Though
identifying data typically are removed from medical image files before they are
shared for research, a Mayo Clinic study finds that this may not be enough to
protect patient privacy.
"At
Mayo Clinic, we take patient privacy as a core value," says Christopher
Schwarz, Ph.D., a Mayo Clinic researcher and computer scientist in the Center
for Advanced Imaging Research, and the study's lead author. "We are studying
potential gaps in deidentification as we seek ways to improve these
techniques."
The study,
described in a letter published in the New England Journal of Medicine, finds
that it's possible to use commercial facial recognition software to identify
people from brain MRI that includes imagery of the face, despite steps that
researchers typically take to protect patient privacy. This is a potential
issue for study participants who share brain imaging data. It is not related to
patient care, and it is not limited or specific to studies at Mayo Clinic.
"This
is only applicable if people can get access to the MRI scans in publicly
available research databases. It is not related to medical care, where data is
secured," Dr. Schwarz says.
The
researchers add that this risk is only applicable to people whose imaging data
has been released into the public domain through their participation in
research studies, and typically before researchers can gain access to the data
they are required to sign a data-use agreement in which they state they will
not try to identify the participants.
Today's
standard when sharing MRI scans for research is to remove identifiers such as
name and identification number. But imagery of the face included in MRI remains
accessible. Software programs to remove or blur faces in MRIs have been
available for many years, but they haven't been widely used because they can
degrade researchers' ability to automatically measure brain structures from the
images, according to Dr. Schwarz. Even when used, the software may not fully
prevent reidentification of the patient.
To determine
whether facial recognition software could identify people from an MRI,
researchers recruited 84 volunteers who had an existing brain MRI from within
the past three months and then took additional photographs. Researchers then
created facial reconstruction images from each MRI and attempted to match these
images to the photographs using publicly available facial recognition software.
For 70 of 84
participants, the correct MRI image was chosen as the software's No. 1 match
for those participants' photographs, an 83% success rate. In 80 of 84 cases,
the correct MRI image was among the top five possible matches for participants'
photos, a 95% success rate.
"Our
study's 83% match rate suggests that facial recognition presents a possible
means to reidentify research participants from their cranial MRIs,"
according to the researchers. This could mean a breach of associated health
information, including diagnoses, genetic data and results of other imaging.
Institutions
typically only share imaging data with researchers who legally commit not to
attempt to identify participants. Still, "We understand there are concerns
about the negative impact of facial recognition technology on personal
privacy," says Clifford Jack, M.D., a Mayo Clinic radiologist and senior
author, who also is a member of National Academy of Medicine. Dr. Jack is the
Alexander Family Professor of Alzheimer's Disease Research.
"Dr.
Schwarz's work points out that these concerns include the possibility of
identifying individual research participants who have been guaranteed anonymity
as a condition of their participation in medical research. This is an issue
that the medical research community must be aware of and address."
The Mayo
team plans to publish another manuscript detailing their novel potential
solution and how it improves on existing privacy protection efforts.
"We are
making good progress toward an initial solution," says Dr. Schwarz.
"Making data private and keeping it private is an always-evolving field.
The insights we gained in this study will help us in our work to keep patient
data private and use it more effectively for research into diseases and potential
new therapies."
"With
advances in digital technologies, in this case facial recognition software,
it's critical that we continue to revisit the promises that we've made to our
patients, particularly promises related to the confidentiality of their medical
data," says Richard Sharp, Ph.D., Lloyd A. and Barbara A. Amundson
Professor of Biomedical Ethics and director of the Biomedical Ethics Research
Program, who was involved in this research. "Much of our work in
biomedical ethics focuses on protecting patients from unanticipated harms and
this is an excellent illustration of the importance of that work."
Source: https://medicalxpress.com/news/2019-10-mayo-clinic-patient-privacy-mri.html
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