Thermal imaging today and its relevance to diabetes

Thermal threshold for knee osteoarthritis people evaluated with infrared thermography: A scoping review

INTRODUCTION

Knee degenerative processes, such as osteoarthritis, are disabling. An early intervention is generally more effective making important a timely diagnosis. A pre-diagnosis tool could be the thermal camera that allows the detection of joint inflammation. Consequently, the objective of the present study was to evaluate the literature and propose a thermal attention threshold for infrared thermography data in people with knee osteoarthritis.

METHODS

four electronic databases were searched with specific keywords until the 25th of March 2024. Only original articles about joint inflammation due to osteoarthritis evaluated through digital infrared thermal images were included. A quality assessment analysis was performed. The attention threshold was extracted through the median of the extracted data. The findings were narratively discussed.

RESULTS

A total of 9 studies have been included after the eligibility criteria selection. The studies presented some differences in terms of acquisition protocol, thermal imaging camera, data extrapolation, and analysis. Despite these differences, the studies presented similar thermal data.

CONCLUSION

A knee thermography of or above 31.3 °C could indicate osteoarthritis, highlighting the necessity of further, more specific, and accurate analysis.

Thermal Imaging of the Tongue Surface as a Predictive Method in the Diagnosis of Type 2 Diabetes Mellitus

Over the past 20 years, the high prevalence of diabetes has become a global public health problem.

BACKGROUND

The objective of this study was to develop a non-invasive screening method for diabetes which will enable the detection of the disease at an early stage.

METHODS

This study included 63 adult patients of both sexes: 30 patients with type 2 diabetes (t2DM) and 33 healthy volunteers. The temperature distribution on the tongue's dorsum and apex surface was studied in patients after a mouth-cooling procedure had been introduced. The study used an FLIR T540 thermal imaging camera. An analysis of the correlation between the ∆T values of the tongue dorsum and apex and the glycated hemoglobin (HbA1c) level was performed.

RESULTS

The median of the average dorsum temperature measured 10 min after mouth rinsing was almost 0.8 [°C] lower than for healthy individuals. Also, studies showed a positive average correlation with a Pearson coefficient of r = 0.46 between the HbA1c level and the ∆T of the tongue dorsum.

CONCLUSIONS

Tongue temperature measured using the IRT showed a correlation with standard biochemical parameters; it may also differentiate patients and constitute a specific screening method for patients with t2DM.

Automatic Diabetic Foot Ulcer Recognition Using Multi-Level Thermographic Image Data

Lower extremity diabetic foot ulcers (DFUs) are a severe consequence of diabetes mellitus (DM). It has been estimated that people with diabetes have a 15% to 25% lifetime risk of acquiring DFUs which leads to the risk of lower limb amputations up to 85% due to poor diagnosis and treatment. Diabetic foot develops planter ulcers where thermography is used to detect the changes in the planter temperature. In this study, publicly available thermographic image data including both control group and diabetic group patients are used. Thermograms at image level as well as patch level are utilized for DFU detection. For DFU recognition, several machine-learning-based classification approaches are employed with hand-crafted features. Moreover, a couple of convolutional neural network models including ResNet50 and DenseNet121 are evaluated for DFU recognition. Finally, a CNN-based custom-developed model is proposed for the recognition task. The results are produced using image-level data, patch-level data, and image-patch combination data. The proposed CNN-based model outperformed the utilized models as well as the state-of-the-art models in terms of the AUC and accuracy. Moreover, the recognition accuracy for both the machine-learning and deep-learning approaches was higher for the image-level thermogram data in comparison to the patch-level or combination of image-patch thermograms.

Joint Response to Exercise Is Affected by Knee Osteoarthritis: An Infrared Thermography Analysis

Infrared thermography can be used to evaluate the inflammation characterizing the joint environment of OA knees, but there is limited evidence on the response to physical exercise. Identifying the response to exercise of OA knees and the influencing variables could provide important information to better profile patients with different knee OA patterns. Sixty consecutive patients (38 men/22 women, 61.4 ± 9.2 years) with symptomatic knee OA were enrolled. Patients were evaluated with a standardized protocol using a thermographic camera (FLIR-T1020) positioned at 1 m with image acquisition of an anterior view at baseline, immediately after, and at 5 min after a 2-min knee flexion-extension exercise with a 2 kg anklet. Patients' demographic and clinical characteristics were documented and correlated with the thermographic changes. This study demonstrated that the temperature response to exercise in symptomatic knee OA was affected by some demographic and clinical characteristics of the assessed patients. Patients with a poor clinical knee status presented with a lower response to exercise, and women showed a greater temperature decrease than men. Not all evaluated ROIs showed the same trend, which underlines the need to specifically study the different joint subareas to identify the inflammatory component and joint response while investigating knee OA patterns.

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

Venous leg ulcers (VLUs) are the most common chronic wound types in older populations, with many wounds not healing in the normal trajectory. Many older people with wounds are treated in their homes, currently assessed by monitoring the wound area over weeks to ascertain the potential for healing. A noncontact method using thermal imaging has been shown to predict the healing trajectory of diabetes-related foot ulcers, although has not been tested in VLU or the home setting. This project investigated the effectiveness of using thermal imaging to predict VLU healing in the homes of participants. Images of 78 ulcers were collected weekly using a thermal camera from 67 participants in their homes, at 5 consecutive time points. Final follow-up calls were undertaken at 12 weeks to ascertain healing status (healed/unhealed). Images were preprocessed and segmented and the area of the region of the wound was extracted. Kruskal-Wallis tests were performed to test the association of the change of areas over the 5 consecutive weeks with the healing status of the ulcers at 12 weeks. The 95% confidence interval plots were obtained to study the distribution of the area in the healed and unhealed cases. This study found that the difference in the imaged areas between unhealed ulcers at 12 weeks did not reach statistical significance using thermal imaging. Therefore, thermal images could not predict healing progression in VLUs when the images were taken in the homes of participants. Future research to improve the prediction of venous leg ulcer healing should include developing a protocol to standardize conditions, improve imaging process methods, and use machine learning.

Reference Standard for Digital Infrared Thermography of the Surface Temperature of the Lower Limbs

Digital infrared thermographic imaging (DITI) is a supplementary diagnostic technique to visualize the surface temperature of the human body. However, there is currently no reference standard for the lower limbs for accurate diagnosis. In this study, we performed DITI on the lower limbs of 905 healthy Korean volunteers (411 males and 494 females aged between 20 and 69 years) to obtain reference standard data. Thermography was conducted on the front, back, lateral sides, and sole area, and 188 regions of interest (ROIs) were analyzed. Additionally, subgroup analysis was conducted according to the proximity of ROIs, sex, and age groups. The mean temperatures of ROIs ranged from 24.60 ± 5.06 to 28.75 ± 5.76 °C and the absolute value of the temperature difference between both sides reached up to 1.06 ± 2.75 °C. According to subgroup analysis, the sole area had a significantly lower temperature than any other areas, men had higher temperatures than women, and the elderly had higher temperatures than the young adults except for the 20s age group (p < 0.001, respectively). This result could be used as a foundation for the establishment of a reference standard for DITI. Practical patient DITI can be accurately interpreted using these data, and it can serve as a basis for further scientific research.

A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images

Diabetes mellitus (DM) is one of the most prevalent diseases in the world, and is correlated to a high index of mortality. One of its major complications is diabetic foot, leading to plantar ulcers, amputation, and death. Several studies report that a thermogram helps to detect changes in the plantar temperature of the foot, which may lead to a higher risk of ulceration. However, in diabetic patients, the distribution of plantar temperature does not follow a standard pattern, thereby making it difficult to quantify the changes. The abnormal temperature distribution in infrared (IR) foot thermogram images can be used for the early detection of diabetic foot before ulceration to avoid complications. There is no machine learning-based technique reported in the literature to classify these thermograms based on the severity of diabetic foot complications. This paper uses an available labeled diabetic thermogram dataset and uses the k-mean clustering technique to cluster the severity risk of diabetic foot ulcers using an unsupervised approach. Using the plantar foot temperature, the new clustered dataset is verified by expert medical doctors in terms of risk for the development of foot ulcers. The newly labeled dataset is then investigated in terms of robustness to be classified by any machine learning network. Classical machine learning algorithms with feature engineering and a convolutional neural network (CNN) with image-enhancement techniques are investigated to provide the best-performing network in classifying thermograms based on severity. It is found that the popular VGG 19 CNN model shows an accuracy, precision, sensitivity, F1-score, and specificity of 95.08%, 95.08%, 95.09%, 95.08%, and 97.2%, respectively, in the stratification of severity. A stacking classifier is proposed using extracted features of the thermogram, which is created using the trained gradient boost classifier, XGBoost classifier, and random forest classifier. This provides a comparable performance of 94.47%, 94.45%, 94.47%, 94.43%, and 93.25% for accuracy, precision, sensitivity, F1-score, and specificity, respectively.

A Technical Review of Foot Temperature Measurement Systems

People suffering from diabetes are at risk of developing foot ulcerations which, if left untreated, could also lead to amputation. Monitoring of the foot temperature can help in the prevention of these foot complications, and various studies have shown that elevated temperatures may be indicative of ulceration. Over the years, there have been various devices that were designed for foot temperature monitoring, for both clinical and home use. The technologies used included infrared thermometry, liquid crystal thermography, infrared thermography, and a vast range of analogue and digital temperature sensors incorporated into different measurement platforms. All these systems are able to collect thermal data from the foot, with some being able to acquire data only when the foot is stationary and others being able to acquire data from the foot in motion, which can give more in-depth insight into any emerging problems. The aim of this review is to evaluate the available literature related to the technologies used in these systems, outlining the benefits of each and what further developments may be required to make the foot temperature analysis more effective.

Potential Use of Novel Image and Signal Processing Methods to Develop a Quantitative Assessment of the Severity of Acute Radiation Dermatitis in Breast Cancer Radiotherapy

More than 95% of patients who undergo radiotherapy report symptoms of radiation dermatitis, which is a side effect of this therapy. Erythema, edema, dry and moist desquamation intensify with each fraction of irradiation and can significantly reduce a patient's quality of life. Therefore, an effective skin care procedure is needed for skin that has been exposed to ionizing radiation in order to avoid unplanned treatment interruptions. The methods that are currently used to assess the severity of an acute radiation reaction are based on visual scales (RTOG, EORTC, NCI CTCAE, LENT-SOMA). Because the assessment is made subjectively, the results depend on the researchers, their experience and perceptiveness. Until now, several studies have been carried out to check the possibility of using an objective methods like hyperspectral imaging, thermal imaging, laser Doppler flowmetry, dielectric and electrochemical methods, reflection spectrophotometry and Courage-Khazaka Multi-skin instrument to radiation-induced dermatitis assessment. Unfortunately, due to various limitations that occurred in the research, none of these techniques was successfully implement as alternative for visual assessment. The continuous development of technology enables researchers to access new techniques that might constitute useful diagnostic and cognitive tools. Infrared thermal imaging, hyperspectral imaging and reflectance spectroscopy are examples of the visual techniques that have been used for many years in various fields of medicine, including dermatology and chronic wound or burn care. They provide information on the skin parameters, such as the temperature, concentration and distribution of chromophores (eg, hemoglobin and melanin), saturation or perfusion changes. The aim of this study is to review the available literature on the use of imaging methods in the clinical assessment of skin with lesions of various origins, evaluation of their suitability for the assessment of radiation reaction and consideration the possibility of creating a quantitative scale for assessing severity of acute radiation dermatitis.

OCULAR SURFACE TEMPERATURE DIFFERENCES IN RETINAL VASCULAR DISEASES

PURPOSE

To define the effect of age-related macular degeneration (AMD) and diabetic retinopathy (DR) on the ocular thermographic profile.

METHODS

This retrospective cross-sectional study included subjects diagnosed with DR or AMD between January and April 2019. Individuals without ocular disease served as controls. A thermal imaging camera was used for ocular surface temperature (OST) acquisition. The mean temperatures of the medial cantus, lateral cantus, and cornea were calculated.

RESULTS

Thermographic images were obtained from 133 subjects (260 eyes, 97 DR and 163 AMD) and 48 controls (55 eyes). Ocular surface temperature was higher among patients with AMD and lowest among patients with DR (P < 0.001). A subgroup analysis revealed that eyes with diabetic macular edema had significantly higher OSTs than DR eyes without diabetic macular edema. Moreover, the OST in eyes with diabetic macular edema was similar to the measurements of the AMD group. There were no differences in OSTs between neovascular and nonneovascular AMD eyes.

CONCLUSION

Although AMD and DR are considered posterior segment conditions, their effect on OST implies that the entire globe is involved. Although both conditions result from similar multifactorial pathophysiologic changes, the differences in OST between DR and AMD might be due to dissimilarity in the balance of pathologic processes involved in each condition. Further research is required to better understand the pathophysiology of these diseases and their effect on OST as well as to determine the effect of vasculature, circulation, and tissue metabolism on ocular temperature.

Ocular Surface Temperature: Characterization in a Large Cohort of Healthy Human Eyes and Correlations to Systemic Cardiovascular Risk Factors

Purpose: To characterize ocular surface temperature (OST) in healthy eyes and its association with systemic risk factors of cardiovascular and ischemic heart disease. Methods: This prospective cross-sectional study included consenting subjects who were examined at the Institute for Medical Screening in Sheba Medical Center. A Therm-App™ thermal imaging camera (Opgal LTD, Israel) was used for OST acquisition, and the mean OST of the medial canthal, lateral canthal, and central cornea regions were measured. Room and body temperatures were also recorded. Past medical and ocular history as well as data from various clinical examinations performed at the same visit were obtained. Results: Thermographic images were obtained from 186 subjects, 150 of which were included in the final analysis. OST was significantly higher in the medial canthal, central cornea, and lateral canthal regions in people with a history of ischemic heart disease (p = 0.02, p = 0.02, and p = 0.03, respectively). There were no significant OST differences (ANOVA test) associated with the presence of hypertension, diabetes mellitus, or active smoking status. Conclusions: OST correlated positively with the presence of ischemic heart disease. This correlation, its pathophysiological base, and its clinical application warrants further investigation.

An analysis of tumor-related skin temperature differences in malignant soft-tissue tumors

Background

Soft tissue tumors are often accompanied with elevated skin temperature; however, studies concerning the relationship between soft-tissue tumors and skin temperature elevation are scarce. We aimed to evaluate the clinical significance of skin temperature elevation in soft-tissue tumors and identify factors related to skin temperature elevation.

Patients and methods

This study comprised 118 patients at our hospital with soft-tissue tumors, excluding lipomatous tumors, whose pathological diagnosis was surgically confirmed between February 2017 and March 2021. Sixty-one and 57 patients had been diagnosed with benign lesions and malignant tumors, respectively (men, 64; women, 54; median age, 61 [range, 20–92] years). The relationship between skin temperature, monitored using a thermography camera, and the presence of soft-tissue malignancy was investigated. We reviewed clinical data to identify factors related to elevated skin temperature.

Results

Temperature differences ≥ 0.2 °C compared to the unaffected side were significantly associated with the presence of malignant tumors (p < 0.001). Logistic regression analysis indicated that intertumoral blood supply was associated with elevated skin temperature (OR 3.22, 95% CI 2.03–5.13; p < 0.001).

Conclusions

Elevated skin temperature, influenced by intertumoral blood supply, may be an important adjunct to physical findings when diagnosing malignant soft-tissue tumors.

Clinical relevance

Intertumoral blood supply influenced elevated skin temperature in malignant soft-tissue tumors. A skin temperature difference ≥ 0.2 °C compared to the unaffected side can help differentiate between benign and malignant tumors. Skin temperature differences may help in diagnosing malignant soft-tissue tumors.

A machine learning model for early detection of diabetic foot using thermogram images

Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the institution of preventative measures through education and offloading. Several studies have reported that thermogram images may help to detect an increase in plantar temperature prior to DFU. However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. A comparison of the inference time for the best-performing networks confirmed that the proposed algorithm can be deployed as a smartphone application to allow the user to monitor the progression of the DFU in a home setting.

Infrared Thermal Imaging of Patients With Acute Upper Respiratory Tract Infection: Mixed Methods Analysis

Background

Upper respiratory tract infection is a common disease of the respiratory system. Its incidence is very high, and it can even cause pandemics. Infrared thermal imaging (IRTI) can provide an objective and quantifiable reference for the visual diagnosis of people with acute respiratory tract infection, and it can function as an effective indicator of clinical diagnosis.

Objective

The aims of this study are to observe and analyze the infrared expression location and characteristics of patients with acute upper respiratory tract infection through IRTI technology and to clearly express the quantification of temperature, analyze the role of IRTI in acute upper respiratory tract diagnostic research, and understand the impact of IRTI in qualitative and quantitative research.

Methods

From December 2018 to February 2019, 154 patients with acute upper respiratory tract infection were randomly selected from the emergency department of the First Affiliated Hospital of Guangzhou Medical University. Among these patients, 73 were men and 81 were women. The subjects were divided into two groups according to the presence of fever, namely, fever and nonfever groups. Qualitative and quantitative analyses of the infrared thermal images were performed to compare the results before and after application of the technology.

Results

Using the method described in this paper, through the analysis of experimental data, we elucidated the role of IRTI in the diagnosis of acute upper respiratory tract infection, and we found that qualitative and quantitative IRTI analyses play important roles. Through the combination of theory and experimental data, the IRTI analysis showed good results in identifying acute upper respiratory tract infection.

Conclusions

IRTI technology plays an important role in identifying the infrared expression location and characteristics of patients with acute upper respiratory tract infection as well as in the quantification of clear expression of body temperature, and it provides an objective and quantifiable reference basis for elucidating the pathogenesis of these patients.

Effect of 660/850 nm LED on the microcirculation of the foot: neurovascular biphasic reflex

Phototherapy (LED) can be used to stimulate the healing of chronic ulcers of the lower limb, as it affects healing cells and neurons. In this way, this study has sought to know if the heat stimulus of the 660-/850-nm contact LED is sufficient to trigger the response in the peripheral sympathetic nervous system of normal volunteers. The LED was applied on the right foot of forty-two normal volunteers followed by serial infrared images. After the stimulus, a biphasic hyperthermia curve was observed synchronously in both feet, in the right and left halluxes, while hyperthermia was attributed to the redistribution of postural blood flow in the plantar region, which may indicate independent neurovascular mechanisms. Thus, periodic thermographic analysis can be used in the evolution of the LED treatment.

Opportunities and challenges for the building monitoring systems in the age-pandemic of COVID-19: Review and prospects

The latest COVID-19 pandemic outbreak posed a significant risk to millions of people worldwide who are safe and well-being. As the environment continues to be open from lockdowns and becomes unprecedentedly tenuous or what many called a “new norm,” it makes sense to focus on what the society has experienced, re-examine our fundamental beliefs, and map the path of designing and creating a sustainable world. This article has summarized the latest technologies that have been recently implemented to control the spreading of COVID-19 through embedded smart monitoring systems and communicate effectively with the building management infrastructure. This article also discussed the statistical research analysis, which motivates the achievement of the targeted sustainable development goals (SDGs). Last but not least, the implemented technologies and their related variables to be controlled, challenges, and new perspectives were also addressed.

Review of the efficacy of infrared thermography for screening infectious diseases with applications to COVID-19

Purpose: The recent coronavirus disease 2019 (COVID-19) pandemic, which spread across the globe in a very short period of time, revealed that the transmission control of disease is a crucial step to prevent an outbreak and effective screening for viral infectious diseases is necessary. Since the severe acute respiratory syndrome (SARS) outbreak in 2003, infrared thermography (IRT) has been considered a gold standard method for screening febrile individuals at the time of pandemics. The objective of this review is to evaluate the efficacy of IRT for screening infectious diseases with specific applications to COVID-19. Approach: A literature review was performed in Google Scholar, PubMed, and ScienceDirect to search for studies evaluating IRT screening from 2002 to present using relevant keywords. Additional literature searches were done to evaluate IRT in comparison to traditional core body temperature measurements and assess the benefits of measuring additional vital signs for infectious disease screening. Results: Studies have reported on the unreliability of IRT due to poor sensitivity and specificity in detecting true core body temperature and its inability to identify asymptomatic carriers. Airport mass screening using IRT was conducted during occurrences of SARS, Dengue, Swine Flu, and Ebola with reported sensitivities as low as zero. Other studies reported that screening other vital signs such as heart and respiratory rates can lead to more robust methods for early infection detection. Conclusions: Studies evaluating IRT showed varied results in its efficacy for screening infectious diseases. This suggests the need to assess additional physiological parameters to increase the sensitivity and specificity of non-invasive biosensors.

Plantar thermography predicts freedom from major amputation after endovascular therapy in critical limb ischemic patients

Although plantar thermography can evaluate the immediate perfusion result after an endovascular therapy (EVT) has been performed, a relevant wound outcome study is still lacking.This study was to investigate whether angiosome-based plantar thermography could predict wound healing and freedom from major amputation after EVT in patients with critical limb ischemia (CLI).All 124 patients with CLI (Rutherford category 5 and 6) who underwent EVT from January 2017 to February 2019 were prospectively enrolled. All patients received thermography both before and after EVT. Both wound healing and freedom from major amputation at the 6-month follow-up period were recorded. There were 61 patients in the healing group and 63 patients in the non-healing group, whereas the major amputation total was 14 patients. The mean pre- and post-EVT temperature of the foot was significantly higher in the healing group than in the non-healing group (30.78 °C vs 29.42 °C, P = .015; and 32.34 °C vs 30.96 °C, P = .004, respectively). DIFF2 was significantly lower in the non-healing group (-1.38 vs -0.90, P = .009). DIFF1 and DIFF2 were significantly lower in the amputation group (-1.85 °C vs -1.11 °C, P = .026; and -1.82 °C vs -1.08 °C, P = .004). Multivariate analysis showed that DIFF2 stood out as an independent predictor for freedom from major amputation (hazard ratio 0.51, P = .045). Receiver operating characteristic curve analysis showed a DIFF2 cut-off value of -1.30 °C, which best predicts freedom from major amputation.Plantar thermography is associated with wound healing and helps predict freedom from major amputation in CLI patients undergoing EVT.

Musculoskeletal applications of infrared thermography on back and neck syndromes: a systematic review

INTRODUCTION

Thermography is a noninvasive method to detect temperature changes on or near the surface of the body. Despite its utility has not yet been fully verified, it may be used as a complementary method to screening and/or monitoring treatment effectiveness. This systematic review evaluates the role of infrared thermography as a helpful outcome measure tool in subjects with back and neck syndromes.

EVIDENCE ACQUISITION

A literature search was conducted across the National Library of Medicine (MEDLINE), Web of Science and Scopus databases for studies that evaluated the role of infrared thermography as a helpful outcome measure tool in subjects with back and neck syndromes. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA).

EVIDENCE SYNTHESIS

The search strategy and selection criteria yielded 812 articles. From these, 268 duplicates were removed, and only 16 were in line with the aim of this review. Ultimately, only seven precisely fulfilled the inclusion and exclusion criteria and were included in the review. According to the articles reviewed, thermography seems to give an objective notion of change in inflammatory activity, which can corroborate the usefulness of treatment or the improvement/worsening of the patient's symptoms. The overall quality of research was uneven in the study design, endpoint measures, and sample characteristics.

CONCLUSIONS

The number of high-quality studies of the role of infrared thermography in patients with back and neck syndromes remains limited. More than a diagnostic tool, thermography can be an objective tool for monitoring the effectiveness of treatment by identifying deviations from a healthy state.

Use of a smartphone thermometer to monitor thermal conductivity changes in diabetic foot ulcers: a pilot study

OBJECTIVE

To investigate the dependability of a thermal gadget connecting to a smartphone. Comparing the exact temperature of damaged tissue with adjacent parts of the limb and to evaluate the changes in thermal conductivity of hard-to-heal wounds in patients with a diabetic foot ulcer (DFU).

METHODS

Potential candidates were divided into three groups and selected from different hospitals in Tehran. Group 1 contained patients with inflammation, Group 2 were patients with vascular complications, and Group 3 were patients who were managing to control their glucose levels to an acceptable level, according to their medical records (i.e. 'healthy cases'). All thermal images were taken without any external stimulus, in room temperature conditions after 15 minutes' rest. All medical records were confirmed by therapeutic supervisors. Moreover, the tissue conditions in patients were considered in the computational part of the study. The temperatures of the ulcer and adjacent tissues were observed and compared. The collected data were used in a suggested model for human tissues and the method of calculation in this study was trial and error. In this study, patients in Group 2 were considered in the computational section of the study.

RESULTS

Temperature difference between the wounds and adjacent tissues for the big toe in three patients in Group 2 was 2.2ºC for the healthier candidate and almost 6.9ºC in the worst case. By comparing the thermal conductivity of normal and damaged tissues, a significant reduction in thermal conductivity was observed for the candidate with the worst status of big toe by about 84.3%. For the other two candidates in this category, it was almost 68.86% and 20.47%.

CONCLUSION

The variation in thermal conductivity represents the change in tissue properties. Thermal conductivity can be applied for early DFU detection. This data may allow introduction of the smartphone thermometer as an authentic and alternative apparatus that is beneficial in diabetic clinics as well as self-assessment by patients. Moreover, due to the decrease in thermal conductivity, this study suggests using intelligent thermal sheets in vulnerable parts of the diabetic foot.

A computer aided diagnostic method for the evaluation of type II diabetes mellitus in facial thermograms

Almost 50% of individuals around the globe are unaware of diabetes and its complications. So, an early screening of diabetes is very important at this current situation. To overcome the difficulties such as pain and discomfort to the subjects obtained from the biochemical diagnostic procedures; an infrared thermography is the diagnostic technique which measures the skin surface temperature noninvasively. Thus, the aim of our proposed study was to evaluate the type II diabetes in facial thermograms and to develop a computer aided diagnosis (CAD) system to classify the normal and diabetes. The facial thermograms (n = 160) including male (n = 79) and female (n = 81) were captured using FLIR A 305sc infrared thermal camera. The Haralick textural features were extracted from the facial thermograms based on gray level co-occurrence matrix algorithm. The T_ROI, T_MAX, and T_TOT are the statistical temperature parameters exhibited a significant negative correlation with HbA1c (r = - 0.421, - 0.411, - 0.242, p < 0.01 (T_ROI); r = - 0.259, p < 0.01(T_MAX) and - 0.173, p < 0.05 (T_TOT)). An optimal regression equation has been constructed by using the significant facial variables and standard HbA1c values. The model has achieved sensitivity, specificity, and accuracy rate as 91.42%, 88.57%, and 90% respectively. The anthropometrical variables, extracted textural features and temperature parameters were fed into the classifiers and their performances were compared. The Support Vector Machine outperformed the Linear Discriminant Analysis (84.37%) and k-Nearest Neighbor (81.25%) classifiers with the maximum accuracy rate of 89.37%. The developed CAD system has achieved 89.37% of accuracy rate for the classification of diabetes. Thus, the facial thermography could be used as the basic non-invasive prognostic tool for the evaluation of type II diabetes mellitus.

Post-operative monitoring of free flaps using a low-cost thermal camera: a pilot study

Background

Careful post-operative monitoring of free flaps is important in flap survival; immediate action increases flap salvage rate. Although various methods are available, room for improvement remains. Thermal cameras have proven their value in medicine and are nowadays readily available at low costs. The objective of this study was to evaluate the potential of an affordable infrared thermal camera and software in the detection of failing free flaps during post-operative monitoring.

Methods

Free myocutaneous rectus abdominis flaps were harvested in 16 female landrace pigs and replanted after several hours of storage. All flaps were assessed with indocyanine green fluorescence angiography as well as hourly clinical assessment of skin colour, turgor and capillary refill. Furthermore, thermal photographs were taken simultaneously with the FLIR One thermal camera smartphone module. These photographs were processed in MATLAB and evaluated on their additional value as an indicator for flap failure.

Results

Out of 16 flaps, three flaps failed due to arterial failure and one flap developed venous congestion. The mean flap temperature compared to adjacent control skin proved to be most indicative for flap failure. All unsuccessful flaps showed lower temperatures after failure compared to the uncompromised free flaps.

Conclusions

An affordable thermal camera module can potentially contribute to post-operative free flap monitoring. Vascular compromise in free flaps can be distinguished by investigating relative temperature differences between the flap and reference skin. Until the FLIR One camera has been extensively investigated in a human population, it should be used in conjunction with conventional monitoring techniques.

Level of evidence: Level IV, diagnostic study

Deep Learning Classification for Diabetic Foot Thermograms

According to the World Health Organization (WHO), Diabetes Mellitus (DM) is one of the most prevalent diseases in the world. It is also associated with a high mortality index. Diabetic foot is one of its main complications, and it comprises the development of plantar ulcers that could result in an amputation. Several works report that thermography is useful to detect changes in the plantar temperature, which could give rise to a higher risk of ulceration. However, the plantar temperature distribution does not follow a particular pattern in diabetic patients, thereby making it difficult to measure the changes. Thus, there is an interest in improving the success of the analysis and classification methods that help to detect abnormal changes in the plantar temperature. All this leads to the use of computer-aided systems, such as those involved in artificial intelligence (AI), which operate with highly complex data structures. This paper compares machine learning-based techniques with Deep Learning (DL) structures. We tested common structures in the mode of transfer learning, including AlexNet and GoogleNet. Moreover, we designed a new DL-structure, which is trained from scratch and is able to reach higher values in terms of accuracy and other quality measures. The main goal of this work is to analyze the use of AI and DL for the classification of diabetic foot thermograms, highlighting their advantages and limitations. To the best of our knowledge, this is the first proposal of DL networks applied to the classification of diabetic foot thermograms. The experiments are conducted over thermograms of DM and control groups. After that, a multi-level classification is performed based on a previously reported thermal change index. The high accuracy obtained shows the usefulness of AI and DL as auxiliary tools to aid during the medical diagnosis.

Clinical significance of thermal detection of soft-tissue tumors

BACKGROUND

Soft-tissue tumors are often accompanied by abnormal temperature distribution detected during palpation. However, the assessment of temperature distribution is subjective, limiting its wide use in cancer screening. The aim of this study was to evaluate the clinical significance of the thermal detection of soft-tissue tumors.

METHODS

This study involved 100 soft-tissue tumor patients, the pathological diagnosis of which was confirmed by surgery from February 2017 to March 2019 in our hospital. Sixty patients were diagnosed with benign lesions, while 40 patients had malignant tumors. The cohort consisted of 52 males and 48 females, with a median age of 62 (range 22-84). Temperature difference detection by orthopedic oncologists, as well as the consistency and accuracy of temperature distribution detection by orthopedic oncologists, were investigated. The relationship between abnormal temperature distribution and the presence of malignancy in soft tissue was also explored.

RESULTS

We found that more than half of the orthopedic oncologists could detect a temperature difference of 0.2 °C or higher. All three surgeons reported consistent temperature distribution findings after palpation in 92 out of 100 soft-tumor patients. The presence of abnormal temperature distribution was significantly associated with the presence of malignancy (P < 0.0017). Temperature differences of 0.2 °C or higher were significantly associated with the presence of malignant tumors (P < 0.001).

CONCLUSIONS

Diagnosis of abnormal temperature distribution by orthopedic oncologists could suggest the presence of malignancy in patients with soft-tissue lesions.

FLIR vs SEEK thermal cameras in biomedicine: comparative diagnosis through infrared thermography

BACKGROUND

In biomedicine, infrared thermography is the most promising technique among other conventional methods for revealing the differences in skin temperature, resulting from the irregular temperature dispersion, which is the significant signaling of diseases and disorders in human body. Given the process of detecting emitted thermal radiation of human body temperature by infrared imaging, we, in this study, present the current utility of thermal camera models namely FLIR and SEEK in biomedical applications as an extension of our previous article.

RESULTS

The most significant result is the differences between image qualities of the thermograms captured by thermal camera models. In other words, the image quality of the thermal images in FLIR One is higher than SEEK Compact PRO. However, the thermal images of FLIR One are noisier than SEEK Compact PRO since the thermal resolution of FLIR One is 160 × 120 while it is 320 × 240 in SEEK Compact PRO.

CONCLUSION

Detecting and revealing the inhomogeneous temperature distribution on the injured toe of the subject, we, in this paper, analyzed the imaging results of two different smartphone-based thermal camera models by making comparison among various thermograms. Utilizing the feasibility of the proposed method for faster and comparative diagnosis in biomedical problems is the main contribution of this study.

Hyperthermia associated with spinal radiculopathy as determined by digital infrared thermographic imaging

In general, in digital infrared thermographic imaging (DITI) of patients with unilateral spinal radicular pain, the thermal pattern of the extremities of the side of lesion shows hypothermia compared to the opposite, intact side. However, sometimes, DITI shows hyperthermia on the side of the lesion, and this variation can cause confusion. We compared the data of both hypothermia and hyperthermia patients to clarify the factors determining different thermal characteristics in spinal radiculopathy.We retrospectively collected data from patients who underwent DITI at a single center. The final cohort (n = 224) was allocated into 2 groups, a hypothermia group (n = 180) or a hyperthermia group (n = 44). We compared the various factors, including demographic factors and symptom-related factors, that might affect the results of DITI.Except the presence of trauma history (13.9% vs 31.8%, odds ratio 2.893, P = .008), no significant intergroup difference was found in baseline demographic factors, including age, gender, diabetes mellitus, spinal level of pathology, and intervention history. Among symptom-related factors, in the hyperthermia group, the symptom duration was shorter (10.64 weeks [95% confidence interval (CI) 8.36-13.04] vs 2.10 weeks [95% CI 1.05-3.53], P < .001) and Visual Analogue Scale (VAS) of radicular pain was higher (4.23 ± 1.29 vs 5.18 ± 1.40, P < .001) than in the hypothermia group. Also, in the regression analysis, significant factors for hyperthermia include the presence of trauma history, shorter symptom duration (cut-off value 2.50 weeks or less) and higher VAS of radicular pain (cut-off value 4.50 or more).In patients with trauma history, acute phase, and severe radicular pain, hyperthermia in DITI is not unusual and careful interpretation of the DITI results is necessary for proper diagnosis and treatment decisions in spinal radiculopathy.

The association of temperature of Diabetic Foot Ulcers with Chronic Kidney Disorder

The area of the diabetic foot ulcer (DFU) and its reduction over weeks is used for assessment in clinical practices; however, literature reports that this is not reliable parameter. This work has investigated the association of change in the mean temperature of the ulcers with three clinical conditions relevant to wound healing, i.e. peripheral vascular disease (PVD), chronic kidney disease (CKD) and ischemic heart disease (IHD). Thermal and RGB images of 23 DFUs of the first two weeks of ulceration were studied. One-way ANOVA was performed on the change in mean temperature of the ulcers and change in area and it was found that the weekly change in mean temperature was higher for patients with CKD (p-value=0.009). Also, change in area measured from RGB images did not show any association with the clinical conditions. The application of this work is that the temperature obtained from thermal image of the ulcer can be used as a prognostic parameter for its assessment.

Human Tongue Thermography Could Be a Prognostic Tool for Prescreening the Type II Diabetes Mellitus

Diabetes mellitus is one of the life threatening diseases over the globe, and an early prediction of diabetes is of utmost importance in this current scenario. International Diabetes Federation (IDF) reported nearly half of the world's population was undiagnosed and unaware of being developed into diabetes. In 2017, around 84 million individuals were living with diabetes, and it might increase to 156 million by the end of 2045 stated by IDF. Generally, the diagnosis of diabetes relies on the biochemical method that may cause uneasiness and probability of infections to the subjects. To overcome such difficulties, a noninvasive method is much needed around the globe for primary screening. A change in body temperature is an indication of various diseases. Infrared thermal imaging is relatively a novel technique for skin temperature measurement and turned out to be well known in the medical field due to being noninvasive, risk-free, and repeatable. According to traditional Chinese medicine, the human tongue is a sensitive mirror that reflects the body's pathophysiological condition. So, we have (i) analysed and classified diabetes based on thermal variations at human tongue, (ii) segmented the hot spot regions from tongue thermogram by RGB (red, green, blue) based color histogram image segmentation method and extracted the features using gray level co-occurrence matrix algorithm, (iii) classified normal and diabetes using various machine learning algorithms, and (iv) developed computer aided diagnostic system to classify diabetes mellitus. The baseline measurements and tongue thermograms were obtained from 140 subjects. The measured tongue surface temperature of the diabetic group was found to be greater than normal. The statistical correlation between the HbA_1c and the thermal distribution in the tongue region was found to be r² = 0.5688. The Convolutional Neural Network has outperformed the other classifiers with 94.28% accuracy rate. Thus, tongue thermograms could be used as a preliminary screening approach for diabetes prognosis.

A Synoptic Overview of Neurovascular Interactions in the Foot

Diabetes is a worldwide public health concern as it is associated with various complications. One of the major complications of diabetes is diabetic foot syndrome that results in catastrophic events such as ulceration and amputation. Therefore, the main four strategies of diabetic foot care involve risk prediction, prevention, and early diagnosis and prompt intervention. The drivers of ulceration are multifactorial, and importantly, include microcirculatory changes in the diabetic skin. Cutaneous microcirculation on the foot is greatly influenced by the small fibers which mediate thermal sensation and pain perception in addition to sympathetic activities such as thermoregulation and vasodilation. The interdependence between the neurovascular elements means with the loss of small fiber functions, the corresponding microcirculatory responses may be compromised. Thus, it can be hypothesized that the impairment of the microcirculation may follow the order of the corresponding small fiber nerve dysfunction or vice versa. In this review, select neurovascular investigations that inform the cutaneous microcirculatory and small fiber nerve function in response to pain, cold, and heat and pressure stimuli are reviewed and discussed in this order of sensory loss: the loss of pain, cold, warmth, touch and deep pressure sensation. We also discuss the neurological and vascular characteristics of each of these neurovascular responses. This review highlights the influence of small fibers on cutaneous microcirculation and the need for prospective studies that can determine the course of microcirculatory impairment over time. This, in turn, may help clarify the exact role of microcirculatory changes in the pathway of ulceration. The insights from this review can be pertinent to understand key microcirculatory disturbances and given that the microcirculatory impairment develops at an early stage, relevant interventions can be implemented to possibly reverse or regress the course of the disease. Therefore, knowledge of the neurovascular interactions aids to map the disease progression for early diagnosis and prevention of adverse complications.

Comparison of sensitivity and plantar cutaneous temperature of patients with stroke and Diabetes Mellitus: A pilot case-control study

BACKGROUND

Stroke combined with Diabetes Mellitus may cause sensibility and vascular alterations.

OBJECTIVE

To determine whether sensitivity and plantar cutaneous temperature of clinically controlled patients with stroke and DM are different from those of patients with stroke only.

METHODS

This is a cross-sectional case-control study. The volunteers were assessed for sensitivity by monofilament esthesiometry in their plantar region, and for temperature by infrared thermal imaging. The data was presented as means and standard deviations and comparisons were conducted with the Mann-Whitney statistical test, with statistical significance set at p< 0.05.

RESULTS

Five cases and 11 controls were included according to the eligibility and pairing criteria. There were no discrepancies between the plegic and contralateral sides regarding temperature and sensibility of both cases and controls. However, in the control group, there was an observable tendency for different temperatures between the plegic and the contralateral sides, with p< 0.05 in most of the comparisons.

CONCLUSIONS

There is no evidence that the cases and controls have different plantar sensibility nor different plantar temperature on their plegic and contralateral sides. However, significant temperature discrepancies between both plegic and contralateral sides were observed in the control group.

Relationship between skin temperature and soft tissue hardness in diabetic patients: an exploratory study

OBJECTIVE

The role of skin temperature and soft tissue hardness in the development of plantar ulcers is still in debate. However, the relationship between skin temperature and soft tissue hardness has not been explored. This study intends to analyse an eventual association between skin temperature and soft tissue hardness in the foot of diabetic patients Approach: Twenty diabetic patients enrolled for this study. The analysis was done at the foot level, therefore, skin temperature and soft tissue hardness data of the plantar surface of 40 feet were obtained in eight regions of the foot, two in the heel, two in the midfoot, three in the forefoot and one in the hallux. Information regarding glycaemic control (HbA1c levels) was retrieved from the clinical records of the patients.

MAIN RESULTS

After averaging skin temperature and soft tissue hardness in the calcaneum (medial and lateral), in the midfoot (medial and lateral) and in the metatarsal head (1st, 2nd-3rd and 4th-5th), a negative, moderate and significant association was found between skin temperature and soft tissue hardness in the metatarsal head (rho  =  -0.553; p   <  0.001), a positive, low and significant association was found in the midfoot (rho  =  0.333; p   =  0.036), but no association was found in the heel. The multiple linear regression models with skin temperature as dependent variable and soft tissue hardness as predictor were statistically significant in the metatarsal heads and midfoot, and explained 28.8% (R ²  =  0.288, F _(1,38)  =  15.37, p   <  0.001) and 11.9% (R ²  =  0.119, F _(1,38)  =  5.151, p   =  0.029) of the variance in skin temperature, respectively.

SIGNIFICANCE

Skin temperature is negatively associated with soft tissue hardness in the metatarsal head region and positively associated with soft tissue hardness in the midfoot. These findings imply that soft tissue hardness should be considered in the assessment of diabetic foot patients and that this variable should be controlled in studies assessing the determinants of foot skin temperature.

Risk of breast cancer based on thermal tomography characteristics

Background

There is no uniform standard for the diagnosis of breast lesions by thermal tomography (TT). This study aimed to widely analyse the predictive value of TT in patients with breast cancer and establish a uniform standard for the diagnosis of breast lesions.

Methods

We retrospectively analysed data from women who suffered from non-inflammatory unilateral single breast lesion and underwent TT from January 2014 to July 2016. Changes in TT parameters were correlated with the pathologic diagnosis, and its predictive value was assessed.

Results

A total of 407 patients underwent TT examinations during the study period, including 196 subsequently diagnosed with breast cancer. Several characteristics were found to be significantly correlated with breast cancer: age ≥60 years [odds ratio (OR) =109.296, P<0.001], age ≥35 and <60 years (OR =25.720, P<0.001), q-r curve as an angle of 30°–45° (OR =14.895, P<0.001), ΔTs (surface temperature difference between the neoplastic side and the healthy side) ≥0.65 °C (OR =4.129, P<0.001), ΔTn (nipple temperature difference between the neoplastic side and the healthy side) ≥0.45 °C (OR =2.683, P=0.006), isotherm asymmetry (OR =2.297, P=0.035), and vascular plentiful (OR =3.333, P=0.004). Q value as a novel predictive indicator based on the multiple predictor modelling improved the diagnostic rate for breast cancer, and the accuracy in this study was up to 86.7%.

Conclusions

Age, q-r curve, ΔTs, ΔTn, isotherm, and vascular features were independent predictors of breast cancer. Q value could be used to assess the risk of breast cancer as an additional diagnostic tool for breast cancer screening and diagnosis.

Analysis of thyroid thermographic images for detection of thyroid tumor: An experimental-numerical study

Thermography is a developing and noninvasive medical imaging technique that can be used for diagnosis of body disorders based on temperature deviation from normal body temperature. This research investigates the feasibility of thermography method in conjunction with artificial neural networks (ANNs) for detection of thyroid tumors. For this purpose, first, a 3-D model of the healthy human neck is constructed based on patient-specific computed tomography (CT) images. This model is used for analyzing bio-heat transfer in the human neck. The healthy thyroid gland is considered as a heat source and generates heat according to its temporal temperature. Finite element results verify the thermography potential for detection of thyroid gland location and estimation of its butterfly shape on the neck thermogram. The numerical analysis is carried out on 35 models with varying thermo-physical parameters of the healthy thyroid gland, including heat generation and blood perfusion. The acquired thermograms are used to develop an ANN for correlating the thermo-physical parameters of the gland and temperature profile on the neck surface. In the next stage, dynamic thermal images are captured from 10 healthy and three cancerous human cases. The experimental thermal images are analyzed by the developed ANN and the corresponding thermo-physical parameters are obtained. Results show that the estimated heat generation values for the healthy cases are about 3000 Wm3 while it increases to more than 12 000 Wm3 for the cases with tumors. This significant variation confirms the potential of dynamic thermography in diagnosis of thyroid tumors.

Is Thermal Imaging a Useful Predictor of the Healing Status of Diabetes-Related Foot Ulcers? A Pilot Study

INTRODUCTION

In clinical practice, both area and temperature of the ulcer have been shown to be effective in tracking the healing status of diabetes-related foot ulcer (DRFU). However, traditionally, the area of the DRFU is measured regardless of the temperature distribution. The current prospective, observational study used thermal imaging, as a more accurate tool, to measure both the area and the temperature of DRFU. We aimed to predict healing of DRFU using thermal imaging within the first 4 weeks of ulceration.

METHOD

A pilot study was conducted where thermal and color images of 26 neuropathic DRFUs (11 healing vs 15 nonhealing) from individuals with type 1 or 2 diabetes were taken at the initial clinic visit (baseline), at week 2, and at week 4. The thermal images were segmented into isothermal patches to identify the wound boundary and area corresponding to temperature distribution. Five parameters were obtained: temperature of the wound bed, area of the isothermal patch of the wound bed, area of isothermal patch of periwound, number of isolated isothermal patches of the wound region, and physical wound bed area from color image. The ulcers were also measured by experienced podiatrists over 4 consecutive weeks and used as the healing reference.

RESULTS

For healing cases, the ratio of the area of the wound bed to its baseline measured using thermal images was found to be significantly lower at 2 weeks compared to nonhealing cases and this corresponded with a 50% reduction in area of DRFU at 4 weeks (group rank-based nonparametric analysis of variance P = .036). In comparison, neither the planimetric area measured using color images nor the temperature of the wound bed was associated with the healing.

CONCLUSION

This study of 26 patients demonstrates that change in the isothermal area of DRFU can predict the healing status at week 4. Thermal imaging of DRFUs has the advantage of incorporating both area and temperature allowing for early prediction of the healing of these ulcers. Further studies with greater sample sizes are required to test the significance of these results.

Accurate segmentation of inflammatory and abnormal regions using medical thermal imagery

Methodologies reported in the existing literature for identification of a region of interest (ROI) in medical thermograms suffer from over- and under-extraction of the abnormal and/or inflammatory region, thereby causing inaccurate diagnoses of the spread of an abnormality. We overcome this limitation by exploiting the advantages of a logarithmic transformation. Our algorithm extends the conventional region growing segmentation technique with a modified similarity criteria and a stopping rule. In this method, the ROI is generated by taking common information from two independent regions produced by two different versions of a region-growing algorithm that use different parameters. An automatic multi-seed selection procedure prevents missed segmentations in the proposed approach. We validate our technique by experimentation on various thermal images of the inflammation of affected knees and abnormal breasts. The images were obtained from three databases, namely the Knee joint dataset, the DBT-TU-JU dataset, and the DMR-IR dataset. The superiority of the proposed technique is established by comparison to the performance of state-of-the-art competing methodologies. This study performed temperature emitted inflammatory area segmentation on thermal images of knees and breasts. The proposed segmentation method is of potential value in thermal image processing applications that require expediency and automation.

An exploration of the relationship between foot skin temperature and blood flow in type 2 diabetes mellitus patients: a cross-sectional study

[Purpose] The current study aimed to investigate the reliability of infrared thermography as a method of determining foot skin temperature, and to determine the relationship between foot skin temperature and blood flow in type 2 diabetes mellitus (DM) patients. [Participants and Methods] Eighty-five patients were recruited and their foot skin temperature and the ankle brachial index (ABI) were measured using infrared thermography and an automated oscillometry, respectively. A correlation between foot skin temperature and blood flow was performed. The patients were screened and classified according to two groups; diabetic peripheral neuropathy (DPN) and non-DPN. Discriminant validity was determined by comparing the foot skin temperature between the two groups. [Results] The test-retest reliability of foot skin temperature was high. A positive correlation was found between foot skin temperature and ABI in both feet. The foot skin temperatures in the DPN group were found to be significant lower when compared with those in the non-DPN group. [Conclusion] Foot skin temperature is an indirect method of evaluating blood flow in the feet of diabetic patients and can be used as a clinical outcome measurement of treatments used to improve blood flow in type 2 DM patients.

Prognostic value of infrared thermography in an emergency department

OBJECTIVE

In this study, we aimed to investigate the prognostic potential of infrared thermography in a population of medical patients admitted to the emergency department. Central-to-peripheral temperature gradients were analyzed for association with 30-day mortality.

METHODS

This prospective observational study included 198 medical patients admitted to the Emergency Department, at Odense University Hospital. A standardized thermal picture was taken and temperatures of the inner canthus, the earlobe, the nose tip, and the tip of the third finger were reported. The inner canthus was chosen as a marker for central temperature and the three others as markers for peripheral temperatures, resulting in three gradients per patient. Thirty-day follow-up was performed and 30-day mortality was reported.

RESULTS

One hundred and ninety-eight patients were included and the number of events was nine. The gradient between the inner canthus and the nose tip (ΔN) and the gradient between the inner canthus and the fingertip (ΔF) showed a significant association with 30-day mortality (ΔN: odds ratio: 1.31; 95% confidence interval: 1.05-1.64 and ΔF: odds ratio: 1.27; 95% confidence interval: 1.02-1.57).

CONCLUSION

ΔN and ΔF showed a significant association with 30-day mortality, suggesting a prognostic value. However, this was a small pilot study with few events. Larger studies are warranted for confirmation of these findings.

Best practices for standardized performance testing of infrared thermographs intended for fever screening

Infrared (IR) modalities represent the only currently viable mass fever screening approaches for outbreaks of infectious disease pandemics such as Ebola virus disease and severe acute respiratory syndrome. Non-contact IR thermometers (NCITs) and IR thermographs (IRTs) have been used for fever screening in public areas such as airports. While NCITs remain a more popular choice than IRTs, there has been increasing evidences in the literature that IRTs can provide great accuracy in estimating body temperature if qualified systems are used and appropriate procedures are consistently applied. In this study, we addressed the issue of IRT qualification by implementing and evaluating a battery of test methods for objective, quantitative assessment of IRT performance based on a recent international standard (IEC 80601-2-59). We tested two commercial IRTs to evaluate their stability and drift, image uniformity, minimum resolvable temperature difference, and radiometric temperature laboratory accuracy. Based on these tests, we illustrated how experimental and data processing procedures could affect results, and suggested methods for clarifying and optimizing test methods. Overall, the insights into thermograph standardization and acquisition methods provided by this study may improve the utility of IR thermography and aid in comparing IRT performance, thus improving the potential for producing high quality disease pandemic countermeasures.

The identification of higher forefoot temperatures associated with peripheral arterial disease in type 2 diabetes mellitus as detected by thermography

AIMS

The purpose of this study was to investigate whether heat emitted from the feet of patients with type 2 diabetes (DM) and peripheral arterial disease (PAD) differed from those with type 2 diabetes without complications (DM).

METHODS

A non-experimental, comparative prospective study design was employed in a tertiary referral hospital. Out of 223 randomly selected participants (430 limbs) who were initially tested, 62 limbs were categorized as DM+PAD and 22 limbs as DM without PAD. Subjects with evidence of peripheral neuropathy were excluded. Participants underwent thermographic imaging. Automatic segmentation of regions of interest extracted the temperature data.

RESULTS

A significant difference in temperature in all the toes between the two groups was found (p=0.005, p=0.033, p=0.015, p=0.038 and p=0.02 for toes 1-5 respectively). The mean forefoot temperature in DM+PAD was significantly higher than that in DM (p=.019), with DM+PAD having a higher mean temperature (28.3°C) compared to DM (26.2°C). Similarly, the toes of subjects with DM+PAD were significantly warmer than those of subjects with DM only.

CONCLUSIONS

Contrary to expectations the mean toe and forefoot temperatures in DM patients with PAD is higher than in those with DM only. This unexpected result could be attributed to disruption of noradrenergic vasoconstrictor thermoregulatory mechanisms with resulting increased flow through cutaneous vessels and subsequent increased heat emissivity. These results demonstrate that thermography may have potential in detecting PAD and associated temperature differences.

Reliability of a novel thermal imaging system for temperature assessment of healthy feet

Background

Thermal imaging is a useful modality for identifying preulcerative lesions (“hot spots”) in diabetic foot patients. Despite its recognised potential, at present, there is no readily available instrument for routine podiatric assessment of patients at risk. To address this need, a novel thermal imaging system was recently developed. This paper reports the reliability of this device for temperature assessment of healthy feet.

Methods

Plantar skin foot temperatures were measured with the novel thermal imaging device (Diabetic Foot Ulcer Prevention System (DFUPS), constructed by Photometrix Imaging Ltd) and also with a hand-held infrared spot thermometer (Thermofocus® 01500A3, Tecnimed, Italy) after 20 min of barefoot resting with legs supported and extended in 105 subjects (52 males and 53 females; age range 18 to 69 years) as part of a multicentre clinical trial. The temperature differences between the right and left foot at five regions of interest (ROIs), including 1st and 4th toes, 1st, 3rd and 5th metatarsal heads were calculated. The intra-instrument agreement (three repeated measures) and the inter-instrument agreement (hand-held thermometer and thermal imaging device) were quantified using intra-class correlation coefficients (ICCs) and the 95% confidence intervals (CI).

Results

Both devices showed almost perfect agreement in replication by instrument. The intra-instrument ICCs for the thermal imaging device at all five ROIs ranged from 0.95 to 0.97 and the intra-instrument ICCs for the hand-held-thermometer ranged from 0.94 to 0.97. There was substantial to perfect inter-instrument agreement between the hand-held thermometer and the thermal imaging device and the ICCs at all five ROIs ranged between 0.94 and 0.97.

Conclusions

This study reports the performance of a novel thermal imaging device in the assessment of foot temperatures in healthy volunteers in comparison with a hand-held infrared thermometer. The newly developed thermal imaging device showed very good agreement in repeated temperature assessments at defined ROIs as well as substantial to perfect agreement in temperature assessment with the hand-held infrared thermometer. In addition to the reported non-inferior performance in temperature assessment, the thermal imaging device holds the potential to provide an instantaneous thermal image of all sites of the feet (plantar, dorsal, lateral and medial views).

Trial registration

Diabetic Foot Ulcer Prevention System NCT02317835, registered December 10, 2014

Reliability of Infrared Thermography Images in the Analysis of the Plantar Surface Temperature in Diabetes Mellitus

Objective

The purpose of this study was to evaluate the intraexaminer and interexaminer reliability of image assessment of infrared thermography of the plantar surface of people with diabetes mellitus.

Methods

Fifty-one participants with diabetes were included. The interexaminer reliability (test) consisted of measuring the temperature of the plantar surface by 2 evaluators who separately performed the analysis of thermographic images. The intraexaminer reliability (retest) consisted of the revaluation of the images by a single evaluator 10 days after the first analysis.

Results

The analysis of intrareliability and interreliability indicated excellent levels of correlation (intraclass correlation coefficient >0.75, 95% confidence interval >0.70) in the plantar surface points analyzed.

Conclusion

Infrared thermography image evaluation identified intrareliability and interreliability for temperature analysis of the plantar surface of people with diabetes mellitus. However, further studies need to be conducted to assess validity and its application in health care.

Peripheral circulatory disorders in essential thrombocythemia

A significant number of patients with essential thrombocythemia (ET) complain of symptoms including distal parts of the extremities (e.g., paresthesias or Raynaud's phenomenon). The aim of the present study was to examine peripheral circulation in the upper extremities of individuals with ET. The study included 45 ET patients and 30 control subjects. All participants were subjected to thermography, photoplethysmography, impedance plethysmography, and applanation tonometry pulse wave analysis. The patients with ET differed significantly from the control subjects in terms of 3rd finger skin temperature (mean 31.04 vs. 32.45°C), skin temperature gradient (mean 1.82 vs. 0.11°C), photoplethysmographic amplitude (median 0.25 vs. 0.74%), and pulse waveform in the radial artery (more frequent occurrence of type B waveform). Pulse wave parameters correlated with the skin temperature gradient. The study findings imply the altered regulation of peripheral circulation in ET, including a decreased flow and an increased resistance.

Applications of Infrared Thermography for Noncontact and Noninvasive Mass Screening of Febrile International Travelers at Airport Quarantine Stations

Infrared thermography (IRT), one of the most valuable tools, is used for noncontact, noninvasive, and rapid monitoring of body temperature; this has been used for mass screening of febrile travelers at places such as airport quarantine stations for over 10 years after the 2003 severe acute respiratory syndrome (SARS) outbreak. The usefulness of thermography for mass screening has been evaluated in many recent studies; its sensitivity varies from 40 to 89.4% under various circumstances. In this chapter, we perform IRT evaluations for detecting febrile international travelers entering Japan at Nagoya Airport, immediately after the SARS epidemic, from June 2003 to February 2004, and at Naha International Airport from April 2005 to March 2009. The correlation of body surface temperature measured via thermography with the axillary temperature was significant. Through IRT, febrile individuals were detected with good accuracy and the detection accuracy was improved by corroborating surveillance with self-reporting questionnaires. However, there are several limitations associated with the use of IRT for fever screening. For instance, taking antifebrile medications results in rapid modification of the body temperature and directly affects the efficiency of IRT. To solve this unreliability and obtain higher accuracy in mass screening, we have developed a novel infection screening system using multisensor data, i.e., heart and respiration rates are determined by microwave radar in noncontact manner and facial skin temperature is monitored through IRT. The detection accuracy of the system improved, which is notably higher compared to the conventional screening method using only IRT.

Thermal Imaging in Medical Science

Thermal imaging is a non-destructive, non-contact and rapid system. It reports temperature through measuring infrared radiation emanated by an object/ material surface. Automated thermal imaging system involves thermal camera equipped with infrared detectors, signal processing unit and image acquisition system supported by computer. It is elaborated in wide domains applications. Extensive focus is directed to the thermal imaging in the medical domain especially breast cancer detection. This chapter provided the main concept and the different applications of thermal imaging. It explores and analyses several works in the light of studding the thermograph. It is an effective screening tool for breast cancer prediction. Studies justify that thermography can be considered a complementary tool to detect breast diseases. The current chapter reviews many usages and limitations of thermography in biomedical field. Extensive recommendations for future directions are summarized to provide a structured vision of breast thermography.

Supportive Noninvasive Tool for the Diagnosis of Breast Cancer Using a Thermographic Camera as Sensor

Breast cancer is the leading disease in incidence and mortality among women in developing countries. The opportune diagnosis of this disease strengthens the survival index. Mammography application is limited by age and periodicity. Temperature is a physical magnitude that can be measured by using multiple sensing techniques. IR (infrared) thermography using commercial cameras is gaining relevance in industrial and medical applications because it is a non-invasive and non-intrusive technology. Asymmetrical temperature in certain human body zones is associated with cancer. In this paper, an IR thermographic sensor is applied for breast cancer detection. This work includes an automatic breast segmentation methodology, to spot the hottest regions in thermograms using the morphological watershed operator to help the experts locate the tumor. A protocol for thermogram acquisition considering the required time to achieve a thermal stabilization is also proposed. Breast thermograms are evaluated as thermal matrices, instead of gray scale or false color images, increasing the certainty of the provided diagnosis. The proposed tool was validated using the Database for Mastology Research and tested in a voluntary group of 454 women of different ages and cancer stages with good results, leading to the possibility of being used as a supportive tool to detect breast cancer and angiogenesis cases.