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Insulin resistance: Risk factors, diagnostic approaches and mathematical models for clinical practice, epidemiological studies, and beyond

Krzymien Janusz, Ladyzynski Piotr

Biocybernetics and Biomedical Engineering

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2024

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Vol. 44, no. 1

55--67

EN

Insulin resistance (IR) is a multifactorial metabolic disorder associated with the development of cardiometabolic syndrome, cardiovascular diseases and obesity. Factors such as inflammation, hyperinsulinemia, hyperglucagonemia, mitochondrial dysfunction, glucotoxicity and lipotoxicity contribute to the development of IR. Despite being extensively studied for over 60 years, assessing the incidence of IR, developing effective prevention strategies, and implementing appropriate therapeutic approaches remain challenging. This review explores the multifaceted nature of IR, including its association with various conditions such as obesity, primary hypertension, dyslipidemia, obstructive sleep apnea, Alzheimer’s disease, non-alcoholic fatty liver disease, polycystic ovary syndrome, chronic kidney disease and cancer. Additionally, we discuss the complexity of diagnosing and quantifying IR, emphasizing the lack of absolute, common criteria for classification. We delve into the use of mathematical models in clinical and epidemiological studies, focusing on the choice between insulin, triglycerides, or waist-to-hip ratio as IR determinants. Furthermore, we highlight the importance of reliable input data and caution in interpreting results when utilizing mathematical models for IR assessment. This narrative review aims to provide insights into the challenges and considerations involved in conducting IR diagnostics, with implications for clinical practice, epidemiological research, and future advancements in this field.

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Internet service for wound area measurement using digital planimetry with adaptive calibration and image segmentation with deep convolutional neural networks

Foltynski Piotr, Ladyzynski Piotr

Biocybernetics and Biomedical Engineering

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2023

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Vol. 43, no. 1

17--29

EN

Uncontrolled diabetes leads to serious complications comparable to cancer. Infected foot ulcer causes a 5-year mortality of 50%. Proper treatment of foot wounds is essential, and wound area monitoring plays an important role in this area. In this article, we describe an automatic wound area measurement service that facilitates area measurement and the measurement result is based on adaptive calibration for larger accuracy at curved surfaces. Users need to take a digital picture of a wound and calibration markers and send them for analysis using an Internet page. The deep learning model based on convolutional neural networks (CNNs) was trained using 565 wound images and was used for image segmentation to identify the wound and calibration markers. The developed software calculates the wound area based on the number of pixels in the wound region and the calibration coefficient determined from distances between ticks at calibration markers. The result of the measurement is sent back to the user at the provided e-mail address. The median relative error of wound area measurement in the wound models was 1.21%. The efficacy of the CNN model was tested on 41 wounds and 73 wound models. The averaged values for the dice similarity coefficient, intersection over union, accuracy and specificity for wound identification were 90.9%, 83.9%, 99.3% and 99.6%, respectively. The service proved its high efficacy and can be used in wound area monitoring. The service may be used not only by health care specialists but also by patients. Thus, it is important tool for wound healing monitoring.

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Wound surface area measurement methods

Foltynski Piotr, Ciechanowska Anna, Ladyzynski Piotr

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 4

1454--1465

EN

Assessment of progress in chronic wound healing is very important as it enables deciding when the applied therapy should be replaced with a more advanced one. Wound healing societies recommend using the rate in wound surface area reduction as a marker of the therapy effectiveness. If the wound surface area did not reduce by 50% or more in 4 weeks of standard treatment, advanced therapy options should be introduced. The decrease of wound surface area by 10–15% in a week may also be useful in estimating the probability of wound closure. There is a range of methods for wound surface area measurements that differ in the technology used, accuracy, repeatability, and level of required contact with the patient’s skin or wound itself. Technical advancement of these methods is very wide, from area estimation based on linear measurements to 3D techniques able to analyze skin curvature using sophisticated models. Some methods are based on specialized equipment, thus may be less useful in telemedicine than, for instance, those based on a smartphone with dedicated software. This review presents the current state-of-the-art methods in wound area measurements, presenting selected commercial devices and the latest developments.

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Effect of glucose concentration and culture substrate on HUVECs viability in in vitro cultures: A literature review and own results

Ciechanowska Anna, Gora Ilona, Sabalinska Stanislawa, Foltynski Piotr, Ladyzynski Piotr

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 4

1390--1405

EN

Some clinical studies reported that glucose variability increased the risk of developing diabetes-related late complications more than constant hyperglycemia, while others claimed that the evidence was not strong enough to support such a conclusion. A few in vitro studies investigated the effect of constantly high or variable glucose levels (VGLs) on endothelial cells (EC). The first aim of this work was to review these studies and demonstrate that most of them support the notion that viability and other metabolic parameters of EC deteriorate faster in cell cultures with VGLs than in cultures with stable normal or high glucose concentration. The second aim was to verify whether the effect of glucose concentration is the same regardless of other culture conditions such as the substrate on which the cells are grown. We cultured Human Umbilical Vein Endothelial Cells (HUVECs) for 7 or 14 days in constant (5 mM or 20 mM) or variable (switching between 5 mM and 20 mM once a day) glucose concentration in culture plates, which were either not-covered with any additional substrate or were covered with fibronectin or gelatin. We assessed the cell viability using a propidium iodide test. The ANOVA revealed that HUVECs viability was affected not only by glucose concentration and duration of the cell culturing but also by the type of substrate and interactions of these three factors. In conclusion, the effect of glucose level on EC viability should not be analyzed in isolation from other culture conditions that may amplify or attenuate this effect.