Cortical Bone MRI via T1 Dixon Workflow
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional MRI sequences cannot reliably detect cortical bone due to fast T2 decay, and existing methods for radiation therapy planning and PET/MR systems lack accurate electron density information, leading to suboptimal imaging and radiation exposure.
Innovation Solution
A T1-weighted Dixon acquisition and reconstruction workflow is used for tissue classification and cortical bone imaging, generating bone-enhanced images and electron density maps, which are then used to create digitally reconstructed radiographs (DRRs) and improve radiation therapy planning by accurately segmenting cortical bone and soft tissues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional MRI sequences are used for imaging, then soft tissue contrast is good, but cortical bone detection is unreliable due to fast T2 decay
Solution Approach 1:
The patent changes the echo time parameter to an ultrashort echo time (TE < 100 μs) to capture the bone signal before fast T2 decay eliminates it. This parameter change allows detection of cortical bone while maintaining soft tissue contrast, resolving the contradiction between reliable bone detection and measurement precision.
2Measurement precision
If CT is used for attenuation correction in PET/CT, then accurate electron density information is obtained, but radiation exposure increases
Solution Approach 1:
The patent uses MRI as an intermediary modality to obtain electron density information for PET attenuation correction instead of using CT. By developing MRI sequences that can detect cortical bone and generate accurate electron density maps, the system provides the necessary precision for PET correction without the harmful radiation exposure of CT.
Solution Approach 2:
The patent replaces the X-ray based CT system with an MRI system for obtaining attenuation correction data. This substitution uses magnetic resonance physics instead of ionizing radiation, eliminating the harmful effects while maintaining the ability to generate accurate electron density information through specialized pulse sequences and post-processing.
3Object-affected harmful factors
If MRI is used for radiation therapy planning, then radiation exposure is reduced, but electron density information accuracy is insufficient
Solution Approach 1:
The patent performs preliminary actions by acquiring multiple MRI images with different pulse sequences (T1-weighted, T2-weighted, proton density) and performing tissue classification before radiation therapy planning. This preliminary tissue segmentation and electron density map generation ensures accurate information is available for treatment planning, compensating for the traditionally insufficient electron density accuracy of MRI.
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 enhances the accuracy of radiation therapy planning and reduces radiation exposure by providing reliable cortical bone segmentation and improved soft tissue contrast, enabling more precise treatment planning and reduced artifacts in imaging.
Implementation Method 1
Conventional MRI sequences cannot reliably detect cortical bone due to fast T2 decay
Implementation Method 2
A T1-weighted Dixon acquisition and reconstruction workflow is used for tissue classification and cortical bone imaging
Data Source
AI summary
A medical apparatus (300, 400, 500) includes a magnetic resonance imaging system (302) for acquiring magnetic resonance data (342) from an imaging zone (308); a processor (330) for controlling the medical apparatus; a memory (336) storing machine executable instructions (350, 352, 354, 356). Execution of the instructions causes the processor to: acquire (100, 200) the magnetic resonance data using a pulse sequence (340) which specifies an echo time greater than 400 μs; reconstruct (102, 202) a magnetic resonance image using the magnetic resonance data; generate (104, 204) a thresholded image (346) by thresholding the magnetic resonance image to emphasize bone structures and suppressing tissue structures in the magnetic resonance image; and generate (106, 206) a bone-enhanced image by applying a background removal algorithm to the thresholded image.


