Objectives. To collect normative baseline data and identify any significant differences between hand and foot thermographic distribution patterns in a healthy adult population.Design. A single-centre, randomized, prospective study.Methods. Thermographic data was acquired using a FLIR camera for the data acquisition of both plantar and dorsal aspects of the feet, volar aspects of the hands, and anterior aspects of the lower limbs under controlled climate conditions.Results. There is general symmetry in skin temperature between the same regions in contralateral limbs, in terms of both magnitude and pattern. There was also minimal intersubject temperature variation with a consistent temperature pattern in toes and fingers. The thumb is the warmest digit with the temperature falling gradually between the 2nd and the 5th fingers. The big toe and the 5th toe are the warmest digits with the 2nd to the 4th toes being cooler.Conclusion. Measurement of skin temperature of the limbs using a thermal camera is feasible and reproducible. Temperature patterns in fingers and toes are consistent with similar temperatures in contralateral limbs in healthy subjects. This study provides the basis for further research to assess the clinical usefulness of thermography in the diagnosis of vascular insufficiency.

Aim. To evaluate the potential of thermography as an assessment tool for the detection of foot complications by understanding the variations in temperature that occur in type 2 diabetes mellitus (DM). Methods. Participants were categorized according to a medical examination, ankle brachial index, doppler waveform analysis, and 10-gram monofilament testing into five groups: healthy adult, DM with no complications, DM with peripheral neuropathy, DM with neuroischaemia, and DM with peripheral arterial disease (PAD) groups. Thermographic imaging of the toes and forefeet was performed. Results. 43 neuroischaemic feet, 41 neuropathic feet, 58 PAD feet, 21 DM feet without complications, and 126 healthy feet were analyzed. The temperatures of the feet and toes were significantly higher in the complications group when compared to the healthy adult and DM healthy groups. The higher the temperatures of the foot in DM, the higher the probability that it is affected by neuropathy, neuroischaemia, or PAD. Conclusions. Significant differences in mean temperatures exist between participants who were healthy and those with DM with no known complications when compared to participants with neuroischaemia, neuropathy, or PAD. As foot temperature rises, so does the probability of the presence of complications of neuropathy, neuroischaemia, or peripheral arterial disease.

This work develops a method for automatically extracting temperature data from prespecified anatomical regions of interest from thermal images of human hands, feet, and shins for the monitoring of peripheral arterial disease in diabetic patients. Binarisation, morphological operations, and geometric transformations are applied in cascade to automatically extract the required data from 44 predefined regions of interest. The implemented algorithms for region extraction were tested on data from 395 participants. A correct extraction in around 90% of the images was achieved. The process of automatically extracting 44 regions of interest was performed in a total computation time of approximately 1 minute, a substantial improvement over 10 minutes it took for a corresponding manual extraction of the regions by a trained individual. Interrater reliability tests showed that the automatically extracted ROIs are similar to those extracted by humans with minimal temperature difference. This set of algorithms provides a sufficiently accurate and reliable method for temperature extraction from thermal images at par with human raters with a tenfold reduction in time requirement. The automated process may replace the manual human extraction, leading to a faster process, making it feasible to carry out large-scale studies and to increase the regions of interest with minimal cost. The code for the developed algorithms, to extract the 44 ROIs from thermal images of hands, feet, and shins, has been made available online in the form of MATLAB functions and can be accessed from http://www.um.edu.mt/cbc/tipmid.

The identification of the key contributing factors which predispose the foot to ulceration, increasing the risk of recurrence and slow wound healing in diabetes mellitus (DM), has led to some significant research studies over the last 30 years, providing valuable insight into the mechanism leading to diabetic foot ulceration (DFU). Although, these contributory factors are similar to those identified in pressure ulceration occurring in other parts of the body (such as “bed pressure sores’) where magnitude and/or duration of mechanical stress in the presence of sensory deficits are key causal factors, research investigating pressure ulceration has also included measurement of temperature and relative humidity at the interface between the skin and supporting surface. The possible influence of these parameters (in-shoe temperature and humidity) does not appear frequently in diabetic foot ulceration research. Referred to as “microclimate”, this has an important role in the pathway to tissue breakdown evidenced in pressure ulcer research and may be particularly relevant in countries with warm and humid climates. As the microclimate is influential in the ulceration pathway for other body sites, its role in the DFU causal pathway justifies further investigation.