Applications of the new Aeva-HE™ imaging system: Its link with the visual evaluation of facial wrinkles and its potential in screening tensile products.

OBJECTIVES: To evaluate, in vivo, a recently developed imaging system (Aeva-HE™), based on fringe projection methodology: (i) its correlation with expert's assessments and real age of 85 French Caucasian women and (ii) its potential, as a screening tool, in rapidly selecting prototypes of tensile cosmetic products. MATERIALS AND METHODS: First, the bare faces of 85 differently aged French/Caucasian women were photographed under standard conditions and further analyzed by the Aeva-HE™ device. An expert aesthetician graded the severity of wrinkling on a fixed scale, helped by the use of a dedicated Skin Aging Atlas. A panel of 15 judges performed the same task on full-face standard photographs. The Aeva-HE™ software yielded various wrinkle's parameters (density, volume, mean depth, etc.) on different facial locations, according to age-groups. Second, seven women, balanced in age and wrinkling severity, were recruited in a separate study. These women applied at Day 1 a prototype of the tensile product and at Day 2, they applied another prototype of the tensile product. The whole faces (before and after products application) of the seven studied women were captured and analyzed by the Aeva-HE™ system. RESULTS: The density of wrinkles was significantly highly correlated with the aesthetician scores and, unsurprisingly, with age. Some parameters (volume, depths) of different wrinkles (glabellar, crow's feet, cheeks) were quantified, showing different absolute values and of statistically different progressions with age. The amplitudes of the rapid effects brought by the two prototypes of tensile products were clearly differentiated. CONCLUSION: The recently developed device Aeva-HE™ is an efficient system for rapidly establishing a faithful and precise status of facial wrinkles, in vivo and seems like a precious tool in the rapid screening of tensile products, possibly performed on a rather limited number of subjects.

In vitro and in vivo validation of a new three-dimensional fringe projection-based device (AEVA-HE) dedicated to skin surface mapping.

BACKGROUND: Aging signs are much visible on the surface of the skin that presents different changes: cheeks start to sag, more and deeper wrinkles appear, and pigmentation spots increase. Face diagnostic to recommend products includes assessing cutaneous micro-relief or the micro-depressive network on the face. Furthermore, there is an increasing demand for clinical and instrumental methods to prove the efficacy of anti-aging treatments. As a result, very accurate and sensitive three-dimensional (3D) devices are developed and validated to measure and quantify aging skin and to catch fine anti-aging products acting on wrinkles and fine lines. METHODS: AEVA-HE, a non-invasive 3D method based on fringe projection technology, is used to robustly characterize the skin micro-relief from a full-face acquisition and from multiple extracted zones of interest. In vitro and in vivo studies are conducted to assess the reproducibility of this system and its precision toward a standard fringe projection system, DermaTOP. RESULTS: The AEVA-HE successfully measured micro-relief and wrinkles and demonstrated the reproducibility of measurements.  AEVA-HE parameters were found highly correlated to DermaTOP. CONCLUSION: The present work illustrates the performance of the AEVA-HE device and its dedicated software kit as a precious tool for quantifying the major characteristics of wrinkles appearing with age and thus offers a high potential for assessing the effect of anti-wrinkling products.

Prediction of treatment effect perception in cosmetics using machine learning.

Perception of treatment effect (TE) in cosmetics is multifaceted and influenced by multiple parameters that need to be considered simultaneously when evaluating TE. Here we provide a global approach to predicting TE perception using Random Forest (RF) classifier. Data from three randomized double-blind clinical studies with a total of 50 subjects were used. Different products were applied to each facial cheek of subjects at each visit, and post-application photographs were taken. Nine primary endpoints relating to skin pores were assessed by a specific image analysis algorithm. Twenty judges evaluated the relative pore visibility in all possible pairs of cheek photographs. RF was used to construct a prediction model for TE perception based on the primary endpoints and judge's evaluation. Intra-study product ranking was done using the Bradley-Terry model on mean judges' predicted preference. RF demonstrated overall good accuracy in predicting TE perception. Applying RF technique not only addresses issues of multiplicity, nonlinearity and interactions between multiple criteria but also focuses decision-making on one discrete parameter thereby simplifying interpretability and allowing for more consumer-centered claim substantiation in clinical trials.Abbreviations: RF: Random Forest classifier; FDA: The US Food and Drug Agency; ID: Identifier; MCID: Minimal clinical important difference; Param: Parameter; PGIC: Patients' Global Impression of Change; TE: Treatment effect; TRT: Treatment.