Diagnostic Value of Deep Learning-Based Rapid MRI in Preoperative Evaluation of Acute Cholecystitis
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Acute Cholecystitis. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Fast Abdominopelvic MRI With Deep Learning-Based Reconstruction Algorithm: Image Quality Evaluation and Application in Patients With Common Abdominal and Pelvic Diseases
Overview
This is a single-center, prospective observational study at Peking Union Medical College Hospital. The main goal is to evaluate the image quality and clinical value of a new fast abdominopelvic MRI sequence that uses deep learning-based reconstruction. The study will include adult patients (18 years or older) who need an MRI scan of the abdomen or pelvis as part of their routine care. These patients will receive both the standard MRI sequence and the new fast sequence, with the goal of comparing the two. The fast sequence is designed to be shorter (5-8 minutes) while maintaining or improving image quality, which can help reduce patient discomfort and motion-related artifacts. Radiologists will assess the quality of the images from both sequences. The study will also look at how well the fast sequence can detect common abdominal and pelvic diseases, such as gallstones, inflammation, and tumors. This study does not involve new drugs, invasive procedures, or changes to standard care. No additional risks to patients are expected beyond those of a standard MRI scan.
Primary outcome measures
- Image Quality Score of Fast Abdominopelvic MRI With Deep Learning Reconstruction [Time frame: Immediately after MRI scan completion]
Eligibility criteria
Inclusion criteria
- Age ≥ 18 years
- Clinical indication for abdominopelvic MRI examination
- Able to understand and sign the informed consent form
- Able to lie supine and cooperate with breath-holding/respiratory commands during MRI
Exclusion criteria
- Presence of absolute contraindications to MRI (e.g., pacemaker, ferromagnetic foreign body, severe claustrophobia)
- Inability to complete the MRI scan due to severe pain, instability, or altered mental status
- Pregnant or breastfeeding women (unless explicitly approved by protocol)
- Previous abdominal/pelvic surgery with contraindications to MRI sequences
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Peking Union Medical College Hospital — Beijing
Publications
- Li T, Zhao Y, Dong L, Han J, Zhao B, Lin C, Wang W. Preoperative Iron Isomaltoside administration enhances postoperative anemia recovery in robotic pancreatic surgery. J Robot Surg. 2026 Feb 7;20(1):227. doi: 10.1007/s11701-026-03176-0. PMID 41653278
Identifiers
NCT: NCT07551375 · I-24PJ1043