Implications of surface-rendered facial CT images in patient privacy.
Academic Article
Overview
abstract
OBJECTIVE: Three-dimensional and multiplanar reconstruction of CT images has become routine in diagnostic imaging. The technology also facilitates surface reconstruction, in which facial features and, as a result, patient identity may be recognized, leading to risk of violations of patient privacy rights. The purpose of this study was to assess whether volunteer viewers can recognize faces on 3D reconstructed images as specific patients. SUBJECTS AND METHODS: A total of 328 participants were included: 29 patients underwent clinically indicated CT of the maxillofacial sinuses or cerebral vasculature and were also photographed (group A); 150 patients volunteered to have their faces photographed (group B); and 149 observers reviewed the images. Surface-reconstructed 3D images of group A were generated from CT data, and digital photographs of both groups A and B were acquired for a total of 179 facial photographs. Image reviewers were recruited with a web-based questionnaire that required observers to match surface-reconstructed images generated from CT data with randomized digital photographs from among the 179 photographs. Data analyses were performed to determine the ability of observers to successfully match surface-reconstructed images with facial photographs. RESULTS: The overall accuracy among the image observers was approximately 61%. No significant differences were found with regard to sex, age, or ethnicity and accuracy of image observers. CONCLUSION: Image reviewers were relatively poor at even side-by-side matching of patient photographs with 3D surface-reconstructed images. This finding suggests that successful identification of patients using surface-rendered faces may be a relatively difficult task for observers.
