Implementation and validation of face de-identification (de-facing) in ADNI4.

Autor: Schwarz CG; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Choe M; Northern California Institute for Research and Education, San Francisco Veterans Affairs Medical Center, San Francisco, California, USA., Rossi S; Department of Radiology, University of California, San Francisco, San Francisco, California, USA., Das SR; Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Ittyerah R; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Fletcher E; Department of Neurology, University of California, Davis, Davis, California, USA., Maillard P; Department of Neurology, University of California, Davis, Davis, California, USA., Singh B; Department of Neurology, University of California, Davis, Davis, California, USA., Harvey DJ; Division of Biostatistics Department of Public Health Sciences, , University of California, Davis, Davis, California, USA., Malone IB; Dementia Research Centre, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK., Prosser L; Dementia Research Centre, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK., Senjem ML; Department of Information Technology, Mayo Clinic, Rochester, Minnesota, USA., Matoush LC; Department of Information Technology, Mayo Clinic, Rochester, Minnesota, USA., Ward CP; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Prakaashana CM; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Landau SM; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, USA., Koeppe RA; Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA., Lee J; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, USA., DeCarli C; Department of Neurology, University of California, Davis, Davis, California, USA., Weiner MW; Department of Radiology, University of California, San Francisco, San Francisco, California, USA., Jack CR Jr; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Jagust WJ; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, USA., Yushkevich PA; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Tosun D; Northern California Institute for Research and Education, San Francisco Veterans Affairs Medical Center, San Francisco, California, USA.; Department of Radiology, University of California, San Francisco, San Francisco, California, USA.
Jazyk: angličtina
Zdroj: Alzheimer's & dementia : the journal of the Alzheimer's Association [Alzheimers Dement] 2024 Nov; Vol. 20 (11), pp. 8048-8061. Date of Electronic Publication: 2024 Oct 11.
DOI: 10.1002/alz.14303
Abstrakt: Introduction: Recent technological advances have increased the risk that de-identified brain images could be re-identified from face imagery. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a leading source of publicly available de-identified brain imaging, who quickly acted to protect participants' privacy.
Methods: An independent expert committee evaluated 11 face-deidentification ("de-facing") methods and selected four for formal testing.
Results: Effects of de-facing on brain measurements were comparable across methods and sufficiently small to recommend de-facing in ADNI. The committee ultimately recommended mri_reface for advantages in reliability, and for some practical considerations. ADNI leadership approved the committee's recommendation, beginning in ADNI4.
Discussion: ADNI4 de-faces all applicable brain images before subsequent pre-processing, analyses, and public release. Trained analysts inspect de-faced images to confirm complete face removal and complete non-modification of brain. This paper details the history of the algorithm selection process and extensive validation, then describes the production workflows for de-facing in ADNI.
Highlights: ADNI is implementing "de-facing" of MRI and PET beginning in ADNI4. "De-facing" alters face imagery in brain images to help protect privacy. Four algorithms were extensively compared for ADNI and mri_reface was chosen. Validation confirms mri_reface is robust and effective for ADNI sequences. Validation confirms mri_reface negligibly affects ADNI brain measurements.
(© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
Databáze: MEDLINE
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