Adaptive MRI Workflow Metal Detection Algorithm
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Solution Overview
Problem
The presence of metal implants in patients during MRI scans often goes undetected until after the localizer scan, leading to disruption of the scanning workflow, resulting in unusable images or poor image quality and wasted scan time, as existing systems lack a priori knowledge of metal presence and require repeated scans to adjust imaging parameters.
Innovation Solution
A computer-implemented method and system that initiates a prescan using a metal detection algorithm to identify metal implants, allowing for adaptive switching into a metal implant scan mode, optimizing imaging pulse sequences and parameters based on detected metal regions, and providing notifications for lower field strength scanners when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metal detection is performed after localizer scan, then metal implants can be detected, but scanning workflow is disrupted and scan time is wasted
Solution Approach 1:
The patent performs metal detection during the prescan phase, which occurs before the main diagnostic imaging sequence. By integrating metal detection algorithms into the prescan entry point (using existing prescan data), the system identifies metal implants early in the workflow, allowing for appropriate protocol adjustments to be made before committing to a full diagnostic scan sequence, thereby avoiding wasted scan time.
Solution Approach 2:
The patent segments the scanning workflow into distinct phases: prescan (with metal detection), protocol selection, and main diagnostic scanning. By separating metal detection as an independent step within the prescan phase, the system can detect metal without disrupting the overall workflow structure, enabling efficient protocol adaptation while maintaining detection accuracy.
2Manufacturing precision
If scanning protocol is modified after metal detection, then image quality is improved, but workflow disruption increases
Solution Approach 1:
The patent implements a feedback mechanism where metal detection results from the prescan automatically trigger appropriate protocol selections. The system uses the detected metal information to feed back into protocol selection algorithms, which then automatically adjust imaging parameters (such as using metal-artifact-reduction techniques like MAVRIC or SEMAC sequences) without requiring manual technologist intervention, thus maintaining workflow continuity while improving image quality.
Solution Approach 2:
The system performs self-service by automatically selecting and adjusting scanning protocols based on metal detection results. Rather than requiring technologist manual intervention to modify protocols when metal is detected, the system autonomously adapts the imaging parameters and sequence selection based on the prescan metal detection data, reducing workflow disruption while ensuring optimal image quality for metal-containing regions.
3Speed
If metal detection algorithm is executed during prescan, then detection speed is improved, but processing complexity increases
Solution Approach 1:
The patent leverages the prescan data, which is already acquired for routine patient positioning and orientation purposes, and repurposes it for metal detection. By making the prescan data multi-functional (serving both positioning and metal detection purposes), the system achieves fast metal detection without requiring additional dedicated detection sequences or complex additional hardware, thus improving detection speed while minimizing processing complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables faster, automatic detection of metal implants, reduces cognitive burden on technologists, improves image quality, optimizes scan parameters for pathology in the presence of metal, and avoids wasting scan time by allowing for adaptive adjustments during the scanning process.
Implementation Method 1
the resulting set of received nuclear magnetic resonance (NMR) signals are digitized and processed to reconstruct the image
Implementation Method 2
magnetic field gradients (Gx, Gy, and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradient fields vary according to the particular localization method being used
Data Source
AI summary
A computer-implemented method for performing a scan of a subject utilizing a magnetic resonance imaging (MRI) system includes initiating, via a processor, a prescan of the subject by an MRI scanner of the MRI system without a priori knowledge as to whether the subject has a metal implant. The computer-implemented method also includes executing, via the processor, a metal detection algorithm during a prescan entry point of the prescan to detect whether the metal implant is present in the subject. The computer-implemented method further includes determining, via the processor, to proceed with a calibration scan and the scan utilizing predetermined scan parameters when no metal implant is detected in the subject. The computer-implemented method even further includes switching, via the processor, into a metal implant scan mode when one or more metal implants are detected in the subject.