A medical thermal imaging device for the prevention of diabetic foot ulceration

Machin, G.; Whittam, Aaron; Ainarkar, S; Allen, John; Bevans, John; Edmonds, Michael; Kluwe, Ben; Macdonald, Andrew; Petrova, Nina L.; Plassmann, P.; Ring, Francis; Rogers, Leon J.; Simpson, Robert L.

doi:10.1088/1361-6579/aa56b1

Cited by 22 publications

(23 citation statements)

References 14 publications

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“…This study did not include healthy controls, yet hotspots of more than 2.2°C have been found in a study of healthy feet ( n = 103) although the majority significantly reduced after ten minutes, indicating the importance of the rest interval prior to measurement. 19 In contrast, Macdonald et al found 32% of those with healthy feet had at least one hotspot even after ten minutes resting with the subjects’ legs supported, 20 many of which were attributed to uncontrolled factors prior to the test such as caffeine intake, increased physical activity, or slower rates of temperature transition between feet. 20 An added problem is that the difference in the severity and extension of peripheral vascular disease may contribute to an asymmetry of temperature.…”

Section: Microclimate Predictionmentioning

confidence: 98%

Prediction of Diabetic Foot Ulceration: The Value of Using Microclimate Sensor Arrays

Jones

Bibb

Davies

et al. 2019

J Diabetes Sci Technol

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Background: Accurately predicting the risk of diabetic foot ulceration (DFU) could dramatically reduce the enormous burden of chronic wound management and amputation. Yet, the current prognostic models are unable to precisely predict DFU events. Typically, efforts have focused on individual factors like temperature, pressure, or shear rather than the overall foot microclimate. Methods: A systematic review was conducted by searching PubMed reports with no restrictions on start date covering the literature published until February 20, 2019 using relevant keywords, including temperature, pressure, shear, and relative humidity. We review the use of these variables as predictors of DFU, highlighting gaps in our current understanding and suggesting which specific features should be combined to develop a real-time microclimate prognostic model. Results: The current prognostic models rely either solely on contralateral temperature, pressure, or shear measurement; these parameters, however, rarely reach 50% specificity in relation to DFU. There is also considerable variation in methodological investigation, anatomical sensor configuration, and resting time prior to temperature measurements (5-20 minutes). Few studies have considered relative humidity and mean skin resistance. Conclusion: Very limited evidence supports the use of single clinical parameters in predicting the risk of DFU. We suggest that the microclimate as a whole should be considered to predict DFU more effectively and suggest nine specific features which appear to be implicated for further investigation. Technology supports real-time in-shoe data collection and wireless transmission, providing a potentially rich source of data to better predict the risk of DFU.

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Section: Microclimate Predictionmentioning

confidence: 98%

Prediction of Diabetic Foot Ulceration: The Value of Using Microclimate Sensor Arrays

Jones

Bibb

Davies

et al. 2019

J Diabetes Sci Technol

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“…Thermography was carried out with a novel thermal imaging device (Fig. ) . The thermal imaging device is a portable two‐camera battery‐operated instrument for imaging plantar, dorsal, medial and lateral sites of each foot.…”

Section: Participants and Methodsmentioning

confidence: 99%

“…If such lesions are promptly detected and managed in a timely manner, many ulcers can be prevented. To test this hypothesis, a novel prototype of a thermal imaging system for the feet (the Diabetic Foot Ulcer Prevention System) was developed by Photometrix Imaging Ltd in association with the University of South Wales . The application of this device in the assessment of healthy feet, as well as its reliability in temperature assessment of feet, have been previously reported .…”

Section: Introductionmentioning

confidence: 99%

Infrared thermography and ulcer prevention in the high‐risk diabetic foot: data from a single‐blind multicentre controlled clinical trial

et al. 2019

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Aim To assess the usefulness of monthly thermography and standard foot care to reduce diabetic foot ulcer recurrence. Methods People with diabetes (n = 110), neuropathy and history of ≥ 1 foot ulcer participated in a single‐blind multicentre clinical trial. Feet were imaged with a novel thermal imaging device (Diabetic Foot Ulcer Prevention System). Participants were randomized to intervention (active thermography + standard foot care) or control (blinded thermography + standard foot care) and were followed up monthly until ulcer recurrence or for 12 months. Foot thermograms of participants from the intervention group were assessed for hot spots (areas with temperature ≥ 2.2°C higher than the corresponding contralateral site) and acted upon as per local standards. Results After 12 months, 62% of participants were ulcer‐free in the intervention group and 56% in the control group. The odds ratios of ulcer recurrence (intervention vs control) were 0.82 (95% CI 0.38, 1.8; P = 0.62) and 0.55 (95% CI 0.21, 1.4; P = 0.22) in univariate and multivariate logistic regression analyses, respectively. The hazard ratios for the time to ulcer recurrence (intervention vs control) were 0.84 (95% CI 0.45, 1.6; P = 0.58) and 0.67 (95% CI 0.34, 1.3; P = 0.24) in univariate and multivariate Cox regression analyses, respectively. Conclusions Monthly intervention with thermal imaging did not result in a significant reduction in ulcer recurrence rate or increased ulcer‐free survival in this cohort at high risk of foot ulcers. This trial has, however, informed the design of a refined study with longer follow‐up and group stratification, further aiming to assess the efficacy of thermography to reduce ulcer recurrence.

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“…Moreover, thermography has the potential to identify regions of plantar of feet that are at risk of ulceration in diabetic patients. In most diabetic patients, symptoms of ulcers are not observed until the ulcer is infected [41][42][43]. Ischemic foot and neuropathic foot are two complications of diabetic patients.…”

Section: Introductionmentioning

confidence: 99%

Rapid extraction of the hottest or coldest regions of medical thermographic images

Etehadtavakol

Emrani

2018

Med Biol Eng Comput

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Early detection of breast tumors, feet pre-ulcers diagnosing in diabetic patients, and identifying the location of pain in patients are essential to physicians. Hot or cold regions in medical thermographic images have potential to be suspicious. Hence extracting the hottest or coldest regions in the body thermographic images is an important task. Lazy snapping is an interactive image cutout algorithm that can be applied to extract the hottest or coldest regions in the body thermographic images quickly with easy detailed adjustment. The most important advantage of this technique is that it can provide the results for physicians in real time readily. In other words, it is a good interactive image segmentation algorithm since it has two basic characteristics: (1) the algorithm produces intuitive segmentation that reflects the user intent with given a certain user input and (2) the algorithm is efficient enough to provide instant visual feedback. Comparing to other methods used by the authors for segmentation of breast thermograms such as K-means, fuzzy c-means, level set, and mean shift algorithms, lazy snapping was more user-friendly and could provide instant visual feedback. In this study, twelve test cases were presented and by applying lazy snapping algorithm, the hottest or coldest regions were extracted from the corresponding body thermographic images. The time taken to see the results varied from 7 to 30 s for these twelve cases. It was concluded that lazy snapping was much faster than other methods applied by the authors such as K-means, fuzzy c-means, level set, and mean shift algorithms for segmentation. Graphical abstract Time taken to implement lazy snapping algorithm to extract suspicious regions in different presented thermograms (in seconds). In this study, ten test cases are presented that by applying lazy snapping algorithm, the hottest or coldest regions were extracted from the corresponding body thermographic images. The time taken to see the results varied from 7 to 30 s for the ten cases. It concludes lazy snapping is much faster than other methods applied by the authors.

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A medical thermal imaging device for the prevention of diabetic foot ulceration

Cited by 22 publications

References 14 publications

Prediction of Diabetic Foot Ulceration: The Value of Using Microclimate Sensor Arrays

Prediction of Diabetic Foot Ulceration: The Value of Using Microclimate Sensor Arrays

Infrared thermography and ulcer prevention in the high‐risk diabetic foot: data from a single‐blind multicentre controlled clinical trial

Rapid extraction of the hottest or coldest regions of medical thermographic images

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