AI in Medical Imaging: What You Need to Know About Privacy Risks

AI in Medical Imaging: What You Need to Know About Privacy Risks

Medical imaging has always involved sensitive data — X-rays, CT scans, MRIs contain not just anatomical details but often personal identifiers. Now that artificial intelligence is being used to read, analyze, and even generate images, a new layer of privacy concern has emerged. A recent article from the Radiological Society of North America (RSNA) framed it bluntly: AI in medical imaging “opens a Pandora’s box of privacy-related risks.” For patients who undergo scans, that warning is worth understanding.

What happened

The RSNA piece, published in late May 2026, outlines how AI systems in radiology rely on large datasets of medical images. Many of these images are stored in the cloud, shared between institutions, and used to train algorithms. While hospitals and vendors de-identify images by stripping direct identifiers like names or Social Security numbers, research has shown that facial recognition techniques or image metadata can sometimes re-identify patients. The RSNA authors point out that current privacy frameworks — including HIPAA in the United States — were designed before AI became a routine part of clinical workflows, leaving gaps in how secondary use of scans is governed.

Why it matters

For patients, the practical risks are not hypothetical. If your CT scan is uploaded to an AI training database, and that database is later breached, your medical image could be linked back to you. Even if the image is “de-identified,” AI tools are becoming better at reconstructing faces from medical scans or matching images to publicly available profiles. There is also the issue of consent: many consent forms for imaging procedures include broad language about “data use for research and development,” but patients are rarely told that AI companies may use their scans to train commercial algorithms. And once the data is out there, it is nearly impossible to revoke.

Another concern is transparency. When a hospital uses an AI tool to help interpret your mammogram or lung scan, questions arise about who has access to the raw image, where the data is processed (some cloud servers may be in other countries), and whether the algorithm itself introduces bias or error. Most patients have no way to verify these details.

What readers can do

You do not need to decline a recommended scan. But you can take a few practical steps to protect your health data.

First, ask your radiologist or imaging center: “Will my images be used to train AI, and if so, can I opt out?” Some institutions now offer a checkbox on consent forms. If they don’t, ask for clarification in writing.

Second, look at the privacy notice of the imaging facility. Many post it online. It should describe how they handle data sharing with third-party AI vendors. If the language is vague — “we may share data with partners for quality improvement” — that likely includes AI development. Express your preference to keep your data for clinical use only.

Third, understand your rights under HIPAA. The law gives you the right to request an accounting of disclosures of your protected health information. That includes disclosures to AI vendors, if they are considered business associates. You can also request that your medical images be stored locally rather than on a cloud server, though this may not always be feasible.

Fourth, be cautious about uploading your own medical images to free online AI services for second opinions. Many of those services claim ownership of uploaded data in their terms of service. Instead, ask your provider for a formal referral.

Finally, stay informed about legislative changes. The RSNA article itself is a signal that the radiology community is aware of the problem. Proposed updates to HIPAA and new FDA guidance on AI in medical devices may strengthen protections. Meanwhile, your best ally is being a curious patient who asks questions before the scan.

Sources

• Radiological Society of North America (RSNA): “Medical Imaging AI Opens a Pandora’s Box of Privacy-Related Risks” (May 20, 2026)
• U.S. Department of Health and Human Services: HIPAA Privacy Rule
• FDA guidance on artificial intelligence and machine learning in medical devices (as of 2026)

Note: The RSNA article is behind a membership paywall; the summary above is based on publicly available RSS content and the publication date.