Infrared Thermography Sensor for Disease Activity Detection in Rheumatoid Arthritis Patients

Chronic Pain and Joint Hypermobility: A Brief Diagnostic Review for Clinicians and the Potential Application of Infrared Thermography in Screening Hypermobile Inflamed Joints

Joint hypermobility syndromes, particularly chronic pain associated with this condition, including Hypermobile Ehlers-Danlos Syndrome (hEDS) and Hypermobility Spectrum Disorders (HSD), present diagnostic challenges due to their multifactorial origins and remain poorly understood from biomechanical and genomic-molecular perspectives. Recent diagnostic guidelines have differentiated hEDS, HSD, and benign joint hypermobility, providing a more objective diagnostic framework. However, incorrect diagnoses and underdiagnoses persist, leading to prolonged journeys for affected individuals. Musculoskeletal manifestations, chronic pain, dysautonomia, and gastrointestinal symptoms illustrate the multifactorial impact of these conditions, affecting both the physical and emotional well-being of affected individuals. Infrared thermography (IRT) emerges as a promising tool for joint assessment, especially in detecting inflammatory processes. Thermal distribution patterns offer valuable insights into joint dysfunctions, although the direct correlation between pain and inflammation remains challenging. The prevalence of neuropathies among hypermobile individuals accentuates the discordance between pain perception and thermographic findings, further complicating diagnosis and management. Despite its potential, the clinical integration of IRT faces challenges, with conflicting evidence hindering its adoption. However, studies demonstrate objective temperature disparities between healthy and diseased joints, especially under dynamic thermography, suggesting its potential utility in clinical practice. Future research focused on refining diagnostic criteria and elucidating the underlying mechanisms of hypermobility syndromes will be essential to improve diagnostic accuracy and enhance patient care in this complex and multidimensional context.

Subclinical joint inflammation in rheumatoid arthritis: comparing thermal and ultrasound imaging at the metacarpophalangeal joint

BACKGROUND

While ultrasound and MRI are both superior to clinical examination in the detection of joint inflammation, there is presently a lack of data whether thermography may be similarly useful in the assessment of joint inflammation in patients with RA. Our study aims to evaluate the use of thermography in detecting subclinical joint inflammation at clinically quiescent (non-tender and non-swollen) metacarpophalangeal joints (MCPJs) in patients with rheumatoid arthritis (RA). The outcomes from thermography in our study will be compared with ultrasonography (which is a more established imaging tool used for joint inflammation assessment in RA).

METHODS

The minimum (Tmin), average (Tavg) and maximum (Tmax) temperatures at the 10 MCPJs of each patient were summed to obtain the Total Tmin, Total Tavg and Total Tmax, respectively. Ultrasound grey-scale (GS) and power Doppler (PD) joint inflammation (scored semi-quantitatively, 0-3) at the 10 MCPJs were summed up to derive the respective TGS and TPD scores per patient. Pearson's correlation and simple linear regression were respectively used to assess correlation and characterize relationships between thermographic parameters (Total Tmin, Total Tavg and Total Tmax) and ultrasound imaging parameters (TGS, TPD and the number of joint(s) with PD ≥ 1 or GS ≥ 2).

RESULTS

In this cross-sectional study, 420 clinically non-swollen and non-tender MCPJs from 42 RA patients were examined. All thermographic parameters (Total Tmin, Total Tavg and Total Tmax) correlated significantly (P-values ranging from 0.001 to 0.0012) with TGS score (correlation coefficient ranging from 0.421 to 0.430), TPD score (correlation coefficient ranging from 0.383 to 0.424), and the number of joint(s) with PD ≥ 1 or GS ≥ 2 (correlation coefficient ranging from 0.447 to 0.465). Similarly, simple linear regression demonstrated a statistically significant relationship (P-values ranging from 0.001 to 0.005) between all thermographic parameters (Total Tmin, Total Tavg and Total Tmax) and ultrasound imaging parameters (TPD and TGS).

CONCLUSION

For the first time, thermographic temperatures were shown to correlate with ultrasound-detected joint inflammation at clinically quiescent MCPJs. The use of thermography in the detection of subclinical joint inflammation in RA appears promising and warrants further investigation.

Thermal profile classification of the back of sportive and sedentary healthy individuals

BACKGROUND

Infrared thermography (IRT) is a non-harmful, risk-free imaging technique and it has application for healthy and pathological population.

OBJECTIVE

The aim of this study is to evaluate the thermographic profiles of the back of sport practitioners from different disciplines and compare it with those of sedentary healthy individuals.

METHOD

The back of 160 healthy subjects were evaluated, and participants were grouped considering their sport practice: team sport (TS), individual sport (IS), weight training (WT), inactive (I). Three regions of interest were identified to analyze the cervical, thoracic and lumbar temperatures of the back.

RESULTS

The Multivariate analysis of variance (MANOVA) resulted significant showing statistical differences for the cervical (p < 0.001), dorsal (p = 0.0011), and lumbar areas (p = 0.0366). The Tukey post-hoc test for pairwise comparison showed statistically significant differences between groups. For the cervical area significance was found between the IN and WT group (p = 0.002), the IN and IS group (p < 0.001), IN and TS group (p = 0.020). The dorsal area resulted significant between the IN and WT group (p = 0.007), the IN and IS group (p < 0.001), IN and TS group. The lumbar area showed significant differences only between the IN and WT group and the IN and IS group (p = 0.043).

CONCLUSION

This study demonstrated that inactive individuals manifest a statistically significant higher temperature in the cervical, dorsal and lumbar area of the back compared to sportive individuals.

Medical imaging in rheumatoid arthritis: A review on deep learning approach

Arthritis is a musculoskeletal disorder. Millions of people have arthritis, making it one of the most common joint disorders. Osteoarthritis (OA) and rheumatoid arthritis (RA) are the most common types of arthritis among the many different types available. Pain, stiffness, and inflammation are among the early signs of arthritis, which can progress to severe immobility at a later stage if left untreated. Although arthritis cannot be cured at any point in time, it can be managed if diagnosed and treated correctly. Clinical diagnostic and medical imaging methods are currently used to evaluate OA and RA, both debilitating conditions. This review is focused on deep learning approaches used by taking medical imaging (X-rays and magnetic resonance imaging) as input for the detection of RA.

Sex differences in long-term effects of collagen-induced arthritis in middle-aged mice

Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory disorder with high prevalence among middle-aged women. Collagen-induced arthritis (CIA) is the most widely used animal model of RA, however, sex differences and long-term effects of CIA in mice are poorly described in the literature. Aim: Therefore, the present study aimed to analyze the long-term effects of CIA on the joints of middle-aged mice of both sexes and to describe potential sex differences. Materials and methods: CIA was induced in middle-aged DBA/1J mice by immunization with bovine type II collagen and complete Freund's adjuvant. Saline was administered to control mice. Arthritis score assessment, plethysmometry, and thermal imaging of the joints were performed weekly for 15 weeks. Locomotor activity, micro-computed tomography, joint histology and biochemical analyses were performed at the end of the experiment. Results: Our results indicate a similar prevalence of arthritis in both sexes of mice-67% (8/12) of females and 89% (8/9) males with an earlier onset in males (day 14 vs. day 35). After the arthritis scores peaked on day 56 for males and day 63 for females, they steadily declined until the end of the experiment on day 105. A similar dynamics was observed in paw volume and temperature analyzing different aspects of joint inflammation. Long-term consequences including higher proteinuria (by 116%), loss of bone density (by 33.5%) and joint damage in terms of synovial hyperplasia as well as bone and cartilage erosions were more severe in CIA males compared to CIA females. There were no significant differences in locomotor activity between CIA mice and CTRL mice of any sex. Conclusion: This is the first study to describe the long-term effects of the CIA model in terms of sex differences in DBA/1J mice. Our results indicate sex differences in the dynamics, but not in the extent of arthritis. An earlier onset of arthritis and more severe consequences on joints, bones and kidneys were found in males. The underlying immune pathomechanisms responsible for the limited duration of the arthritis symptoms and the opposite sex difference in comparison to RA patients require further investigation.

Modification of the structural stability of human serum albumin in rheumatoid arthritis

Differential scanning calorimetry (DSC) can indicate changes in structure and/or concentration of the most abundant proteins in a biological sample via heat denaturation curves (HDCs). In blood serum for example, HDC changes result from either concentration changes or altered thermal stabilities for 7-10 proteins and has previously been shown capable of differentiating between sick and healthy human subjects. Here, we compare HDCs and proteomic profiles of 50 patients experiencing joint-inflammatory symptoms, 27 of which were clinically diagnosed with rheumatoid arthritis (RA). The HDC of all 50 subjects appeared significantly different from expected healthy curves, but comparison of additional differences between the RA and the non-RA subjects allowed more specific understanding of RA samples. We used mass spectrometry (MS) to investigate the reasons behind the additional HDC changes observed in RA patients. The HDC differences do not appear to be directly related to differences in the concentrations of abundant serum proteins. Rather, the differences can be attributed to modified thermal stability of some fraction of the human serum albumin (HSA) proteins in the sample. By quantifying differences in the frequency of artificially induced post translational modifications (PTMs), we found that HSA in RA subjects had a much lower surface accessibility, indicating potential ligand or protein binding partners in certain regions that could explain the shift in HSA melting temperature in the RA HDCs. Several low abundance proteins were found to have significant changes in concentration in RA subjects and could be involved in or related to binding of HSA. Certain amino acid sites clusters were found to be less accessible in RA subjects, suggesting changes in HSA structure that may be related to changes in protein-protein interactions. These results all support a change in behavior of HSA which may give insight into mechanisms of RA pathology.

What Influences Proprioceptive Impairments in Patients with Rheumatic Diseases? Analysis of Different Factors

Rheumatic diseases lead to postural problems, which increase the risk of falls and lead to greater disability. The aim of the present work is to evaluate posture disorders in patients with osteoarthritis (OA) and rheumatoid arthritis (RA), as well as to evaluate the influence of other factors. A total of 71 subjects were enrolled in this study. Joint position sense (JPS) and the functional assessment of proprioception on a balance platform for both lower limbs were examined. The Average Trace Error (ATE), test time (t), and Average Platform Force Variation (AFV) were calculated. Additionally, an equilibrium test was carried out in the one-legged standing position (Single Leg Stance-SLS). The results were compared in several ways and revealed the following: (1) A JPS of 10° plantar flexion in RA obtained significantly worse results when repeating the movement than OA; the ATEs were significantly lower in RA; and RA needed more support during SLS assessment. (2) RA patients with higher DAS28 had statistically significantly higher values in JPS, with 5° plantar flexion and 10° dorsal flexion, SLS assessment, and stabilometric rates. A statistically significant correlation between DAS28 and RA was found in a JPS of 10° plantar flexion. The VAS ruler demonstrated a significant moderate correlation with t. (3) Patients who experienced at least one fall demonstrated higher JPS and t. Our study shows that proprioception is the most influenced by the nature of the disease and the level of disease activity. We can see that the stability and balance functions are also greatly influenced by the patient's falling experience and the level of pain. These findings may be useful in designing an optimal proprioception-enhancing movement training plan.

Microwave Radiometry for the Diagnosis and Monitoring of Inflammatory Arthritis

The ability of microwave radiometry (MWR) to detect with high accuracy in-depth temperature changes in human tissues is under investigation in various medical fields. The need for non-invasive, easily accessible imaging biomarkers for the diagnosis and monitoring of inflammatory arthritis provides the background for this application in order to detect the local temperature increase due to the inflammatory process by placing the appropriate MWR sensor on the skin over the joint. Indeed, a number of studies reviewed herein have reported interesting results, suggesting that MWR is useful for the differential diagnosis of arthritis as well as for the assessment of clinical and subclinical inflammation at the individual large or small joint level and the patient level. MWR showed higher agreement with musculoskeletal ultrasound, used as a reference, than with clinical examination in rheumatoid arthritis (RA), while it also appeared useful for the assessment of back pain and sacroiliitis. Further studies with a larger number of patients are warranted to confirm these findings, taking into account the current limitations of the available MWR devices. This may lead to the production of easily accessible and inexpensive MWR devices that will provide a powerful impetus for personalized medicine.

Automated segmentation and classification of hand thermal images in rheumatoid arthritis using machine learning algorithms: A comparison with quantum machine learning technique

The aims and objectives of the study were to i) perform image segmentation using a color-based k-means clustering algorithm and feature extraction using binary robust invariant scalable key points (BRISK), maximum stable extremal regions (MSER), features from accelerated segment test (FAST), Harris, and orientated FAST and rotated BRIEF (ORB); ii) compare the performance of classical machine learning techniques such as LogitBoost, Bagging, and SVM with a quantum machine learning technique. For the proposed study, 240 hand thermal images were acquired in the dorsal view and ventral view of both the right and left-hand regions of RA and normal subjects. The hot spot regions from the thermograms were segmented using a color-based k-means clustering technique. The features from the segmented hot spot region were extracted using different feature extraction methods. Finally, normal and RA groups were categorized using LogitBoost, Bagging, and support vector machine (SVM) classifiers. The proposed study used two testing methods, such as 10-fold cross-validation and a percentage split of 80-20%. The LogitBoost classifier outperformed with an accuracy of 93.75% using the 10-fold cross-validation technique compared to other classifiers. Also, the quantum support vector machine (QSVM) obtained a prediction accuracy of 92.7%. Furthermore, the QSVM model reduces the computational cost and training time of the model to classify the RA and normal subjects. Thus, thermograms with classical machine learning and quantum machine learning algorithms could be considered a feasible technique for classifying normal and RA groups.

Receiver operating characteristic analysis using a novel combined thermal and ultrasound imaging for assessment of disease activity in rheumatoid arthritis

We aim to determine whether combined thermal and ultrasound (CTUS) imaging can identify rheumatoid arthritis (RA) patients with at least moderate disease activity (DAS28 > 3.2). Temperature differences of maximum (T_max), average (T_avg) and minimum (T_min) temperatures from a control temperature at 22 joints (bilateral hands) were summed up to derive the respective MAX, AVG and MIN per patient. MAX (PD), AVG (PD) and MIN (PD) are CTUS results derived by multiplying MAX, AVG and MIN by a factor of 2 when a patient's total ultrasound power Doppler (PD) joint inflammation score > median score, which otherwise remained unchanged. Receiver operating characteristic (ROC) analysis was used to determine whether CTUS imaging can identify patients with DAS28 > 3.2. In this cross-sectional study, 814 joints were imaged among 37 RA patients (mean disease duration, 31 months). CTUS (but not single modality) imaging parameters were all significantly greater comparing patients with DAS28 > 3.2 versus those with DAS28 ≤ 3.2 (all P < 0.01). Area under the ROC curves (AUCs) using cut-off levels of ≥ 94.5, ≥ 64.6 and ≥ 42.3 in identifying patients with DAS28 > 3.2 were 0.73 , 0.76 and 0.76 for MAX (PD), AVG (PD) and MIN (PD), respectively (with sensitivity ranging from 58 to 61% and specificity all 100%). The use of CTUS in detecting a greater severity of joint inflammation among patients with at least moderate disease activity (DAS28 > 3.2) appears promising and will require further validation in independent RA cohorts.

An update on thermal imaging in rheumatoid arthritis

This review aims to summarise the recent literature concerning the usage of thermal imaging in the study of rheumatoid arthritis (RA). Most RA studies have applied thermal imaging as a static process alone although thermal imaging has been conducted with an additional dynamic/functional component. Algorithms to automate the analysis of thermal imaging in RA have also been described. Several RA thermal imaging studies have demonstrated differences in thermographic findings between RA patients and healthy controls and/or compared thermographic parameters with other clinical/functional/imaging parameters; while fewer studies have assessed the role of thermal imaging in discriminating disease severity in RA. Thermal imaging is a relatively low cost, non-invasive imaging technique offering an objective measurement of joint surface temperature in RA joint inflammation assessment. Although there has been an increasing literature build up on the use of thermography in RA, more validation work is still necessary to delineate the potential role(s) of its use among patients with RA. This timely review focusses on the recent literature concerning thermal imaging, and provides clinicians with an update on its recent development in RA.

A Feasible Multimodal Photoacoustic Imaging Approach for Evaluating the Clinical Symptoms of Inflammatory Arthritis

Numerous traditional medical imaging methods, including computed tomography with X-rays, positron emission tomography (PET), and magnetic resonance imaging (MRI), are utilized frequently in medical settings to screen for illnesses, diagnose patients, and track the effectiveness of treatments. When examining bone protrusions, CT is preferred over MRI for scanning connective tissue. Although the picture quality of PET is inferior to that of CT and MR, it is outstanding for detecting the molecular markers and metabolic functions of illnesses. To give high-resolution structural pictures and improved ailment sensitivity and specificity within another image, multimodal data and substantial therapeutic influence on advanced diagnostics and therapeutics have been used. The goal was to evaluate the clinical significance of multimodal photoacoustic/ultrasound (PA/US) articular imaging scoring, a cutting-edge image technique that may show the microvessels and oxygen levels of rheumatoid arthritis-related inflamed joints (RA). The PA/US imaging technology analyzed seven tiny joints. The PA and power Doppler (PD) impulses were semiquantified using a 0-3 grading scale, and the averages of the PA and PD scores for the seven joints are computed. Three PA+SO2 types were found determined by the relative oxygen levels (SO2) measurements of the affected joints. Researchers evaluated the relationships between the disease activity ratings and the PA/US imaging ratings. The PA scores and medical ratings that reflect the extent of the pain have strong relationships with each other, as do the PA+SO2 combinations. PA may be clinically useful in assessing RA. Thus, the research evaluated the clinical symptoms of inflammatory arthritis using a multimodal photoacoustic image process.

Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review

Investigation of the potential applications of artificial intelligence (AI), including machine learning (ML) and deep learning (DL) techniques, is an exponentially growing field in medicine and healthcare. These methods can be critical in providing high-quality care to patients with chronic rheumatological diseases lacking an optimal treatment, like rheumatoid arthritis (RA), which is the second most prevalent autoimmune disease. Herein, following reviewing the basic concepts of AI, we summarize the advances in its applications in RA clinical practice and research. We provide directions for future investigations in this field after reviewing the current knowledge gaps and technical and ethical challenges in applying AI. Automated models have been largely used to improve RA diagnosis since the early 2000s, and they have used a wide variety of techniques, e.g., support vector machine, random forest, and artificial neural networks. AI algorithms can facilitate screening and identification of susceptible groups, diagnosis using omics, imaging, clinical, and sensor data, patient detection within electronic health record (EHR), i.e., phenotyping, treatment response assessment, monitoring disease course, determining prognosis, novel drug discovery, and enhancing basic science research. They can also aid in risk assessment for incidence of comorbidities, e.g., cardiovascular diseases, in patients with RA. However, the proposed models may vary significantly in their performance and reliability. Despite the promising results achieved by AI models in enhancing early diagnosis and management of patients with RA, they are not fully ready to be incorporated into clinical practice. Future investigations are required to ensure development of reliable and generalizable algorithms while they carefully look for any potential source of bias or misconduct. We showed that a growing body of evidence supports the potential role of AI in revolutionizing screening, diagnosis, and management of patients with RA. However, multiple obstacles hinder clinical applications of AI models. Incorporating the machine and/or deep learning algorithms into real-world settings would be a key step in the progress of AI in medicine.

Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos

Shock is one of the major killers in intensive care units, and early interventions can potentially reverse it. In this study, we advance a noncontact thermal imaging modality for continuous monitoring of hemodynamic shock working on 1,03,936 frames from 406 videos recorded longitudinally upon 22 pediatric patients. Deep learning was used to preprocess and extract the Center-to-Peripheral Difference (CPD) in temperature values from the videos. This time-series data along with the heart rate was finally analyzed using Long-Short Term Memory models to predict the shock status up to the next 6 h. Our models achieved the best area under the receiver operating characteristic curve of 0.81 ± 0.06 and area under the precision-recall curve of 0.78 ± 0.05 at 5 h, providing sufficient time to stabilize the patient. Our approach, thus, provides a reliable shock prediction using an automated decision pipeline that can provide better care and save lives.

Skin Temperature of Acupoints in Health and Disease: A Systematic Review

Introduction: Despite substantial progress made in the field of acupuncture research, the existence and specificity of acupoints remain controversial. In recent years, the concept of acupoint sensitization has emerged as a theoretical framework for understanding acupoints as dynamic functional entities that are sensitized in pathological conditions. Based on this premise, some have claimed that specific acupoints are thermally distinct between healthy and clinical populations, but no systematic review has been conducted to synthesize and evaluate the quality of studies supporting such claims. In this review, we provide a summary and quality assessment of the existing literature addressing the question of whether changes in skin temperature at specific acupoints are indicative of pathological conditions. Methods: A systematic literature search was performed in PubMed, EMBASE, and AltHealthWatch (EBSCO Host), by combining variations of search terms relevant to acupoints and temperature. The search was limited to the English language, and publication dates ranged from database inception to December 2020. Two authors independently screened all resulting abstracts and subsequently read full-text articles for eligibility. Information on study design, sample, acupoints, parameters of skin temperature assessments, and main findings were extracted from included studies. Quality of the thermal sensing methodology was evaluated using a thermal assessment checklist, adapted from the Thermographic Imaging in Sports and Exercise Medicine (TISEM) consensus checklist, and a modified Newcastle-Ottawa Scale (NOS) for case-control studies. Results: The search strategy yielded a total of 1771 studies, of which 10 articles met the eligibility criteria. Eight studies compared skin temperature at acupoints in healthy versus clinical populations, and two studies assessed within-subject changes in temperature of acupoints in relation to changes in health status. There were seven clinical conditions examined in the included studies: chronic bronchial asthma, chronic hepatitis, hyperplasia of mammary glands, infertility, intracranial hypertension, obesity, and primary dysmenorrhea. There were numerous methodological quality issues related to skin temperature measurements. Eight studies with case-control designs reported significant differences between healthy and clinical populations in temperature at certain acupoints. Two studies with pre-post designs reported that changes in health-disease status could be associated with changes in temperature at specific acupoints. Conclusion: A review of the available literature suggests that certain acupoints may be thermally distinct between healthy and unhealthy states. However, given the methodological limitations and heterogeneity across included studies, no definitive conclusion could be drawn as to whether changes in skin temperature at specific acupoints are indicative of pathological conditions.

The Value of Thermal Imaging for Knee Arthritis: A Single-Center Observational Study

PURPOSE

To compare (non-contact) thermal imaging with power Doppler (PD) for the evaluation of knee arthritis with joint effusion.

MATERIALS AND METHODS

We enrolled patients with knee arthritis who were scheduled to undergo an arthrocentesis of the knee from April to December 2020 at a single tertiary hospital. A thermography camera, FLIR ONE Pro, was used to obtain both thermographic and digital images on subjects. For each subject, thermography, ultrasonography, arthrocentesis, and blood tests were conducted at the same study visit. Thermal imaging findings and clinical characteristics were compared by dividing the subjects into PD-positive and PD-negative groups on ultrasound. The receiver operating characteristic (ROC) curve analysis was used to determine the accuracy of PD positivity.

RESULTS

A total of 30 knee arthritis patients were enrolled in this study. Knee temperature was significantly higher in PD-positive group compared to PD-negative group [maximum temperature (T max): 33.2℃ vs. 30.5℃, p=0.025; minimum temperature (T min): 30.7℃ vs. 27.0℃, p=0.015; average temperature (T ave): 32.1℃ vs. 29.1℃, p=0.016]. Also, the joint fluid white blood cell count was considerably higher in PD-positive group than in PD-negative group (24556 cells/mm³ vs. 7840 cells/mm³, p=0.010). The area under the ROC curve of the point measurement of T max, T min, and T ave ranged between 0.764 and 0.790.

CONCLUSION

In this study, we found that high thermographic temperatures of the knee suggest a positive PD signal. Thus, thermography might be used as an adjuvant tool of PD for non-invasive evaluation of knee arthritis.

A computational method to differentiate rheumatoid arthritis patients using thermography data

BACKGROUND

The traditional rheumatoid arthritis (RA) diagnosis is very complicated because it uses many clinical and image data. Therefore, there is a need to develop a new method for diagnosing RA using a consolidated set of blood analysis and thermography data.

OBJECTIVE

The following issues related to RA are discussed: 1) Which clinical data are significant in the primary diagnosis of RA? 2) What parameters from thermograms should be used to differentiate patients with RA from the healthy? 3) Can artificial neural networks (ANN) differentiate patients with RA from the healthy?

METHODS

The dataset was composed of clinical and thermal data from 65 randomly selected patients with RA and 104 healthy subjects. Firstly, the univariate logistic regression model was proposed in order to find significant predictors. Next, the feedforward neural network model was used. The dataset was divided into the training set (75% of data) and the test set (25% of data). The Broyden-Fletcher-Goldfarb-Shanno (BFGS) and non-linear logistic function to transformation nodes in the output layer were used for training. Finally, the 10 fold Cross-Validation was used to assess the predictive performance of the ANN model and to judge how it performs.

RESULT

The training set consisted of the temperature of all fingers, patient age, BMI, erythrocyte sedimentation rate, C-reactive protein and White Blood Cells (10 parameters in total). High level of sensitivity and specificity was obtained at 81.25% and 100%, respectively. The accuracy was 92.86%.

CONCLUSIONS

This methodology suggests that the thermography data can be considered in addition to the currently available tools for screening, diagnosis, monitoring of disease progression.

Infrared Thermography and Ultrasonography of the Hands in Rheumatoid Arthritis Patients

Ultrasonography (US) and power Doppler US (PDUS) are used worldwide for diagnosing rheumatoid arthritis (RA). Superb microvascular imaging (SMI) is a good tool for evaluating inflammatory activity. Thermal imaging is a noncontact, noninvasive procedure using skin temperature measurement. We report a case wherein the thermal and ultrasound images of the hand are compared and evaluated for inflammatory activity in patients with RA. Case: US imaging of the left hand of a 75-year-old woman with RA revealed a hypoechoic lesion of the left wrist joint. PDUS and SMI evaluated blood flow according to the blood flow at Grade 2. The temperature of the hypoechoic lesion with high blood flow was higher than that of the same location on the opposite side. This study shows that combining thermal and blood flow images may be useful for detecting inflammatory activity levels in RA patients.

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.

Palm Temperature Differences after Static and Dynamic Load on High Bar

Thermal imaging is used in various fields of industry and research to measure temperature and its possible differences. Since there is a lack of research and literature on palm temperatures and prevention of blisters on hands, our question was how palm temperature differs in human hands after different loads (Hang and Swing in Hang) for 30 s on a high bar. Thirty-eight students from the Faculty of Sport at the University of Ljubljana were measured with a high-quality thermal imaging camera. Palm temperatures were measured before the load was applied, immediately after and every 30 s for a period of 5 min after the load. Each hand was divided into nine different regions of interest (ROIs). Mean (XA), standard deviation (SD), maximum and minimum, and number of pixels were calculated. We found that there was no difference between the left and right hand. The temperature right after the load was applied decreased significantly for both loads and then increased above the level before the load was applied. After the static load, the temperature reached a constant higher level after 3 min. After the dynamic load, the temperatures continued to increase throughout the measurement period. Further investigation is needed to determine the time period in which the hand temperature reaches the temperature before the load is applied.

Ocular surface temperature differences in glaucoma

PURPOSE

Accumulating evidence suggests that neuroinflammation and immune response are part of the sequence of pathological events leading to optic nerve damage in glaucoma. Changes in tissue temperature due to inflammation can be measured by thermographic imaging. We investigated the ocular surface temperature (OST) profile of glaucomatous eyes to better understand the pathophysiology of these conditions.

METHODS

Subjects diagnosed with glaucoma (primary open angle glaucoma [POAG] or pseudo exfoliation glaucoma [PXFG]) treated at the Sam Rothberg Glaucoma Center (11/2019-11/2020.) were recruited. Healthy subjects with no ocular disease served as controls. The Therm-App thermal imaging camera was used for OST acquisition. Room and body temperatures were recorded, and the mean temperatures of the medial cantus, lateral cantus, and cornea were calculated with image processing software.

RESULTS

Thermographic images were obtained from 52 subjects (52 eyes: 25 POAG and 27 PXFG) and 66 controls (66 eyes). Eyes with glaucoma had a significantly higher OST compared to controls (mean 0.9 ± 0.3°C, p < 0.005). The difference between the two groups remained significant after adjustment for age, sex, intraocular pressure (IOP) and room and body temperatures. Lens status and topical IOP-lowering medication did not significantly affect OST. A subgroup analysis revealed that the OST was higher among eyes with POAG compared to eyes with PXFG, but not significantly.

CONCLUSIONS

Differences in the OST between glaucomatous and normal eyes strengthens current thinking that inflammation affects the pathophysiology of glaucoma. Longitudinal studies are warranted to establish the prognostic value of thermographic evaluations in these patients.

Thermography as a non-ionizing quantitative tool for diagnosing periapical inflammatory lesions

Background

Thermography is a contemporary imaging modality based on acquiring and analyzing thermal data using non-contact devices. The aim of the present study was to assess the validity of thermography, compared with that of the reference-standard, for the diagnosis of periapical inflammatory lesions and to evaluate the temperature ranges for acute pulpitis with apical periodontitis (AAP), acute periapical abscess (AA) and chronic periapical abscess (CA).

Methods

AAP, AA and CA were diagnosed based on clinical and radiographic criteria. Thermographic data were acquired using the FLIR E-5 Infrared Camera. Extraoral thermal images were taken from the front and right and left sides of patients whose mouths were closed, and one intraoral thermal image was taken from the palatal perspective. Agreement in the diagnoses based on the combination of clinical and radiographic assessments and the thermographic evaluation was calculated. The temperature ranges of the three diagnostic subgroups were also measured.

Results

A total of 80 patients were enrolled in this study. The mean intraoral thermal image temperature for AA was 37.26 ± 0.36, that for CA was 35.03 ± 0.63 and that for AAP was 36.07 ± 0.45. The differences between the mean intraoral thermal temperatures of the three diagnostic groups were statistically significant (P < 0.001). The result of the Kappa coefficient of agreement between the combination of clinical and radiographic assessments and the thermographic evaluation was significant (P < 0.001).

Conclusions

Thermography is an effective, quantitative and nonionizing approach that can be used for the diagnosis of periapical inflammatory lesions. The results of the present study indicated that the highest thermal image temperatures were recorded for AA. Thermography might be able to detect inflammatory reactions during the preclinical stage, leading to early diagnosis.

Molecular Imaging of Inflammatory Disease

Inflammatory diseases include a wide variety of highly prevalent conditions with high mortality rates in severe cases ranging from cardiovascular disease, to rheumatoid arthritis, to chronic obstructive pulmonary disease, to graft vs. host disease, to a number of gastrointestinal disorders. Many diseases that are not considered inflammatory per se are associated with varying levels of inflammation. Imaging of the immune system and inflammatory response is of interest as it can give insight into disease progression and severity. Clinical imaging technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) are traditionally limited to the visualization of anatomical information; then, the presence or absence of an inflammatory state must be inferred from the structural abnormalities. Improvement in available contrast agents has made it possible to obtain functional information as well as anatomical. In vivo imaging of inflammation ultimately facilitates an improved accuracy of diagnostics and monitoring of patients to allow for better patient care. Highly specific molecular imaging of inflammatory biomarkers allows for earlier diagnosis to prevent irreversible damage. Advancements in imaging instruments, targeted tracers, and contrast agents represent a rapidly growing area of preclinical research with the hopes of quick translation to the clinic.

Power-Oriented Monitoring of Clock Signals in FPGA Systems for Critical Application

This paper presents a power-oriented monitoring of clock signals that is designed to avoid synchronization failure in computer systems such as FPGAs. The proposed design reduces power consumption and increases the power-oriented checkability in FPGA systems. These advantages are due to improvements in the evaluation and measurement of corresponding energy parameters. Energy parameter orientation has proved to be a good solution for detecting a synchronization failure that blocks logic monitoring circuits. Key advantages lay in the possibility to detect a synchronization failure hidden in safety-related systems by using traditional online testing that is based on logical checkability. Two main types of power-oriented monitoring are considered: detecting a synchronization failure based on the consumption and the dissipation of power, which uses temperature and current consumption sensors, respectively. The experiments are performed on real FPGA systems with the controlled synchronization disconnection and the use of the computer-aided design (CAD) utility to estimate the decreasing values of the energy parameters. The results demonstrate the limited checkability of FPGA systems when using the thermal monitoring of clock signals and success in monitoring by the consumption current.

Refinement and validation of infrared thermal imaging (IRT): a non-invasive technique to measure disease activity in a mouse model of rheumatoid arthritis

Background

The discovery and development of new medicines requires high-throughput screening of possible therapeutics in a specific model of the disease. Infrared thermal imaging (IRT) is a modern assessment method with extensive clinical and preclinical applications. Employing IRT in longitudinal preclinical setting to monitor arthritis onset, disease activity and therapeutic efficacies requires a standardized framework to provide reproducible quantitative data as a precondition for clinical studies.

Methods

Here, we established the accuracy and reliability of an inexpensive smartphone connected infrared (IR) camera against known temperature objects as well as certified blackbody calibration equipment. An easy to use protocol incorporating contactless image acquisition and computer-assisted data analysis was developed to detect disease-related temperature changes in a collagen-induced arthritis (CIA) mouse model and validated by comparison with two conventional methods, clinical arthritis scoring and paw thickness measurement. We implemented IRT to demonstrate the beneficial therapeutic effect of nanoparticle drug delivery versus free methotrexate (MTX) in vivo.

Results

The calibrations revealed high accuracy and reliability of the IR camera for detecting temperature changes in the rheumatoid arthritis animal model. Significant positive correlation was found between temperature changes and paw thickness measurements as the disease progressed. IRT was found to be superior over the conventional techniques specially at early arthritis onset, when it is difficult to observe subclinical signs and measure structural changes.

Conclusion

IRT proved to be a valid and unbiased method to detect temperature changes and quantify the degree of inflammation in a rapid and reproducible manner in longitudinal preclinical drug efficacy studies.

A novel use of combined thermal and ultrasound imaging in detecting joint inflammation in rheumatoid arthritis

PURPOSE

To evaluate the use of combined thermal and ultrasound imaging to assess joint inflammation in rheumatoid arthritis (RA).

METHOD

22-joint (bilateral hands) thermography and ultrasonography were performed. For each patient, the MAX, MIN and AVG represent the sum of the temperature differences with a control temperature, for the respective maximum (Tmax), minimum (Tmin) and average (Tavg) temperatures at the joints. MAX (PD), MIN (PD) and AVG (PD) represent the results of combined thermal imaging with a patient's total ultrasound power Doppler (PD) joint inflammation score (Total PD) (when Total PD > median score, MAX, MIN and AVG was multiplied by a factor of 2, otherwise MAX (PD), MIN (PD) and AVG (PD) remained the same as the MAX, MIN and AVG). Pearson correlation and linear regression were used to assess correlation and characterize relationships of imaging parameters with the 28-joint disease activity score (DAS28).

RESULTS

In this cross-sectional study, 814 joints were examined in 37 adult RA patients (75.7 % female, 75.7 % Chinese; mean DAS28, 4.43). Among the imaging parameters, only MAX (PD) and AVG (PD) correlated significantly with DAS28 (correlation coefficient (95 % CI): MAX (PD), 0.393 (0.079, 0.636), P = 0.016; AVG (PD): 0.376 (0.060, 0.624), P = 0.022). Similarly, only MAX (PD) and AVG (PD) demonstrated a statistically significant relationship with DAS28 (regression coefficient (95 % CI): MAX (PD), 0.009 (0.002, 0.015), P = 0.016; AVG (PD), 0.011 (0.002, 0.020), P = 0.022).

CONCLUSIONS

Novel use of combined thermal and ultrasound imaging in RA shows superiority to either imaging alone in terms of correlation with DAS28.

Nanomechanical Properties of Articular Cartilage Due to the PRP Injection in Experimental Osteoarthritis in Rabbits

The purpose of this study was twofold. Firstly, we proposed a measurement protocol for the atomic force microscopy (AFM) method to determine the nanomechanical properties of articular cartilage in experimental osteoarthritis in rabbits. Then, we verified if mechanical properties can be evaluated with AFM shortly after platelet-rich plasma (PRP) injection. We hypothesized that the modulus determined by AFM indentation experiments could be utilized as a progressive disease marker during the treatment of osteoarthritis. The rabbits were equally divided into three groups of six: control (group 1); injections of saline (0.5 mL) and 10% surgical talc (Talcum Pharmaceutical^®, Minsk, Belarus) were delivered into the right knee under the patella (group 2 and 3); and PRP was injected into the right knee (group 3). In group 2, the arithmetic average of absolute values (Ra) change was a 25% increase; the maximum peak height (Rp) increased by over 102%, while the mean spacing between local peaks (S) increased by 28% (p < 0.05). In group 3, Ra increased by 14% and Rp increased by 32%, while S decreased by 75% (p < 0.05). The Young’s modulus of the surface layers decreased by 18% as a result of induced model of osteoarthritis (IMO) (p < 0.05), and it increased by 9% (p < 0.05) as a result of PRP therapy, which means that the mechanical properties of cartilage were partially recovered. This research demonstrates that Young’s modulus utilized on a nanometer scale has potential to be a progressive disease marker during the treatment of osteoarthritis.

AFM-Based Method for Measurement of Normal and Osteoarthritic Human Articular Cartilage Surface Roughness

In osteoarthrosis, pathological features of articular cartilage are associated with degeneration and nanomechanical changes. The aim of this paper is to show that indentation-atomic force microscopy can monitor wear-related biomechanical changes in the hip joint of patients with osteoarthritis. Fifty patients (N = 50), aged 40 to 65, were included in the study. The mechanical properties and the submicron surface morphology of hyaline cartilage were investigated using atomic force microscopy. Measurements of the roughness parameters of cartilage surfaces were performed, including the arithmetic average of absolute values (Ra), the maximum peak height (Rp), and the mean spacing between local peaks (S). The arithmetic mean of the absolute values of the height of healthy cartilage was 86 nm, while wear began at Ra = 73 nm. The maximum changes of values of the roughness parameters differed from the healthy ones by 71%, 80%, and 51% for Ra, Rp, and S, respectively. Young's modulus for healthy cartilage surfaces ranged from 1.7 to 0.5 MPa. For the three stages of cartilage wear, Young's modulus increased, and then it approached the maximum value and decreased. AFM seems to be a powerful tool for surface analysis of biological samples as it enables indentation measurements in addition to imaging.

Performance Assessment of Low-Cost Thermal Cameras for Medical Applications

* Correspondence: evilla@iac [...].

Development of Rheumatoid Arthritis Classification from Electronic Image Sensor Using Ensemble Method

Rheumatoid arthritis (RA) is an autoimmune illness that impacts the musculoskeletal system by causing chronic, inflammatory, and systemic effects. The disease often becomes progressive and reduces physical function, causes suffering, fatigue, and articular damage. Over a long period of time, RA causes harm to the bone and cartilage of the joints, weakens the joints' muscles and tendons, eventually causing joint destruction. Sensors such as accelerometer, wearable sensors, and thermal infrared camera sensor are widely used to gather data for RA. In this paper, the classification of medical disorders based on RA and orthopaedics datasets using Ensemble methods are discussed. The RA dataset was gathered from the analysis of white blood cell classification using features extracted from the image of lymphocytes acquired from a digital microscope with an electronic image sensor. The orthopaedic dataset is a benchmark dataset for this study, as it posed a similar classification problem with several numerical features. Three ensemble algorithms such as bagging, Adaboost, and random subspace were used in the study. These ensemble classifiers use k-NN (K-nearest neighbours) and Random forest (RF) as the base learners of the ensemble classifiers. The data classification is accessed using holdout and 10-fold cross-validation evaluation methods. The assessment was based on set of performance measures such as precision, recall, F-measure, and receiver operating characteristic (ROC) curve. The performance was also measured based on the comparison of the overall classification accuracy rate between different ensembles classifiers and the base learners. Overall, it was found that for Dataset 1, random subspace classifier with k-NN shows the best results in terms of overall accuracy rate of 97.50% and for Dataset 2, bagging-RF shows the highest overall accuracy rate of 94.84% over different ensemble classifiers. The findings indicate that the efficiency of the base classifiers with ensemble classifier have substantially improved.

Detection of inflammation from finger temperature profile in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory tissue disease that leads to cartilage, bone, and periarticular tissue damage. This study aimed to investigate whether the use of infrared thermography and measurement of temperature profiles along the hand fingers could detect the inflammation and improve the diagnostic accuracy of the cold provocation test (0 °C for 5 s) and rewarming test (23 °C for180 s) in RA patients. Thirty RA patients (mean age = 49.5 years, standard deviation = 13.0 years) and 22 controls (mean age = 49.8 years, standard deviation = 7.5 years) were studied. Outcomes were the minimal and maximal: baseline temperature (T1), the temperature post-cooling (T2), the temperature post-rewarming (T3), and the Tmax-Tmin along the axis of each finger. The statistical significance was observed for the thumb, index finger, middle finger, and ring finger post-cooling and post-rewarming. Receiver operating characteristics (ROC) analysis to distinguish between the two groups revealed that for the thumb, index finger, middle finger, and ring finger, the area under the ROC curve was statistically significantly (p < 0.05) post-cooling. The cold provocation test used in this study discriminates between RA patients and controls and detects an inflammation in RA patients by the measurement of temperature profiles along the fingers using an infrared camera. Graphical abstract.

Non-Invasive Forehead Segmentation in Thermographic Imaging

The temperature of the forehead is known to be highly correlated with the internal body temperature. This area is widely used in thermal comfort systems, lie-detection systems, etc. However, there is a lack of tools to achieve the segmentation of the forehead using thermographic images and non-intrusive methods. In fact, this is usually segmented manually. This work proposes a simple and novel method to segment the forehead region and to extract the average temperature from this area solving this lack of non-user interaction tools. Our method is invariant to the position of the face, and other different morphologies even with the presence of external objects. The results provide an accuracy of 90% compared to the manual segmentation using the coefficient of Jaccard as a metric of similitude. Moreover, due to the simplicity of the proposed method, it can work with real-time constraints at 83 frames per second in embedded systems with low computational resources. Finally, a new dataset of thermal face images is presented, which includes some features which are difficult to find in other sets, such as glasses, beards, moustaches, breathing masks, and different neck rotations and flexions.