MRI Scan Geometry Adaptation for Patient Motion
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Solution Overview
Problem
Existing MRI systems face challenges in maintaining accurate scan geometries due to patient movement during scans, leading to geometrical mismatches between acquired and intended regions of interest, which is costly and time-consuming to correct.
Innovation Solution
A method that predefines scan geometries, analyzes the position of the region of interest after each scan, and updates the geometry if a deviation exceeds a threshold, ensuring that subsequent scans share the same physical geometry by applying a transformation matrix to all scans in the queue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If scan geometries are predefined and shared across multiple scans, then scanning efficiency is improved and setup time is reduced, but patient movement causes geometrical mismatch between acquired and intended regions of interest
Solution Approach 1:
The system performs image registration between sequentially acquired images to detect patient movement, then uses the derived transformation matrix to update scan parameters for subsequent scans. This closed-loop feedback mechanism ensures that predefined scan geometries remain accurate despite patient motion, resolving the contradiction between scanning efficiency and geometrical accuracy.
Solution Approach 2:
The patent transforms the static, predefined scan geometry into a dynamic system that automatically adapts to patient movement. By continuously updating scan parameters based on real-time image registration results, the system maintains geometrical accuracy while preserving the efficiency benefits of predefined geometries.
2Reliability
If scan parameters are updated locally for time-sliced scans, then motion correction within a scan is improved, but geometrical mismatch between separate scans with shared geometries persists
Solution Approach 1:
The patent extends the motion correction mechanism to work universally across both time-sliced scans and shared geometry scans. By updating the shared scan geometry definition itself rather than just local parameters, the system provides a unified solution that maintains geometrical accuracy across all scan types, resolving the contradiction between motion correction reliability and geometry sharing compatibility.
3Productivity
If multiple scans are performed with common geometry, then workflow efficiency is improved, but reordering scans to match geometries becomes costly and time-consuming
Solution Approach 1:
The system performs image registration and calculates transformation matrices in real-time during the scanning process, before the scanning workflow is complete. This preliminary action prevents the need for time-consuming post-processing reordering operations, as scans are already acquired with correct geometrical alignment, thus preserving workflow efficiency while eliminating reordering time.
Data Source
AI summary
A method for acquiring image data from a patient with a magnetic resonance imaging (MRI) system. The proposed method comprises the steps of: a) predefining a number of scan geometries for acquiring the image data from at least one region of interest (ROI) relative to the patient, b) performing at least one scan for acquiring the image data in accordance with at least one of the predefined scan geometries, c) analysing in the image data a position of the region of interest to detect a deviation from the at least one predefined scan geometry, d) changing the at least one predefined scan geometry if said deviation exceeds a predetermined threshold value, and e) repeating steps b) to d) until a predetermined number of scans has been performed. Thus, by means of the proposed method the utility of such predefined scan geometries is greatly enhanced.