Locally developed digital image archive for diabetic foot clinic: a DGH experience

Clinical validation of a machine-learning-based handheld 3-dimensional infrared wound imaging device in venous leg ulcers

Chronic venous insufficiency is a chronic disease of the venous system with a prevalence of 25% to 40% in females and 10% to 20% in males. Venous leg ulcers (VLUs) result from venous insufficiency. VLUs have a prevalence of 0.18% to 1% with a 1‐year recurrence of 25% to 50%, bearing significant socioeconomic burden. It is therefore important for regular assessment and monitoring of VLUs to prevent worsening. Our study aims to assess the intra‐ and inter‐rater reliability of a machine learning‐based handheld 3‐dimensional infrared wound imaging device (WoundAide [WA] imaging system, Konica Minolta Inc, Tokyo, Japan) compared with traditional measurements by trained wound nurse. This is a prospective cross‐sectional study on 52 patients with VLUs from September 2019 to January 2021 using three WA imaging systems. Baseline patient profile and clinical demographics were collected. Basic wound parameters (length, width and area) were collected for both traditional measurements and measurements taken by the WA imaging systems. Intra‐ and inter‐rater reliability was analysed using intra‐class correlation statistics. A total of 222 wound images from 52 patients were assessed. There is excellent intra‐rater reliability of the WA imaging system on three different image captures of the same wound (intra‐rater reliability ranging 0.978‐0.992). In addition, there is excellent inter‐rater reliability between the three WA imaging systems for length (0.987), width (0.990) and area (0.995). Good inter‐rater reliability for length and width (range 0.875‐0.900) and excellent inter‐rater reliability (range 0.932‐0.950) were obtained between wound nurse measurement and each of the WA imaging system. In conclusion, high intra‐ and inter‐rater reliability was obtained for the WA imaging systems. We also obtained high inter‐rater reliability of WA measurements against traditional wound measurement. The WA imaging system is a useful clinical adjunct in the monitoring of VLU wound documentation.

Wound assessment, imaging and monitoring systems in diabetic foot ulcers: A systematic review

Patients with diabetes mellitus have a lifetime risk of 15% to 25% of developing diabetic foot ulcers (DFUs). DFU is associated with significant morbidity and mortality. Wound imaging systems are useful adjuncts in monitoring of wound progress. Our study aims to review existing literature on the available wound assessment and monitoring systems for DFU. This is a systematic review of articles from PubMed and Embase (1974 - March 2020). All studies related to wound assessment or monitoring systems in DFUs were included. Articles on other types of wounds, review articles, and non-English texts were excluded. Outcomes include clinical use, wound measurement statistics, hospital system integration, and other advantages and challenges. The search identified 531 articles. Seventeen full-text studies were eligible for the final analysis. Five modalities were identified: (a) computer applications or hand-held devices (n = 5), (b) mobile applications (n = 2), (c) optical imaging (n = 2), (d) spectroscopy or hyperspectral imaging (n = 4), and (e) artificial intelligence (n = 4). Most studies (n = 16) reported on wound assessment or monitoring. Only one study reported on data capturing. Two studies on the use of computer applications reported low inter-observer variability in wound measurement (inter-rater reliability >0.99, and inter-observer variability 15.9% respectively). Hand-held commercial devices demonstrated high accuracy (relative error of 2.1%-6.8%). Use of spectroscopy or hyperspectral imaging in prediction of wound healing has a sensitivity and specificity of 80% to 90% and 74%to 86%, respectively. Majority of the commercially available wound assessment systems have not been reviewed in the literature on measurement accuracy. In conclusion, most imaging systems are superior to traditional wound assessment. Wound imaging systems should be used as adjuncts in DFU monitoring.