Digital 3D Reconstruction Predicts Small Bowel Length

NCT ID: NCT05338567

Last Updated: 2022-07-20

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-10-02

Study Completion Date

2023-10-02

Brief Summary

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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.

Detailed Description

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Conditions

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Small Intestine Length Measurement

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Open/laparoscopic surgery

Small bowel length measurement by laparoscopy or laparotomy

No interventions assigned to this group

3D reconstruction

Small bowel length measurement by 3D digital model

Small intestine length measurement method

Intervention Type DIAGNOSTIC_TEST

Accuracy of digital 3D reconstruction for predicting small bowel length

Interventions

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Small intestine length measurement method

Accuracy of digital 3D reconstruction for predicting small bowel length

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Patients eligible for surgical treatment of T2DM were selected based on the Chinese Guidelines for the Surgical Treatment of Obesity and Type 2 Diabetes (2019 )

Exclusion Criteria

* Adhesions, peritonitis, and patients who have had bowel resection (small intestine, colon or rectum) that hinder the measurement of the entire intestinal length
* Non-weight loss surgery patients whose incision is less than 6 cm are not suitable for measuring the length of the small intestine.
Minimum Eligible Age

16 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Daping Hospital and the Research Institute of Surgery of the Third Military Medical University

OTHER

Sponsor Role lead

Responsible Party

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fan li

DapingH

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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fan Li, PhD

Role: STUDY_DIRECTOR

Army medical universtiy daping hospital

Locations

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Daping hospital

Chongqing, , China

Site Status RECRUITING

Countries

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China

Central Contacts

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fan Li, PhD

Role: CONTACT

Facility Contacts

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fan Li, PhD

Role: primary

Other Identifiers

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3DRABL-BS

Identifier Type: -

Identifier Source: org_study_id

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