Total Small Bowel Length Measurement Using Computed Tomography and Magnetic Resonance Imaging in Obese Patients (SBOM-AI)

September 26, 2023 updated by: Niccolo Petrucciani, University of Roma La Sapienza

Set up and Validation of Total Small Bowel Length Measurement Using Computed Tomography and Magnetic Resonance Imaging With 3D Reconstruction and Artificial Intelligence Tool in Obese Patients Candidates to Metabolic Surgery

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

The total length of the small intestine (TSBL) represents a crucial parameter for obtaining a safe and successful minimally invasive surgery in metabolic/bariatric bypass surgery.

Nowadays, the standard of small intestine measurement is the intraoperative measurement. Laparoscopy represents the standard approach for baratric/metabolic, making the TSBL measurement time-consuming and risky in case of intestinal lesions. An accurate and effective non-invasive preoperative measurement of the TSBL will allow to evaluate the variability of the TSBL, which affects the surgical strategy. Cross-sectional imaging could play an important role in this setting thanks to the possibility of measuring in a non-invasive way the TSBL. Some studies performed with both Computed Tomography (CT) and Magnetic Resonance (MR) report promising results. However, they are limited by the small size of the sample, the lack of standardized technique and the lack of an automatic method based on Artificial Intelligence (AI).

The evaluation of a reliable preoperative method to measure TSBL using cross-sectional imaging will potentially reduce intraoperative complications and insufficient long-term weight loss or nutritional deficiencies. In this scenario a possible solution could be the implementation of analysis method through the development of an AI algorithm capable of automatically segmenting the small intestine.

The PRIMARY END POINT of this study is to set up and validate a reliable and reproductible automatic method to measure the TSBL in patients candidates for laparoscopic bariatric/metabolic surgery, based on preoperative radiological imaging

The main phases of the project will be:

  1. evaluate the feasibility of preoperative CT and MRI-base measurement of the TSBL in a large cohort of obese patients and compare radiological measurement with intraoperative laparoscopic measurement (method of elongation) as a reference standard (1).
  2. Evaluate the more accurate cross-sectional imaging between CT and MRI to measure the length of the small intestine.
  3. Build an AI tool that can automatically measure TSBL on transversal slice imaging.

Three high-volume Italian centers will enroll 195 obese patients who are candidates for metabolic surgery for obesity. Part of them will be established 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.

Study Type

Interventional

Enrollment (Estimated)

195

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • 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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Artificial intelligence training cohort and validation cohort
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
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Concordance between AI-based total small bowel length measure and laparoscopic total small bowel length measure
Time Frame: 1 month
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Roma La Sapienza

Collaborators

Federico II University
University of Padova

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 1, 2023

Primary Completion (Estimated)

November 1, 2025

Study Completion (Estimated)

February 1, 2026

Study Registration Dates

First Submitted

September 13, 2023

First Submitted That Met QC Criteria

September 26, 2023

First Posted (Actual)

October 4, 2023

Study Record Updates

Last Update Posted (Actual)

October 4, 2023

Last Update Submitted That Met QC Criteria

September 26, 2023

Last Verified

September 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • C.88

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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