Can Thermal Imaging Technique be Used to Predict the Healing Status of a Venous Leg Ulcer?

Author:

Ogrin Rajna123ORCID,Motin Mohammod A.2ORCID,Aliahmad Behzad2,Elder Kylie1,Anderson Jacinta1,Kumar Dinesh2

Affiliation:

1. Bolton Clarke, Victoria, Australia

2. Royal Melbourne Institute of Technology University, Melbourne, Victoria, Australia

3. Griffith University, Brisbane, Queensland, Australia

Abstract

Venous leg ulcers (VLUs) are the most common chronic wound types in older populations, with many wounds not healing in the normal trajectory. Many older people with wounds are treated in their homes, currently assessed by monitoring the wound area over weeks to ascertain the potential for healing. A noncontact method using thermal imaging has been shown to predict the healing trajectory of diabetes-related foot ulcers, although has not been tested in VLU or the home setting. This project investigated the effectiveness of using thermal imaging to predict VLU healing in the homes of participants. Images of 78 ulcers were collected weekly using a thermal camera from 67 participants in their homes, at 5 consecutive time points. Final follow-up calls were undertaken at 12 weeks to ascertain healing status (healed/unhealed). Images were preprocessed and segmented and the area of the region of the wound was extracted. Kruskal–Wallis tests were performed to test the association of the change of areas over the 5 consecutive weeks with the healing status of the ulcers at 12 weeks. The 95% confidence interval plots were obtained to study the distribution of the area in the healed and unhealed cases. This study found that the difference in the imaged areas between unhealed ulcers at 12 weeks did not reach statistical significance using thermal imaging. Therefore, thermal images could not predict healing progression in VLUs when the images were taken in the homes of participants. Future research to improve the prediction of venous leg ulcer healing should include developing a protocol to standardize conditions, improve imaging process methods, and use machine learning.

Publisher

SAGE Publications

Subject

General Medicine,Surgery

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