PT  - JOURNAL ARTICLE
AU  - Selfridge, Aaron R.
AU  - Spencer, Benjamin A.
AU  - Abdelhafez, Yasser G.
AU  - Nakagawa, Keisuke
AU  - Tupin, John D.
AU  - Badawi, Ramsey D.
TI  - Facial Anonymization and Privacy Concerns in Total-Body PET/CT
AID  - 10.2967/jnumed.122.265280
DP  - 2023 Aug 01
TA  - Journal of Nuclear Medicine
PG  - 1304--1309
VI  - 64
IP  - 8
4099  - http://jnm.snmjournals.org/content/64/8/1304.short
4100  - http://jnm.snmjournals.org/content/64/8/1304.full
SO  - J Nucl Med2023 Aug 01; 64
AB  - Total-body PET/CT images can be rendered to produce images of a subject’s face and body. In response to privacy and identifiability concerns when sharing data, we have developed and validated a workflow that obscures (defaces) a subject’s face in 3-dimensional volumetric data. Methods: To validate our method, we measured facial identifiability before and after defacing images from 30 healthy subjects who were imaged with both [18F]FDG PET and CT at either 3 or 6 time points. Briefly, facial embeddings were calculated using Google’s FaceNet, and an analysis of clustering was used to estimate identifiability. Results: Faces rendered from CT images were correctly matched to CT scans at other time points at a rate of 93%, which decreased to 6% after defacing. Faces rendered from PET images were correctly matched to PET images at other time points at a maximum rate of 64% and to CT images at a maximum rate of 50%, both of which decreased to 7% after defacing. We further demonstrated that defaced CT images can be used for attenuation correction during PET reconstruction, introducing a maximum bias of −3.3% in regions of the cerebral cortex nearest the face. Conclusion: We believe that the proposed method provides a baseline of anonymity and discretion when sharing image data online or between institutions and will help to facilitate collaboration and future regulatory compliance.