Histological Segmentation of the Superficial Femoral Artery From Microscan to CT Using Artificial Intelligence

NCT06260488 | Recruiting

• 1 other identifier: 8925
• Study Type: interventional
• Target: 20
• Locations: 1 country
• Sites: 1

Brief Summary

The femoropopliteal artery segment (FPAS) is one of the longest arteries in the human body, undergoing torsion, compression, flexion and extension due to lower limb movements. Endovascular surgery is considered to be the treatment of choice for the peripheral arterial disease, the results of which depend on the physiological forces on the arterial wall, the anatomy of the vessels and the characteristics of the lesions being treated. The atheromatous disease includes, in a simple way, 3 categories of plaques: calcified, fibrous, and lipidic. The study of these plaques and their differentiation in imaging and histology in the FPAS has already been the subject of research. To treat them, there are angioplasty balloons and stents with different designs and components, with different mechanical properties and different impregnated molecules. There is no non-invasive method (imaging) to accurately differentiate lesions along the FPAS. The analysis is performed from the preoperative CT scan, but there are high-resolution scanners that allow a quasi-histological analysis of the tissue. This microscanner can be used ex vivo. In the framework of a project, the learning algorithm was be créated (Convolutional Neural Networks) to automatically segment microscanner slices: after taking FPAS from amputated limbs, we correlated ex-vivo microscanner images of the arteries with their histology. The correlation was then performed manually between the microscanner images, and the histological sections obtained. the algorithm well be trained on these slices and validated its performance. The validation of the CT and microscanner concordance was the subject of scientific publications.

Conditions

Peripheral Artery Disease; Femoropopliteal Stenosis

Outcome Measures

Primary Outcomes (1)

• Assessing the feasibility of histological segmentation of the superficial femoral artery on preoperative microscanner using artificial intelligence

  Rate of slices (in %) for which segmentation is considered sufficient. The quality of segmentation will be assessed by the clinician using a Likert scale. Segmentation is considered sufficient if the scale is ≥ 3 and insufficient if it is \< 3

  1 hour

Study Arms (1)

transfemoral amputation

OTHER

Subject with a planned transfemoral amputation in the vascular surgery department of the Hôpitaux Universitaires de Strasbourg as standard care

Procedure: Endovascular surgery

Interventions

Endovascular surgery PROCEDURE

routine endovascular surgery and FPAS harvesting from amputated limbs to evaluate the technical feasibility of histological segmentation by the FPAS algorithm from CT

transfemoral amputation

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Male or female of legal age
• Subject with a planned transfemoral amputation in the vascular surgery department of the Hôpitaux Universitaires de Strasbourg as standard care
• Subject with a CT as part of standard care
• Subject who has given his/her non-opposition to participate in the study

You may not qualify if:

• \- Impossible to give the subject informed information (subject in emergency situation, difficulties in understanding)

Sponsors & Collaborators

• University Hospital, Strasbourg, France: lead

Study Sites (1)

Hôpitaux Universitaire de Strasbourg

Strasbourg, Bas-Rhin, 67 091, France

RECRUITING

MeSH Terms

Conditions

Peripheral Arterial Disease

Condition Hierarchy (Ancestors)

Atherosclerosis; Arteriosclerosis; Arterial Occlusive Diseases; Vascular Diseases; Cardiovascular Diseases; Peripheral Vascular Diseases

Central Study Contacts

Salomé KUNTZ, Doctor

CONTACT

+31 3 69 55 01 98; salome.kuntz@chru-strasbourg.fr

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 19, 2023
• First Posted: February 15, 2024
• Study Start: March 15, 2024
• Primary Completion: June 15, 2025
• Study Completion: August 15, 2025
• Last Updated: April 25, 2025

Record last verified: 2025-04

Locations

FR (1)