CATH Lab Imaging With De-Identification for Procedure Evaluation
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Solution Overview
Problem
Existing medical imaging systems lack effective methods for evaluating operator techniques during procedures, integrating data from multiple devices, and facilitating remote clinician assistance, while ensuring secure sharing and protection of patient information.
Innovation Solution
A system that tracks medical instrument motion, integrates data from devices like ablation generators with imaging systems, and enables secure remote consultation, while protecting patient information through permission-based access and de-identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If imaging systems capture and store detailed medical procedure data, then evaluation and research capabilities improve, but data security and patient privacy protection become more difficult
Solution Approach 1:
The system extracts and removes personally identifiable information from medical imaging data through de-identification processes. This allows the medical procedure data to be retained for evaluation and research purposes while the harmful personal identifiers are extracted and eliminated, resolving the contradiction between data utility and privacy protection.
Solution Approach 2:
The patent introduces an intermediary de-identification layer between the original medical data and its use in evaluation systems. This intermediary process transforms the data to remove personal identifiers while preserving clinical information, enabling both patient privacy protection and procedure evaluation capabilities.
2Loss of information
If multiple medical devices are integrated into a unified system, then data completeness and evaluation accuracy improve, but system complexity increases
Solution Approach 1:
The system employs universal data collection standards and protocols that allow multiple different medical devices to integrate their data into a common evaluation framework. By creating a multi-functional integration layer that can handle various device types through standardized interfaces, the system achieves data completeness without proportionally increasing complexity.
Solution Approach 2:
The integration architecture is segmented into modular components, with each device connecting through standardized interfaces to a central evaluation platform. This segmentation allows individual devices to be added or removed independently, managing overall system complexity while maintaining data completeness from multiple sources.
3Measurement precision
If real-time tracking of medical instruments is implemented, then operator technique assessment improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of tracking data by pre-defining regions of interest, pre-configuring assessment parameters, and pre-establishing evaluation criteria. This preliminary action reduces the computational burden during real-time processing, enabling precise operator technique assessment without excessive processing time.
Solution Approach 2:
The system applies partial processing to full tracking datasets by focusing computational resources on critical motion parameters and key procedural moments rather than analyzing every data point in detail. This selective processing maintains assessment accuracy while reducing overall processing time and resource requirements.
Data Source
AI summary
Example systems and techniques are disclosed that may determine characteristics of lesions. An example system may include memory configured to store at least one computer vision model and processing circuitry communicatively coupled to the memory. The processing circuitry may be configured to receive imaging data of at least a portion of a vasculature of a patient generated during a cardiac catheterization procedure. The processing circuitry may be configured to execute the at least one computer vision model to determine characteristics of a lesion in the vasculature based on the received imaging data.