Functional Infrared Thermal Imaging: A Contemporary Tool in Soft Tissue Screening

Functional infrared thermography imaging can be used to assess the effectiveness of Maxicam Gel® in pre-emptively treating transient synovitis and lameness in horses

Introduction

Diagnosing and treating lameness in horses is essential to improving their welfare. In equine orthopedic practice, infrared thermography (IRT) can indirectly detect soreness. Non-steroidal anti-inflammatory drugs can treat painful and inflammatory processes in horses. Using IRT, the efficacy of meloxicam (Maxicam Gel®) was evaluated in pre-treating transient synovitis in horses induced by a middle carpal joint injection of lipopolysaccharides (LPS) from E. coli 055:B5 at a dose of 10 endotoxin units.

Methods

In a cross-over design, six healthy horses were randomly assigned to receive either 0.6 mg/kg of oral Maxicam Gel® (MAXVO) or a mock administration (control group, C) following a two-week washout period. IRT of the middle carpal joint, visual lameness assessment and joint circumference were recorded over time. Clinical and hematological evaluations were performed. Synovial fluid aspirates were analyzed for total nucleated cell count, total protein, and prostaglandin E2. A mixed effects analysis of variance was performed for repeated measures over time, followed by Tukey's test. A multinomial logistic regression was conducted to determine whether there is a relationship between a thermography temperature change and the lameness score.

Results

There were no changes in joint circumference. The MAXVO group showed a lower rectal temperature 4 h after synovitis induction. The C group presented an increase in neutrophils and a decrease in total hemoglobin and hematocrit 8 h after induction. No changes were observed in the synovial fluid between groups. The horses that received meloxicam did not show clinically significant lameness at any time, while the C group showed an increase in lameness 2, 4, and 8 h after synovitis induction.

Discussion

IRT indicated that the skin surface temperature of the middle carpal joint was lower in horses who received meloxicam, suggesting a reduction in the inflammatory process induced by LPS. It was observed that the maximum temperature peaks in the dorsopalmar and lateropalmar positions can be utilized to predict the severity of lameness, particularly when the temperature rises above 34°C. Horses pre-treated with meloxicam showed either reduced or no indication of mild to moderate pain and presented a lowehr thermographic temperature, which indicates the effectiveness of Maxicam Gel® as an anti-inflammatory.

Methods of ex vivo analysis of tissue status in vascularized composite allografts

Vascularized composite allotransplantation can improve quality of life and restore functionality. However, the complex tissue composition of vascularized composite allografts (VCAs) presents unique clinical challenges that increase the likelihood of transplant rejection. Under prolonged static cold storage, highly damage-susceptible tissues such as muscle and nerve undergo irreversible degradation that may render allografts non-functional. Skin-containing VCA elicits an immunogenic response that increases the risk of recipient allograft rejection. The development of quantitative metrics to evaluate VCAs prior to and following transplantation are key to mitigating allograft rejection. Correspondingly, a broad range of bioanalytical methods have emerged to assess the progression of VCA rejection and characterize transplantation outcomes. To consolidate the current range of relevant technologies and expand on potential for development, methods to evaluate ex vivo VCA status are herein reviewed and comparatively assessed. The use of implantable physiological status monitoring biochips, non-invasive bioimpedance monitoring to assess edema, and deep learning algorithms to fuse disparate inputs to stratify VCAs are identified.

An exploration of new methods for metabolic syndrome examination by infrared thermography and knowledge mining

Metabolic syndrome (MS) is a clinical syndrome with multiple metabolic disorders. As the diagnostic criteria for MS still lacking of imaging laboratory method, this study aimed to explore the differences between healthy people and MS patients through infrared thermography (IRT). However, the observation region of the IRT image is uncertain, and the research tried to solve this problem with the help of knowledge mining technology. 43 MS participants were randomly included through a cross-sectional method, and 43 healthy participants were recruited through number matching. The IRT image of each participant was segmented into the region of interest (ROI) through the preprocessing method proposed in this research, and then the ROI features were granulated by the K-means algorithm to generate the formal background, and finally, the two formal background were separately built into a knowledge graph through the knowledge mining method based on the attribute partial order structure. The baseline data shows that there is no difference in age, gender, and height between the two groups (P > 0.05). The image preprocessing method can segment the IRT image into 18 ROI. Through the K-means method, each group of data can be separately established with a 43 × 36 formal background and generated a knowledge graph. It can be found through knowledge mining and independent-samples T test that the average temperature and maximum temperature difference between the chest and face of the two groups are statistically different (P < 0.01). IRT could reflect the difference between healthy people and MS people. The measurement regions were found by the method of knowledge mining on the premise of unknown. The method proposed in this paper may add a new imaging method for MS laboratory examinations, and at the same time, through knowledge mining, it can also expand a new idea for clinical research of IRT.

Applications of thermal imaging with infrared thermography in Orthopaedics

BACKGROUND

Pathological conditions with ongoing inflammatory processes result in specific heat signatures at the affected body parts; infrared thermography (IRT) detects these changes and can be utilied in screening such conditions. The modern devices are advanced and their non contact, convenient and precise readings can aid in multiple medical sub fields. Orthopaedics as a broad entity has witnessed utilisation of this technology for different indications and the present scoping review was done to assess these established indications and further scope of its utility.

METHOD

ology: A Medline search was done on April 26, 2021 with specific keywords for studies of any design in English language discussing the usage of thermography in Orthopaedics. Animal studies, conference abstracts, systematic reviews, e-posters, case reports, book chapters, and studies describing the use of thermography in non-Orthopaedic patients were excluded.

RESULTS

Total number of hits were 1380. 43 studies including case series and case control studies were included in the review. The subfields or indications described were pain/arthritis, Charcot's foot/neuropathic ulcers, infections associated with diabetic feet and arthroplasties, reflex sympathetic dystrophy, carpal tunnel syndrome, sports medicine, paediatric orthopaedics, spine, ergonomics and compartment syndrome.

CONCLUSION

IRT has been described to be effective in orthopaedic conditions with specific heat signatures and this can assess the trend of the ongoing inflammatory process as well as response to a particular treatment. Additionally, it can specifically determine the exact loci of the pathology for targeted interventions.

Regions of interest selection and thermal imaging data analysis in sports and exercise science: a narrative review

OBJECTIVE

Infrared thermography (IRT) is a non-invasive, contactless and low-cost technology that allows recording of the radiating energy that is released from a body, providing an estimate of its superficial temperature. Thanks to the improvement of infrared thermal detectors, this technique is widely used in the biomedical field to monitor the skin temperature for different purposes (e.g. assessing circulatory diseases, psychophysiological state, affective computing). Particularly, in sports and exercise science, thermography is extensively used to assess sports performance, to investigate superficial vascular changes induced by physical exercise, and to monitor injuries. However, the methods of analysis employed to treat IRT data are not standardized, and hence introduce variability in the results.

APPROACH

This review focuses on the methods of analysis currently used for thermal imaging in sports and exercise science.

MAIN RESULTS

Firstly, the procedures employed for the selection of regions of interest (ROIs) from anatomical body districts are reviewed, paying attention also to the potentialities of morphing algorithms to increase the reproducibility of thermal results. Secondly, the statistical approaches utilized to characterize the temperature frequency and spatial distributions within ROIs are investigated, showing their strengths and weaknesses. Moreover, the importance of employing tracking methods to analyze the temporal thermal oscillations within ROIs is discussed. Thirdly, the capability of employing procedures of investigation based on machine learning frameworks on thermal imaging in sports science is examined.

SIGNIFICANCE

Finally, some proposals to improve the standardization and the reproducibility of IRT data analysis are provided, in order to facilitate the development of a common database of thermal images and to improve the effectiveness of IRT in sports science.