Total Small Bowel Length Measurement Using Computed Tomography and Magnetic Resonance Imaging in Obese Patients

NCT06065917 | Recruiting

• 1 other identifier: C.88
• Study Type: interventional
• Target: 195
• Locations: 1 country
• Sites: 1

Brief Summary

The aim of the study is to set up and validate a reliable and reproducible automated method using preoperative radiological imaging to measure the TSBL in patients undergoing laparoscopic bariatric/metabolic surgery.

Conditions

Obesity; Bariatric Surgery Candidate

Keywords

obesity; artificial intelligence; computed tomography; bariatric surgery; small bowel lenght; metabolic surgery; magnetic resonance

Outcome Measures

Primary Outcomes (1)

• Concordance between AI-based total small bowel length measure and laparoscopic total small bowel length measure

  the main outcome is to set up and validate a reliable and reproducible automated method using preoperative radiological imaging to measure the TSBL in patients candidates for laparoscopic bariatric/metabolic surgery. The results of AI measurement will be compared with those of laparoscopic measurement to examine the level of concordance

  1 month

Study Arms (1)

Artificial intelligence training cohort and validation cohort

EXPERIMENTAL

Three high-volume Italian centers will enroll 195 obese patients who are candidates for metabolic surgery for obesity. Part of them will be established a training cohort (total = 105 patients), used to set up the AI-based method of TSBL measurement. The other 90 patients (30 for each center) will represent the validation cohort.

Diagnostic Test: Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool

Interventions

Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool DIAGNOSTIC_TEST

The intervention consists in performing CT and MR imaging with small bowel length measurement before bariatric/metabolic surgery in obese patients. Then, during surgery the patients will undergo laparoscopic stretched small bowel measurement as the reference gold standard method to measure the small bowel length. The imaging of the training cohort will be used to trained an AI to set up an automatic method of small bowel length measurement via the analysis of CT and MRI imaging.

Artificial intelligence training cohort and validation cohort

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• BMI \> 35 kg/m2 and at least one obesity-related comorbidity
• BMI \> 40 kg/m2
• failure of at least six months of dietary and/or medical treatment of obesity
• indication for intervention validated after multidisciplinary evaluation in a specific board meeting

Sponsors & Collaborators

• University of Roma La Sapienza: lead
• University of Padova: collaborator
• Federico II University: collaborator

Study Sites (1)

Azienda Ospedaliera Universitaria Sant'Andrea

Rome, RM, 00189, Italy

RECRUITING

MeSH Terms

Conditions

Obesity

Interventions

Magnetic Resonance Imaging

Condition Hierarchy (Ancestors)

Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Tomography; Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis

Central Study Contacts

Niccolò Petrucciani, MD

CONTACT

3496311476; niccolo.petrucciani@uniroma1.it

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD, PhD, Associate Professor of Surgery

Study Record Dates

• First Submitted: September 13, 2023
• First Posted: October 4, 2023
• Study Start: January 2, 2024
• Primary Completion: November 1, 2025
• Study Completion: February 1, 2026
• Last Updated: May 10, 2024

Record last verified: 2024-05

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)