Imaging-based internal body temperature measurements: The journal Temperature toolbox

2D ultrasound thermometry during thermal ablation with high-intensity focused ultrasound

The clinical use of high intensity focused ultrasound (HIFU) therapy for noninvasive tissue ablation has recently gained momentum. Guidance is provided by either magnetic resonance imaging (MRI) or conventional B-mode ultrasound imaging, each with its own advantages and disadvantages. The main limitation of ultrasound imaging is its inability to provide temperature measurements over the ranges corresponding to the target temperatures during ablative thermal therapies (between 55 °C and 70 °C). Here, variations in ultrasound backscattered energy (ΔBSE) were used to monitor temperature increases in liver tissue up to an absolute value of 90 °C during and after HIFU treatment. In vitro experimental measurements were performed in 47 bovine liver samples using a toroidal HIFU transducer operating at 2.5 MHz to increase the temperature of tissues. An ultrasound imaging probe working at 7.5 MHz was placed in the center of the HIFU transducer to monitor the backscattered signals. The free-field acoustic power was set to 9 W, 12 W or 16 W in the different experiments. HIFU sonications were performed for 240 s using a duty cycle of 83 % to allow ultrasound imaging and raw radiofrequency data acquisition during exposures. Measurements showed a linear relationship between ΔBSE (in dB) and temperature (r = 0.94, p < 0.001) over a temperature range from 37 °C to 90 °C, with a high reliability of temperature measurements below 75 °C. Monitoring can be performed at the frame rate of ultrasound imaging scanners with an accuracy within an acceptable threshold of 5 °C, given the temperatures targeted during thermal ablations. If the maximum temperature reached is below 70 °C, ΔBSE is also a reliable approach for estimating the temperature during cooling. Histological analysis shown the impact of the treatment on the spatial arrangement of cells that can explain the observed variation of ΔBSE. These results demonstrate the ability of ΔBSE measurements to estimate temperature in ultrasound images within an effective therapeutic range. This method can be implemented clinically and potentially applied to other thermal-based therapies.

Mechanism involved of post-exercise cold water immersion: Blood redistribution and increase in energy expenditure during rewarming

Thermogenesis is well understood, but the relationships between cold water immersion (CWI), the post-CWI rewarming and the associated physiological changes are not. This study investigated muscle and systemic oxygenation, cardiorespiratory and hemodynamic responses, and gastrointestinal temperature during and after CWI. 21 healthy men completed randomly 2 protocols. Both protocols consisted of a 48 minutes heating cycling exercise followed by 3 recovery periods (R1-R3), but they differed in R2. R1 lasted 20 minutes in a passive semi-seated position on a physiotherapy table at ambient room temperature. Depending on the protocol, R2 lasted 15 minutes at either ambient condition (R2_AMB) or in a CWI condition at 10°C up to the iliac crest (R2_CWI). R3 lasted 40 minutes at AMB while favoring rewarming after R2_CWI. This was followed by 10 minutes of cycling. Compared to R2_AMB, R2_CWI ended at higherV ˙ O2 in the non-immersed body part due to thermogenesis (7.16(2.15) vs. 4.83(1.62) ml.min-1.kg-1) and lower femoral artery blood flow (475(165) vs. 704(257) ml.min-1) (p < 0.001). Only after CWI, R3 showed a progressive decrease in vastus and gastrocnemius medialis O2 saturation, significant after 34 minutes (p < 0.001). As blood flow did not differ from the AMB protocol, this indicated local thermogenesis in the immersed part of the body. After CWI, a lower gastrointestinal temperature on resumption of cycling compared to AMB (36.31(0.45) vs. 37.30(0.49) °C, p < 0.001) indicated incomplete muscle thermogenesis. In conclusion, the rewarming period after CWI was non-linear and metabolically costly. Immersion and rewarming should be considered as a continuum rather than separate events.

Magnetic resonance fingerprinting based thermometry (MRFT): application toex vivoimaging near DBS leads

The purpose of this study is to demonstrate the first work ofT1-based magnetic resonance thermometry using magnetic resonance fingerprinting (dubbed MRFT). We compared temperature estimation of MRFT with proton resonance frequency shift (PRFS) thermometry onex vivobovine muscle. We demonstrated MRFT's feasibility in predicting temperature onex vivobovine muscles with deep brain stimulation (DBS) lead.B0maps generated from MRFT were compared with gold standardB0maps near the DBS lead. MRFT and PRFS estimated temperatures were compared in the presence of motion. All experiments were performed on a 3 Tesla whole-body GE Premier system with a 21-channel receive head coil (GE Healthcare, Milwaukee, WI). Four fluoroptic probes were used to measure the temperature at the center of a cold muscle (probe 1), the room temperature water bottle (probe 2), and the center and periphery of the heated muscle (probes 3 and 4). We selected regions of interest (ROIs) around the location of the probes and used simple linear regression to generate the temperature sensitivity calibration equations that convertT1maps and Δsmaps to temperature maps. We then repeated the same setup and compared MRFT and PRFS thermometry temperature estimation with gold standard probe measurements. For the MRFT experiment on DBS lead, we taped the probe to the tip of the DBS lead and used a turbo spin echo sequence to induce heating near the lead. We selected ROIs around the tip of the lead to compare MRFT temperature estimation with probe measurements and compared with PRFS temperature estimation. Vendor-suppliedB0mapping sequence was acquired to compare with MRFT-generatedB0maps. We found strong linear relationships (R2> 0.958) betweenT1and temperature and Δsand temperatures in our temperature sensitivity calibration experiment. MRFT and PRFS thermometry both accurately predict temperature (RMSE < 1.55 °C) compared to probe measurements. MRFT estimated temperature near DBS lead has a similar trend as the probe temperature. BothB0maps show inhomogeneities around the lead. MRFT estimated temperature is less sensitive to motion.

Diagnostic of Patients with COVID-19 Pneumonia Using Passive Medical Microwave Radiometry (MWR)

BACKGROUND

Chest CT is widely regarded as a dependable imaging technique for detecting pneumonia in COVID-19 patients, but there is growing interest in microwave radiometry (MWR) of the lungs as a possible substitute for diagnosing lung involvement.

AIM

The aim of this study is to examine the utility of the MWR approach as a screening tool for diagnosing pneumonia with complications in patients with COVID-19.

METHODS

Our study involved two groups of participants. The control group consisted of 50 individuals (24 male and 26 female) between the ages of 20 and 70 years who underwent clinical evaluations and had no known medical conditions. The main group included 142 participants (67 men and 75 women) between the ages of 20 and 87 years who were diagnosed with COVID-19 complicated by pneumonia and were admitted to the emergency department between June 2020 to June 2021. Skin and lung temperatures were measured at 14 points, including 2 additional reference points, using a previously established method. Lung temperature data were obtained with the MWR2020 (MMWR LTD, Edinburgh, UK). All participants underwent clinical evaluations, laboratory tests, chest CT scans, MWR of the lungs, and reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2.

RESULTS

The MWR exhibits a high predictive capacity as demonstrated by its sensitivity of 97.6% and specificity of 92.7%.

CONCLUSIONS

MWR of the lungs can be a valuable substitute for chest CT in diagnosing pneumonia in patients with COVID-19, especially in situations where chest CT is unavailable or impractical.

Three dimensional models of human thermoregulation: A review

Numerous human thermoregulatory models have been developed and widely used in various applications such as aerospace, medicine, public health, and physiology research. This paper is a review of three dimensional (3D) models for human thermoregulation. This review begins with a short introduction of thermoregulatory model development followed by key principles for mathematical description of human thermoregulation systems. Different representations of 3D human bodies are discussed with respect to their detail and prediction capability. The human body was divided into fifteen layered cylinders in early 3D models (cylinder model). Recent 3D models have utilized medical image datasets to develop geometrically correct human models (realistic geometry model). The finite element method is mostly used to solve the governing equations and get numerical solutions. The realistic geometry models provide a high degree of anatomical realism and predict whole-body thermoregulatory responses at high resolution and at organ and tissue levels. Thus, 3D models extend to a wide range of applications where temperature distribution is critical, such as hypothermia/hyperthermia therapy and physiology research. The development of thermoregulatory models will continue with the growth in computational power, advancement in numerical methods and simulation software, advances in modern imaging techniques, and progress in the basic science of thermal physiology.

Improving the Efficiency of Oncological Diagnosis of the Breast Based on the Combined Use of Simulation Modeling and Artificial Intelligence Algorithms

This work includes a brief overview of the applications of the powerful and easy-to-perform method of microwave radiometry (MWR) for the diagnosis of various diseases. The main goal of this paper is to develop a method for diagnosing breast oncology based on machine learning algorithms using thermometric data, both real medical measurements and simulation results of MWR examinations. The dataset includes distributions of deep and skin temperatures calculated in numerical models of the dynamics of thermal and radiation fields inside biological tissue. The constructed combined dataset allows us to explore the limits of applicability of the MWR method for detecting weak tumors. We use convolutional neural networks and classic machine learning algorithms (k-nearest neighbors, naive Bayes classifier, support vector machine) to classify data. The construction of Kohonen self-organizing maps to explore the structure of our combined dataset demonstrated differences between the temperatures of patients with positive and negative diagnoses. Our analysis shows that the MWR can detect tumors with a radius of up to 0.5 cm if they are at the stage of rapid growth, when the tumor volume doubling occurs in approximately 100 days or less. The use of convolutional neural networks for MWR provides both high sensitivity (sens=0.86) and specificity (spec=0.82), which is an advantage over other methods for diagnosing breast cancer. A new modified scheme for medical measurements of IR temperature and brightness temperature is proposed for a larger number of points in the breast compared to the classical scheme. This approach can increase the effectiveness and sensitivity of diagnostics by several percent.

Comparative Analysis of Human Body Temperatures Measured with Noncontact and Contact Thermometers

Body temperature measurement is one of the basic methods in clinical diagnosis. The problems of thermometry—interpretation of the accuracy and repeatability of various types of thermometers—are still being discussed, especially during the current pandemic in connection with the SARS-CoV-2 virus responsible for causing the COVID-19 disease. The aim of the study was to compare surface temperatures of the human body measured by various techniques, in particular a noncontact thermometer (infrared) and contact thermometers (mercury, mercury-free, electronic). The study included 102 randomly selected healthy women and men (age 18–79 years). The Bland–Altman method was used to estimate the 95% reproducibility coefficient, i.e., to assess the degree of conformity between different attempts. Temperatures measured with contact thermometers in the armpit are higher than temperatures measured without contact at the frontal area of the head. The methods used to measure with contact thermometers and a noncontact infrared thermometer statistically showed high measurement reliability. In order to correctly interpret the result of measuring human body temperature, it is necessary to indicate the place of measurement and the type of thermometer used.

Infrared Thermal Imaging of Patients With Acute Upper Respiratory Tract Infection: Mixed Methods Analysis

Background

Upper respiratory tract infection is a common disease of the respiratory system. Its incidence is very high, and it can even cause pandemics. Infrared thermal imaging (IRTI) can provide an objective and quantifiable reference for the visual diagnosis of people with acute respiratory tract infection, and it can function as an effective indicator of clinical diagnosis.

Objective

The aims of this study are to observe and analyze the infrared expression location and characteristics of patients with acute upper respiratory tract infection through IRTI technology and to clearly express the quantification of temperature, analyze the role of IRTI in acute upper respiratory tract diagnostic research, and understand the impact of IRTI in qualitative and quantitative research.

Methods

From December 2018 to February 2019, 154 patients with acute upper respiratory tract infection were randomly selected from the emergency department of the First Affiliated Hospital of Guangzhou Medical University. Among these patients, 73 were men and 81 were women. The subjects were divided into two groups according to the presence of fever, namely, fever and nonfever groups. Qualitative and quantitative analyses of the infrared thermal images were performed to compare the results before and after application of the technology.

Results

Using the method described in this paper, through the analysis of experimental data, we elucidated the role of IRTI in the diagnosis of acute upper respiratory tract infection, and we found that qualitative and quantitative IRTI analyses play important roles. Through the combination of theory and experimental data, the IRTI analysis showed good results in identifying acute upper respiratory tract infection.

Conclusions

IRTI technology plays an important role in identifying the infrared expression location and characteristics of patients with acute upper respiratory tract infection as well as in the quantification of clear expression of body temperature, and it provides an objective and quantifiable reference basis for elucidating the pathogenesis of these patients.

Non-contact infrared assessment of human body temperature: The journal Temperature toolbox

The assessment of human internal/core temperature (T core) is relevant in many scientific disciplines, but also for public health authorities when attempting to identify individuals with fever. Direct assessment of T core is often invasive, impractical on a large scale, and typically requires close contact between the observer and the target subject. Non-contact infrared thermometry (NCIT) represents a practical solution in which T core can potentially be assessed from a safe distance and in mass screening scenarios, by measuring skin temperature at specific anatomical locations. However, the COVID-19 pandemic has clearly demonstrated that these devices are not being used correctly, despite expert guided specifications available in International Standard Organization (ISO) documents. In this review, we provide an overview of the most pertinent factors that should be considered by users of NCIT. This includes the most pertinent methodological and physiological factors, as well as an overview on the ability of NCIT to track human T core. For practical use, we provide a checklist based on relevant ISO standards which are simple to follow and should be consulted prior to using NCIT for assessment of human T core. Our intention is for users of NCIT to adopt this checklist, which may improve the performance of NCIT for its ability to track T core.