APIR4EMC: Autocalibrated parallel imaging reconstruction for extended multi-contrast imaging.

Area of Science:

• Magnetic Resonance Imaging
• Medical Imaging Reconstruction

Background:

• Accelerated multi-contrast MRI is crucial for efficient clinical workflows.
• Existing reconstruction methods can introduce artifacts and noise, particularly at high acceleration factors.

Purpose of the Study:

• To introduce and evaluate Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC).
• To improve image quality in accelerated multi-contrast MRI by treating contrasts as virtual coils.

Main Methods:

• APIR4EMC reconstructs multi-contrast images within an autocalibrated parallel imaging framework.
• Signal evolution compensation was applied to enhance prediction of missing k-space samples.
• Joint reconstruction and optimized k-space sampling were performed for T1, T1-Fatsat, T2, PD, and FLAIR contrasts.

Main Results:

• APIR4EMC demonstrated reduced artifacts and improved signal-to-noise ratio (SNR) compared to GRAPPA in phantom studies.
• Quantitative analysis showed substantial reduction in noise amplification (g-factor) and root mean square error (RMSE) with APIR4EMC.
• In vivo experiments achieved 1 mm³ isotropic 3D images across multiple contrasts in 7.5 minutes with an acceleration factor of 9.

Conclusions:

• APIR4EMC significantly reduces artifacts and noise amplification in accelerated multi-contrast MRI.
• The proposed method outperforms conventional single-contrast reconstruction techniques like GRAPPA.