Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes

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dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorFERREIRA JUNIOR, Jose Raniery
dc.contributor.authorCARDENAS, Diego Armando Cardona
dc.contributor.authorMORENO, Ramon Alfredo
dc.contributor.authorREBELO, Marina de Fatima de Sa
dc.contributor.authorKRIEGER, Jose Eduardo
dc.contributor.authorGUTIERREZ, Marco Antonio
dc.date.accessioned2021-08-13T15:12:31Z
dc.date.available2021-08-13T15:12:31Z
dc.date.issued2021
dc.description.abstractCOVID-19 is a highly contagious disease that can cause severe pneumonia. Patients with pneumonia undergo chest X-rays (XR) to assess infiltrates that identify the infection. However, the radiographic characteristics of COVID-19 are similar to the other acute respiratory syndromes, hindering the imaging diagnosis. In this work, we proposed identifying quantitative/radiomic biomarkers for COVID-19 to support XR assessment of acute respiratory diseases. This retrospective study used different cohorts of 227 patients diagnosed with pneumonia; 49 of them had COVID-19. Automatically segmented images were characterized by 558 quantitative features, including gray-level histogram and matrices of co-occurrence, run-length, size zone, dependence, and neighboring gray-tone difference. Higher-order features were also calculated after applying square and wavelet transforms. Mann-Whitney U test assessed the diagnostic performance of the features, and the log-rank test assessed the prognostic value to predict Kaplan-Meier curves of overall and deterioration-free survival. Statistical analysis identified 51 independently validated radiomic features associated with COVID-19. Most of them were wavelet-transformed features; the highest performance was the small dependence matrix feature of ""low gray-level emphasis"" (area under the curve of 0.87, sensitivity of 0.85, p<0.001). Six features presented short-term prognostic value to predict overall and deterioration-free survival. The features of histogram ""mean absolute deviation"" and size zone matrix ""non-uniformity"" yielded the highest differences on Kaplan-Meier curves with a hazard ratio of 3.20 (p<0.05). The radiomic markers showed potential as quantitative measures correlated with the etiologic agent of acute infectious diseases and to stratify short-term risk of COVID-19 patients.eng
dc.description.indexMEDLINEeng
dc.description.sponsorshipFoxconn Brazil
dc.description.sponsorshipZerbini Foundation
dc.identifier.citationJOURNAL OF DIGITAL IMAGING, v.34, n.2, Special Issue, p.297-307, 2021
dc.identifier.doi10.1007/s10278-021-00421-w
dc.identifier.eissn1618-727X
dc.identifier.issn0897-1889
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/41355
dc.language.isoeng
dc.publisherSPRINGEReng
dc.relation.ispartofJournal of Digital Imaging
dc.rightsrestrictedAccesseng
dc.rights.holderCopyright SPRINGEReng
dc.subjectCOVID-19eng
dc.subjectRadiomicseng
dc.subjectCoronaviruseng
dc.subjectChest radiographyeng
dc.subjectMedical image analysiseng
dc.subject.wosRadiology, Nuclear Medicine & Medical Imagingeng
dc.titleNovel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomeseng
dc.typearticleeng
dc.type.categoryoriginal articleeng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.citation.scopus15
hcfmusp.contributor.author-fmusphcJOSE RANIERY FERREIRA JUNIOR
hcfmusp.contributor.author-fmusphcDIEGO ARMANDO CARDONA CARDENAS
hcfmusp.contributor.author-fmusphcRAMON ALFREDO MORENO
hcfmusp.contributor.author-fmusphcMARINA DE FATIMA DE SA REBELO
hcfmusp.contributor.author-fmusphcJOSE EDUARDO KRIEGER
hcfmusp.contributor.author-fmusphcMARCO ANTONIO GUTIERREZ
hcfmusp.description.beginpage297
hcfmusp.description.endpage307
hcfmusp.description.issue2
hcfmusp.description.issueSpecial Issue
hcfmusp.description.volume34
hcfmusp.origemWOS
hcfmusp.origem.pubmed33604807
hcfmusp.origem.scopus2-s2.0-85101218322
hcfmusp.origem.wosWOS:000619400500003
hcfmusp.publisher.cityNEW YORKeng
hcfmusp.publisher.countryUNITED STATESeng
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hcfmusp.scopus.lastupdate2024-06-14
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Artigos e Materiais de Revistas Científicas - FM/MCP
Artigos e Materiais de Revistas Científicas - COVID-19
Artigos e Materiais de Revistas Científicas - HC/InCor
Artigos e Materiais de Revistas Científicas - LIM/13
Artigos e Materiais de Revistas Científicas - LIM/65
Artigos e Materiais de Revistas Científicas - ODS/03