Clinical trial NCT06065917: Total Small Bowel Length Measurement Using Computed Tomography and Magnetic Resonance Imaging in Obese Patients
Official title: 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
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Obesity
Bariatric Surgery Candidate
Keywords: obesity
artificial intelligence
computed tomography
bariatric surgery
small bowel lenght
metabolic surgery
magnetic resonance
Lead sponsor: University of Roma La Sapienza
Sponsor class: OTHER
Collaborators: name: University of Padova
name: Federico II University
First posted: 2023-10-04
Enrollment: 195
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: DIAGNOSTIC

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.

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.

Eligibility criteria: 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

Primary outcomes:
measure: Concordance between AI-based total small bowel length measure and laparoscopic total small bowel length measure
timeFrame: 1 month
Secondary outcomes:
Other outcomes:
Locations:
city: Rome
country: Italy
facility: Azienda Ospedaliera Universitaria Sant'Andrea
state: RM
Study officials:
References: