Fast T2WI with DLR-Enhanced SSFSE: A Reliable Solution for diagnosing Acute Abdominal Pain in Emergency Settings

Motivation: To determine if SSFSE T2-weighted imaging with deep learning reconstruction (DLR) can provide a reliable and time-efficient diagnostic tool for acute abdominal pain in emergency settings. Goal(s): To compare the image quality and diagnostic performance of SSFSE with DLR, SSFSE alone, and PROPELLER T2WI. Approach: The study included 35 healthy volunteers and 35 patients with acute abdomen from emergency room. Image quality and diagnostic performance were assessed across three T2WI datasets: SSFSE-DLR, SSFSE, and PROPELLER. Each dataset contained coronal fat-suppressed, non-fat-suppressed, and axial non-fat-suppressed images. Results: SSFSE-DLR provided superior image quality and diagnosis performance while significantly reduced acquisition time. Impact: This study highlights the potential of combining deep learning reconstruction with SSFSE T2WI to significantly improve image quality and diagnostic performance compared to conventional T2WI, offering a rapid and reliable diagnostic option for evaluating acute abdominal conditions in emergency settings.