Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.

Journal: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PMID: 39222703

Abstract

BACKGROUND: Early prediction of hematoma expansion (HE) is important for the development of therapeutic strategies for spontaneous intracerebral hemorrhage (sICH). Radiomics can help to predict early hematoma expansion in intracerebral hemorrhage. However, complex image processing procedures, especially hematoma segmentation, are time-consuming and dependent on assessor experience. We provide a fully automated hematoma segmentation method, and construct a hybrid predictive model for risk stratification of hematoma expansion.

Authors

  • Menghui Wang
    School of Medicine, Jianghan University, Wuhan, Hubei 430056, China.
  • Yi Liang
    Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510405, People's Republic of China.
  • Hui Li
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Jun Chen
    Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.
  • Hua Fu
    Department of Radiology, The Fifth Affiliated Hospital of Nanchang University, Fuzhou, Jiangxi 344099, China.
  • Xiang Wang
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Yuanliang Xie
    Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.

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