Differentiating Bacterial and Non-Bacterial Pneumonia on Chest CT Using Multi-Plane Features and Clinical Biomarkers.

Journal: Academic radiology
Published Date: Jun 9, 2025

Abstract

RATIONALE AND OBJECTIVES: Timely and accurate classification of bacterial pneumonia (BP) is essential for guiding antibiotic therapy. However, distinguishing BP from non-bacterial pneumonia (NBP) using computed tomography (CT) is challenging due to overlapping imaging features and limited biomarker specificity, often leading to delayed or empirical treatment. This study aimed to develop and evaluate MPMT-Pneumo, a multi-plane, multi-modal deep learning model, to improve BP versus NBP differentiation.

Authors

  • Liming Song
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR (L.S., Y.W., M.Z., Z.L., G.R., J.C.).
  • Yuefu Zhan
    Department of Radiology, Hainan Women and Children's Medical Center, Haikou, China.
  • Lifeng Li
    Department of Pharmacy, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
  • Xiaohua Li
    Zuoshouyisheng Inc, Beijing, China.
  • Yuyao Wu
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR (L.S., Y.W., M.Z., Z.L., G.R., J.C.).
  • Mayang Zhao
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, 999077, Hong Kong SAR.
  • Zhichun Li
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR (L.S., Y.W., M.Z., Z.L., G.R., J.C.).
  • Ge Ren
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong.
  • Jing Cai
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.

Keywords

External Resources

Popular Topics
Recent Journals