locations on the skin. The phase change of surface wave propagation over the two locations can be calculated with a cross-spectrum method. The cross-spectrum S(f) of two signals s₁(t) and s₂(t) is defined as (Hasegawa and Kanai 2006),

$$S(f)=S_1^{*}(f)\cdot S_2(f)=|S_1(f)\cdot S_2(f)|\cdot e^{-j\Delta \phi (f)},$$ (1)

where S₁(f) and S₂(f) are the Fourier transforms of s₁(t) and s₂(t), respectively; * denotes the complex conjugate, and Δϕ (f) is the phase change between s₁(t) and s₂(t) over distance at frequency f.

The phase change of surface wave with distance is used to measure the surface wave speed,

$$c_s=2\pi f\left|\Delta r/\Delta \varphi \right|,$$ (2)

where Δr is the radial distance of two measuring locations, Δϕ is the wave phase change over distance, and f is the frequency. The estimation of surface wave speed can be improved by measuring the phase change over multiple locations using a regression model $\Delta \widehat{\varphi }=-\alpha \Delta r+\beta$, where $\Delta \widehat{\varphi }$ denotes the regression value of multiple Δϕ measurements, α and β are regression parameters, and c_s = 2πf/α.

For soft tissue under low frequency harmonic excitation, the Voigt’s model, which consists of a spring of elasticity μ₁ and a damper of viscosity μ₂ connected in parallel, has been proven to be effective in modeling linear viscoelastic materials (Catheline, et al. 2004, Chen, et al. 2009, Prim, et al. 2016, Zhou, et al. 2017). The wave dispersion curve of wave speed c_s with respect to the angular frequency ω=2πf can be formulated by,

$$c_s=\frac{1}{1.05}\sqrt{\frac{2\left({\mu }_1^2+{\omega }^2{\mu }_2^2\right)}{\rho \left({\mu }_1+\sqrt{{\mu }_1^2+{\omega }^2{\mu }_2^2}\right)}}.$$ (3)

The elasticity and viscosity were calculated using a least square fitting procedure based on the wave speed dispersion curve.

Human Study Protocol

Human studies were approved by the Mayo Clinic Institutional Review Board. Each participant completed an informed consent form. Patients were enrolled in this research study based on their clinical diagnoses. In this paper, we report 26 SSc patients who were studied during January 2017 through April 2018. Patients’ mean age was 60.31 years (range 47–82, 7 males and 19 females).

A subject was tested in a sitting position while his/her left or right forearm and upper arm were placed horizontally on a pillow in a relaxed state. The skin of both left and right forearms and upper arms of subjects was tested. These locations were in the central part of the arm and on the dorsal side.

Figure 1a shows representative B-mode images of the skin for a patient. The top dark area of the image shows the Aquaflex® standoff gel pad. On the skin surface, nine locations were used to measure the surface wave propagation over about 7 mm. The phase change of the surface wave over distance is used to measure the local surface wave speed. Figure 1b shows a representative wave speed at 100 Hz for a patient on the right forearm location. The surface wave speed was in the format of mean ± standard error as 2.41 ± 0.19 m/s for the patient. The dotted black lines indicated a 95% confidence interval of the prediction. The surface wave speed was measured at three excitation frequencies of 100, 150, and 200 Hz. Surface wave speed typically increases with frequency for soft tissues. Using average wave speed values at the three frequencies, both elasticity and viscosity are estimated using equation (3). Most soft tissues have a mass density close to 1.0 g/cm³, which is the value used for the mass density of skin in this paper.

Figure 1.

(a) Representative B-mode image of skin on the right forearm of a patient. An ultrasound gel pad standoff was used to improve imaging of the skin. The top dark area in the image was associated with the gel pad. Nine locations on the skin surface were used to measure the surface wave speed of skin. (b) Measurement of skin surface wave speed. Skin motion at the first location is used as the reference. The wave phase delay of the remaining locations, relative to the first location, is used to measure the surface wave speed. Representative examples of wave speed at 100 Hz for the patient.

RESULTS

The average elasticity and viscosity at the four locations are used for each patient. Figure 2 shows correlation of the average skin surface wave speeds with the MRSS for 100, 150, and 200 Hz. Figure 3 shows correlation of the average of skin elasticity μ1 and viscosity μ2 with the MRSS.

Figure 2.

Correlations of average skin surface wave speed at the four locations with the MRSS for patients at (a) 100 Hz, (b) 150 Hz, and (c) 200 Hz.

Figure 3.

Correlations of skin elasticity μ1 (a) and viscosity μ2 (b) with the MRSS.

DISCUSSION

The aim of this study was to correlate skin surface wave speed and viscoelasticity measurements with the clinical standard - MRSS. A Verasonics ultrasound system using a plane-wave pulse transmission method with a high pulse repetition rate of 2000 frame/s was used to detect skin motion in response to excitations of 100, 150, and 200 Hz. Skin motion velocities at these locations were measured in the normal direction of skin using the ultrasound tracking beams through those locations (Hasegawa and Kanai 2006, Zhang 2011). The surface wave speed on the skin was measured by analyzing ultrasound data directly from the skin. Therefore, the wave speed measurement was local and independent of the excitation location.

SWE techniques use acoustic radiation force (ARF) to generate tissue motion. To generate sufficient tissue motion using ARF, a high-intensity ultrasound field is needed. Although ARF has been widely used in many organs—including the liver, ARF should not be applied to vulnerable organs such as lung and eye. In addition, long periods of ultrasound pulses with relatively high-intensity ultrasound energy may damage the ultrasound system, e.g., probe element damage. Because ARF cannot be generated on surface tissues such as skin, a standoff ultrasound gel pad is needed for the ultrasound probe to generate and measure the waves. However, the standoff pad also decays the ARF and complicates the ARF signal on the skin. In USWE, the mechanical excitation is directly applied to the skin and the standoff pad is only used to improve imaging. USWE provides accurate measurement of wave speed at each frequency. For example, a 0.1 second 100 Hz signal of 10 cycles generates and measures wave speeds at 100 Hz. USWE provides much higher signal to noise ratios for wave speed measurement compared with SWE, which uses a short pulse of ultrasound to generate shear waves in the tissue. USWE provides a much stronger wave generation than SWE, but the mechanical generation is safe and simple.

In an optical-based technique, the generated surface waves on the skin were measured using a laser vibrometry system (Polytec-PI, Inc., Auburn, MA 01501). In that study, we tested skin viscoelasticity for 30 healthy volunteers and 10 patients with SSc (Zhang 2011). We measured at the following six sites: forearm, forearm dorsal, mid medial calf, mid medial thigh, mid medial back, and palm of hand. We found that skin elasticity and viscosity were significantly higher in patients than in healthy volunteers. In USWE, wave generation is safely produced using a gentle mechanical vibration on the skin. Diagnostic ultrasound is only used for detection of wave propagation. Therefore, USWE can be used for skin and can be safely used for subcutaneous organs including the lung (Zhang, et al. 2017) and eye (Sit, et al. 2017). Our recent patient studies using USWE demonstrated that both skin elasticity and viscosity of patients were statistically higher than those of healthy subjects (Zhang, et al. 2018).

Although the MRSS is the current standard for assessing SSc, the MRSS is subjective, associated with high intra-observer and inter-observer variabilities and low sensitivity of score changes over time (Clements, et al. 1995, Czirjak, et al. 2007, Furst, et al. 1998, Postlethwaite, et al. 2008, Rodnan, et al. 1979). Skin thickness can be measured using ultrasonography (USG) (Huang, et al. 2007, Ihn, et al. 1995, Lagarde, et al. 2005, Vogt and Ermert 2007). USG is actively used for assessing various fibrotic skin disorders (Ch’ng, et al. 2013, Hesselstrand, et al. 2008, Kaloudi, et al. 2010, Osmola-Mankowska, et al. 2013, Scheja and Akesson 1997). However, USG does not measure skin stiffness. In addition to USG, USWE provides both skin imaging and viscoelasticity measurements using the same ultrasound system. Further development and validation of USWE may provide a quantitative technique for assessing SSc.

Skin surface wave speeds of both left and right forearms and upper arms were tested at three excitation frequencies and their viscoelasticity were analyzed. It can be seen from Figure 2 that the average skin surface wave speed correlates positively with the MRSS at the three frequencies. This indicates that the stiffening of skin can be detected by both skin surface wave speed and the MRSS measurements. Figure 3a shows positive correlation between skin elasticity and the MRSS. However, the correlation between skin viscosity and the MRSS is almost flat (Figure 3b). SSc can be characterized as early-stage (less than 3 years) or late stage (more than 6 years) from the time of the first symptom. In the early stage, skin thickness increases rapidly, peaks during the transition from early to late stage, and then begins to regress (Medsger 2003). In the early stage, skin swelling may precede hardening. The dermis becomes infiltrated with collagen and becomes thicker after an initial period of induration. Additionally, sclerosis of subdermal connective tissue leads to dermal tethering and limited skin mobility (Clements, et al. 1993). We tried to use Bland-Altman analysis to see the agreements between USWE and the MRSS. However, due to the large difference in magnitudes of the MRSS and shear elasticity, as well as, shear viscosity, it is difficult to tell the correlation between USWE and the MRSS.

We expect that skin viscosity may be sensitive to early inflammation changes with edema, and elasticity may be sensitive to changes in progressive fibrosis. This pilot study provides some evidence that skin elasticity correlates with the MRSS and skin viscosity does not correlate with the MRSS for these SSc patients. We will study if viscosity is more sensitive for detecting the early changes of skin viscoelastic properties.

CONCLUSIONS

USWE is a noninvasive technique for measuring skin surface wave speed and analyzing skin viscoelasticity. In this study, the correlations between skin surface wave speeds at three frequencies, skin viscoelasticity with the MRSS were studied. Surface wave speeds are positively correlated with the MRSS. Skin elasticity is also positively correlated with the MRSS. However, there is no correlation between skin viscosity and the MRSS for these SSc patients. We will further study if skin viscosity is sensitive enough to detect early edema from inflammation changes of SSc.