Methods/Technique: Fifteen subjects (10 women and 5 men) between the ages of 18-75 were imaged using a dual camera system and three-dimensional optical analysis (ARAMIS, Trilion Quality Systems, PA). Each subject was imaged at rest and engaged in the following facial expressions: 1) smile, 2) laughter, 3) surprise, 4) anger, 5) grimace, and 6) whistling. All subjects had no prior history of rejuvenation procedures. The maximum, minimum, and average principle strains were computed from each dominant vector of facial movement for each subject and compared.
Results/Complications: Three-dimensional imaging is an effective measure with which to investigate facial aging. Dominant vectors of facial expression within the perioral region highlight significant dynamic changes in the aging face while vectors within the midface reflect more static changes over time. The differences reflected in the strains of these vectors provide a new paradigm with which to analyze the aging face.
Conclusion: Although the subject of aging has been highly investigated, our understanding of this complex topic is far from complete. We demonstrate here that three-dimensional imaging technology can adequately capture and evaluate the vectors of facial strain, enabling quantifiable comparisons across age groups. This model of anatomic aging highlights critical changes in the aging face and is directly applicable to developing and improving anti-aging therapies.