AI in Medical Imaging: What You Should Know About Your Privacy
Artificial intelligence is being used more and more to help radiologists read X-rays, MRIs, and CT scans. These tools can spot patterns that human eyes might miss, speed up diagnosis, and reduce workloads. That’s good for patients. But as AI becomes a standard part of medical imaging, a quieter question is getting attention: what happens to your data after the image is taken?
A recent report from the Radiological Society of North America (RSNA) outlines the privacy risks that come with medical imaging AI. The report warns that the same technology that improves care can also expose sensitive patient information in ways many people don’t expect.
What happened
The RSNA report details how AI systems in radiology collect far more than just the image itself. Each scan carries metadata: date and time, location, equipment serial numbers, patient identifiers, and sometimes even facial features if the scan includes part of the head. When an AI model processes these images, all that data may be stored, transmitted, or used to train future algorithms.
The report points to several specific risks:
- Data breaches. Imaging databases are large and sometimes not as well protected as other medical records.
- Re-identification. Even when names are removed, AI can piece together other data points—unique bone structure, date of birth, or device serial numbers—to re-identify a person.
- Secondary use without consent. Your images could be used to train commercial AI products without your knowledge.
- Model inversion attacks. An attacker can query an AI model to reconstruct images of patients whose data was used in training.
These aren’t hypothetical. Research has shown that de-identified medical images can often be linked back to individuals with relative ease.
Why it matters
For patients, a medical scan is a private moment. It captures the inside of your body. That information can reveal not just medical conditions but also lifestyle details, genetic predispositions, and potentially embarrassing findings.
When you sign a consent form for an imaging procedure, you may be agreeing to share your data for research, algorithm training, or quality improvement. Many patients aren’t told this in plain language. And once your image is part of a training dataset, you lose control over where it goes.
The RSNA report is not an attack on AI. It’s a call for transparency and safeguards. As a patient, you have a right to know how your data is being handled and to make informed choices.
What readers can do
You don’t need to refuse an MRI to protect your privacy. A few practical steps can help:
Ask your provider. Before the exam, ask if AI will be used to process your images. Ask how your data will be stored and whether it will be shared outside the hospital.
Request anonymization. Ask if your images can be stripped of identifying metadata before being used for any purpose outside your direct care. Many healthcare systems offer this if you ask.
Read the consent form carefully. Look for language about data sharing, research, or commercial use. If it’s vague, ask the staff to explain it. You can often opt out of secondary uses without affecting your treatment.
Check your patient portal. Some systems let you see what information is attached to your records, including whether your images have been used in research.
Be aware of re-identification risk. Even anonymized data is not completely safe. If you are particularly concerned, ask if your provider uses techniques like differential privacy or synthetic data generation to protect training data.
Keep copies. You have a right to your own medical images. Having a copy on your own device gives you more control if you change providers or want to check on usage later.
Sources
- Radiological Society of North America, “Medical Imaging AI Opens a Pandora’s Box of Privacy-Related Risks.” Published online May 2026.
- Additional reporting on re-identification risks in medical imaging from academic research and industry guidelines.