Respiratory Motion Estimation in Emission Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In emission imaging techniques like PET and SPECT, respiratory motion causes image degradation, and existing methods require respiratory monitors to achieve accurate gating, which can be cumbersome and less effective for various radiopharmaceutical distributions and organ movements.
Innovation Solution
An amplitude-based respiratory gating method that estimates respiratory motion by identifying a motion assessment image feature in reconstructed emission imaging data, generating a displacement versus time curve, and binning data into amplitude-based gates to reduce motion blur without the need for respiratory monitors, allowing for more accurate and adaptable motion compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If respiratory gating is performed using a respiration monitor belt, then respiratory motion impact is limited, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The emission imaging device itself serves as the respiratory motion monitoring tool by using its own detected radiation data to generate respiratory gating signals, eliminating the need for external respiration monitor belts or separate monitoring devices
Solution Approach 2:
The emission imaging device performs dual functions: acquiring emission imaging data and simultaneously monitoring respiratory motion through the same detected radiation, making the device multi-functional and eliminating additional equipment
2Measurement precision
If respiratory gating is performed using a respiration monitor, then respiratory motion impact is limited, but ease of operation worsens due to cumbersome monitoring device attachment
Solution Approach 1:
The emission imaging device uses its own detected radiation data to derive respiratory gating signals, eliminating the need for patients to wear or be attached to external monitoring devices during the imaging procedure
Solution Approach 2:
The respiratory monitoring function is extracted from separate external devices and integrated into the emission imaging data processing itself, removing the need for additional monitoring equipment attachment
3Manufacturing precision
If conventional respiratory gating is used, then respiratory motion blur is reduced, but adaptability to different radiopharmaceutical distributions and organ movements deteriorates
Solution Approach 1:
The respiratory gating approach is made dynamic and adaptive by using actual detected emission data from the specific radiopharmaceutical distribution in each patient to derive gating signals, allowing the system to adapt to different organ movements and radiopharmaceutical distributions rather than using fixed gating protocols
Solution Approach 2:
The gating parameters are changed from fixed predetermined values to variable values derived from the actual emission data characteristics, including the specific radiopharmaceutical distribution pattern and resulting organ motion patterns for each imaging case
4Measurement precision
If extended emission imaging data acquisition time is employed to collect enough data, then signal-to-noise ratio is improved, but respiratory motion impact increases
Solution Approach 1:
The emission imaging data acquisition is organized into periodic respiratory gating cycles, where data are collected and reconstructed for specific phases of the respiratory cycle (such as end-exhalation), allowing extended total acquisition time while maintaining image quality by selectively using data from quiescent respiratory phases
Solution Approach 2:
The extended acquisition time is segmented into multiple respiratory gating cycles, with data sorted into different bins corresponding to different respiratory phases, allowing the system to accumulate sufficient signal while compensating for motion by reconstructing only from appropriate segments
Data Source
AI summary
A respiratory motion estimation method (30) includes reconstructing emission imaging data (22) to generate a reconstructed image (50). The emission imaging data comprises lines of response (LORs) acquired by a positron emission tomography (PET) imaging device or projections acquired by a gamma camera. One or several assessment volumes (66) are defined within the reconstructed images. The emission imaging data are binned into time interval bins based on time stamps of the LORs or projections. A displacement versus time curve (70) is generated by computing, for each time interval bin, a statistical displacement metric of the LORs or projections that both are binned in the time interval bin and intersect the motion assessment volume. The motion assessment volume may be selected to overlap a motion assessment image feature (60) identified in the reconstructed image.