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

José Raniery Ferreira, Diego Armando Cardona Cárdenas, Ramon A. Moreno, Marina de Fátima de Sá Rebelo, José Eduardo Krieger, Marco A. Gutiérrez

2021Journal of Digital Imaging27 citationsDOIOpen Access PDF

Abstract

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, [Formula: see text]). 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 ([Formula: see text]). 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.

Topics & Concepts

MedicineRadiographyHistogramCoronavirus disease 2019 (COVID-19)Mann–Whitney U testPneumoniaReceiver operating characteristicSurvival analysisRadiologyRetrospective cohort studyLog-rank testNuclear medicineStatisticsArtificial intelligenceInternal medicineMathematicsDiseaseComputer scienceImage (mathematics)Infectious disease (medical specialty)Radiomics and Machine Learning in Medical ImagingCOVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education
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