Background/Purpose: Objective method to evaluate the skin involvement in the patients with scleroderma has not been definitely established. We have developed Vesmeter, a computer-linked device to simultaneously quantify the skin characteristics such as viscosity, elasticity and softness, and have reported its usefulness to evaluate the skin characteristics of patients with scleroderma. Here, we validated Vesmeter as a diagnostic tool of scleroderma.

Methods: Using Vesmeter, we evaluated the skin characteristics of patients with scleroderma and healthy volunteers. 17 points of the body were evaluated, like modified Rodnan’s skin score. First, we compared the skin characteristics of scleroderma patients with that of healthy volunteers matched by age and sex. Second, we conducted bivariate Receiver Operating Characteristic (ROC) analyses to examine which points and parameters are useful to diagnose scleroderma. Third, using whole data of healthy volunteers, we conducted logistic regression and ROC analysis to validate Vesmeter as a diagnostic tool of scleroderma.

Results: 39 patients with scleroderma and 413 healthy volunteers were included. Among the healthy volunteers, 78 people were selected at random, matching age and sex with patients as the control group for the first and second analyses. Regarding the background of the 2 groups, body weight of patients was lighter than controls. As the result of the comparison of skin characteristics, patients’ skin were statistically harder and showed higher elasticity than control on both fingers, left hand, both forearms (Figure 1), both lower legs, and both feet. Viscosity of patients’ skin were also statistically higher than control on both fingers, both hands, both forearms, face, chest, right femur, and right foot. As the result of bivariate ROC analyses, moderate accuracy to distinguish patients from control was recognized by softness of both fingers and both forearms, elasticity of right finger and both forearm, and viscosity of left finger, right hand, both forearms, and face. Based on this result, age, body weight, softness of both fingers and right forearm, elasticity of left forearm, and viscosity of face, left finger, right hand, and both forearms were selected variables for the next logistic regression and ROC analysis using whole data of 413 healthy volunteers. (One of softness and elasticity was used because of the multi-collinearity). This ROC analysis resulted in high accuracy (AUC = 0.92514, Sensitivity = 0.7949, Specificity = 0.9562) to diagnose scleroderma (Figure 2).

Conclusion: Vesmeter showed high accuracy to diagnose scleroderma.