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Volume 11
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10.3390/microorganisms11071740
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Article

Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients

by
Catharina Gerhards
1,*,
Verena Haselmann
1,
Samuel F. Schaible
2,
Volker Ast
1,
Maximilian Kittel
1,
Manfred Thiel
3,
Alexander Hertel
2,
Stefan O. Schoenberg
2,
Michael Neumaier
1,† and
Matthias F. Froelich
2,†
1
Institute for Clinical Chemistry, Medical Faculty Mannheim of the University of Heidelberg, Theodor Kutzer Ufer 1-3, 68167 Mannheim, Germany
2
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim of the University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
3
Department of Anaesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim of the University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Microorganisms 2023, 11(7), 1740; https://doi.org/10.3390/microorganisms11071740
Submission received: 17 June 2023 / Revised: 23 June 2023 / Accepted: 29 June 2023 / Published: 3 July 2023
(This article belongs to the Special Issue Coronaviruses: Past, Present, and Future)
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Abstract

Background: Severe courses and high hospitalization rates were ubiquitous during the first pandemic SARS-CoV-2 waves. Thus, we aimed to examine whether integrative diagnostics may aid in identifying vulnerable patients using crucial data and materials obtained from COVID-19 patients hospitalized between 2020 and 2021 (n = 52). Accordingly, we investigated the potential of laboratory biomarkers, specifically the dynamic cell decay marker cell-free DNA and radiomics features extracted from chest CT. Methods: Separate forward and backward feature selection was conducted for linear regression with the Intensive-Care-Unit (ICU) period as the initial target. Three-fold cross-validation was performed, and collinear parameters were reduced. The model was adapted to a logistic regression approach and verified in a validation naïve subset to avoid overfitting. Results: The adapted integrated model classifying patients into “ICU/no ICU demand” comprises six radiomics and seven laboratory biomarkers. The models’ accuracy was 0.54 for radiomics, 0.47 for cfDNA, 0.74 for routine laboratory, and 0.87 for the combined model with an AUC of 0.91. Conclusion: The combined model performed superior to the individual models. Thus, integrating radiomics and laboratory data shows synergistic potential to aid clinic decision-making in COVID-19 patients. Under the need for evaluation in larger cohorts, including patients with other SARS-CoV-2 variants, the identified parameters might contribute to the triage of COVID-19 patients.
Keywords: COVID-19; SARS-CoV-2; coronavirus infection; integrative medicine; intensive care units; thoracic radiography; cell-free nucleic acid; algorithms COVID-19; SARS-CoV-2; coronavirus infection; integrative medicine; intensive care units; thoracic radiography; cell-free nucleic acid; algorithms

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MDPI and ACS Style

Gerhards, C.; Haselmann, V.; Schaible, S.F.; Ast, V.; Kittel, M.; Thiel, M.; Hertel, A.; Schoenberg, S.O.; Neumaier, M.; Froelich, M.F. Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients. Microorganisms 2023, 11, 1740. https://doi.org/10.3390/microorganisms11071740

AMA Style

Gerhards C, Haselmann V, Schaible SF, Ast V, Kittel M, Thiel M, Hertel A, Schoenberg SO, Neumaier M, Froelich MF. Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients. Microorganisms. 2023; 11(7):1740. https://doi.org/10.3390/microorganisms11071740

Chicago/Turabian Style

Gerhards, Catharina, Verena Haselmann, Samuel F. Schaible, Volker Ast, Maximilian Kittel, Manfred Thiel, Alexander Hertel, Stefan O. Schoenberg, Michael Neumaier, and Matthias F. Froelich. 2023. "Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients" Microorganisms 11, no. 7: 1740. https://doi.org/10.3390/microorganisms11071740

APA Style

Gerhards, C., Haselmann, V., Schaible, S. F., Ast, V., Kittel, M., Thiel, M., Hertel, A., Schoenberg, S. O., Neumaier, M., & Froelich, M. F. (2023). Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients. Microorganisms, 11(7), 1740. https://doi.org/10.3390/microorganisms11071740

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