The Society for Imaging Informatics in Medicine (SIIM) annual meeting is taking place from May 21 - 23, 2025 in Portland, Oregon.

In order to get an idea of what attendees can expect, and what's been happening in imaging informatics recently, HCB News spoke to Nina Kottler, SIIM's Associate Chief Medical Officer for AI. Here's what she had to say.

HCB News: What inspired you to get into healthcare and more specifically, into imaging informatics?
Nina Kottler: I didn’t originally plan to become a doctor. I started out pursuing a graduate degree in applied mathematics. As part of that work, I built mathematical models of human physiology—creating mathematical representations of the cornea and kidney. In doing so, I had to learn quite a bit of medical science, and to my surprise, I found that content incredibly compelling. Over time, the clinical questions became more interesting to me than the math itself, and that ultimately led me to pivot toward medicine.

Radiology felt like a natural fit—it’s visual, analytical, and deeply tied to technology. Imaging informatics took that a step further, combining my math and engineering background with clinical care. It’s a space where I can solve complex problems, contribute to innovation, and still stay grounded in patient-centered work. I feel lucky to have found a path that connects both sides of my interests so well.

HCB News: How long have you been a member of SIIM?
NK: I’ve been a member of SIIM for over 10 years. In fact, it was the first professional meeting I attended when I set out to learn more about imaging informatics, and I’ve been going to SIIM ever since.

HCB News: In what ways has SIIM supported your career development?
NK: SIIM has played a big role in my career development across several dimensions. First and foremost, the networking has been invaluable—being part of a community of people who are equally passionate about imaging informatics and AI has opened the door to collaborations, mentorship, and friendships that continue to shape my career.

I've also benefited from the cutting-edge content and breadth of educational opportunities SIIM provides. In fact, I recently signed up for a SIIM webinar on agentic AI! While I’ve learned a great deal about radiology informatics, I appreciate how SIIM’s offerings extend across the healthcare enterprise. This broader perspective has deepened my understanding of how imaging informatics fits into the larger healthcare IT landscape.

Another key area is standards development. I’ve had the opportunity to be involved in some of this work, which has given me a deeper appreciation for how complex but essential it is to create shared frameworks for interoperability and AI implementation. At the same time, I’ve greatly benefited from the standards that SIIM and other groups are developing—these frameworks provide clarity and consistency in a rapidly evolving field and have help guide my work.

Finally, the culture at SIIM stands out. There’s a real commitment to inclusion and a clear feeling of community since “everyone belongs at SIIM.” This culture of belonging has made it easier to engage fully, ask questions, and feel part of a shared mission.

HCB News: What trends in imaging informatics do you expect to shape the industry over the next few years?
NK: Over the next few years, I think we’re going to see exciting shifts in imaging informatics, especially with the rise of foundation models including LLMs, LMMs, and intelligent agents. Combined with model context protocols (MCPs), these tools will make it much easier to build agentic workflows—systems that can combine data sources with available tools to take on complex, multi-step tasks autonomously. This development has huge implications for radiology and healthcare. Rather than spending time on administrative or purely perceptual tasks, we’ll be able to focus more on higher-level cognitive work, contributing more meaningfully to patient care.

Another big shift will be the integration of data from across the healthcare ecosystem. Right now, valuable information is often siloed—genetic data in one place, imaging in another, clinical notes somewhere else and we rely on the human to integrate this information. But with better interoperability and intelligent systems, we’ll be able to bring together radiomics, genomics, proteomics, molecular imaging, blood-based biomarkers, and more. That advancement opens the door to truly personalized medicine, where diagnosis and treatment are tailored precisely to the individual. It’s a transformation I’m really looking forward to being part of.

HCB News: How is AI currently being integrated into medical imaging workflows, and what challenges still need to be addressed for wider adoption?
NK: AI is already playing a meaningful role in medical imaging workflows, particularly by supporting tasks like detection, quantification, triage, and diagnosis. These tools are helping improve accuracy and, in some cases, also bringing efficiency gains. On the reporting side, large language models (LLMs) are stepping in to help with everything from drafting reports and translating them for different audiences, to summarizing findings, recommending follow-ups, supporting clinical decision-making, and even helping with billing compliance. It’s a pretty comprehensive integration that will change how radiologists work.

AI is also helping connect the dots across the broader healthcare system. AI-powered care coordination tools are starting to streamline communication between specialists, breaking down silos and making it easier to collaborate across teams. That said, while adoption is growing, there are still challenges including interoperability between systems, consistent performance across institutions, regulatory approval of novel, general AI systems, and building transparency and explainability into AI outputs. Addressing these issues will be key to unlocking AI’s full potential in clinical practice.

HCB News: What are some of the key topics that will be highlighted at this year's SIIM meeting, and which sessions should attendees not miss?
NK: This year’s SIIM meeting will spotlight the future of healthcare, policy adaptation in the face of rapid innovation, and the critical (yet often overlooked) role technology can play in addressing burnout and improving efficiency. I’d also highlight sessions focused on belonging.

As for can’t-miss sessions, be sure to catch the opening keynote by Rohini Kosoglu on AI innovation and policy, and the closing keynote debate “AI vs. Human” with Kathy Andriole and Rich Wiggins. Other standout sessions include “Imaging at the Crossroads,” “Measuring & Maximizing Clinical Impact,” “Private Practice Workflow Integration,” and “SIIM Women in Imaging Informatics: How to Build the Strategic Plan of You.” Several of my colleagues are speaking at the meeting this year and are great to follow including Dr. Jason Poff, Dr. Walter Wiggins, Sylvia Devlin, and Matt Hayes. I’m also moderating a vendor panel on GenAI’s impact on radiology in 2025 and looking forward to that conversation!

Finally, RadEqual is bringing back its Imaging Informatics Awards, with the ceremony taking place Thursday evening at SIIM. This year, they’re introducing a new honor—the RadEqual Catalyst Award—created in recognition of Dr. Geraldine McGinty’s extensive contributions. It’s sure to be a memorable event and one you won’t want to miss!

HCB News: Interoperability remains a challenge in imaging informatics—what progress is being made to improve the seamless exchange of data?
NK: Interoperability remains one of the biggest challenges in imaging informatics, but there has been progress on several fronts. One major policy development is the Information Blocking Rule from the 21st Century Cures Act, which prohibits healthcare providers, IT developers, and networks from unreasonably restricting access to electronic health information. However, it's important to note that this rule currently applies to data housed in certified health IT systems—primarily electronic medical records (EMRs)—and does not extend to full-fidelity diagnostic imaging data stored in PACS. So, while radiology reports and links to imaging may fall under this rule, the images themselves often do not.

Technical standards are advancing in parallel. Integrating the Healthcare Enterprise (IHE) continues to develop profiles that guide how imaging systems exchange data. These standards are key to making sure that different systems can communicate effectively with AI tools, especially across institutional boundaries.

We’re also seeing progress with ontologies like RadLex, which is standardizing the naming of imaging series to improve consistency in how imaging studies are labeled. Likewise, Common Data Elements (CDEs) are being adopted to bring more structure to radiology reporting, enabling better semantic interoperability across systems.

While we still lack a simple, universal mechanism for the seamless exchange of imaging data and need health IT vendors to begin using the standards, these regulatory and technical efforts are laying a strong foundation. Over time, they’ll help reduce fragmentation and support more connected, patient-centered care.