Imaging AI in Practice demonstration
The Imaging AI in Practice (IAIP) demonstration is presented at the RSNA annual meeting to showcase new technologies and communication standards needed to integrate AI into the diagnostic radiology workflow. It uses real-world clinical scenarios and interoperability standards to demonstrate new tools and practice enhancements enabled by AI.
The demonstration follows a fictional patient through a real-world clinical scenario involving both emergent and long-term care. It includes many steps in the radiology workflow where AI can assist the radiologist and improve the efficiency and quality of care.
The diagrams linked here give a visual overview of the flow of information among systems in a radiology practice with AI tools integrated:
The clinical scenarios and use cases listed below were featured at the IAIP demonstration during RSNA 2022:
Stroke Triage with Incidental Findings
- Clinical Scenario: Follow a patient through their ED stroke work-up and incidental finding follow-up imaging. Witness how AI can help manage multiple concurrent studies with available equipment and staffing in the ED versus inpatient contexts.
- Use cases: Resource utilization, intracranial hemorrhage characterization, pulmonary nodule detection and follow-up
Prostate Cancer Work-Up
- Clinical Scenario: Follow a patient through incidental findings of metastatic osseous disease to diagnosis and work-up for primary prostate cancer.
- Use cases: Intelligent/automated protocoling, pulmonary nodule characterization and AI result modification/rejection, prostate lesion identification, automated follow-up navigation
Mammo to Vehicular Trauma
- Clinical Scenario: Follow a patient from her screening mammogram to ED presentation with intracranial hemorrhage after sustaining vehicular trauma.
- Use cases: Breast asymmetry/mass detection, intracranial hemorrhage characterization, worklist reprioritization, CXR analysis, patient interaction with AI results
The RSNA IAIP demonstration shows how radiology systems can be integrated to efficiently include AI-based applications at key points in the workflow. This seamless integration relies on a set of interoperability standards, including:
- IHE AI Results specifies how results are stored, retrieved, and displayed.
- IHE AI Workflow for Imaging specifies methods to request, manage, perform, and monitor imaging AI algorithms.
- IHE Standardized Operational Log of Events specifies ways to capture workflow event information for use by business intelligence tools.
- HL7 FHIRcast synchronizes clinical applications (EHR, PACS, reporting systems, AI tools) to a given study or patient.
Imaging AI in Practice video archive
View videos featuring previous IAIP demonstration participants performing real-world clinical scenarios to show how AI can be used to support improvements in patient care.
Introduction: Imaging AI Clinical and Data Workflow
Watch an overview of the clinical scenario and process steps for the Imaging AI in Practice demonstration at RSNA 2022.
Imaging AI in Practice Demonstration Introduction
Start here for an overview of the Imaging AI in Practice demonstration’s clinical scenario and process steps.
Work with AI
This video focuses on the interaction between radiologists and AI tools.
Evolve with AI
This video covers implementing and refining AI tools to optimize them for your local environment.
Save Time with AI
This video highlights the efficiencies gained by strategically implementing AI.