RSNA 2026 Highlights Advances in Medical Imaging

Scientific presentations in the Learning Center Theaters will spotlight new approaches, early findings and technologies with the potential to influence imaging practice. Browse the meeting program and add these scientific presentations to your schedule.

Cancer Screening with Imaging in the Era of Precision Medicine

• Multimodal Deep Learning for Preoperative Invasiveness Stratification of Lung Adenocarcinoma Spectrum Nodules: A Multicenter Retrospective Study
• TRACE-LC: Automated Tracheal Phenotyping for Incident Lung Cancer Risk Stratification in LDCT Screening
• Turning Routine CT into a Precision Screening Platform: Fully Automated AI for Opportunistic Detection of Ovarian Cancer Across Institutional, Nationwide, and International Populations
• Image-Only Deep Learning Risk Model Using Digital Breast Tomosynthesis Supports Equitable, Personalized Prediction of Invasive Breast Cancer Risk
• AI Image-Based Breast Cancer Risk Stratification Increases Cancer Yield and Reduces Supplemental MRI Costs Compared with Breast Density

Imaging of Early Chronic and Metabolic Diseases

• The Q-Dixon MRI-Derived Renal Fat Fraction and R2* for Evaluating Early Kidney Involvement in Patients With MASLD: Body Composition as a Metabolic Link in the Liver-Kidney Axis
• Incremental Prognostic Value of Fully Automated Multiorgan CT Biomarkers for Incident Cardiometabolic Event
• Opportunistic CT Body Composition Screening: A Sex-Specific Framework for Cardiometabolic Risk Stratification From Routine Imaging
• Diffusion Basis Spectrum Imaging of Early Brain Involvement in Obesity: White-Matter Microstructural Correlates of Systemic Inflammation
• Hepatic Fat as an Independent, Synergistic, and Graded Predictor of Type 2 Diabetes on Whole-Body MRI: Findings From Over 15,000 Individuals

Imaging Biomarkers for Next-Generation Immune, Cellular, and Gene Therapies

• DC-Engineered MRI for Visualizing Mature Tertiary Lymphoid Structures: An Imaging Biomarker for Glioma Immunotherapy Response
• A Natural-History-Referenced Bayesian Counterfactual Framework for Evaluating Therapy in Ultra-Rare Monogenic Arteriopathy
• AI-Enhanced MRI Biomarker for Patient Selection and Staging in Alzheimer Immunotherapies
• Ultrasound Detection of Synovitis in Immune Checkpoint Inhibitor Therapy- Prevalence and Clinical Correlates
• Splenic Hyperpolarized Carbon- 13 Pyruvate MRI Detects Early Immune-Metabolic Activation After Checkpoint Inhibitor Therapy in Gynecologic Cancers

High-Impact Clinical Trials in Radiology

• Physician Connection Time and Emergency Escalation Under Virtual Contrast Supervision Following Permanent CMS Authorization: A Study of 165,350 Outpatient Examinations
• Deep Learning-Based MRI Acceleration at Scale: 20% Higher Throughput Across 598,833 MRI Examinations Without Added Staffing
• Cancer Detection Rates of Artificial Intelligence Augmented Prostate Fusion Biopsy: Two-Year Results of a Prospective Clinical Trial
• AI as Reading Aid Versus Triaging in Breast Cancer Screening: A Prospective Multicenter Study
• Tozorakimab Reduces the Number of Lung Segments with CT-Based Mucus Plugs in Patients with COPD at High Risk of Exacerbations: Integrated Analysis of the Replicate OBERON and TITANIA Phase 3 Studies

Novel Applications of Photon Counting CT Not Currently Possible with “Standard” Spectral Energy Integrating Detectors (EID)

• Photon-Counting CT for Myocardial Fibrosis Quantification in Hypertrophic Cardiomyopathy: Validation Against Cardiac Magnetic Resonance
• Ultrahigh-Resolution Photon-Counting CT Angiography for Quantifying Cervical Internal Carotid Artery In-Stent Restenosis: A Phantom-to-Patient Comparison with Conventional and Dual-Energy CT
• Photon-Counting CT Enables Tantalum- Iodine Separation Using Threshold Ratio Mapping: Initial Results of a Novel Material-Specific Imaging Technique
• A Novel Application of Spectral Virtual Non-Calcium Reconstruction for the Detection of Extra-Axial Hemorrhage
• Feasibility of Novel Virtual Non- Contrast Images in Low-Dose Photon-Counting CT For Lung Cancer Evaluation: A Multicenter Head-to-Head Study