Accurate AI-based Characterisation of Surface Size, Depth and Tissue Composition in Hard-to-Heal Wounds

NCT ID: NCT07211295

Last Updated: 2025-10-07

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 25 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2025-07-01
• Study Completion Date: 2025-09-18

Brief Summary

This study aims to determine and evaluate the clinical accuracy, precision, and safety of SeeWound 2, an AI-driven wound assessment application, designed for the measurement of wound surface area (cm²), wound depth (mm), and the estimation of the proportion of fibrin covering (slough) and necrosis (%) in real-world clinical settings for patients with hard-to-heal wounds. The study also seeks to validate the non-invasive method for measuring wound depth, as current standard care involves invasive probing of the wound to estimate depth - a practice that this investigational device is intended to replace with a digital, contact-free measurement approach.

Detailed Description

SeeWound 2 is a software-based medical device that utilises artificial intelligence to classify and quantify wound tissue types, specifically fibrin covering (slough) and necrosis, as well as to measure wound surface area and depth through digital image analysis. The system operates as a mobile camera-based application, whereby healthcare professionals capture an image of a hard-to-heal wound. The software then automatically analyses the image using integrated AI models in combination with the LiDAR sensor technology embedded in the mobile camera hardware. The product's capability to automatically measure wound surface area, estimate wound depth in a non-invasive manner, and objectively quantify the proportion of slough and necrosis within the wound bed represents a novel functionality not currently available in clinical practice.

Conditions

Difficult to Heal Wounds

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Cohort

cohort

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

Older than 18 years, men and women Difficult to heal wounds due to diabetes, VLU; Pressure wounds wound larger than 0.5 cm2

Exclusion Criteria

Use of SeeWound 2 is not intended for, or is contraindicated in, the following situations:

Patients under 18 years of age. Wounds located in anatomical regions where the full wound surface and depth cannot be captured (e.g. deep fistulas, tunnels, or undermined areas not accessible through surface imaging).

Wounds with excessive exudation or infection that prevents adequate visual assessment.

Patients who are unable or unwilling to provide informed consent. Patients with a known allergy or adverse reaction to any component used in the image acquisition process (where applicable).

Wounds with specific identifiable attributes (e.g. on the face, or containing birthmarks or tattoos) where ethical considerations regarding data handling apply.

• Minimum Eligible Age: 19 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University Hospital, Linkoeping

OTHER

Sponsor Role: lead

Responsible Party

Folke Sjoberg

Prof

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

BRIVA, Intensive Care for Burns,

Linköping, Östergötland County, Sweden

Countries

Sweden

Other Identifiers

CIP-MDR-SWD001-V1.0-2025, ver,

Identifier Type: -

Identifier Source: org_study_id