Bone Depiction via Ultra-Short Echo Time MRI Sequences
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Solution Overview
Problem
Conventional Magnetic Resonance Imaging (MRI) techniques face challenges in depicting and segmenting cortical bone structures due to low proton density and short signal lifetimes, making it difficult for meaningful bone signal detection, especially in applications like MR-based PET attenuation correction and radiation therapy planning.
Innovation Solution
The use of proton density-weighted ultra-short echo time (UTE) and zero echo time (ZTE) pulse sequences with short echo times, combined with RF bias correction and inverse logarithmic scaling, enables fast and accurate depiction and segmentation of bone structures without relying on echo subtraction or anatomical prior knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional MRI pulse sequences with millisecond-range echo times are used, then soft tissue imaging is adequate, but bone signal detection is too slow and meaningless due to short signal lifetimes
Solution Approach 1:
The patent changes the echo time parameter from millisecond-range to ultra-short echo time (microsecond range), which matches the short signal lifetime of bone (T2 ~0.4 msec at 3 T). This parameter change enables the MRI system to capture bone signals before they decay, simultaneously improving acquisition speed and bone signal detection accuracy.
2Measurement precision
If long T2 suppression methods like echo subtraction and saturation pre-pulses are applied to selectively depict bone, then bone segmentation is achieved, but the methods are slow and suffer from robustness and accuracy issues
Solution Approach 1:
The patent extracts only the necessary information (bone signal) by using ultra-short echo time imaging combined with proton density weighting. This approach directly captures bone signals without requiring additional suppression pulses or echo subtraction operations, thereby achieving accurate bone segmentation while maintaining high imaging speed.
3Measurement precision
If atlas-based methods with anatomical prior knowledge are used, then bone depiction is improved, but the methods are less flexible in handling patient abnormalities due to pathologies
Solution Approach 1:
The patent employs proton density-weighted ultra-short echo time imaging that inherently provides high contrast between bone and surrounding tissues. This self-contrasting mechanism eliminates the need for atlas-based anatomical priors, enabling accurate bone depiction while maintaining full adaptability to patient-specific abnormalities and pathologies.
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 provides robust, efficient, and accurate bone segmentation, improving the depiction of cortical bone tissue and reducing motion artifacts, while maintaining high signal-to-noise ratio efficiency, suitable for applications like MR-based PET attenuation correction and radiation therapy planning.
Implementation Method 1
Conventional Magnetic Resonance Imaging (MR or MRI) is intrinsically less suited for the depiction and segmentation of cortical bone structures
Implementation Method 2
Because of low proton density (−20% of water) and short signal lifetimes (T2 ̃0.4 msec at 3 T), there are challenges to apply MRI techniques for depiction of solid bone structures
Implementation Method 3
Conventional gradient echo, or spin echo pulse sequences with echo times (TE) in the millisecond-range are too slow for meaningful bone signal detection. Ultra-short echo time (UTE) pulse sequences with center-out k-space sampling starting immediately following the RF excitation enable fast enough MR data acquisition to capture the rapidly decaying bone signals
Implementation Method 4
PD-weighted, short TE imaging can be implemented in the form of a RUFIS-type (Rotating Ultra-fast Imaging Sequence) ZTE pulse sequence and optimized for efficient capture of both short T2 bone signals, and flat PD contrast for soft tissues. A logarithmic image scaling can be used to highlight bone and differentiate it from surrounding soft-tissue and air
Implementation Method 5
Furthermore, a bias correction method is applied as a pre-processing step for subsequent threshold-based 3-class (air, soft-tissue, bone) segmentation
Data Source
AI summary
Systems and methods of classifying component tissues of magnetic resonance images, where the method includes performing a proton density weighted, short echo-time magnetic resonance imaging measurement over a first volume field-of-view region of interest (ROI), repeating a series refining the first volume field-of-view ROI into a plurality of subsequent smaller ROI volumes having respective smaller resolutions, reconstructing a complex image from the plurality of magnetic resonance imaging measurements, performing a bias correction on at least one of the plurality of subsequent smaller ROI volumes, and classifying the ROI volumes by tissue type based on the bias-corrected image signal, wherein at least one tissue type is bone. A non-transitory medium containing processor instructions and a system are disclosed.