CT System with Decision Tree for Patient-Specific Scan Control
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Solution Overview
Problem
CT systems lack control mechanisms that account for patient-specific factors, leading to incomplete coverage of scan complexities and potential human errors in selecting optimal scan protocols.
Innovation Solution
Integration of a logical decision tree within the CT system's computer system to automatically determine and set examination and scan parameters based on patient-specific parameters, including organ to be examined, clinical question, and physiological values, thereby selecting the optimal scan mode and excluding impossible scan modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If predefined scan protocols are used for average patients, then the CT system can operate efficiently with standardized settings, but the system cannot account for patient-specific factors and complexities
Solution Approach 1:
The system automatically adjusts scan parameters (tube voltage, dose power, scan mode) based on patient-specific parameters such as weight, height, age, organ to be examined, and clinical questions. This dynamic parameter adaptation resolves the contradiction by moving from fixed standardized settings to flexible patient-tailored settings.
Solution Approach 2:
The CT system performs self-adjustment through an integrated evaluation unit that automatically selects optimal scan protocols based on input patient parameters without requiring manual intervention by operators. The system serves itself by making intelligent decisions about scan configuration based on patient characteristics.
2Ease of operation
If manual selection of scan protocols is performed by operators, then flexibility in protocol selection is available, but human errors in selecting optimal scan modes may occur
Solution Approach 1:
The evaluation unit processes patient parameters and automatically determines optimal scan settings, providing a feedback mechanism that replaces manual operator decisions with automated intelligent selection. This reduces human error while maintaining or improving operational flexibility through the system's ability to interpret patient-specific factors.
Solution Approach 2:
The system performs self-configuration by automatically selecting scan protocols based on patient parameters, eliminating the need for manual protocol selection by operators. This self-service capability improves reliability by removing human error from the selection process while maintaining ease of operation through automated decision-making.
3Measurement precision
If comprehensive patient-specific parameters are collected and processed, then optimal patient-specific scan settings can be determined, but the system complexity and processing requirements increase
Solution Approach 1:
The evaluation unit processes patient parameters through a structured logical decision tree that segments the complex decision-making process into manageable steps. Patient parameters are evaluated systematically to determine scan mode, boundary conditions, and optimal settings, breaking down the complex task of patient-specific protocol selection into organized processing stages.
Data Source
AI summary
A CT system for scanning a patient is disclosed. In at least one embodiment, the system includes a tube/detector system, which can be set by a control device in respect of tube voltage and/or dose power; a patient couch, which can be displaced in a controlled fashion at least in the direction of a system axis; and a computer system, which can control the CT system. In at least one embodiment, the system includes an evaluation unit for a prescribed logical decision tree, which is integrated into the computer system, and which determines examination and scan parameters for the CT system on the basis of the input of at least one patient parameter described in a parameter list and operates the CT system using these examination and scan parameters.