ArticleThe British journal of radiology2021
A CT-based radiomics nomogram for predicting prognosis of coronavirus disease 2019 (COVID-19) radiomics nomogram predicting COVID-19.
Article in The British journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- Prediction of potential severe coronavirus disease 2019 patients based on CT radiomics: A retrospective study.Medical physics · 2022Trial
- CT-based radiomics models for predicting the prognosis of children with mycoplasma pneumonia.Frontiers in cellular and infection microbiology · 2026Article
- Semi-quantitative software evaluation of COVID-19 CT examinations-correlation with clinical parameters.Journal of thoracic disease · 2025Article
- From images to clinical insights: an educational review on radiomics in lung diseases.Breathe (Sheffield, England) · 2025Review
- Development of a radiomics-based model using computed tomography imaging to assess the incidence of extrapulmonary organ involvement inFrontiers in medicine · 2025Article
- Tracheal computed tomography radiomics model for prediction of the Omicron variant of severe acute respiratory syndrome coronavirus 2.Radiologie (Heidelberg, Germany) · 2024Article
- Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.Computers in biology and medicine · 2024Review
- Development of a radiomics nomogram to predict the treatment resistance of Chinese MPO-AAV patients with lung involvement: a two-center study.Frontiers in immunology · 2023Article
- Toward the determination of sensitive and reliable whole-lung computed tomography features for robust standard radiomics and delta-radiomics analysis in a nonhuman primate model of coronavirus disease 2019.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- CT-based radiomic nomogram for predicting the severity of patients with COVID-19.European journal of medical research · 2022Article
- The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review.Diagnostics (Basel, Switzerland) · 2021Review
- Study on the prognosis predictive model of COVID-19 patients based on CT radiomics.Scientific reports · 2021Article
- A Meta-Analysis of Computerized Tomography-Based Radiomics for the Diagnosis of COVID-19 and Viral Pneumonia.Diagnostics (Basel, Switzerland) · 2021Article
- A Combined Model to Improve the Prediction of Local Control for Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy Based on Radiomic Signature Plus Clinical and Dosimetric Parameters.Frontiers in oncology · 2021Article
- CT Quantification of COVID-19 Pneumonia at Admission Can Predict Progression to Critical Illness: A Retrospective Multicenter Cohort Study.Frontiers in medicine · 2021Article
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7 authors.
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Abstract
objectivesTo identify the value of radiomics method derived from CT images to predict prognosis in patients with COVID-19.
methodsA total of 40 patients with COVID-19 were enrolled in the study. Baseline clinical data, CT images, and laboratory testing results were collected from all patients. We defined that ROIs in the absorption group decreased in the density and scope in GGO, and ROIs in the progress group progressed to consolidation. A total of 180 ROIs from absorption group (
resultsA total of 15 radiomics features with respective coefficients were calculated. The AUC values of radiomics models (kNN, SVM, and LR) were 0.88, 0.88, and 0.84, respectively, showing a good performance. The C-index of the clinical factors model was 0.82 [95% CI (0.75-0.88)] in the training set and 0.77 [95% CI (0.59-0.90)] in the validation set. The radiomics nomogram showed optimal prediction performance. In the training set, the C-index was 0.91 [95% CI (0.85-0.95)], and in the validation set, the C-index was 0.85 [95% CI (0.69-0.95)]. For the training set, the C-index of the radiomics nomogram was significantly higher than the clinical factors model (
conclusionsThe radiomics nomogram based on CT images showed favorable prediction performance in the prognosis of COVID-19. The radiomics nomogram could be used as a potential biomarker for more accurate categorization of patients into different stages for clinical decision-making process. ADVANCES IN KNOWLEDGE: Radiomics features based on chest CT images help clinicians to categorize the patients of COVID-19 into different stages. Radiomics nomogram based on CT images has favorable predictive performance in the prognosis of COVID-19. Radiomics act as a potential modality to supplement conventional medical examinations.
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