ObesitySBOM-AINCT06065917
Total Small Bowel Length Measurement Using Computed Tomography and Magnetic Resonance Imaging in Obese Patients
A study testing Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool in people with Obesity and Bariatric Surgery Candidate, run by University of Roma La Sapienza at 1 site in Italy.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Obesity, Bariatric Surgery Candidate
- What is being tested?
- Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 195 participants
- Where
- 1 siteItaly
- Study dates
- 2 Jan 2024to Feb 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
Italy1 site, 1 recruiting
- Recruiting
Azienda Ospedaliera Universitaria Sant'Andrea
Rome, RM, 00189
Niccolo Petrucciani, MD, 00390633775634, niccolo.petrucciani@uniroma1.it
About this study
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
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.
Read the 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:
- 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).
- Evaluate the more accurate cross-sectional imaging between CT and MRI to measure the length of the small intestine.
- 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.
- Conditions
- Obesity, Bariatric Surgery Candidate
- Being tested
- Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool
- Keywords
- obesity, artificial intelligence, computed tomography, bariatric surgery, small bowel lenght, metabolic surgery, magnetic resonance
- Medical subject headings
- Obesity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI toolDiagnostic 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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Diagnostic Test: Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Oct 2023
- Study start2 Jan 2024
- Primary completionNov 2025 (estimated)
- Study completionFeb 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for ObesityStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 195 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Roma La Sapienza
- Sponsor type
- University, hospital or other
- Collaborators
- University of Padova, Federico II University
- Responsible party
- Principal investigator, Niccolo Petrucciani, University of Roma La Sapienza
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06065917
- Sponsor's protocol ID
- C.88
- Acronym
- SBOM-AI
- Status last verified
- May 2024
- First submitted
- 13 Sep 2023
- Last updated
- 10 May 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 10 May 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT06065917
- Acronym / sponsor ID
- SBOM-AI / C.88
- Conditions
- Obesity, Bariatric Surgery Candidate
- Keywords
- obesity, artificial intelligence, computed tomography, bariatric surgery, small bowel lenght, metabolic surgery, magnetic resonance
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 195 participants (estimated)
- Lead sponsor
- University of Roma La SapienzaUniversity, hospital or other
- Collaborators
- University of Padova, Federico II University
- Study start
- 2 Jan 2024 (actual)
- Primary completion
- Nov 2025 (estimated)
- Study completion
- Feb 2026 (estimated)
- First posted
- 4 Oct 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- 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).
- Evaluate the more accurate cross-sectional imaging between CT and MRI to measure the length of the small intestine.
- 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 design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Artificial intelligence training cohort and validation cohort | Experimental | Diagnostic Test: Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI toolThree 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. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (0 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI toolThe 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. | Diagnostic test | Artificial intelligence training cohort and validation cohort |
Primary outcome
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
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 May 2024.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Measurement of the total small bowel length using CT scan and MRI with 3D reconstruction and AI tool in people with Obesity and Bariatric Surgery Candidate, run by University of Roma La Sapienza at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 0 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 10 May 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Niccolò Petrucciani, MD (3496311476, niccolo.petrucciani@uniroma1.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Concordance between AI-based total small bowel length measure and laparoscopic total small bowel length measure (time frame: 1 month). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 May 2024.