Chanjuan Liu

Infrared thermal imaging for automated detection of diabetic foot complications.

Background: Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods: The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had diffuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results: No differences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with diffuse complications, mean temperature differences of >3 °C between ipsilateral and contralateral foot were found. Conclusions: With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or diffuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

Diagnostic Values for Skin Temperature Assessment to Detect Diabetes-Related Foot Complications

BACKGROUND Skin temperature assessment is a promising modality for early detection of diabetic foot problems, but its diagnostic value has not been studied. Our aims were to investigate the diagnostic value of different cutoff skin temperature values for detecting diabetes-related foot complications such as ulceration, infection, and Charcot foot and to determine urgency of treatment in case of diagnosed infection or a red-hot swollen foot. MATERIALS AND METHODS The plantar foot surfaces of 54 patients with diabetes visiting the outpatient foot clinic were imaged with an infrared camera. Nine patients had complications requiring immediate treatment, 25 patients had complications requiring non-immediate treatment, and 20 patients had no complications requiring treatment. Average pixel temperature was calculated for six predefined spots and for the whole foot. We calculated the area under the receiver operating characteristic curve for different cutoff skin temperature values using clinical assessment as reference and defined the sensitivity and specificity for the most optimal cutoff temperature value. Mean temperature difference between feet was analyzed using the Kruskal-Wallis tests. RESULTS The most optimal cutoff skin temperature value for detection of diabetes-related foot complications was a 2.2°C difference between contralateral spots (sensitivity, 76%; specificity, 40%). The most optimal cutoff skin temperature value for determining urgency of treatment was a 1.35°C difference between the mean temperature of the left and right foot (sensitivity, 89%; specificity, 78%). CONCLUSIONS Detection of diabetes-related foot complications based on local skin temperature assessment is hindered by low diagnostic values. Mean temperature difference between two feet may be an adequate marker for determining urgency of treatment.

Infrared dermal thermography on diabetic feet soles to predict ulcerations: a case study

Diabetic foot ulceration is a major complication for patients with diabetes mellitus. If not adequately treated, these ulcers may lead to foot infection, and ultimately to lower extremity amputation, which imposes a major burden to society and great loss in health-related quality of life for patients. Early identification and subsequent preventive treatment have proven useful to limit the incidence of foot ulcers and lower extremity amputation. Thus, the development of new diagnosis tools has become an attractive option. The ultimate objective of our project is to develop an intelligent telemedicine monitoring system for frequent examination on patients’ feet, to timely detect pre-signs of ulceration. Inflammation in diabetic feet can be an early and predictive warning sign for ulceration, and temperature has been proven to be a vicarious marker for inflammation. Studies have indicated that infrared dermal thermography of foot soles can be one of the important parameters for assessing the risk of diabetic foot ulceration. This paper covers the feasibility study of using an infrared camera, FLIR SC305, in our setup, to acquire the spatial thermal distribution on the feet soles. With the obtained thermal images, automated detection through image analysis was performed to identify the abnormal increased/decreased temperature and assess the risk for ulceration. The thermography for feet soles of patients with diagnosed diabetic foot complications were acquired before the ordinary foot examinations. Assessment from clinicians and thermography were compared and follow-up measurements were performed to investigate the prediction. A preliminary case study will be presented, indicating that dermal thermography in our proposed setup can be a screening modality to timely detect pre-signs of ulceration.

Statistical analysis of spectral data: a methodology for designing an intelligent monitoring system for the diabetic foot

Abstract. Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as “healthy” or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

PS8 - 3. Infrared dermal thermography for automatic detection of diabetic foot complications

Inflammation is an early and predictive warning sign for diabetic foot complications, and temperature has been proven to be a vicarious marker for inflammation. Studies have shown that infrared dermal thermography can be a valuable diagnostic tool for early recognition of diabetic foot ulceration, which in turn may prevent further complications.