Chest computed tomography radiomics to predict the outcome for patients with COVID-19 at an early stage
Diagn Interv Radiol
; 29(1): 91-102, 2023 01 31.
Article
in English
| MEDLINE | ID: covidwho-2287060
ABSTRACT
PURPOSE:
Early monitoring and intervention for patients with novel coronavirus disease-2019 (COVID-19) will benefit both patients and the medical system. Chest computed tomography (CT) radiomics provide more information regarding the prognosis of COVID-19.METHODS:
A total of 833 quantitative features of 157 COVID-19 patients in the hospital were extracted. By filtering unstable features using the least absolute shrinkage and selection operator algorithm, a radiomic signature was built to predict the prognosis of COVID-19 pneumonia. The main outcomes were the area under the curve (AUC) of the prediction models for death, clinical stage, and complications. Internal validation was performed using the bootstrapping validation technique.RESULTS:
The AUC of each model demonstrated good predictive accuracy [death, 0.846; stage, 0.918; complication, 0.919; acute respiratory distress syndrome (ARDS), 0.852]. After finding the optimal cut-off for each outcome, the respective accuracy, sensitivity, and specificity were 0.854, 0.700, and 0.864 for the prediction of the death of COVID-19 patients; 0.814, 0.949, and 0.732 for the prediction of a higher stage of COVID-19; 0.846, 0.920, and 0.832 for the prediction of complications of COVID-19 patients; and 0.814, 0.818, and 0.814 for ARDS of COVID-19 patients. The AUCs after bootstrapping were 0.846 [95% confidence interval (CI) 0.844-0.848] for the death prediction model, 0.919 (95% CI 0.917-0.922) for the stage prediction model, 0.919 (95% CI 0.916-0.921) for the complication prediction model, and 0.853 (95% CI 0.852-0.0.855) for the ARDS prediction model in the internal validation. Based on the decision curve analysis, the radiomics nomogram was clinically significant and useful.CONCLUSION:
The radiomic signature from the chest CT was significantly associated with the prognosis of COVID-19. A radiomic signature model achieved maximum accuracy in the prognosis prediction. Although our results provide vital insights into the prognosis of COVID-19, they need to be verified by large samples in multiple centers.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Respiratory Distress Syndrome
/
COVID-19
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Diagn Interv Radiol
Journal subject:
Diagnostic Imaging
/
Radiology
Year:
2023
Document Type:
Article
Affiliation country:
Dir.2022.21576
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