Thermographic patterns of the upper and lower limbs : baseline data

This study was supported by an internal University of Malta Research Grant PODRP01-1. The study sponsor had no involvement in the execution and analysis of this study.To collect normative baseline data and identify any significant differences between hand and foot thermographic distribution patterns in a healthy adult population. Design. A single-centre, randomized, prospective study. Methods. Thermographic data was acquired using a FLIR camera for the data acquisition of both plantar and dorsal aspects of the feet, volar aspects of the hands, and anterior aspects of the lower limbs under controlled climate conditions. Results. There is general symmetry in skin temperature between the same regions in contralateral limbs, in terms of both magnitude and pattern. There was also minimal intersubject temperature variation with a consistent temperature pattern in toes and fingers. The thumb is the warmest digit with the temperature falling gradually between the 2nd and the 5th fingers. The big toe and the 5th toe are the warmest digits with the 2nd to the 4th toes being cooler. Conclusion. Measurement of skin temperature of the limbs using a thermal camera is feasible and reproducible. Temperature patterns in fingers and toes are consistent with similar temperatures in contralateral limbs in healthy subjects. This study provides the basis for further research to assess the clinical usefulness of thermography in the diagnosis of vascular insufficiency.peer-reviewe

Thermographic patterns of the upper and lower limbs: baseline data.

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

An early diagnostic tool for diabetic peripheral neuropathy in rats

The skin's rewarming rate of diabetic patients is used as a diagnostic tool for early diagnosis of diabetic neuropathy. At present, the relationship between microvascular changes in the skin and diabetic neuropathy is unclear in streptozotocin (STZ) diabetic rats. The aim of this study was to investigate whether the skin rewarming rate in diabetic rats is related to microvascular changes and whether this is accompanied by changes observed in classical diagnostic methods for diabetic peripheral neuropathy. Computer-assisted infrared thermography was used to assess the rewarming rate after cold exposure on the plantar skin of STZ diabetic rats' hind paws. Peripheral neuropathy was determined by the density of intra-epidermal nerve fibers (IENFs), mechanical sensitivity, and electrophysiological recordings. Data were obtained in diabetic rats at four, six, and eight weeks after the induction of diabetes and in controls. Four weeks after the induction of diabetes, a delayed rewarming rate, decreased skin blood flow and decreased density of IENFs were observed. However, the mechanical hyposensitivity and decreased motor nerve conduction velocity (MNCV) developed 6 and 8 weeks after the induction of diabetes. Our study shows that the skin rewarming rate is related to microvascular changes in diabetic rats. Moreover, the skin rewarming rate is a non-invasive method that provides more information for an earlier diagnosis of peripheral neuropathy than the classical monofilament test and MNCV in STZ induced diabetic rats

COMPUTER-AIDED QUANTITATIVE EARLY DIAGNOSIS OF DIABETIC FOOT

Diabetes is an incurable metabolic disease characterized by high blood sugar levels. The feet of people with diabetes are at the risk of a variety of pathological consequences including peripheral vascular disease, deformity, ulceration, and ultimately amputation. The key to managing the diabetic foot is prevention and early detection. Unfortunately, current hospital centered reactive diabetes care and the availability of inadequate qualitative diagnostic screening procedures causes physicians to miss the diagnosis in 61% of the patients. We have developed a computer aided diagnostic system for early detection of diabetic foot. The key idea is that diabetic foot exhibits significant neuropathic and vascular damages. When a diabetic foot is placed under cold stress, the thermal recovery will be much slower. This thermal recovery speed can be a quantitative measure for the diagnosis of diabetic foot condition. In our research, thermal recovery of the feet following cold stress is captured using an infrared camera. The captured infrared video is then filtered, segmented, and registered. The temperature recovery at each point on the foot is extracted and analyzed using a thermal regulation model, and the problematic regions are identified. In this thesis, we present our research on the following aspects of the developed computer aided diagnostic systems: subject measurement protocols, a trustful numerical model of the camera noise and noise parameter estimations, infrared video segmentation, new models of thermal regulations, thermal patterns classifications, and our preliminary findings based on small scale clinical study of about 40 subjects, which demonstrated the potential the new diagnostic system

Vincristine-Induced Peripheral Neuropathy: Assessing Preventable Strategies in Paediatric Acute Lymphoblastic Leukaemia

Background: Acute Lymphoblastic Leukaemia is the most common cancer experienced by children with overall survival rates now exceeding 90%. However, most children will experience vincristine-induced peripheral neuropathy (VIPN) during treatment resulting in sensory-motor abnormalities. To date, there are no approved preventative therapeutics or mitigation strategies for VIPN. This body of work set out to: (1) establish a high-throughput and high-content assay with the capacity to identify neuroprotective compounds, (2) test the feasibility of repurposing olesoxime as a neuroprotectant, and (3) compare traditional statistical methods with machine learning models to identify patients at risk of VIPN. Methods: (1) In vitro neuronal cultures were exposed to vincristine to recapitulate the VIPN phenotype and olesoxime assessed as a positive control. The neurotoxicity assay was miniaturised in 384-well microplates with automation steps to reduce manual handling. (2) Olesoxime and vincristine were applied to proliferating malignant cell lines to ensure the efficacy of vincristine was maintained. (3) Machine learning algorithms were developed using data from a local retrospective cohort to predict VIPN. Results: (1) Neurite length was reduced in a dose-responsive manner with vincristine. Assay miniaturisation and automation steps helped facilitate a high-throughput workflow. An optimised multiplexed dye solution enabled image acquisition and neurite quantification. Further, olesoxime was found to protect neurites and deemed suitable as a positive control (2) Cell viability assays confirmed olesoxime did not interfere with vincristine efficacy in leukemia cells. (3) Machine learning algorithms showed equivalency to traditional univariate analysis. The observation of severe class imbalance meant that patients who were least susceptible to VIPN could be identified. Conclusions: This body of work demonstrates the successful development of a neurotoxicity assay suitable for neuroprotectant drug discovery. Olesoxime was found suitable as a positive control in the assay. Further, viability studies indicated that vincristine retains it efficacy with olesoxime, opening the possibility of its use as an adjunctive therapy. Finally, this work developed machine learning models with the capacity to identify patients with VIPN-free survival. The utility of this model may mean that it can be used to stratify patients prospectively in the clinic based on favourable clinical features

Foot assessment in people with diabetes: A quantitative diagnostic approach

Background: Diabetic foot ulcers are a serious and costly complication of diabetes. The leading causes of diabetic foot ulceration are mechanical trauma and the breakdown of plantar soft tissues. Biomechanical factors linked to an increase in diabetic foot ulceration are changes in plantar soft tissue mechanical properties and increased plantar pressure. These represent important internal and external risk factors for ulceration that are not commonly assessed within clinical practice due to a lack of clinically applicable measurement techniques. The measurement of Shore hardness has been identified as a potential method to assess these internal and external biomechanical factors due to its previous use in various soft tissue applications and its simplicity, ease of use, and low cost. However, key questions remain regarding the physical meaning of Shore hardness when used within biological soft tissues to assess the mechanical properties of the plantar soft tissues of the foot. In addition, the clinical relevance of Shore hardness when applied to the diabetic foot needs further exploration. Finally, the association between Shore hardness and plantar pressure in people with diabetes has not been fully investigated. Nevertheless, Shore hardness presents a potential method to assess the external risk factors associated with ulceration. Aim: The primary aim of this research was to investigate if the measurement of Shore hardness can be used within a clinical setting as a method to assess the mechanical properties of the plantar soft tissues. The secondary aim of this research was to investigate if the measurement of Shore hardness is associated with changes in plantar pressure during walking in people with diabetes and, if so, can Shore hardness in combination with other biomechanical measurements be used to predict these changes. Methods: Finite element (FE) analysis was conducted to investigate the physical meaning of Shore hardness using an anatomically accurate model of the heel pad. Additionally, the ability of Shore hardness to individually assess the mechanical properties of skin and subcutaneous soft tissue was investigated. The clinical relevance of Shore hardness was assessed within a cohort of 40 adults with diabetes and diabetic peripheral neuropathy classified as having a high risk of foot ulceration. The average age of participants was 63(±9) years, with an average duration of diabetes of 15(±9) years. To assess the clinical relevance of the measurement of Shore hardness, Spearman’s rank correlation tests were performed between Shore hardness and the previously established parameters found to increase the risk of mechanical trauma to the foot, such as blood biochemistry, loading, and age. The association between Shore hardness and plantar pressure as the external risk factor for ulceration was also investigated within this cohort of 40 adults using multiple regression analyses. Specifically, the ability of Shore hardness in combination with measurements of 2D sagittal plane range of motion, to predict regional changes in plantar pressure and loading was assessed. Results: The results of the FE analysis showed that the measurement of Shore hardness offers an assessment of stiffness that is a combination of both the mechanical behaviour of the skin and the underlying subcutaneous tissue. It was concluded that, on its own, the measurement of plantar soft tissue Shore hardness does not provide an assessment of the stress-strain behaviour of the heel pad’s constituent layers but instead offers an assessment of the bulk tissue’s overall capacity to deform. As a result, differentiating between the stiffness of skin and that of the subcutaneous tissue based on the conventional assessment of Shore hardness remains a challenge. Additionally, through FE analysis, it was found that by altering the size of the Shore hardness indenter within the currently available limits, the measurement of Shore hardness cannot independently assess the mechanical properties of the skin or subcutaneous soft tissue. However, the results of the FE analysis also highlighted that an indenter that is less than 2mm in diameter and 1mm in length might potentially be able to infer differences between the mechanical properties of the skin and subcutaneous soft tissue. The clinical relevance of Shore hardness was shown by confirming correlations with age, blood biochemistry, and loading, whereby an increase triglyceride levels was associated with increases in tissue hardness. In contrast, an increase in loading causes a decrease in plantar tissue hardness. These results were all found to align with current literature indicating that Shore hardness can indeed be a clinically viable approach for assessing the internal risk factors associated with ulceration. Finally, Shore hardness, in combination with foot and ankle range of motion, was able to predict changes in peak plantar pressures and pressure time integral within the midfoot region. A reduction in midfoot dorsiflexion and an increase in Shore hardness at the midfoot are predictive variables for an increase in peak plantar pressure and pressure time integral. These results thus highlight the potential usefulness of the assessment of Shore hardness as a method to monitor changes in the external risk factors associated with ulceration. Conclusion: These findings show that Shore hardness can be a simple, cost-effective and reliable method for assessing both the internal and external biomechanical risk factors associated with diabetic foot ulceration within a clinic setting. This is specifically relevant to low resource settings where access to sophisticated equipment such as ultrasound elastography or plantar pressure platforms can be limited

Empowering Foot Health: Harnessing the Adaptive Weighted Sub-Gradient Convolutional Neural Network for Diabetic Foot Ulcer Classification

In recent times, DFU (diabetic foot ulcer) has become a universal health problem that affects many diabetes patients severely. DFU requires immediate proper treatment to avert amputation. Clinical examination of DFU is a tedious process and complex in nature. Concurrently, DL (deep learning) methodologies can show prominent outcomes in the classification of DFU because of their efficient learning capacity. Though traditional systems have tried using DL-based models to procure better performance, there is room for enhancement in accuracy. Therefore, the present study uses the AWSg-CNN (Adaptive Weighted Sub-gradient Convolutional Neural Network) method to classify DFU. A DFUC dataset is considered, and several processes are involved in the present study. Initially, the proposed method starts with pre-processing, excluding inconsistent and missing data, to enhance dataset quality and accuracy. Further, for classification, the proposed method utilizes the process of RIW (random initialization of weights) and log softmax with the ASGO (Adaptive Sub-gradient Optimizer) for effective performance. In this process, RIW efficiently learns the shift of feature space between the convolutional layers. To evade the underflow of gradients, the log softmax function is used. When logging softmax with the ASGO is used for the activation function, the gradient steps are controlled. An adaptive modification of the proximal function simplifies the learning rate significantly, and optimal proximal functions are produced. Due to such merits, the proposed method can perform better classification. The predicted results are displayed on the webpage through the HTML, CSS, and Flask frameworks. The effectiveness of the proposed system is evaluated with accuracy, recall, F1-score, and precision to confirm its effectual performance