Clinical evaluation of fever-screening thermography: impact of consensus guidelines and facial measurement location.
Identifieur interne : 000244 ( Main/Corpus ); précédent : 000243; suivant : 000245Clinical evaluation of fever-screening thermography: impact of consensus guidelines and facial measurement location.
Auteurs : Yangling Zhou ; Pejman Ghassemi ; Michelle Chen ; David Mcbride ; Jon P. Casamento ; T Joshua Pfefer ; Quanzeng WangSource :
- Journal of biomedical optics [ 1560-2281 ] ; 2020.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), Area Under Curve (MeSH), Betacoronavirus (MeSH), Body Temperature (MeSH), Coronavirus Infections (diagnosis), Face (physiology), Female (MeSH), Fever (diagnosis), Humans (MeSH), Infrared Rays (MeSH), Male (MeSH), Mass Screening (methods), Middle Aged (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnosis), Practice Guidelines as Topic (MeSH), ROC Curve (MeSH), Reproducibility of Results (MeSH), Thermography (methods), Young Adult (MeSH).
- MESH :
- diagnosis : Coronavirus Infections, Fever, Pneumonia, Viral.
- methods : Mass Screening, Thermography.
- physiology : Face.
- Adolescent, Adult, Aged, Area Under Curve, Betacoronavirus, Body Temperature, Female, Humans, Infrared Rays, Male, Middle Aged, Pandemics, Practice Guidelines as Topic, ROC Curve, Reproducibility of Results, Young Adult.
Abstract
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.
DOI: 10.1117/1.JBO.25.9.097002
PubMed: 32921005
PubMed Central: PMC7486803
Links to Exploration step
pubmed:32921005Le document en format XML
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Casamento</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Pfefer, T Joshua" sort="Pfefer, T Joshua" uniqKey="Pfefer T" first="T Joshua" last="Pfefer">T Joshua Pfefer</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Wang, Quanzeng" sort="Wang, Quanzeng" uniqKey="Wang Q" first="Quanzeng" last="Wang">Quanzeng Wang</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32921005</idno><idno type="pmid">32921005</idno><idno type="doi">10.1117/1.JBO.25.9.097002</idno><idno type="pmc">PMC7486803</idno><idno type="wicri:Area/Main/Corpus">000244</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000244</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Clinical evaluation of fever-screening thermography: impact of consensus guidelines and facial measurement location.</title><author><name sortKey="Zhou, Yangling" sort="Zhou, Yangling" uniqKey="Zhou Y" first="Yangling" last="Zhou">Yangling Zhou</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>University of Maryland, Department of Mechanical Engineering, Baltimore County, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Ghassemi, Pejman" sort="Ghassemi, Pejman" uniqKey="Ghassemi P" first="Pejman" last="Ghassemi">Pejman Ghassemi</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Chen, Michelle" sort="Chen, Michelle" uniqKey="Chen M" first="Michelle" last="Chen">Michelle Chen</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Johns Hopkins University, Department of Chemical and Biomolecular Engineering, Baltimore, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Mcbride, David" sort="Mcbride, David" uniqKey="Mcbride D" first="David" last="Mcbride">David Mcbride</name><affiliation><nlm:affiliation>University of Maryland, University Health Center, College Park, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Casamento, Jon P" sort="Casamento, Jon P" uniqKey="Casamento J" first="Jon P" last="Casamento">Jon P. Casamento</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Pfefer, T Joshua" sort="Pfefer, T Joshua" uniqKey="Pfefer T" first="T Joshua" last="Pfefer">T Joshua Pfefer</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author><author><name sortKey="Wang, Quanzeng" sort="Wang, Quanzeng" uniqKey="Wang Q" first="Quanzeng" last="Wang">Quanzeng Wang</name><affiliation><nlm:affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Journal of biomedical optics</title><idno type="eISSN">1560-2281</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent (MeSH)</term><term>Adult (MeSH)</term><term>Aged (MeSH)</term><term>Area Under Curve (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>Body Temperature (MeSH)</term><term>Coronavirus Infections (diagnosis)</term><term>Face (physiology)</term><term>Female (MeSH)</term><term>Fever (diagnosis)</term><term>Humans (MeSH)</term><term>Infrared Rays (MeSH)</term><term>Male (MeSH)</term><term>Mass Screening (methods)</term><term>Middle Aged (MeSH)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (diagnosis)</term><term>Practice Guidelines as Topic (MeSH)</term><term>ROC Curve (MeSH)</term><term>Reproducibility of Results (MeSH)</term><term>Thermography (methods)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Coronavirus Infections</term><term>Fever</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Mass Screening</term><term>Thermography</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Face</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Aged</term><term>Area Under Curve</term><term>Betacoronavirus</term><term>Body Temperature</term><term>Female</term><term>Humans</term><term>Infrared Rays</term><term>Male</term><term>Middle Aged</term><term>Pandemics</term><term>Practice Guidelines as Topic</term><term>ROC Curve</term><term>Reproducibility of Results</term><term>Young Adult</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>SIGNIFICANCE</b></p><p>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.</p></div><div type="abstract" xml:lang="en"><p><b>AIM</b></p><p>Perform a clinical study to assess the diagnostic effectiveness of standardized IRT-based fever screening and evaluate the effect of facial measurement location.</p></div><div type="abstract" xml:lang="en"><p><b>APPROACH</b></p><p>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.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>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.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>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.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32921005</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>29</Day></DateCompleted><DateRevised><Year>2020</Year><Month>10</Month><Day>01</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1560-2281</ISSN><JournalIssue CitedMedium="Internet"><Volume>25</Volume><Issue>9</Issue><PubDate><Year>2020</Year><Month>09</Month></PubDate></JournalIssue><Title>Journal of biomedical optics</Title><ISOAbbreviation>J Biomed Opt</ISOAbbreviation></Journal><ArticleTitle>Clinical evaluation of fever-screening thermography: impact of consensus guidelines and facial measurement location.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.1117/1.JBO.25.9.097002</ELocationID><Abstract><AbstractText Label="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.</AbstractText><AbstractText Label="AIM">Perform a clinical study to assess the diagnostic effectiveness of standardized IRT-based fever screening and evaluate the effect of facial measurement location.</AbstractText><AbstractText Label="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.</AbstractText><AbstractText Label="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.</AbstractText><AbstractText Label="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.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhou</LastName><ForeName>Yangling</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>University of Maryland, Department of Mechanical Engineering, Baltimore County, Maryland, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ghassemi</LastName><ForeName>Pejman</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Michelle</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Johns Hopkins University, Department of Chemical and Biomolecular Engineering, Baltimore, Maryland, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>McBride</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>University of Maryland, University Health Center, College Park, Maryland, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Casamento</LastName><ForeName>Jon P</ForeName><Initials>JP</Initials><AffiliationInfo><Affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pfefer</LastName><ForeName>T Joshua</ForeName><Initials>TJ</Initials><AffiliationInfo><Affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Quanzeng</ForeName><Initials>Q</Initials><AffiliationInfo><Affiliation>Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>J Biomed Opt</MedlineTA><NlmUniqueID>9605853</NlmUniqueID><ISSNLinking>1083-3668</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName><SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019540" MajorTopicYN="N">Area Under Curve</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001831" MajorTopicYN="Y">Body Temperature</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005145" MajorTopicYN="N">Face</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005334" MajorTopicYN="N">Fever</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007259" MajorTopicYN="N">Infrared Rays</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008403" MajorTopicYN="N">Mass Screening</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017410" MajorTopicYN="N">Practice Guidelines as Topic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012372" MajorTopicYN="N">ROC Curve</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013817" MajorTopicYN="N">Thermography</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">COVID-19</Keyword><Keyword MajorTopicYN="Y">Pearson correlation coefficients</Keyword><Keyword MajorTopicYN="Y">fever screening</Keyword><Keyword MajorTopicYN="Y">infectious disease epidemics</Keyword><Keyword MajorTopicYN="Y">inner canthi</Keyword><Keyword MajorTopicYN="Y">medical guidelines</Keyword><Keyword MajorTopicYN="Y">receiver operating characteristic (ROC) curve</Keyword><Keyword MajorTopicYN="Y">thermography</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>06</Month><Day>29</Day></PubMedPubDate><PubMedPubDate 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