A dynamic approach for MR T2-weighted pelvic imaging

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T2-weighted 2D fast spin echo sequence serves as the standard sequence in
clinical pelvic MR imaging protocols. However, motion artifacts and blurring caused
by peristalsis present significant challenges. Patient preparation such as administering
antiperistaltic agents is often required before examination to reduce artifacts, which
discomfort the patients. This work introduce a novel dynamic approach for T2
weighted pelvic imaging to address peristalsis-induced motion issue without any patient
preparation.
Approach: A rapid dynamic data acquisition strategy with complementary sampling
trajectory is designed to enable highly undersampled motion-resistant data sampling,
and an unrolling method based on deep equilibrium model is leveraged to reconstruct
images from the dynamic sampled k-space data. Moreover, the fix-point convergence of
the equilibrium model ensures the stability of the reconstruction. The high acceleration
factor in each temporal phase, which is much higher than that in traditional static
imaging, has the potential to effectively freeze pelvic motion, thereby transforming
the imaging problem from conventional motion prevention or removal to motion
reconstruction.
Main results: Experiments on both retrospective and prospective data have
demonstrated the superior performance of the proposed dynamic approach in reducing
motion artifacts and accurately depicting structural details compared to standard static
imaging.
Significance: The proposed dynamic approach effectively captures motion states
through dynamic data acquisition and deep learning-based reconstruction, addressing
motion-related challenges in pelvic imaging.