AI in Medical Imaging Raises New Privacy Risks – Here’s How to Protect Your Data

Artificial intelligence is now a regular part of radiology. AI tools read CT scans, flag suspicious lesions, and speed up analysis. But the same technology that improves diagnosis also introduces privacy risks that many patients don’t know about. Recent research shows that AI can even generate fake X‑rays that fool radiologists—a scenario that raises questions about data integrity, insurance fraud, and patient trust.

If you’ve ever had an X‑ray, MRI, or CT scan, your images are likely stored in digital systems that may be shared for AI training. Here’s what’s happening and what you can do.

What happened

In 2026, researchers presented findings at the Radiological Society of North America (RSNA) showing that deepfake chest X‑rays created by AI were able to deceive both radiologists and automated detection systems. The fake images appeared nearly identical to real scans and could theoretically be used to fake a pneumonia diagnosis or alter a patient’s medical record.

This study is part of a larger trend. Medical imaging data is increasingly shared across hospitals, research institutions, and private AI vendors. While de‑identification (removing names and social security numbers) is supposed to protect patients, researchers have repeatedly shown that it’s possible to re‑identify individuals from imaging metadata—such as the unique shape of their lungs or the patterns in their bone structure. A 2020 study found that facial recognition AI could match 3D CT reconstructions to patient identities with high accuracy.

Why it matters

For patients, the risks fall into several categories:

  • Data breaches. Medical imaging databases are valuable targets. A breach could expose sensitive health information—including images that reveal conditions like cancer, heart disease, or mental health status—and leave patients vulnerable to discrimination, stigma, or identity theft.
  • Deepfakes and fraud. Fake medical images could be used to falsely support an insurance claim, obtain disability benefits, or even frame someone for medical fraud. The RSNA study confirms this is no longer theoretical.
  • Errors in diagnosis. If AI‑generated images are mixed into real systems, they could cause misdiagnosis. A falsified X‑ray showing a tumor that isn’t there could lead to unnecessary surgery, while a fake clean scan could delay treatment.
  • Loss of control. Many patients aren’t asked before their images are used for AI training. Even when consent is obtained, the terms often allow indefinite use, and images may be sold to third parties.

Current U.S. privacy regulations like HIPAA were written before AI and deepfakes became common. They don’t fully cover the newer risks—such as AI re‑identification or the use of synthetic medical images. Some states are moving to update laws, but the patchwork is slow and uneven.

What readers can do

You don’t need to refuse medical imaging—but you can take steps to protect your data.

  • Ask your provider about AI use. Before a scan, ask: “Will my images be used to train any AI system?” If the answer is yes, ask whether you can opt out. Many hospitals offer an opt‑out for research use, though it’s not always advertised.
  • Request written data policies. Ask for a copy of the facility’s privacy policy specifically regarding medical images and AI. Look for promises about encryption, access controls, and deletion timelines.
  • Demand encryption and audit trails. Imaging systems should encrypt data both in transit and at rest. Ask whether the facility logs who accesses your images and for what purpose.
  • Opt out of sharing when possible. Some radiology departments allow patients to restrict their data to internal use only. You have the right to limit how your protected health information is used—though for treatment purposes some sharing is unavoidable.
  • Keep your own copy. Download or request a copy of your images on a CD or secure digital link. This gives you visibility into what exists and can help you spot any unauthorized changes later.
  • Monitor your insurance statements. If you see a charge for an imaging procedure you didn’t have, it could be a sign someone used your data—or a deepfake of your images—to file a fraudulent claim.

Sources

  • RSNA 2026 research presentation on deepfake X‑rays and their ability to fool radiologists and AI detection systems.
  • Publicly available studies on re‑identification of medical imaging data (e.g., facial recognition from CT images, 2020).
  • HIPAA Privacy Rule, U.S. Department of Health and Human Services.

Medical AI is not going away, and its benefits are real. But the privacy risks are equally real. Understanding what’s at stake is the first step to keeping your medical images—and your trust—secure.