Patient-specific biomechanical modeling of incisional hernias with AI and finite element analysis

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This is a retrospective, single-center, non-interventional study using existing CT scans from adults who had abdominal surgery. The team will build patient-specific biomechanical models of the abdominal wall by applying artificial intelligence to identify morphologic features and by incorporating finite element analysis with prior tissue mechanics data. The goal is to tailor a numerical model to each patient’s anatomy and hernia characteristics, based on imaging and clinical information. No active treatment or intervention is performed within the study. Data are anonymized and will be analyzed to explore relationships between hernia morphology and mechanical behavior.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Adults aged 18 years or older.
* Patients who underwent surgery at the University Hospital of Strasbourg between January 1, 2018, and September 1, 2026.
* Midline, lateral, or parastomal incisional hernia.
* Prosthetic reinforcement may or may not have been used.

Exclusion Criteria:

* Written objection documented in the patient's medical record to the reuse of their data for scientific research.
* Legal protection measure.
* Minor patients.
* Pregnancy.

Where it's running

• Service de cchirurgie générale & digestive - CHU de Strasbourg, France
  Strasbourg, France Recruiting

Study contacts

• Study coordinator: Benoit Romain, MD, PhD
• Email: benoit.romain@chru-strasbourg.fr
• Phone: 33 3.88.12.72.43

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.