Is thermal scanner losing its bite in mass screening of fever due to SARS?

Facial and ocular thermal mapping in black-and-gold howler monkey (Alouatta caraya) by infrared thermography: An ex situ study

BACKGROUND

This study used infrared thermography (IRT) for mapping the facial and ocular temperatures of howler monkeys, to determine parameters for the diagnosis of febrile processes. There are no published IRT study in this species.

METHODS

Were evaluated images of a group of monkeys kept under human care at Sorocaba Zoo (São Paulo, Brazil). The images were recorded during 1 year, in all seasons. Face and eye temperatures were evaluated.

RESULTS

There are statistically significant differences in face and eye temperatures. Mean values and standard deviations for facial and ocular temperature were respectively: 33.0°C (2.1) and 36.5°C (1.9) in the summer; 31.5°C (4.5) and 35.3°C (3.6) in the autumn; 30.0°C (4.3) and 35.6°C (3.9) in the winter; 30.8°C (2.9) and 35.5°C (2.1) in the spring.

CONCLUSIONS

The IRT was effective to establish a parameter for facial and ocular temperatures of black-and-gold howler monkeys kept under human care.

The topical application of different galenic formulations can alter the thermographic images of skin: Limitations for public thermal screening on infection control situations

BACKGROUND

To analyze whether the application of topical formulas as cosmetics or sunscreens could affect the skin thermographic readings in terms of infection control in pandemic situations.

METHODS

The temperature of the skin of the dorsal region of the back and the face of 20 volunteers was followed after the application of 6 different types of gels, sunscreens, and make-up under controlled temperature and humidity conditions. High-resolution thermographic images were analyzed to calculate the temperature of treated skin compared to skin free of topical products.

RESULTS

The application of hydroalcoholic gel resulted in a mean drop of more than 2°C just after 1 minute followed by organic sunscreens until 1.7°C. Recovery was observed progressively until minute 9. Color make-up type formulas, rich in iron oxide as well as sunscreens with mineral filters had little or no effect on the skin thermal response.

CONCLUSIONS

It is possible to alter the skin temperature almost immediately by using hydroalcoholic gels and sunscreen cosmetics. So, it is possible to produce false negative data in the readings of patients screened thermically.

InfraNet: Accurate forehead temperature measurement framework for people in the wild with monocular thermal infrared camera

During an epidemic, accurate human temperature screening based on neural networks for disease surveillance is important and challenging. Existing distant human forehead temperature measuring device usually adopts a dual-camera system using paired RGB and thermal infrared images to conduct face detection and temperature measurement. Since the facial RGB image may undermine people's privacy, we designed a monocular thermal system and proposed an effective framework called the InfraNet to measure and calibrate forehead temperature of people in the wild. To address the challenge of temperature floating, the InfraNet calibrates the subject's temperature with one's physical depth and horizontal offset predicted by a single infrared image. Our InfraNet framework mainly consists of three parts: face detection subnet, depth and horizontal offset estimation subnet and temperature calibration subnet. The temperature calibration performance can be improved with the help of spatial regularization term concentrating on predicting precise depth and horizontal offset of people. Besides, we collected a large-scale infrared image dataset in the both lab and wild scenarios, including 8,215 thermal infrared images. Experiments on our wild dataset demonstrated that the InfraNet achieved 91.6% high accuracy of distant multi-subject temperature measurement on average under the standard temperature threshold of strict 0.3°C.

Non-Contact Infrared Thermometers and Thermal Scanners for Human Body Temperature Monitoring: A Systematic Review

In recent years, non-contact infrared thermometers (NCITs) and infrared thermography (IRT) have gained prominence as convenient, non-invasive tools for human body temperature measurement. Despite their widespread adoption in a range of settings, there remain questions about their accuracy under varying conditions. This systematic review sought to critically evaluate the performance of NCITs and IRT in body temperature monitoring, synthesizing evidence from a total of 72 unique settings from 32 studies. The studies incorporated in our review ranged from climate-controlled room investigations to clinical applications. Our primary findings showed that NCITs and IRT can provide accurate and reliable body temperature measurements in specific settings and conditions. We revealed that while both NCITs and IRT displayed a consistent positive correlation with conventional, contact-based temperature measurement tools, NCITs demonstrated slightly superior accuracy over IRT. A total of 29 of 50 settings from NCIT studies and 4 of 22 settings from IRT studies achieved accuracy levels within a range of ±0.3 °C. Furthermore, we found that several factors influenced the performance of these devices. These included the measurement location, the type of sensor, the reference and tool, individual physiological attributes, and the surrounding environmental conditions. Our research underscores the critical need for further studies in this area to refine our understanding of these influential factors and to develop standardized guidelines for the use of NCITs and IRT.

Infrared image method for possible COVID-19 detection through febrile and subfebrile people screening

This study proposed an infrared image-based method for febrile and subfebrile people screening to comply with the society need for alternative, quick response, and effective methods for COVID-19 contagious people screening. The methodology consisted of: (i) Developing a method based on facial infrared imaging for possible COVID-19 early detection in people with and without fever (subfebrile state); (ii) Using 1206 emergency room (ER) patients to develop an algorithm for general application of the method, and (iii) Testing the method and algorithm effectiveness in 2558 cases (RT-qPCR tested for COVID-19) from 227,261 workers evaluations in five different countries. Artificial intelligence was used through a convolutional neural network (CNN) to develop the algorithm that took facial infrared images as input and classified the tested individuals in three groups: fever (high risk), subfebrile (medium risk), and no fever (low risk). The results showed that suspicious and confirmed COVID-19 (+) cases characterized by temperatures below the 37.5 °C fever threshold were identified. Also, average forehead and eye temperatures greater than 37.5 °C were not enough to detect fever similarly to the proposed CNN algorithm. Most RT-qPCR confirmed COVID-19 (+) cases found in the 2558 cases sample (17 cases/89.5%) belonged to the CNN selected subfebrile group. The COVID-19 (+) main risk factor was to be in the subfebrile group, in comparison to age, diabetes, high blood pressure, smoking and others. In sum, the proposed method was shown to be a potentially important new tool for COVID-19 (+) people screening for air travel and public places in general.

The Current State of Optical Sensors in Medical Wearables

Optical sensors play an increasingly important role in the development of medical diagnostic devices. They can be very widely used to measure the physiology of the human body. Optical methods include PPG, radiation, biochemical, and optical fiber sensors. Optical sensors offer excellent metrological properties, immunity to electromagnetic interference, electrical safety, simple miniaturization, the ability to capture volumes of nanometers, and non-invasive examination. In addition, they are cheap and resistant to water and corrosion. The use of optical sensors can bring better methods of continuous diagnostics in the comfort of the home and the development of telemedicine in the 21st century. This article offers a large overview of optical wearable methods and their modern use with an insight into the future years of technology in this field.

Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases

Artificial intelligence (AI) represents a valuable tool that could be widely used to inform clinical and public health decision-making to effectively manage the impacts of a pandemic. The objective of this scoping review was to identify the key use cases for involving AI for pandemic preparedness and response from the peer-reviewed, preprint, and grey literature. The data synthesis had two parts: an in-depth review of studies that leveraged machine learning (ML) techniques and a limited review of studies that applied traditional modeling approaches. ML applications from the in-depth review were categorized into use cases related to public health and clinical practice, and narratively synthesized. One hundred eighty-three articles met the inclusion criteria for the in-depth review. Six key use cases were identified: forecasting infectious disease dynamics and effects of interventions; surveillance and outbreak detection; real-time monitoring of adherence to public health recommendations; real-time detection of influenza-like illness; triage and timely diagnosis of infections; and prognosis of illness and response to treatment. Data sources and types of ML that were useful varied by use case. The search identified 1167 articles that reported on traditional modeling approaches, which highlighted additional areas where ML could be leveraged for improving the accuracy of estimations or projections. Important ML-based solutions have been developed in response to pandemics, and particularly for COVID-19 but few were optimized for practical application early in the pandemic. These findings can support policymakers, clinicians, and other stakeholders in prioritizing research and development to support operationalization of AI for future pandemics.

An Overview of Thermal Infrared Imaging-Based Screenings during Pandemic Emergencies

Infrared thermal imaging (IRI) is a contact-less technology able to monitor human skin temperature for biomedical applications and in real-life contexts. Its capacity to detect fever was exploited for mass screening during past epidemic emergencies as well as for the current COVID-19 pandemic. However, the only assessment of fever may not be selective for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. Hence, novel approaches for IRI data analysis have been investigated. The present review aims to describe how IRI have been employed during the last epidemics, highlighting the potentialities and the limitations of this technology to contain the contagions. Specifically, the methods employed for automatic face recognition and fever assessment and IRI's performances in mass screening at airports and hospitals are reviewed. Moreover, an overview of novel machine learning methods for IRI data analysis, aimed to identify respiratory diseases, is provided. In addition, IRI-based smart technologies developed to support the healthcare during the COVID-19 pandemic are described. Finally, relevant guidelines to fully exploit IRI for COVID-19 identification are defined, to improve the effectiveness of IRI in the detection of the SARS-CoV-2 infection.

[Screening of febrile cows using a small handheld infrared thermography device]

OBJECTIVE

As dairy herds increase in size, close monitoring of health becomes a necessity, but this is expensive and labour-intensive. Early detection of febrile diseases is essential for economical and welfare reasons and to prevent the spread of disease. The goal of this study was therefore to evaluate a mobile, non-invasive technique for measuring the body temperature of cows that precludes the need for restraint of the animals.

MATERIALS AND METHODS

An infrared thermographic imaging camera installed on a smart phone was used to measure the surface temperature of cows. In experiment 1, a metal block heated to defined temperatures was used to obtain infrared thermographic measurements (THM). The accuracy of THM made at different distances from the block and at 2 different ambient temperatures was determined. In experiment 2, non-febrile cows underwent infrared thermographic imaging, and the body regions with the highest correlations between thermographic and rectal temperature were identified. In experiment 3, THM were made in febrile and neighbouring non-febrile cows.

RESULTS

In experiment 1, the thermographic and true temperatures of the block had the strongest relationships at 0.5 and 1.0 m (r = 0.98). The ambient temperature had a significant effect on the THM, which had larger variations and greater deviations from the block temperature at 14.8 °C than at 23.8 °C. In experiment 2, the maximum temperature at the eye (r = 0.37), THM at the muzzle (r = 0.28) and the medial canthus (r = 0.27) showed the strongest relationships with the rectal temperature. After correcting the THM with the mean difference between thermographic and rectal temperatures of the non-febrile cows, sensitivities of 88, 90 and 82 %, respectively, were calculated for THM at the muzzle, eye and medial canthus in febrile cows in experiment 3. The corresponding specificities were 6, 23 and 32 %.

CONCLUSION AND CLINICAL RELEVANCE

Based on the low specificities of the infrared THM, the thermographic imaging camera has limited usefulness for the mass screening of dairy cows for febrile conditions. Cattle falsely identified as febrile need to be separated, caught and re-examined, which causes unnecessary stress to the animal and increases labour input.

Factors Affecting the Cases and Deaths of COVID-19 Victims

This paper attempts to find the factors that affect the number of cases and deaths of coronavirus disease 2019 (COVID-19) patients a year after the first outbreak in Wuhan, China. There were 141 countries affected with COVID-19 involved in the study. Countries were grouped based on population. Using ordinary least squares regression, it was found that the total number of cases and deaths were significantly related with the levels of population of the different countries. On the overall, median age of the country, and average temperature are positively related with the number of deaths from the virus. On the other hand, population density is positively related with the deaths due to COVID for low populated countries. The result of this preliminary study can be used as a benchmark for authorities in the formulation of policies with regards to treating COVID-19 related issues.

Diagnostic accuracy of non-contact infrared thermometers and thermal scanners: a systematic review and meta-analysis

Infrared thermal screening, via the use of handheld non-contact infrared thermometers (NCITs) and thermal scanners, has been widely implemented all over the world. We performed a systematic review and meta-analysis to investigate its diagnostic accuracy for the detection of fever. We searched PubMed, Embase, the Cochrane Library, medRxiv, bioRxiv, ClinicalTrials.gov, COVID-19 Open Research Dataset, COVID-19 research database, Epistemonikos, EPPI-Centre, World Health Organization International Clinical Trials Registry Platform, Scopus and Web of Science databases for studies where a non-contact infrared device was used to detect fever against a reference standard of conventional thermometers. Forest plots and Hierarchical Summary Receiver Operating Characteristics curves were used to describe the pooled summary estimates of sensitivity, specificity and diagnostic odds ratio. From a total of 1063 results, 30 studies were included in the qualitative synthesis, of which 19 were included in the meta-analysis. The pooled sensitivity and specificity were 0.808 (95%CI 0.656-0.903) and 0.920 (95%CI 0.769-0.975), respectively, for the NCITs (using forehead as the site of measurement), and 0.818 (95%CI 0.758-0.866) and 0.923 (95%CI 0.823-0.969), respectively, for thermal scanners. The sensitivity of NCITs increased on use of rectal temperature as the reference. The sensitivity of thermal scanners decreased in a disease outbreak/pandemic setting. Changes approaching statistical significance were also observed on the exclusion of neonates from the analysis. Thermal screening had a low positive predictive value, especially at the initial stage of an outbreak, whereas the negative predictive value (NPV) continued to be high even at later stages. Thermal screening has reasonable diagnostic accuracy in the detection of fever, although it may vary with changes in subject characteristics, setting, index test and the reference standard used. Thermal screening has a good NPV even during a pandemic. The policymakers must take into consideration the factors surrounding the screening strategy while forming ad-hoc guidelines.

Asymptomatic COVID-19 patients and possible screening before an emergency aerosol related endodontic protocols in dental clinic-A Review

Dentistry is related to the cure of oral and dental infections, so exposure and proximity of dental practitioners to oral and nasal fluids of a patient is very obvious. Before you proceed for an aerosol-generating procedure like RCT, and crown preparations, diagnosis, and screening of COVID-19 is very important, as failure may end up infecting yourself and would become a source of infection to your patient community. Due to limitations of data, medicines, and PPE shortage all around the world, screening of asymptomatic carriers of COVID-19 is very troublesome but necessary. To avoid any silent positive patient, the possible way is to ensure mandatory testing of every patient before you treat it. As the door to door surveillance of COVID-19 patients seems near to impossible in the Pandemic era for densely populated developing countries like India. The possible screening regimes include personal surveillance and contact tracing in the very first appointments. So, on the basis of the knowledge and sources we have so far, we have tried to classify the asymptomatic patients seen in the clinics and their possible screening management there. As it is said classification of a disease, is the first step toward a deep understanding of it. After screening, suspects can be sent to more resourceful places for their managements, and incidences of community spread of the disease through dental clinics can be avoided.

Clinical evaluation of fever-screening thermography: impact of consensus guidelines and facial measurement location

SIGNIFICANCE

Infrared thermographs (IRTs) have been used for fever screening during infectious disease epidemics, including severe acute respiratory syndrome, Ebola virus disease, and coronavirus disease 2019 (COVID-19). Although IRTs have significant potential for human body temperature measurement, the literature indicates inconsistent diagnostic performance, possibly due to wide variations in implemented methodology. A standardized method for IRT fever screening was recently published, but there is a lack of clinical data demonstrating its impact on IRT performance.

AIM

Perform a clinical study to assess the diagnostic effectiveness of standardized IRT-based fever screening and evaluate the effect of facial measurement location.

APPROACH

We performed a clinical study of 596 subjects. Temperatures from 17 facial locations were extracted from thermal images and compared with oral thermometry. Statistical analyses included calculation of receiver operating characteristic (ROC) curves and area under the curve (AUC) values for detection of febrile subjects.

RESULTS

Pearson correlation coefficients for IRT-based and reference (oral) temperatures were found to vary strongly with measurement location. Approaches based on maximum temperatures in either inner canthi or full-face regions indicated stronger discrimination ability than maximum forehead temperature (AUC values of 0.95 to 0.97 versus 0.86 to 0.87, respectively) and other specific facial locations. These values are markedly better than the vast majority of results found in prior human studies of IRT-based fever screening.

CONCLUSION

Our findings provide clinical confirmation of the utility of consensus approaches for fever screening, including the use of inner canthi temperatures, while also indicating that full-face maximum temperatures may provide an effective alternate approach.

Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks

Estimation of vital signs using image processing techniques have already been proved tohave a potential for supporting remote medical diagnostics and replacing traditional measurementsthat usually require special hardware and electrodes placed on a body. In this paper, we furtherextend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermalimagery by enhancing acquired sequences using Deep Neural Networks (DNN). To perform extensivebenchmark evaluation, we acquired two thermal datasets using FLIR® cameras with a spatialresolution of 80 × 60 and 320 × 240 from 71 volunteers in total. In-depth analysis of the proposedConvolutional-based Super Resolution model showed that for images downscaled with a factor of 2and then super-resolved using Deep Learning (DL) can lead to better RR estimation accuracy thanfrom original high-resolution sequences. In addition, if an estimator based on a dominating peakin the frequency domain is used, SR can outperform original data for a down-scale factor of 4 andimages as small as 20 × 15 pixels. Our study also showed that RR estimation accuracy is betterfor super-resolved data than for images with color changes magnified using algorithms previouslyapplied in the literature for enhancing vital signs patterns.

Best practices for standardized performance testing of infrared thermographs intended for fever screening

Infrared (IR) modalities represent the only currently viable mass fever screening approaches for outbreaks of infectious disease pandemics such as Ebola virus disease and severe acute respiratory syndrome. Non-contact IR thermometers (NCITs) and IR thermographs (IRTs) have been used for fever screening in public areas such as airports. While NCITs remain a more popular choice than IRTs, there has been increasing evidences in the literature that IRTs can provide great accuracy in estimating body temperature if qualified systems are used and appropriate procedures are consistently applied. In this study, we addressed the issue of IRT qualification by implementing and evaluating a battery of test methods for objective, quantitative assessment of IRT performance based on a recent international standard (IEC 80601-2-59). We tested two commercial IRTs to evaluate their stability and drift, image uniformity, minimum resolvable temperature difference, and radiometric temperature laboratory accuracy. Based on these tests, we illustrated how experimental and data processing procedures could affect results, and suggested methods for clarifying and optimizing test methods. Overall, the insights into thermograph standardization and acquisition methods provided by this study may improve the utility of IR thermography and aid in comparing IRT performance, thus improving the potential for producing high quality disease pandemic countermeasures.

Post-mortem thermal angiography: a pilot study on swine coronary circulation

Thermal imaging (TI) allows the detection of thermal patterns emitted from objects as a function of their temperature in the long-infrared spectrum and produces visible images displaying temperature differences. The aim of this pilot study was to test TI to visualize the coronary circulation of swine hearts. Thirty swine hearts were prepared for ex situ coronarography, and thermal images were acquired through a FlirOne thermal camera (FLIR Systems®) paired with a Google Android Smartphone. Coronary arteries were cannulated, namely the anterior interventricular artery, the circumflex branch of the left coronary artery, and the right coronary artery. The heart was cooled, and contrast medium (CM) consisting of distilled water heated to 40 °C was injected in a coronary vessel, while thermal images were captured. These steps were repeated for each coronary vessel and under experimentally simulated coronary heart disease. Thermal imaging coronarography (TIC) allowed a clear representation of the morphology and course of the coronary vessels and of experimentally simulated coronary heart disease, moreover, demonstrated to be easy to perform during or after autopsies on ex situ hearts, non-destructive, reproducible, and cheap. On the basis of these preliminary results, TIC might allow a subsequent more focused and comprehensive cardiopathological examination of the heart, which remains mandatory for the definitive diagnosis of coronary heart disease. Although these preliminary results seem encouraging, further systematic studies on human hearts, both normal and pathological, are necessary for estimating the sensitivity and specificity of the proposed method and to draw any definitive conclusion.

A pilot study of the Leicester ED medical infrared imaging protocol in fever and sepsis

BACKGROUND

Medical Infrared Imaging (MII) is an investigative method that can be potentially used in emergency care to non-invasively detect thermal signatures associated with change in blood flow. We have developed a protocol for the use of MII in the Emergency Department (ED) and shown that it is feasible. To derive initial data for sample size calculations, we performed an exploratory study in patients with fever and sepsis.

METHODS

The Leicester MII protocol was used to image the temperature patterns along the arm among three patient groups (control, fever and sepsis) of a total 56 patients. Anatomical markers were used to divide this gradient into upper arm, forearm, hand and finger regions. Variations in measurements within and between these regions were described.

RESULTS

The thermal gradient down the arm was successfully extracted in all patients. The distribution of values in each region of the arm was described in control, fever and sepsis patients. There was a significant gradient between upper arm and finger in controls (2.75, p < 0.0001), but no gradient in fever (p = 0.944) or sepsis (p = 0.710). This was reflected in the finger/arm difference, which was of -2.74°C (±3.50) in controls, -0.39C (±2.48) in fever, and -1.80°C (±3.09) in sepsis.

CONCLUSIONS

This study found different thermal gradients along the arm in control and febrile groups, and defined the degree of individual variation. It is likely that the difference between upper arm temperature and finger temperature (representing the temperature gradient down the arm) may be more useful than absolute measurements in future studies.

THERMAL IMAGING AS AN ADJUNCT TOOL FOR IDENTIFYING FETAL GROWTH – A PILOT STUDY

Monitoring the fetal growth and diagnosing any possible abnormality plays a vital role in ensuring the healthy growth of a fetus. Certain health issues like Hyperthermia, Premature Rupture of Membranes (PROM) and Intrauterine Growth Restriction (IUGR) has to be diagnosed early. A pilot study comprising of 27 pregnant and 2 non-pregnant subjects was conducted to check the effectiveness of Thermal imaging in predicting the fetal growth. The heat dissipated by the fetus to the maternal abdominal wall is acquired as a surface thermal distribution. These images were processed qualitatively and quantitatively for better understanding. There was a consistent higher thermal pattern for pregnant women. A more pronounced temperature pattern is notable in the umbilical region that correlates with gestation age. However, as thermal pattern varies with age, gestation period and BMI, it is advisable to track the same person and compare the images for better assessment. This pilot study justifies the need for more elaborate study in building a database for classification and interpretation of thermogram to detect fetal abnormality with reduced human interpretation.

Application of infrared thermography in computer aided diagnosis

The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, improved sensitivity and spatial resolution of thermal sensors. However, despite this progress fundamental issues with this imaging modality still remain. The main problem is that the link between disease and heat radiation is complex and in many cases even non-linear. Furthermore, the change in heat radiation as well as the change in radiation pattern, which indicate disease, is minute. On a technical level, this poses high requirements on image capturing and processing. On a more abstract level, these problems lead to inter-observer variability and on an even more abstract level they lead to a lack of trust in this imaging modality. In this review, we adopt the position that these problems can only be solved through a strict application of scientific principles and objective performance assessment. Computing machinery is inherently objective; this helps us to apply scientific principles in a transparent way and to assess the performance results. As a consequence, we aim to promote thermography based Computer-Aided Diagnosis (CAD) systems. Another benefit of CAD systems comes from the fact that the diagnostic accuracy is linked to the capability of the computing machinery and, in general, computers become ever more potent. We predict that a pervasive application of computers and networking technology in medicine will help us to overcome the shortcomings of any single imaging modality and this will pave the way for integrated health care systems which maximize the quality of patient care.

Clinical trial on the characteristics of zheng classification of pulmonary diseases based on infrared thermal imaging technology

Zheng classification study based on infrared thermal imaging technology has not been reported before. To detect the relative temperature of viscera and bowels of different syndromes patients with pulmonary disease and to summarize the characteristics of different Zheng classifications, the infrared thermal imaging technology was used in the clinical trial. The results showed that the infrared thermal images characteristics of different Zheng classifications of pulmonary disease were distinctly different. The influence on viscera and bowels was deeper in phlegm-heat obstructing lung syndrome group than in cold-phlegm obstructing lung syndrome group. It is helpful to diagnose Zheng classification and to improve the diagnosis rate by analyzing the infrared thermal images of patients. The application of infrared thermal imaging technology provided objective measures for medical diagnosis and treatment in the field of Zheng studies and provided a new methodology for Zheng classification.

BREAST THERMOGRAPHY AS A POTENTIAL NON-CONTACT METHOD IN THE EARLY DETECTION OF CANCER: A REVIEW

This review paper discusses recent research achievements in medical thermography with concerns about the possibility of early breast cancer detection. With the advancements in infrared (IR) technology, image processing methods, and the pathophysiological-based knowledge of thermograms, IR screening is sufficiently mature to be utilized as a first-line complement to both health managing and clinical prognosis. In addition, it explains the performance and environmental conditions in identifying thermography for breast tumor imaging under strict indoor controlled environmental circumstances. An irregular thermogram is indicated as a significant biological risk marker for the presence or growth of breast tumors. Breast thermography is completely non-contact, with no form of radiation and compression. It is useful for all women of all ages, for pregnant and breastfeeding women, for women with implants, for women with dense or fibrocystic breasts, for women on hormone replacement therapy, and for pre or post menopausal women.

Breast thermography is specifically worthwhile during the early stages of fast tumor growth, which is not yet recognizable by mammography as thermography is a physiological test while mammography is an anatomical one. Often, physiological changes precede anatomical changes. This early detection of irregular tissue liveliness gives breast thermography the potential to be greatly useful and economical as an imaging program and provides the opportunity to apply non-invasive treatment to reform breast tissue activity. The non-radiating nature of thermography also permits repeated images. Thus, changes can be compared over time and the results of protective approaches can be observed to ensure utmost care of breast cells.

NEW STANDARDS FOR FEVER SCREENING WITH THERMAL IMAGING SYSTEMS

Infrared thermal imaging has in recent years become more accessible and affordable as a means of remote sensing for human body temperature such as in identifying a person with fever. The implementation and operational guidelines for identifying a febrile human using a screening thermograph as documented in the ISO/TR 13154:2009 ISO/TR 80600 has been deployed for the screening of a total of 402 children. It was found that there was a significant difference between the temperatures measured in non-fevered patients and those with known fever, with the thermal imaging of the eye region being the most rapid non-contact site for measurement.

Mechanisms of Laser-Tissue Interaction: II. Tissue Thermal Properties

Laser-tissue interaction is of great interest due to its significant application in biomedical optics in both diagnostic and treatment purposes. Major aspects of the laser-tissue interaction which has to be considered in biomedical studies are the thermal properties of the tissue and the thermal changes caused by the interaction of light and tissue. In this review paper the effects of light on the tissue at different temperatures are discussed. Then, due to the noticeable importance of studying the heat transfer quantitatively, the equations governing this phenomenon are presented. Finally a method of medical diagnosis called thermography and some of its applications are explained.

Medical applications of infrared thermography: A review

Abnormal body temperature is a natural indicator of illness. Infrared thermography (IRT) is a fast, passive, non-contact and non-invasive alternative to conventional clinical thermometers for monitoring body temperature. Besides, IRT can also map body surface temperature remotely. Last five decades witnessed a steady increase in the utility of thermal imaging cameras to obtain correlations between the thermal physiology and skin temperature. IRT has been successfully used in diagnosis of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has also been used to detect problems associated with gynecology, kidney transplantation, dermatology, heart, neonatal physiology, fever screening and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The present efforts are focused on automatic analysis of temperature distribution of regions of interest and their statistical analysis for detection of abnormalities. This critical review focuses on advances in the area of medical IRT. The basics of IRT, essential theoretical background, the procedures adopted for various measurements and applications of IRT in various medical fields are discussed in this review. Besides background information is provided for beginners for better understanding of the subject.

Assessment of border control measures and community containment measures used in Japan during the early stages of Pandemic (H1N1) 2009

BACKGROUND

In the early stages of Pandemic (H1N1) 2009, border control measures were taken by quarantine stations to block the entry of infected individuals into Japan and community containment measures were implemented to prevent the spreading. The objectives of this study were to describe these measures and the characteristics of infected individuals, and to assess the measures' effectiveness.

METHODOLOGY/PRINCIPAL FINDINGS

Border control and community containment measures implemented from April to June (Period I: April 28-May 21, Period II: May 22-June 18) 2009 were described. Number of individuals identified and disease characteristics were analyzed. For entry screening, a health declaration form and an infrared thermoscanner were used to detect symptomatic passengers. Passengers indicated for the rapid influenza test underwent the test followed by RT-PCR. Patients positive for H1N1 were isolated, and close contacts were quarantined. Entry cards were handed out to all asymptomatic passengers informing them about how to contact a health center in case they developed symptoms. Nine individuals were identified by entry screening and 1 during quarantine to have Pandemic (H1N1) 2009. Health monitoring by health centers was performed in period I for passengers arriving from affected countries and in period II for those who had come into contact with the individuals identified by entry screening. Health monitoring identified 3 infected individuals among 129,546 in Period I and 5 among 746 in Period II. Enhanced surveillance, which included mandatory reporting of details of the infected individuals, identified 812 individuals, 141 (18%) of whom had a history of international travel. Twenty-four of these 141 passengers picked up by enhanced surveillance had been developing symptoms on entry and were missed at screening.

CONCLUSION/SIGNIFICANCE

Symptomatic passengers were detected by the various entry screening measures put in place. Enhanced surveillance provided data for the improvement of public health measures in future pandemics.

CLASSIFICATION OF HUMAN FACIAL AND AURAL TEMPERATURE USING NEURAL NETWORKS AND IR FEVER SCANNER: A RESPONSIBLE SECOND LOOK

Severe Acute Respiratory Syndrome (SARS) is a highly infectious disease caused by a coronavirus. Screening to detect potential SARS infected subject with elevated body temperature plays an important role in preventing the spread of SARS. The use of infrared (IR) thermal imaging cameras has thus been proposed as a non-invasive, speedy, cost-effective and fairly accurate means for mass blind screening of potential SARS infected persons. Infrared thermography provides a digital image showing temperature patterns. This has been previously utilized in the detection of inflammation and nerve dysfunctions. It is believed that IR cameras may potentially be used to detect subjects with fever, the cardinal symptom of SARS and avian influenza. The accuracy of the infrared system can, however, be affected by human, environmental, and equipment variables. It is also limited by the fact that the thermal imager measures the skin temperature and not the body core temperature. Thus, the use of IR thermal systems at various checkpoints for mass screening of febrile persons is scientifically unjustified such as what is the false negative rate and most importantly not to create false sense of security.

This paper aims to study the effectiveness of infrared systems for its application in mass blind screening to detect subjects with elevated body temperature. For this application, it is critical for thermal imagers to be able to identify febrile from normal subjects accurately. Minimizing the number of false positive and false negative cases improves the efficiency of the screening stations. False negative results should be avoided at all costs, as letting a SARS infected person through the screening process may result in potentially catastrophic results. Hitherto, there is lack of empirical data in correlating facial skin with body temperature. The current work evaluates the correlations (and classification) between the facial skin temperatures to the aural temperature using the artificial neural network approach to confirm the suitability of the thermal imagers for human temperature screening. We show that the Train Back Propagation and Kohonen self-organizing map (SOM) can form an opinion about the type of network that is better to complement thermogram technology in fever diagnosis to drive a better parameters for reducing the size of the neural network classifier while maintaining good classification accuracy.

Fever screening during the influenza (H1N1-2009) pandemic at Narita International Airport, Japan

Background

Entry screening tends to start with a search for febrile international passengers, and infrared thermoscanners have been employed for fever screening in Japan. We aimed to retrospectively assess the feasibility of detecting influenza cases based on fever screening as a sole measure.

Methods

Two datasets were collected at Narita International Airport during the 2009 pandemic. The first contained confirmed influenza cases (n = 16) whose diagnosis took place at the airport during the early stages of the pandemic, and the second contained a selected and suspected fraction of passengers (self-reported or detected by an infrared thermoscanner; n = 1,049) screened from September 2009 to January 2010. The sensitivity of fever (38.0°C) for detecting H1N1-2009 was estimated, and the diagnostic performances of the infrared thermoscanners in detecting hyperthermia at cut-off levels of 37.5°C, 38.0°C and 38.5°C were also estimated.

Results

The sensitivity of fever for detecting H1N1-2009 cases upon arrival was estimated to be 22.2% (95% confidence interval: 0, 55.6) among nine confirmed H1N1-2009 cases, and 55.6% of the H1N1-2009 cases were under antipyretic medications upon arrival. The sensitivity and specificity of the infrared thermoscanners in detecting hyperthermia ranged from 50.8-70.4% and 63.6-81.7%, respectively. The positive predictive value appeared to be as low as 37.3-68.0%.

Conclusions

The sensitivity of entry screening is a product of the sensitivity of fever for detecting influenza cases and the sensitivity of the infrared thermoscanners in detecting fever. Given the additional presence of confounding factors and unrestricted medications among passengers, reliance on fever alone is unlikely to be feasible as an entry screening measure.

The Ethics of Responding to a Novel Pandemic

Recent epidemics and pandemics have highlighted a number of ethical concerns about the response to the increasing threat of emerging infectious diseases. Some of these ethical concerns are very fundamental. They include why a pandemic was declared, how much clinical information can be collected for public health without threatening patient confidentiality and how to ensure fairness in the distribution of resources. We discuss these issues and suggest approaches to resolve these dilemmas as we anticipate the next pandemic. Key words: Bioethics, Emerging infectious diseases, Ethics, Influenza, Pandemic, Quarantine, SARS, Surveillance

Mass screening of suspected febrile patients with remote-sensing infrared thermography: alarm temperature and optimal distance

BACKGROUND/PURPOSE

Detection of fever has become an essential step in identifying patients who may have severe acute respiratory syndrome (SARS) or avian influenza. This study evaluated infrared thermography (IRT) and compared the influence of different imagers, ambient temperature discrepancy, and the distance between the subject and imager.

METHODS

IRT-digital infrared thermal imaging (IRT-DITI), thermoguard, and ear drum IRT were used for visitors to Municipal Wang Fang Hospital, Taipei, Taiwan. The McNemar and Chi-squared test, standard Pearson correlation, ANOVA, intraclass correlation coefficient (ICC), and receiver operating characteristic curve (ROC) analysis were used to calculate the alarm temperature for each imager.

RESULTS

A total of 1032 subjects were recruited. Different distances and ambient temperature discrepancy had a significant influence on thermoguard, and lateral and frontal view DITI. By ICC analysis, a significant difference was found at 10 m distance between ear drum IRT and thermoguard (r = 0.45), lateral view DITI (r = 0.37), and frontal view DITI (r = 0.44). With ROC analysis, the optimal preset cut-off temperatures for the different imagers were: 36.05 degrees C for thermoguard (area under the curve [AUC], 0.716), 36.25 degrees C for lateral view DITI (AUC, 0.801), and 36.25 degrees C for frontal view DITI (AUC, 0.812).

CONCLUSION

The temperature readings obtained by IRT may be used as a proxy for core temperature. An effective IRT system with a strict operating protocol can be rapidly implemented at the entrance of a hospital during SARS or avian influenza epidemics.

Advanced integrated technique in breast cancer thermography

Thermography is a passive and non-contact imaging technique used extensively in the medical arena, but in relation to breast care, it has not been accepted as being on a par with mammography. This paper proposes the analysis of thermograms with the use of artificial neural networks (ANN) and bio-statistical methods, including regression and receiver operating characteristics (ROC). It is desired that through these approaches, highly accurate diagnosis using thermography techniques can be achieved. The suggested method is a multi-pronged approach comprising of linear regression, radial basis function network (RBFN) and ROC analysis. It is a novel, integrative and powerful technique that can be used to analyse large amounts of complicated measured data such as temperature values extracted from abnormal and healthy breast thermograms. The use of regression allows the correlation between the variables and the actual health status of the subject, which is decided by other traditional means such as the gold standard of mammography for breast cancer detection. This is important as it helps to select the appropriate variables to be used as inputs for building the neural network. RBFN is next trained to produce the desired outcome that is either positive or negative. When this is done, the RBFN possess the ability to predict the outcome when there are new input variables. The advantages of using RBFN include fast training of superior classification and decision-making abilities as compared to other networks such as backpropagation. Lastly, ROC is applied to evaluate the sensitivity, specificity and accuracy of the outcome for the RBFN test files. The proposed technique has an accuracy rate of 80.95%, with 100% sensitivity and 70.6% specificity in identifying breast cancer. The results are promising as compared to clinical examination by experienced radiologists, which has an accuracy rate of approximately 60-70%. To sum up, technological advances in the field of infrared thermography over the last 20 years warrant a re-evaluation of the use of high-resolution digital thermographic camera systems in the diagnosis and management of breast cancer. Thermography seeks to identify the presence of a tumour by the elevated temperature associated with increase blood flow and cellular activity. Of particular interest would be investigation in younger women and men, for whom mammography is either unsuitable or of limited effectiveness. The paper evaluated the high-definition digital infrared thermographic technology and knowledge base; and supports the development of future diagnostic and therapeutic services in breast cancer imaging. Through the use of integrative ANN and bio-statistical methods, advances are made in thermography application with regard to achieving a higher level of consistency. For breast cancer care, it has become possible to use thermography as a powerful adjunct and biomarker tool, together with mammography for diagnosis purposes.

A near-infrared (NIR) technique for imaging food materials

The results of imaging experiments in food materials are presented, using near-infrared wavelengths. The technique uses a modulated source and a lock-in amplifier detection circuit to give a high sensitivity to changes in through-transmission signal levels. This is shown to lead to a set of images, whereby the internal content of various foods can be imaged. Examples are presented of the detection of foreign bodies, both metallic and nonmetallic, to illustrate the imaging performance.

ANN-based mapping of febrile subjects in mass thermogram screening: facts and myths

Severe Acute Respiratory Syndrome (SARS) is a highly infectious disease caused by a coronavirus. Screening to detect potential SARS-infected subjects with elevated body temperature plays an important role in preventing the spread of SARS. Thermography is being used with ANN/AI to analyse the data collected from the designated SARS hospital in Singapore, and conclusive results are drawn. The current work evaluates the correlations (and classifications) between facial skin temperatures, including eye range and forehead, to aural temperature using a neural network (NN) approach, namely training backpropagation (BP) and Kohonen self-organizing map (SOM), to confirm the suitability of thermal imagers for human temperature screening. Both BP and SOM can form an opinion about the type of network that is better able to complement thermogram technology in fever diagnosis. This can produce better parameters for reducing the size of the NN classifier, while maintaining good classification accuracy. We observe that BP performs better than SOM NN. Confusion matrix (CM), an alternative display instrument, is able to process a high volume of input data and show the clustered output rapidly and accurately. The current research application will remain an interesting and useful reference for both local and overseas manufacturers of thermal scanners, users and various government and private establishments. As the elevation of body temperature is a common presenting symptom for many illnesses, including infectious diseases such as SARS, thermal imagers are useful and essential tools for mass screening of body temperature. This is true not only for SARS but also during other public health crises where widespread transmission of infection such as the danger of avian flu pandemic is a concern, in particular at places like hospitals and cross-border checkpoints.

A global bioheat model with self-tuning optimal regulation of body temperature using Hebbian feedback covariance learning

In the lower brain, body temperature is continually being regulated almost flawlessly despite huge fluctuations in ambient and physiological conditions that constantly threaten the well-being of the body. The underlying control problem defining thermal homeostasis is one of great enormity: Many systems and sub-systems are involved in temperature regulation and physiological processes are intrinsically complex and intertwined. Thus the defining control system has to take into account the complications of nonlinearities, system uncertainties, delayed feedback loops as well as internal and external disturbances. In this paper, we propose a self-tuning adaptive thermal controller based upon Hebbian feedback covariance learning where the system is to be regulated continually to best suit its environment. This hypothesis is supported in part by postulations of the presence of adaptive optimization behavior in biological systems of certain organisms which face limited resources vital for survival. We demonstrate the use of Hebbian feedback covariance learning as a possible self-adaptive controller in body temperature regulation. The model postulates an important role of Hebbian covariance adaptation as a means of reinforcement learning in the thermal controller. The passive system is based on a simplified 2-node core and shell representation of the body, where global responses are captured. Model predictions are consistent with observed thermoregulatory responses to conditions of exercise and rest, and heat and cold stress. An important implication of the model is that optimal physiological behaviors arising from self-tuning adaptive regulation in the thermal controller may be responsible for the departure from homeostasis in abnormal states, e.g., fever. This was previously unexplained using the conventional "set-point" control theory.