What You Should Know About AI and Your Medical Scans’ Privacy

Introduction

Artificial intelligence is now being used to read X‑rays, MRIs, and CT scans in hospitals and imaging centers across the country. The technology can flag abnormalities faster than a radiologist alone, and in some studies it matches or even exceeds human accuracy for certain findings. But as AI tools become more common, a different kind of risk is getting less attention: what happens to the actual images and the sensitive data they contain.

Most patients are never told that their scans may be sent to cloud servers, analyzed by third‑party algorithms, or stored for future AI training. And the privacy protections many assume apply—like de‑identification or encryption—are not always as robust as they seem.

What Happened: The RSNA Warning

In May 2026, the Radiological Society of North America (RSNA) published a report titled “Medical Imaging AI Opens a Pandora’s Box of Privacy-Related Risks.” The report, presented at the RSNA 2026 annual meeting, outlines several ways that patient privacy is being compromised in the rush to deploy AI in radiology.

Researchers pointed to three main issues:

  1. Re‑identification from de‑identified images. Even when scans have names and social security numbers stripped, AI models can sometimes reconstruct a patient’s identity by matching facial features in head scans, using metadata like scanner serial numbers and dates, or analyzing unique anatomical patterns.

  2. Metadata leakage. Medical image files (such as DICOM files) contain a wealth of hidden metadata—hospital location, scanner model, acquisition date, patient age, and sometimes physician notes. This data can be extracted and used to re‑identify individuals even if the image itself is anonymized.

  3. Cloud‑based processing. Many AI tools are hosted on third‑party cloud platforms. When a patient’s scan is sent to the cloud for analysis, it leaves the hospital’s network and its security perimeter. The hospital may not have full control over how that data is stored, who has access to it, or whether it is deleted after analysis.

The RSNA report does not claim that these risks are widespread or that every AI deployment is insecure. Rather, it stresses that the safeguards have not kept pace with the technology, and that both providers and patients need to be aware of the gaps.

Why It Matters for Patients

The immediate risk for most patients is not that their scans will be posted online, but that the data could be used in ways they never consented to. For example, a scan you had for a routine knee injury could end up in a research dataset used to train an AI that is later sold to insurers. Even if the data is “aggregated,” re‑identification attacks have been shown to work on supposedly anonymous medical datasets.

There is also the possibility of a data breach. Because medical images are being stored and transmitted digitally more than ever, they become a target. A breach of an AI vendor’s cloud storage could expose hundreds of thousands of scans, along with the metadata that links them to real people.

Existing laws like HIPAA in the U.S. and GDPR in Europe cover some of these concerns, but they were written before AI tools became commonplace. HIPAA, for instance, does not clearly regulate how de‑identified data can be used once it leaves a covered entity. GDPR gives patients more rights, but enforcement across borders is inconsistent.

What You Can Do About It

You cannot fully control how your medical data is handled, but you can take steps to reduce your exposure before you go in for a scan:

  • Ask about AI use before your appointment. Call the imaging center or your doctor’s office and ask: “Will AI be used to analyze my images? If so, is that done on‑site or does the data leave the facility?” You have a right to this information.

  • Request a clear explanation of data handling. Ask how long they keep your images after the report is finalized, whether they are stored in a cloud service, and whether they are used for AI training. Some facilities may have a consent form you can review ahead of time.

  • Opt out of research databases if you are uncomfortable. Many academic medical centers allow patients to decline having their images used for research or AI development. Look for an “opt‑out” clause in the consent paperwork or ask the staff.

  • Check the facility’s privacy policy. It should describe third‑party vendors and data storage practices. If the policy is vague or unavailable, that is a red flag.

  • Follow up if you receive a breach notification. Under HIPAA, healthcare providers must notify patients if their data is compromised. If you receive such a notice, take it seriously and monitor for identity theft or insurance fraud.

These steps will not eliminate all risks, but they can help you make an informed choice about where to get your imaging done.

Sources