A novel method using textural analysis of thermal images to predict the healing status of diabetic-related foot ulcers

Not Applicable

Recruiting

• Conditions: diabetic related foot ulcer; Metabolic and Endocrine - Diabetes

• Registration Number: ACTRN12623001050640
• Lead Sponsor: niversity of Melbourne

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Study Start: 2023-09-28
• Last Update Posted: 9 September 2024

Recruitment & Eligibility

• Status: Recruiting
• Sex: All
• Target Recruitment: 120

Inclusion Criteria

Phase 1: Clinicians who are working with people who have diabetic foot ulcers;
Phases 1 and 2: Adults diagnosed with diabetes;
Presence of a neuropathic foot ulcer;
Phases 1 and 2: Ability to provide consent;
Phases 1 and 2: Are available to participate over the study period.

Exclusion Criteria

Phases 1 and 2: Unable to provide informed consent;
Phase 2: Pregnancy;
Phase 2: Presence of infection/Osteomyelitis;
Phase 2: Severe cases of peripheral arterial disease (PAD) (toe pressure below 60 mmHg)

Study & Design

• Study Type: Interventional
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Accuracy of a machine learning (AI) model using thermal images to predict delayed healing at 12 weeks. The texture of the thermal image of the wound will be analysed. The ground truth is that the wound is considered healed if at week 12, the ulcer has completely closed while it is considered unhealed if the ulcer has not completely closed.[ Baseline (enrolment of participant) data collection<br>1 week post base-line<br>2 weeks post base-line<br>12 weeks post base-line]