MR Protocol Optimization via Patient Data Rules
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Solution Overview
Problem
Current imaging apparatus protocols, such as in magnetic resonance tomography, often require manual adaptation to patient-specific values, leading to suboptimal settings and reduced image quality due to the lack of user configuration capabilities in existing automation methods.
Innovation Solution
A computer-implemented method for optimizing protocol parameters in medical imaging apparatuses, allowing users to configure conditions and rules for physical parameters, enabling automatic adjustment of protocol settings based on patient-specific data, including lung retention volume and heart rate, without requiring manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adaptation of protocol parameters is performed to patient-specific values, then protocol precision is improved, but operator time and error risk increase
Solution Approach 1:
The system automatically determines protocol parameters by itself using patient data from the patient management system, eliminating the need for manual operator input. The automated system services itself by retrieving necessary patient information and calculating optimal parameters without human intervention.
Solution Approach 2:
The manual mechanical process of operator input and parameter adjustment is replaced with an automated computer-based system that retrieves patient data and calculates protocol parameters algorithmically, substituting human cognitive and manual operations with computational processes.
2Loss of time
If automated creation of measurement sequences is implemented, then operator time is reduced, but user configuration capability is lost
Solution Approach 1:
The system combines dynamic automated parameter determination with configurable user-defined rules and conditions. The automation is not rigid but adaptable, allowing users to configure the behavior of the automated system through programmable rules that can be adjusted based on specific clinical requirements.
Solution Approach 2:
The system serves multiple functions: it automatically determines protocol parameters, allows user configuration through programmable rules, and adapts to different patient-specific scenarios. This multi-functionality resolves the contradiction by making the automated system versatile enough to handle both standard and customized protocols.
3Productivity
If predefined measurement protocols are used, then workflow efficiency is improved, but image quality deteriorates due to suboptimal settings
Solution Approach 1:
The system automatically changes protocol parameters based on patient-specific data retrieved from the patient management system. By dynamically adjusting parameters such as field of view, slice thickness, and acquisition time based on actual patient measurements, the system maintains optimal image quality while preserving workflow efficiency.
Solution Approach 2:
The system performs preliminary automatic determination of protocol parameters before the actual measurement process, using patient data that is already available in the patient management system. This preliminary action ensures optimal settings are established in advance, preventing image quality deterioration while maintaining efficient workflow.
Data Source
AI summary
In a method and a computer-readable storage medium to optimize protocol parameters for an MR measurement protocol, the user can configure conditions for selected physical parameters in advance. Moreover, it is possible to configure rules for these parameters and/or for the conditions. In a next step physical values regarding the selected parameters are measured. The measured values are then applied to the configured conditions and/or rules in order to optimize the protocol parameters.