Application of deep learning techniques for breath-hold, high-precision T2-weighted magnetic resonance imaging of the abdomen.

Purpose: To evaluate the feasibility of a high-precision single-shot fast spin-echo (SS-FSE) sequence using the deep learning-based Precise IQ Engine (PIQE) algorithm in comparison with standard SS-FSE for T2-weighted MR imaging of the abdomen, and to compare the image quality with a multi-shot (MS)-FSE sequence using the PIQE algorithm.

Methods: This retrospective study included 105 patients who underwent abdominal MR including T2-weighted sequences using the PIQE reconstruction algorithm. The image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in high-precision SS-FSE sequences using PIQE were compared to those in standard SS-FSE without PIQE and MS-FSE sequences using PIQE.

Three-Dimensional (3D) Breath-Hold Zoomed MR Cholangiopancreatography (MRCP): Evaluation of Additive Value to Conventional 3D Navigator Triggering MRCP in Patients With Branch Duct Intraductal Papillary Mucinous Neoplasms.

Background: To resolve drawbacks of navigator triggering (NT) three-dimensional (3D) magnetic resonance cholangiopancreatography (MRCP), several approaches were proposed to obtain 3D MRCP within a single breath-hold (BH). However, reduced field-of-view technique in the phase-encoding direction combined with two-dimensional spatially selective radiofrequency excitation pulses has not yet been applied to 3D BH MRCP.

Purpose: To investigate the feasibility and the complementary value of 3D BH zoomed MRCP to conventional 3D NT MRCP in patients with branch duct intraductal papillary mucinous neoplasms (BD-IPMNs) of the pancreas.