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A Multiclass Radiomics Method-Based WHO Severity Scale for Improving COVID-19 Patient Assessment and Disease

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Summary

A novel AI model, AssessNet-19, accurately assesses COVID-19 severity using multiclass lung lesion analysis. This artificial intelligence approach outperforms radiologists and single-class models in chest CT scans.

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Area of Science:

  • Radiology and Artificial Intelligence
  • Medical Imaging Analysis
  • Computational Pathology

Background:

  • Chest computed tomography (CT) is crucial for assessing COVID-19 severity.
  • Accurate segmentation and classification of lung lesions are vital for disease staging.
  • Existing models often use single-class segmentation, potentially limiting accuracy.

Purpose of the Study:

  • To develop and evaluate AssessNet-19, an AI model for multiclass lung lesion segmentation and COVID-19 severity classification.
  • To compare the performance of AssessNet-19 against single-class models and expert radiologists.
  • To validate the model's ability to predict disease severity based on the World Health Organization Clinical Progression Scale.

Main Methods:

  • A 2D-U-Net network was trained for multiclass segmentation of four COVID-19-induced lung lesions.
  • Radiomic features were extracted, reduced using LASSO regression, and fed into an XGBoost classifier.
  • The model was validated on two independent multicenter cohorts for both manual and automated evaluations.

Main Results:

  • AssessNet-19 achieved a superior F1-score of 0.76 for severity classification compared to radiologists (0.63) and a single-class model (0.64).
  • Automated segmentation achieved Dice scores ranging from 0.30 to 0.70 for different lesion types.
  • High agreement (Cohen κ: 0.92–0.95) was observed between AssessNet-19 and radiologists in quantifying disease extent.

Conclusions:

  • The developed artificial intelligence multiclass radiomics model (AssessNet-19) accurately assesses COVID-19 disease severity.
  • AssessNet-19 demonstrates superior performance over single-class models and expert radiologists in chest CT analysis.
  • This AI tool offers a promising approach for objective and precise COVID-19 severity evaluation.