Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes
Carregando...
Citações na Scopus
15
Tipo de produção
article
Data de publicação
2021
Título da Revista
ISSN da Revista
Título do Volume
Editora
SPRINGER
Citação
JOURNAL OF DIGITAL IMAGING, v.34, n.2, Special Issue, p.297-307, 2021
Resumo
COVID-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.
Palavras-chave
COVID-19, Radiomics, Coronavirus, Chest radiography, Medical image analysis
Referências
- Aerts HJWL, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms5006
- Ai T, 2020, RADIOLOGY, V296, pE32, DOI 10.1148/radiol.2020200642
- Azevedo-Marques, 2020, RADIOL BRAS
- Bai HX, 2020, RADIOLOGY, V296, pE46, DOI 10.1148/radiol.2020200823
- Bustos A, 2019, ARXIV PREPRINT ARXIV
- Chandra, P 3 INT C COMP VIS I, P21
- Chung MS, 2020, EUR RADIOL, V30, P2182, DOI [10.1007/s00330-019-06574-1, 10.1148/radiol.2020200230]
- Cohen J. P., 2020, COVID 19 IMAGE DATA
- Degnan AJ, 2019, ACAD RADIOL, V26, P833, DOI 10.1016/j.acra.2018.11.006
- Demner-Fushman D, 2016, J AM MED INFORM ASSN, V23, P304, DOI 10.1093/jamia/ocv080
- Fang YC, 2020, RADIOLOGY, V296, pE115, DOI 10.1148/radiol.2020200432
- Ferreira JR, 2020, INT J COMPUT ASS RAD, V15, P163, DOI 10.1007/s11548-019-02093-y
- Gillies RJ, 2016, RADIOLOGY, V278, P563, DOI 10.1148/radiol.2015151169
- Guan CS, 2020, ACAD RADIOL, V27, P609, DOI 10.1016/j.acra.2020.03.002
- Huang CL, 2020, LANCET, V395, P497, DOI 10.1016/S0140-6736(20)30183-5
- Italian Society of Medical and Interventional Radiology, 2020, COVID 19 DAT
- Kermany DS, 2018, CELL, V172, P1122, DOI 10.1016/j.cell.2018.02.010
- Kolahdouzan, RADIOLOGY CARDIOTHOR, V2
- Kolossvary M, 2018, J THORAC IMAG, V33, P26, DOI 10.1097/RTI.0000000000000268
- Li L, RADIOLOGY
- Li MZ, 2020, ACAD RADIOL, V27, P603, DOI 10.1016/j.acra.2020.03.003
- Liang GB, 2020, COMPUT METH PROG BIO, V187, DOI 10.1016/j.cmpb.2019.06.023
- Liu KC, 2020, EUR J RADIOL, V126, DOI 10.1016/j.ejrad.2020.108941
- Ng Ming-Yen, 2020, Radiol Cardiothorac Imaging, V2, pe200034, DOI 10.1148/ryct.2020200034
- Pazhitnykh I., 2017, LUNG SEGMENTATION 2D
- Randomised Evaluation of COVid-19 thERapY (RECOVERY) Trial, 2020, LOW COST DEX RED DEA
- Ronneberger O., 2015, P INT C MEDICAL IMAG, P234
- Santos Marcel Koenigkam, 2019, Radiol Bras, V52, P387, DOI 10.1590/0100-3984.2019.0049
- Sousa RT, 2013, PROCEDIA COMPUT SCI, V18, P2579, DOI 10.1016/j.procs.2013.05.444
- van Griethuysen JJM, 2017, CANCER RES, V77, pE104, DOI 10.1158/0008-5472.CAN-17-0339
- Yuan ML, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0230548
- Zwanenburg A, 2020, RADIOLOGY, V295, P328, DOI 10.1148/radiol.2020191145
Coleções
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
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