Cath Lab Contrast Usage Monitoring for Real-Time Dosage Control
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Solution Overview
Problem
Current medical imaging systems lack effective methods for tracking and analyzing the motion of medical instruments during procedures to determine optimal operator techniques and instrument selection, and they do not facilitate real-time remote consultation or secure sharing of imaging data for improved treatment planning and education.
Innovation Solution
A system that integrates computer vision and machine learning models to analyze medical instrument motion, track lesion characteristics, and enable secure remote consultation, while ensuring secure sharing and de-identification of patient data, using imaging data from cardiac catheterization procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If imaging data is shared remotely for consultation and collaboration, then treatment planning quality and expert assistance improve, but data security and patient privacy protection become compromised
Solution Approach 1:
The patent extracts and removes personally identifiable information (PII) from imaging data before transmission. The de-identification system separates sensitive patient identifiers from the medical imaging content, allowing the medical information to be shared for consultation while the PII is extracted and protected separately, thus enabling remote collaboration without compromising patient privacy.
Solution Approach 2:
The patent introduces a de-identification server as an intermediary between the local imaging system and remote consultation systems. This intermediary automatically processes imaging data to remove PII before transmission, acting as a security buffer that enables data sharing while protecting patient identity. The intermediary handles the de-identification process transparently, allowing seamless remote collaboration with built-in privacy protection.
2Measurement precision
If contrast material is used generously to ensure adequate imaging quality, then image detail and diagnostic accuracy improve, but patient exposure to harmful substances increases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors contrast material usage and imaging quality metrics in real-time. Based on this feedback, the system dynamically adjusts contrast injection parameters (rate, volume, timing) to maintain adequate image quality while minimizing total contrast exposure. The feedback loop enables adaptive optimization of contrast usage throughout the procedure.
Solution Approach 2:
The patent applies partial action by using contrast material selectively and locally only where diagnostically necessary, rather than uniform distribution. The system identifies specific vascular regions requiring detailed imaging and targets contrast delivery to those areas, reducing overall contrast volume while maintaining image quality in critical zones. This selective approach avoids excessive contrast exposure in non-critical areas.
3Reliability
If multiple imaging modalities and advanced processing are used to improve diagnostic accuracy, then lesion detection and treatment planning improve, but system complexity and operational difficulty increase
Solution Approach 1:
The patent merges multiple imaging modalities (fluoroscopy, angiography, 3D reconstruction) and processing functions into a single integrated imaging system. This consolidation allows seamless switching between modalities and automatic coordination of different imaging techniques without requiring separate equipment or complex manual integration, thereby maintaining high diagnostic accuracy while reducing operational complexity.
Solution Approach 2:
The patent implements self-service through automated image processing and analysis functions. The system automatically performs lesion detection, characterization, and treatment planning recommendations without requiring manual intervention for each processing step. AI-driven algorithms automatically analyze imaging data, identify abnormalities, and suggest treatment options, reducing the operational burden on clinicians while maintaining or enhancing diagnostic accuracy.
Data Source
AI summary
An example system includes a memory; and processing circuitry communicatively coupled to the memory, the processing circuitry being configured to: determine, for a current patient, a maximum contrast dosage for a cardiac catheterization lab procedure; determine, while the cardiac catheterization lab procedure, a cumulative amount of contrast used; and output, for display and during the cardiac catheterization lab procedure, a graphical representation of a comparison between the cumulative amount of contrast used and the maximum contrast dosage.