Nuclear medicine is one of the more venerable medical imaging technologies. Artificial intelligence is one of the newest. How are the two getting on? That question is explored in new point-counterpoint articles in AJR.
Nuclear medicine was an early adopter of computerized image processing, for tasks like image analysis, quantification, and segmentation, giving rise to a cottage industry of niche software developers.
- But this early momentum hasn’t carried over into the AI age: on the FDA’s list of 694 cleared AI medical applications through July 2023, 76% of the listed devices are classified as radiology, while just four address nuclear medicine and PET.
In the AJR articles, the position that AI in nuclear medicine is more hype than reality is taken by Eliot Siegel, MD, and Michael Morris, MD, who note that software has already been developed for most of the image analysis tasks that nuclear medicine physicians need.
- At the same time, Siegel and Morris say the development of AI-type algorithms like convolutional neural networks and transformers has been “relatively slow” in nuclear medicine.
Why the slow uptake? One big reason is the lack of publicly available nuclear medicine databases for algorithm training.
- Also, nuclear medicine’s emphasis on function rather than anatomical changes means fewer tasks requiring detection of subtle changes.
On the other side of the coin, Babak Saboury, MD, and Munir Ghesani, MD, take a more optimistic view of AI in nuclear medicine, particularly thanks to the booming growth in theranostics.
- New commercial AI applications to guide the therapeutic use of radiopharmaceuticals are being developed, and some have received FDA clearance.
As for the data shortage, groups like SNMMI are collaborating with agencies and institutions to create registries – such as for theranostics – to help train algorithms.
- They note that advances are already underway for AI-enhanced applications such as improving image quality, decreasing radiation dose, reducing imaging time, quantifying disease, and aiding radiation therapy planning.
The Takeaway
The AJR articles offer a fascinating perspective on an area of medical imaging that’s often overlooked. While nuclear medicine may never have the broad impact of anatomical-based modalities like MRI and CT, growth in exciting areas like theranostics suggest that it will attract AI developers to create solutions for delivering better patient care.
