Workflow Server Optimizes Medical Imaging Protocols
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Solution Overview
Problem
The inefficiency in managing image acquisition protocols and sequences leads to unnecessary image capture and interpretation overhead, with a significant portion of exams using incorrect protocols, resulting in irrelevant images and decreased efficiency in medical imaging procedures.
Innovation Solution
A workflow server system that analyzes historical data to determine metrics for sequence usage and generates rules to recommend inclusion or exclusion of sequences in subsequent image acquisition procedures based on context, optimizing the selection of protocols and sequences for image orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple sequences are added to protocols to remain contemporary with modern practice, then the protocols become more comprehensive and up-to-date, but the acquisition time increases and protocols become cluttered
Solution Approach 1:
The system performs preliminary analysis of historical image acquisition data to identify which sequences are actually used in practice. This advance knowledge allows protocols to be optimized before new image orders are processed, ensuring that only necessary sequences are included, thus reducing acquisition time while maintaining comprehensiveness.
Solution Approach 2:
The system continuously monitors and analyzes historical data from image acquisition procedures to provide feedback on sequence usage patterns. This feedback loop enables dynamic optimization of protocols, where sequences that are never or rarely used are identified and removed, while necessary sequences are retained, resolving the contradiction between comprehensiveness and time efficiency.
2Adaptability or versatility
If protocols are expanded with additional sequences to cover all potential imaging needs, then the protocols become more versatile, but the complexity of managing and selecting appropriate sequences increases
Solution Approach 1:
The system enables self-service optimization by automatically analyzing historical data and generating optimized protocol configurations without requiring manual intervention. The system serves itself by identifying usage patterns and automatically determining which sequences should be included in protocols, thereby reducing management complexity while maintaining versatility.
Solution Approach 2:
The system changes the parameters of protocols dynamically based on historical usage data. By analyzing actual usage patterns and adjusting protocol parameters (which sequences to include/exclude) accordingly, the system reduces complexity while preserving versatility, as protocols are automatically configured based on empirical evidence rather than manual curation.
3Productivity
If incorrect protocols are used in image acquisition procedures, then the imaging process can proceed without delays in protocol selection, but irrelevant images are captured leading to wasted time and resources
Solution Approach 1:
The system performs preliminary analysis of historical data to establish optimized protocol recommendations before new image orders are processed. This advance preparation ensures that when protocols are selected for new procedures, they are already optimized based on proven usage patterns, preventing the selection of incorrect protocols and avoiding wasted imaging resources while maintaining efficient throughput.
Solution Approach 2:
The system uses feedback from historical data analysis to continuously improve protocol selection accuracy. By monitoring which protocols lead to useful versus irrelevant images, the system refines its recommendations, ensuring that high productivity is maintained while minimizing wasted resources on incorrect protocol selections.
Data Source
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AI summary
A device, system, and method optimizes image acquisition workflows. The method performed at a workflow server includes receiving data associated with previous image acquisition procedures that have been performed, the image acquisition procedures having respective image orders, the image orders having respective contexts, each of the image acquisition procedures having used at least one sequence defining settings to capture an image. The method includes determining at least one metric associated with a use of a first one of the at least one sequence for a first one of the contexts. The method includes generating a rule indicative of whether the first sequence is to be included or excluded for a subsequent image acquisition procedure having the first context based on the at least one metric.