Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-25 @ 12:53 AM
Ignite Modification Date:
2025-12-25 @ 12:53 AM
NCT ID:
NCT05338567
Brief Summary:
The prevalence of type 2 diabetes mellitus (T2DM) has been increasing annually worldwide, and the prevalence of diabetes has reached 11.6% in China. Laparoscopic Roux-en-Y gastric bypass (RYGB) is still widely accepted as a valid surgery in the treatment of obesity and T2DM. But still, there is no consensus on the ideal of the gastric bypass limb lengths. Reported lengths of biliopancreatic limb (BPL) and alimentary limb (AL) varied widely from 10-250 to 35-250 cm, and anatomical data show that the length of small intestine varies greatly among adults. Choosing the same small bowel bypass length for different individuals obviously cannot achieve the expected weight loss effect, and individuals with too short small intestine can cause severe malnutrition complications and even life-threatening conditions. Therefore, measurement of small bowel length is one of the prerequisites for performing precise RYGB. Intraoperative measurement of small bowel length can increase the operative time and the risk of surgical complications such as intestinal perforation. So, predicting the total length of the small intestine is very important for accurately performing bariatric surgery and avoiding the risk of surgical complications. In this study, we propose to perform 3D segmentation and reconstruction of the small intestine by acquiring abdominal CT data through digital technology, and predict the small intestine length by 3D digital measurement of the small intestine, and verify the digital measurement data by performing digital measurement data. Establish a small bowel length prediction model for bariatric surgery to develop a more accurate and personalized gastric bypass surgery plan for patients to obtain weight loss and glucose control.
Study:
NCT05338567
Study Brief:
Protocol Section:
NCT05338567