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Objective Quantification of Wrinkles: Three-Dimensional Analysis of Surface Irregularity

Lumenta, David Benjamin M.D.; Selig, Harald M.D.; Kitzinger, Hugo-Benito M.D.; Kamolz, Lars-Peter M.D., M.Sc.

Plastic & Reconstructive Surgery: April 2012 - Volume 129 - Issue 4 - p 735e–737e
doi: 10.1097/PRS.0b013e318245e74e

Division of Plastic and Reconstructive Surgery, Department of Surgery, Vienna General Hospital, Medical University of Vienna, Vienna, Austria

Correspondence to Dr. Lumenta, Division of Plastic and Reconstructive Surgery, Department of Surgery, Vienna General Hospital, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria

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On the one hand, valid and reliable objective assessment tools for specific characteristics of wrinkles (i.e., location, fold type, and depth) are lacking1 and subjective scoring of varying validity has been used for evaluation of treatments.2,3 On the other hand, objective evaluation of wrinkle assessment is rarely used and has limitations in its clinical application or for technical reasons.4,5 The aim of this work was to evaluate wrinkles using an objective measure for surface irregularity derived from stereophotographic images and to analyze age-related differences of wrinkling in voluntary facial expressions in volunteers.

The stereophotographic system (LifeViz 3D Micro; Quantificare S.A., Sophia Antipolis, France) uses a computerized matching algorithm for estimation of surface area from a reconstructed three-dimensional grid. The field of view was defined as the entire area captured by stereophotography (5 × 4 cm) from a fixed distance of 20 cm. A dual light point projector at the base of the camera system produced two beams of light that intersected once the correct distance to the targeted focus point was obtained. Two simultaneous photographs were recorded by the use of a stereo lens adapter on a digital single-lens reflex camera from a perpendicular direction acquired by the photographer. The images were then digitally processed (Dermapix; Quantificare) and the region of interest was marked manually in the field of view. For measuring surface irregularity of wrinkles, quantifications were based on the “fine analysis” mode with a “sigma = 10” setting. The outline of the region of interest forms a smooth and planar surface against which the hills and valleys of the reconstructed skin surface delimit volumes. Volumes were counted positive regardless of whether they arose from a hill or crest or from a valley or wrinkle. Surface irregularity was defined as the ratio of the sum of all volumes to the surface area of the region of interest (Fig. 1). The greater the volumes extending above or below the neutral surface, the greater the surface irregularity, as follows:

The unit of volume was cubic millimeters and the unit of measurement for surface area was square millimeters, resulting in millimeters as the unit for surface irregularity. Surface irregularity values for different facial expressions are expressed as relative change of surface irregularity from the neutral facial expression: a negative value indicated a reduction of surface irregularity and a positive value demonstrated an increase.

One trained investigator acquired all images, and three-dimensional measurements were performed in a blinded fashion. Frontal images from 94 volunteers (34 male volunteers and 60 female volunteers) were obtained during three different facial expressions: neutral, eyes firmly closed, and brows maximally lifted. The region of interest was selected that contained a representative part of the wrinkling caused by action of the procerus and frontalis muscles during respective movements. Data are presented as medians (minimum/maximum). Confirmation of nonparametric distribution by Shapiro-Wilk normality testing and the Friedman test was used to compare the three different facial expressions, and posttesting was performed by means of Dunn multiple comparison. Only Spearman correlation coefficients of 0.6 or above were considered to demonstrate a strong positive correlation for age and surface irregularity. A value of p < 0.05 was considered statistically significant (GraphPad Prism 5; GraphPad Software, Inc., La Jolla, Calif.).

The median age of the 94 volunteers was 33 years (range, 17 to 81 years). The relative change of the facial expression in the region of interest in percentages from the neutral facial expression are quantified by raw data in Table 1 and illustrated with relative changes in Figure 2. The differences of surface irregularity among the three facial expressions (i.e., neutral, eye closure, and brow lifting) were statistically significant (p < 0.0001, Friedman test). Posttesting by means of Dunn multiple comparison revealed a statistically significant difference for the following pairs: neutral versus brow lift, and eyes closed versus brow lift. Age did not correlate with surface irregularity in any of the facial expressions and the Spearman correlation coefficient for age versus neutral, eye closure, and brow lift was 0.2937 (p = 0.0041, R 2 = 0.1515), 0.2941 (p = 0.0040, R2 = 0.1204), and 0.1342 (p = 0.1972, R2 = 4.91 × 10–6), respectively.

There were no previously published experiences of surface irregularity by the use of three-dimensionally reconstructed digital grids in wrinkles. Therefore, we presented a simple setup that uses objective measurement of the surface irregularity of facial wrinkles and applies this to the comparison of surface irregularity between three different facial expressions. Limitations include the system's restricted field of view, which requires multiple image acquisition for areas of interest outside the field of view, and the lack of an automated region of interest definition and a calculation for surface irregularity. The presented approach incorporated the advantage of using a rapid and noncontact technique, and the resultant data contained all characteristics relevant for wrinkle assessment.

David Benjamin Lumenta, M.D.

Harald Selig, M.D.

Hugo-Benito Kitzinger, M.D.

Lars-Peter Kamolz, M.D., M.Sc.

Division of Plastic and Reconstructive Surgery, Department of Surgery, Vienna General Hospital, Medical University of Vienna, Vienna, Austria

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The authors have no conflict of interest to declare.

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This work was funded in part by European Commission FP7 Health Research grant FP7-HEALTH-F4-2008-202047.

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1. Rohrich RJ. Advances in facial rejuvenation: Botulinum toxin A. Hyaluronic acid dermal fillers, and combination therapies—Consensus recommendations. Editor's Foreword. Plast Reconstr Surg. 2008;121(Suppl):1S–2S.
2. Monheit GD, Gendler EC, Poff B, et al.. Development and validation of a 6-point grading scale in patients undergoing correction of nasolabial folds with a collagen implant. Dermatol Surg. 2010;36(Suppl):1809–1816.
3. Flynn TC. Botulinum toxin: Examining duration of effect in facial aesthetic applications. Am J Clin Dermatol. 2010;11:183–199.
4. Grove GL, Grove MJ, Leyden JJ. Optical profilometry: An objective method for quantification of facial wrinkles. J Am Acad Dermatol. 1989;21:631–637.
5. Branford OA, Dann SC, Grobbelaar AO. The quantitative assessment of wrinkle depth: Turning the microscope on botulinum toxin type A. Ann Plast Surg. 2010;65:285–293.
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