Facial Scanning With a Digital Camera: A Novel Way of Screening for Primary Angle Closure

We hypothesize that patients with primary angle closure (PAC) have common significant facial characteristics that set them apart from an age-matched, sex-matched, and race-matched control population. The primary objective of this study was to test whether a 3-dimensional (3D) camera could pick up these differences in order to differentiate PAC patients from controls.

A total of 55 patients with PAC and 38 controls were included in the study.

Cases and controls had their facial photographs taken using a 3-dimensional digital camera (3dMdFace System). The facial features in the captured photographs were analyzed using a computer software (Neural Network Toolbox). A regression formula was devised to show whether these facial parameters could be used to distinguish between patients and controls.

Thirteen facial parameters were measured, and using a regression formula and neural network classification we were able to mathematically distinguish patients from controls using this method of screening.

PAC patients have distinct facial features that may be differentiated from those of normal individuals mathematically using 3D photography. There is potential for this 3D facial scanning technology in screening for PAC in the general population.