A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions.

Journal: European journal of radiology
Published Date: Apr 1, 2022

Abstract

BACKGROUND: For patients with meningioma, surgical procedures are different because of the status of sinus invasion. However, there is still no suitable technique to identify the status of sinus invasion in patients with meningiomas. We aimed to build a deep learning radiomics model to identify sinus invasion before surgery.

Authors

  • Kai Sun
    Department of Materials Science and Engineering, Jinan University.
  • Jing Zhang
    MOEMIL Laboratory, School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China.
  • Zhenyu Liu
    School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Qi Qiu
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China.
  • Han Gao
    Zhejiang Construction Investment Environment Engineering Co, Ltd., Hangzhou, 310013, PR China.
  • Panpan Liu
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Kuntao Chen
    Department of Radiology, The Fifth Affiliated Hospital of Zunyi Medical University, Zhuhai, China.
  • Wei Wei
    Dept. Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
  • Liang Wang
    Information Department, Dazhou Central Hospital, Dazhou 635000, China.
  • Junting Zhang
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Nansihuan Xilu 119, Fengtai District, Beijing, China. Electronic address: zhangjunting2003@aliyun.com.
  • Junlin Zhou
    Department of Radiology, Lanzhou University Second Hospital, 730030 Lanzhou, Gansu, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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