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

Computerised prediction of healing for venous leg ulcers

Early prediction of delayed healing for venous leg ulcers could improve management outcomes by enabling earlier initiation of adjuvant therapies. In this paper, we propose a framework for computerised prediction of healing for venous leg ulcers assessed in home settings using thermal images of the 0 week. Wound data of 56 older participants over 12 weeks were used for the study. Thermal images of the wounds were collected in their homes and labelled as healed or unhealed at the 12th week follow up. Textural information of the thermal images at week 0 was extracted. Thermal images of unhealed wounds had a higher variation of grey tones distribution. We demonstrated that the first three principal components of the textural features from one timepoint can be used as an input to a Bayesian neural network to discriminate between healed and unhealed wounds. Using the optimal Bayesian neural network, the classification results showed 78.57% sensitivity and 60.00% specificity. This non-contact method, incorporating machine learning, can provide a computerised prediction of this delay in the first assessment (week 0) in participants' homes compared to the current method that is able to do this in 3rd week and requires contact digital planimetry.

Thermal imaging potential and limitations to predict healing of venous leg ulcers

Area analysis of thermal images can detect delayed healing in diabetes foot ulcers, but not venous leg ulcers (VLU) assessed in the home environment. This study proposes using textural analysis of thermal images to predict the healing trajectory of venous leg ulcers assessed in home settings. Participants with VLU were followed over twelve weeks. Digital images, thermal images and planimetry of wound tracings of the ulcers of 60 older participants was recorded in their homes by nurses. Participants were labelled as healed or unhealed based on status of the wound at the 12th week follow up. The weekly change in textural features was computed and the first two principal components were obtained. 60 participants (aged 80.53 ± 11.94 years) with 72 wounds (mean area 21.32 ± 51.28cm2) were included in the study. The first PCA of the change in textural features in week 2 with respect to week 0 were statistically significant for differentiating between healed and unhealed cases. Textural analysis of thermal images is an effective method to predict in week 2 which venous leg ulcers will not heal by week 12 among older people whose wounds are being managed in their homes.