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ID07551375

Evaluating a New Fast MRI Using Deep Learning for Abdomen and Pelvis Scans in Adults with Common Diseases

Led by Peking Union Medical College Hospital · Updated on 2026-04-24

300

Participants Needed

1

Research Sites

20 weeks

Total Duration

AI-Summary

What this Trial Is About

Researchers are conducting a single-center, prospective observational study to evaluate a new fast abdominopelvic MRI sequence that uses deep learning-based reconstruction. The study focuses on adult patients aged 18 years or older who require an MRI scan of the abdomen or pelvis as part of their routine care. The goal is to compare the image quality and diagnostic value of this new fast sequence with the standard MRI sequence, particularly for common abdominal and pelvic diseases such as gallstones, inflammation, and tumors. Participants will undergo both the standard MRI and the new fast MRI sequence, which is designed to be shorter, lasting about 5 to 8 minutes, to reduce discomfort and motion artifacts. The fast sequence uses advanced deep learning technology to reconstruct images quickly while aiming to maintain or improve image quality. This study does not involve any new drugs or invasive procedures and does not change the standard care patients receive. During the study, radiologists will assess and compare the image quality from both MRI sequences immediately after the scans. Researchers will also evaluate how well the fast sequence detects common diseases in the abdomen and pelvis. No additional risks beyond those of a standard MRI scan are expected. The study will continue until the end of 2026, with participants only undergoing the MRI scans and standard clinical procedures as part of their involvement.

CONDITIONS

Brief Title

Diagnostic Value of Deep Learning-Based Rapid MRI in Preoperative Evaluation of Acute Cholecystitis

Research Team

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