Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Medical Imaging Physics
• Biomedical Engineering

Background:

• Quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging offers potential for detailed musculoskeletal tissue characterization.
• Accelerating MRI acquisition is crucial for clinical feasibility, reducing patient discomfort and motion artifacts.
• Compressed sensing (CS) reconstruction techniques show promise in reconstructing high-quality images from undersampled data.

Purpose of the Study:

• To investigate the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging using compressed sensing (CS) reconstruction.
• To evaluate the performance of CS reconstruction in reducing artifacts and maintaining image quality for various qUTE-Cones sequences.
• To assess the accuracy and reliability of quantitative MRI parameters derived from accelerated qUTE-Cones imaging.

Main Methods:

• Implementation of qUTE-Cones sequences for T1 mapping, T1ρ mapping, and quantitative magnetization transfer (MT) on a 3T MR system.
• Retrospective undersampling of k-space data from 20 healthy volunteers undergoing whole-knee MRI.
• Reconstruction of undersampled data using both zero-filling and CS methods, followed by quantitative parameter estimation in defined regions of interest (ROIs).

Main Results:

• CS reconstruction dramatically reduced streaking artifacts and improved Structural Similarity Index (SSIM) compared to zero-filling, achieving a mean SSIM of ~0.90.
• Percentage errors for quantitative parameters remained below 5% even with 50% undersampling (2x acceleration).
• High linear correlation (>0.95) was observed for all estimated qUTE parameters across all subjects, indicating robust quantitative accuracy.

Conclusions:

• Compressed sensing-based reconstruction combined with efficient Cones trajectory enables clinically feasible scan times for qUTE imaging.
• Accelerated qUTE-Cones imaging with CS provides high-quality, quantitative data for musculoskeletal MRI.
• This approach holds significant promise for efficient and accurate assessment of knee joint tissues.