Computer-Aided Triage System for Stroke Imaging Workflow
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Solution Overview
Problem
Current triaging workflows in emergency settings are time-consuming, particularly for conditions like stroke, where delays can lead to significant neuronal loss and reduced treatment options, necessitating a more efficient system for determining and initiating treatment.
Innovation Solution
A computer-aided triage system comprising a router, remote computing system, and client application that processes imaging data to rapidly determine treatment options and transfer patients to specialist care, reducing the time from imaging to specialist notification from over 50 minutes to less than 8 minutes, while maintaining high sensitivity and specificity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a standard radiology workflow is used for triaging, then the radiologist can review images thoroughly and generate a comprehensive report, but the time to determine and initiate treatment increases significantly
Solution Approach 1:
The workflow is segmented into two parallel paths: a fast AI-based triage path for rapid initial assessment and a traditional radiologist review path for comprehensive diagnosis. The AI algorithm performs preliminary analysis of imaging data to generate urgent findings, which are then communicated to the emergency department for immediate action, while the radiologist independently reviews the same images through the traditional workflow for complete diagnostic evaluation.
Solution Approach 2:
The AI algorithm performs preliminary analysis of the imaging data before the radiologist completes their review. This preliminary action identifies urgent findings and triggers immediate notification to the emergency department, allowing treatment initiation to begin while the radiologist's comprehensive review is still in progress. The preliminary AI assessment does not replace but complements the radiologist's thorough analysis.
2Reliability
If the traditional radiology workflow is maintained, then comprehensive diagnostic evaluation is achieved, but patient transfer and specialist notification are delayed
Solution Approach 1:
The AI algorithm serves as an intermediary between the radiology imaging system and the emergency department. It translates radiology imaging data into actionable triage findings and automatically communicates urgent results to the emergency department, bridging the gap between diagnostic imaging and treatment initiation without requiring the radiologist to complete their full review workflow first.
Solution Approach 2:
The manual process of radiologist review followed by report generation and emergency department notification is partially replaced by an automated AI system. The AI algorithm automatically analyzes imaging data, identifies urgent findings, and triggers notifications to the emergency department, replacing the mechanical sequence of human review and communication with an automated system that operates in parallel and significantly reduces time delays.
3Measurement precision
If image data is sent to standard radiology workflow, then thorough image review is performed, but the number of steps and time required increases
Solution Approach 1:
The AI algorithm provides multi-functional capability by simultaneously performing image analysis, generating triage findings, determining urgency levels, and triggering notifications to appropriate departments. This single automated system handles multiple tasks that would otherwise require separate manual steps including radiologist review, report generation, and emergency department communication, thereby reducing workflow complexity while maintaining diagnostic accuracy.
Data Source
AI summary
A system for computer-aided triage can include a router, a remote computing system, and a client application. A method for computer-aided triage can include determining a parameter associated with a data packet, determining a treatment option based on the parameter, and transmitting information to a device associated with a second point of care.