Welcome to the first installment of this year’s Road to RSNA preview for RSNA 2026. Once again, we’re providing a modality-by-modality overview of select scientific presentations to serve as your guide to events at McCormick Place.
In what has become an annual tradition at AuntMinnie, AI is our first stop on our journey along the Road to RSNA. This section will focus on clinical use of AI; stay tuned for additional coverage of AI in our upcoming Imaging Informatics and Advanced Visualization sections. Breast imaging AI research will also be included in our Women’s Imaging preview.
A key trend this year is analysis of AI’s performance in real-world clinical applications, yielding invaluable insights for current and future adopters. In addition, AI may also have utility in theranostics applications, helping to predict treatment response. Other notable hot areas include patient risk assessment and the technology’s potential to support early diagnosis of pancreatic cancer. And another study took a look at how AI could affect radiology malpractice cases.
See below for previews of AI-related scientific talks we’re highlighting at this year's RSNA meeting. These are just a sample of the content on offer, however. Attendees can also look forward to a plethora of other scientific presentations, scientific posters, plenary sessions, and educational courses and exhibits on AI topics, including the highly popular AI Showcase in the South Exhibit Hall. For more information on those presentations and other abstracts, check out the RSNA 2026 meeting program.
Thyroid ultrasound AI yields high agreement with radiologists
Sunday, November 29 | 9:20 a.m.-9:30 a.m. | S1-SSHN01-3 | Room E352
In this scientific presentation, researchers will share findings from a large, real-world deployment of AI software for thyroid ultrasound.
AI predicts cancer risk on LDCT lung cancer screening exams
Sunday, November 29 | 1:00 p.m.-2:00 p.m. | S4-SSCH02-5 | Room E451A
Researchers will describe the performance of a new deep-learning algorithm for predicting malignancy on low-dose CT (LDCT) lung cancer screening exams.
Algorithm assesses mortality risk in heavy smokers
Sunday, November 29 | 1:00 p.m.-2:00 p.m. | S4-SSCH02-7 | Room E451A
A deep-learning model can predict mortality in heavy smokers from CT lung cancer screening exams, adding prognostic value beyond traditional risk factors and body composition measures, according to this presentation.
AI gives rads a boost on prostate MRI exams
Monday, November 30 | 8:00 a.m.-9:00 a.m. | M1-SSGU02-8 | Room E353B
In this talk, researchers will make the case that AI can help radiologists read prostate MRI exams more accurately and consistently.
Does AI negatively affect cognitive burden of radiologists?
Monday, November 30 | 9:30 a.m.-10:30 a.m. | M3-SSIN02-3 | Room E450B
AI doesn’t always lighten radiologists’ mental workload, and in some cases adds to it, researchers will report.
How AI utilization reflects cognitive load for radiologists
Monday, November 30 | 9:30 a.m.-10:30 a.m. | M3-SSIN02-4 | Room E450B
In this talk, researchers will explain how usage logs from AI-assisted reporting tools can effectively measure cognitive load.
Rads and AI: better together for detecting pancreatic cancer
Monday, November 30 | 9:30 a.m.-10:30 a.m. | M3-SSGI03-2 | Room E451B
In this scientific presentation, researchers will describe how radiologists and AI can make an effective team for detecting pancreatic cancer on CT.
Can AI help spot pancreatic cancer sooner?
Monday, November 30 | 9:30 a.m.-10:30 a.m. | M3-SSGI03-3 | Room E451B
An open-source AI system could detect pancreatic cancer on routine CT exams nearly a year before clinical diagnosis, according to this study.
Will AI affect radiology malpractice cases?
Monday, November 30 | 9:30 a.m.-10:30 a.m. | M3-SSIN02-8 | Room E450B
How radiologists utilize AI and how they document that use could sway jurors in a malpractice case, according to this presentation.
Deep learning on chest x-rays matches PREVENT score for cardiac risk
Monday, November 30 | 1:30 p.m.–1:40 p.m. | M6-SSCA03-1 | Room E352
In this session, a study will show that deep-learning models applied to routine chest x-rays can predict cardiovascular risk as accurately as the American Heart Association's standard PREVENT score.
Can LLMs assist radiologists in diagnostic tasks?
Tuesday, December 1 | 3:00 p.m.-4:00 p.m. | T7-SSIN03-8 | Room E353A
Multimodal large language models can generate accurate differential diagnoses and may support clinical decision-making, according to this presentation.
AI software metrics may not reflect clinical performance
Tuesday, December 1 | 3:00 p.m.-4:00 p.m. | T7-SSNPM02-4 | Room S503
Vendor-reported performance metrics don’t guarantee that a radiology AI device will perform well in clinical use, researchers will caution in this talk.
AI predicts survival in metastatic prostate cancer
Tuesday, December 1 | 3:00 p.m.-4:00 p.m. | T7-SSRO02-7 | Room S401CD
For patients with metastatic prostate cancer, deep learning applied to PSMA-PET scans may be better for predicting survival than existing risk tools, according to this presentation.
How does AI affect diagnostic risk in radiology?
Wednesday, December 2 | 9:30 a.m.-10:30 a.m. | W3-SSIN06-3 | Room E450B
Rather than eliminating diagnostic risk in radiology, AI shifts it, according to an analysis set to be presented in Chicago.
AI may not improve patient outcomes for stroke
Wednesday, December 2 | 9:30 a.m.-10:30 a.m. | W3-SSNR10-3 | Room E350
In this presentation, researchers will share how implementing AI software at a comprehensive stroke center didn’t measurably improve patient outcomes.
Rads, AI complement each other for spotting cerebral microbleeds
Wednesday, December 2 | 9:30 a.m.-10:30 a.m. | W3-SSNR10-6 | Room E350
Although an AI algorithm flagged far more cerebral microbleeds on brain MRI than a radiologist did, it also raised more false alarms, researchers will report in this presentation.
Can an AI model predict Pluvicto treatment response?
Wednesday, December 2 | 1:30 p.m.-2:30 p.m. | W6-SSNMMI06-2 | Room S405
An algorithm that combines PSMA-PET imaging features with routine lab values may help predict which patients with mCRPC will respond to Pluvicto radioligand therapy, according to this presentation.
AI triage algorithms yield varied results in real-world use
Thursday, December 3 | 9:30 a.m.-10:30 a.m. | R3-SSIN07-1 | Room E450B
Researchers will present their experience in rolling out 11 triage AI algorithms across three hospitals.
AI can be a safety net for intracranial aneurysms
Thursday, December 3 | 11:00 a.m.-12:00 p.m. | R4-SSHN03-5 | Room N228
An AI algorithm can help spot intracranial aneurysms on routine contrast-enhanced neck CT exams, according to this scientific paper.
AI shines as worklist prioritization tool in detecting PE
Thursday, December 3 | 1:30 p.m.-2:30 p.m. | R6-SSCH08-2 | Room E451A
In this talk, researchers will share their experience with utilizing AI software for detection and triage of pulmonary embolism (PE).
