High-frequency quantitative ultrasound in characterizing human skin aging: an exploration of the non-modeling and modeling approaches.

Abstract

Background: High-frequency quantitative ultrasound (HQUS) technology, with its non-invasiveness, high-resolution, objectivity, and reproducibility, holds significant potential for characterizing skin aging through the analysis of the internal structure of tissues. This study aims to explore a framework for characterizing skin aging assessment through HQUS technology to facilitate the subsequent analysis of skin aging-related studies.

Methods: In this study, an exploration of non-modeling and modeling HQUS techniques in characterizing skin aging was conducted. In particular, we tested the conventional approach using the envelope amplitude, the non-modeling approach based on the small-window entropy and the modeling approach with the Nakagami parameters (m and Ω) at scanning depths of 1 and 1.5 mm, respectively, and discovered that such a characterization framework is well-suitable for quantifying skin aging. These parameters were calculated based on ultrasound backscattered signals at a high frequency of 42 MHz from the facial skin (from the epidermis to the dermis) of 70 female participants aged 24-57 years and then analyzed using the linear fitting and receiver operating characteristic (ROC) curves.

Results: The results show that there exists a linear correlation between all parameters and participant ages at scanning depths of 1 and 1.5 mm, respectively. Among them, the correlation coefficients for parameter m are r²=0.84 (P<0.0001) and r²=0.65 (P<0.0001), which are higher than those for the relative envelope amplitude, small-window entropy, and parameter Ω. Moreover, the parameter m also has the highest area under the curve among the ROC curves, regardless of the scanning depth.

Conclusions: This characterization framework, especially the modeling of the Nakagami parameter m, has great feasibility for the characterization of human skin aging. The proposed framework holds significant potential for assessing the efficacy of facial rejuvenation products, photofacials, and similar treatments.