Technical implications of a novel deep learning system in the segmentation and evaluation of computed tomography angiography before transcatheter aortic valve replacement.

Journal: Therapeutic advances in cardiovascular disease
PMID: 40123453

Abstract

OBJECTIVE: The goal of this study was to compare the computed tomography angiography scans of the segmentation results from the Cvpilot, 3mensio, and Volume Viewer systems to explore the practicability of the Cvpilot system in the automatic segmentation and technical evaluation of the aortic root before transcatheter aortic valve replacement (TAVR).

Authors

  • Min Jin
    National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  • Yu Mao
    Department of Radiology, The Affiliated Hospital of Southwest Medical University, No. 23 Tai Ping Street, Luzhou, 646000, Sichuan, China.
  • Jian Yang
    Drug Discovery and Development Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada.
  • Jian Liu
    Department of Rheumatology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China.
  • Guozhong Chen
    Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China.
  • Timothée Noterdaeme
    Department of Cardiology, Hospital of Liege University, Liege, Belgium.
  • Rüdiger Lange
    Nanjing Saint Medical Technology Co., Ltd., Nanjing, China.
  • Chenming Ma
    Nanjing Saint Medical Technology Co., Ltd., Nanjing, China.
  • Yingqiang Guo
    Department of Cardiovascular Surgery, West China Hospital, Chengdu, China.
  • Haibo Zhang
    Department of Radiology, the Third People's Hospital of Zhongshan, Zhongshan, Guangdong 528451, China.

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