Confounding factors in peripheral thermal recovery time after active cooling.

OBJECTIVES: The effectiveness of normal physiological thermoregulation complicates differentiation between pathologic changes in medical thermography associated with peripheral artery disease and a number of other clinical conditions. In this study we investigate a number of potential confounding factors to the thermal recovery rate after active limb cooling, with the main focus on age and sex. APPROACH: The source data consists of 53 healthy individuals with no diagnosed cardiovascular disease or reported symptoms and with a mean age of 38.4 (± 12.1) years. The sample population was further divided into male (N = 14) and female groups (N = 39). The thermal recovery time was measured using two thermal cameras from both lower limbs on plantar and dorsal sides. The active cooling was achieved using moldable cold pads placed on the plantar and dorsal side of the lower limb. The recovery was measured until the temperature had reached a stable level. The recovery time was determined from an exponential fit to the measured data. RESULTS: The correlation between the thermal recovery time constant and age varied from low to moderate linear correlation (0.31 ≤ ⍴ ≤ 70), depending on the inspected region of interest, with a higher statistically significant correlation in the medial regions. The contralateral limb temperature differences or the thermal time constants did not have statistically significant differences between the male and female sexes. Further, the secondary metrics such as participant's body mass, body-mass index, or systolic blood pressure had low or no correlation with the thermal recovery time in the study group. CONCLUSION: The thermal recovery time constant after active cooling appears as a relatively independent metric from the majority of the measured potential confounding factors. Age should be accounted for when performing thermal recovery measurements. However, dynamic thermal imaging and its methodologies require further research and exploration.

Assessment of chronic limb threatening ischemia using thermal imaging.

OBJECTIVES: Current chronic limb threatening ischemia (CLTI) diagnostics require expensive equipment, using ionizing radiation or contrast agents, or summative surrogate methods lacking in spatial information. Our aim is to develop and improve contactless, non-ionizing and cost-effective diagnostic methods for CLTI assessment with high spatial accuracy by utilizing dynamic thermal imaging and the angiosome concept. APPROACH: Dynamic thermal imaging test protocol was suggested and implemented with a number of computational parameters. Pilot data was measured from 3 healthy young subjects, 4 peripheral artery disease (PAD) patients and 4 CLTI patients. The protocol consists of clinical reference measurements, including ankle- and toe-brachial indices (ABI, TBI), and a modified patient bed for hydrostatic and thermal modulation tests. The data was analyzed using bivariate correlation. RESULTS: The thermal recovery time constant was on average higher for the PAD (88%) and CLTI (83%) groups with respect to the healthy young subjects. The contralateral symmetry was high for the healthy young group and low for the CLTI group. The recovery time constants showed high negative correlation to TBI (ρ = -0.73) and ABI (ρ = -0.60). The relation of these clinical parameters to the hydrostatic response and absolute temperatures (|ρ|<0.3) remained unclear. CONCLUSION: The lack of correlation for absolute temperatures or their contralateral differences with the clinical status, ABI and TBI disputes their use in CLTI diagnostics. Thermal modulation tests tend to augment the signs of thermoregulation deficiencies and accordingly high correlations were found with all reference metrics. The method is promising for establishing the connection between impaired perfusion and thermography. The hydrostatic modulation test requires more research with stricter test conditions.

Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review.

PURPOSE OF THE REVIEW: We aim to review the methods, current research evidence, and future directions in body composition analysis (BCA) with CT imaging. RECENT FINDINGS: CT images can be used to evaluate muscle tissue, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) compartments. Manual and semiautomatic segmentation methods are still the gold standards. The segmentation of skeletal muscle tissue and VAT and SAT compartments is most often performed at the level of the 3rd lumbar vertebra. A decreased amount of CT-determined skeletal muscle mass is a marker of impaired survival in many patient populations, including patients with most types of cancer, some surgical patients, and those admitted to the intensive care unit (ICU). Patients with increased VAT are more susceptible to impaired survival / worse outcomes; however, those patients who are critically ill or admitted to the ICU or who will undergo surgery appear to be exceptions. The independent significance of SAT is less well established. Recently, the roles of the CT-determined decrease of muscle mass and increased VAT area and epicardial adipose tissue (EAT) volume have been shown to predict a more debilitating course of illness in patients suffering from severe acute respiratory syndrome coronavirus 2 (COVID-19) infection. SUMMARY: The field of CT-based body composition analysis is rapidly evolving and shows great potential for clinical implementation.

Profeel-An open source dosimetry data visualization and analysis software.

BACKGROUND AND OBJECTIVES: This article presents Profeel, a Matlab (MathWorks Inc., MA) based open source dosimetry data visualization and analysis software. Profeel aims to support quality assurance, dosimetry and research in the field of radiotherapy by providing an environment to visualize, process and analyse measured and simulated dosimetry data from several data sources used in radiotherapy practice and research. METHODS: The processing and analysis tools are based on routinely used dosimetry analysis methods, such as gamma analysis, different data normalizations and data filtering. Additionally the Profeel performs an automatic 1 dimensional profile and percentage depth dose analysis in accordance with International Electrotechnical Commission definitions. All data can be operated by user created custom functions and lower dimensionality data can be extracted from volume doses and dose planes. RESULTS: Profeel supports data import in all 3 dimensions and offers an intuitive user interface to perform data visualization, processing and analysis between simulated and measured data. Profeel and its source code are distributed free of charge under the General Public Licence (GPL). CONCLUSIONS: Profeel has shown to be an agile tool for fulfilling various needs of several researchers and since Profeel is under constant development and is an open source project, community needs, issues and bug reports are taken into account in the development.

Prediction of Self-Perceived Stress and Arousal Based on Electrodermal Activity.

Electrodermal activity (EDA) reflects the functions of autonomic nervous system and is often used in evaluation of mental states, e.g. short- and long-term stress. In this study, test subjects were exposed to a 3-phase adapted MIST test (relaxation, arousal, stress) during which EDA was recorded, and the self-perceived stress and arousal were assessed. The objective of the study was to evaluate the feasibility of EDA features to predict the MIST test phases and self-perceived stress and arousal. With EDA features, the test phases were classified with accuracy of 94.1%, and the self-perceived stress and arousal were classified with accuracy of 60.5-72.2%. Results are promising for the use of EDA for long-term assessment of self-perceived stress and arousal during work.