Neurophysiological Motion Prediction for Prospective Imaging Gating
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Patient motion during medical imaging processes, such as CT or MRI, leads to corrupted data, which complicates image reconstruction and increases radiation exposure, as current motion correction algorithms are retrospective and cannot detect motion in real-time, necessitating the acquisition of potentially useless data.
Innovation Solution
A system and method that monitor neurophysiological signals to predict patient motion, allowing for the cessation of image data acquisition during anticipated motion periods, using a processor to integrate signals from EEG, MEG, EMG, and other sensors to generate a prediction signal, and modify data acquisition accordingly, potentially aided by a mental focus device to minimize movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If retrospective motion correction algorithms are used, then motion-corrupted data can be identified during reconstruction, but radiation exposure increases due to acquisition of corrupted data that will be rejected
Solution Approach 1:
The system performs preliminary motion detection using neurophysiological signals (EEG, ECG, EMG, respiration) before image data acquisition begins. By predicting patient motion in advance based on physiological patterns, the system can preemptively pause or adjust the imaging process, preventing acquisition of motion-corrupted data and thereby reducing unnecessary radiation exposure while maintaining reconstruction quality
Solution Approach 2:
The system continuously monitors physiological signals during the imaging process and uses this real-time feedback to detect motion patterns. The feedback loop compares expected physiological patterns against actual signals, and when motion is detected, the system automatically adjusts the acquisition process to avoid capturing corrupted data, thus reducing radiation exposure without compromising image quality
2Productivity
If image data acquisition continues during patient motion, then more data is collected for reconstruction, but the data becomes corrupted and reconstruction quality decreases
Solution Approach 1:
The system uses preliminary motion prediction based on neurophysiological signals to identify upcoming motion events before they occur. This allows the acquisition system to pause or adjust timing in advance, ensuring that only high-quality, motion-free data is collected during the imaging process, thereby maintaining both productivity and reconstruction quality
Solution Approach 2:
When motion is detected through physiological signal analysis, the system skips acquisition during the motion period and rapidly resumes acquisition after motion ceases. This approach avoids collecting corrupted data entirely while minimizing interruption to the overall imaging process, maintaining productivity without sacrificing reconstruction quality
3Reliability
If neurophysiological monitoring is implemented for prospective motion gating, then motion-corrupted data acquisition is prevented, but device complexity increases
Solution Approach 1:
The system integrates multiple physiological monitoring functions (EEG for brain activity, ECG for cardiac activity, EMG for muscle activity, and respiration monitoring) into a single unified platform. This multi-functional approach allows one system to perform comprehensive motion detection across multiple physiological domains, reducing the need for separate specialized devices and thereby managing complexity while improving detection accuracy
Solution Approach 2:
The system introduces a physiological signal processing intermediary layer that translates complex multi-source physiological data into simplified motion prediction outputs. This intermediary layer processes raw signals from multiple sensors, applies pattern recognition algorithms, and generates straightforward control signals for the imaging system, thereby managing complexity between the diverse physiological inputs and the imaging control system
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A system, method and non-transitory computer-readable storage medium for monitoring motion during medical imaging. The monitoring of the motion includes initiating an acquisition of image data, measuring physiological signals of a patient, generating a prediction signal by integrating the physiological signals, determining whether patient motion is likely to occur based on the prediction signal and modifying the acquisition of image data, if it is predicted that patient motion is likely to occur.