A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

Journal: Academic radiology
PMID: 39107191

Abstract

RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical factor affecting patient outcomes, yet effective clinical tools for predicting HE are currently lacking. We aim to develop a fully automated framework based on deep learning for predicting HE using only clinical non-contrast CT (NCCT) scans.

Authors

  • Na Li
    School of Nursing, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
  • Shaodong Ding
    Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China (S.D., Z.L., T.L.).
  • Ziyang Liu
    Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ, USA.
  • Wanxing Ye
    China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (N.L., W.Y., J.J., Y.J., X.Z.).
  • Pan Liu
    Jiangsu Key Laboratory of Urban ITS, Southeast University, Si Pai Lou #2, Nanjing, 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Si Pai Lou #2, Nanjing, 210096, China. Electronic address: pan_liu@hotmail.com.
  • Jing Jing
  • Yong Jiang
    Department of Pathology West China Hospital Sichuan University Chengdu China.
  • Xingquan Zhao
    Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (N.L., J.J., X.Z.); China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (N.L., W.Y., J.J., Y.J., X.Z.).
  • Tao Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

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