Artificial intelligence-augmented ultrasound diagnosis of follicular-patterned thyroid neoplasms: a multicenter retrospective study.

Journal: EClinicalMedicine
Published Date:

Abstract

BACKGROUND: Conventional diagnostic tools, including ultrasound, fine-needle aspiration cytology, and intraoperative frozen section pathology, may fail to reliably distinguish between benign and malignant FNs, leading to unnecessary or inadequate surgical interventions. We aimed to develop and validate a deep learning (DL) system for the preoperative diagnosis of follicular-patterned thyroid neoplasms (FNs) using routine ultrasound images, with the goal of improving diagnostic accuracy and reducing unnecessary procedures.

Authors

  • Hui Shen
    College of Mechatronics and Automation, National University of Defense Technology, Changsha, China.
  • Shufang Pei
    Department of Ultrasound, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.
  • Yue Huang
    Xiamen University, Xiamen, Fujian 361005, China.
  • Suqing Wu
    School of Management, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, People's Republic of China.
  • Chifa Zhang
    Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
  • Ting Liang
    Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.
  • Dan Yang
    Baotou Medical College Baotou Inner Mongolia 014060 China 610283014@qq.com dongjiani369@126.com wgdzd@126.com +86 13847201181 +86 13514899325 +86 13474977691.
  • Xiaoxiao Feng
    Department of Food Science & Technology, School of Agriculture & Biology, Shanghai Jiao Tong University, Shanghai, China.
  • Shuyi Liu
    The Experimental High School Attached to Beijing Normal University, No. 14 Erlong Road, Beijing 100051, PR China.
  • Yu Wang
    Clinical and Technical Support, Philips Healthcare, Shanghai, China.
  • Weihan Cao
    Department of Ultrasound, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Ying Cheng
    Changchun SCI-TECH University, Jilin Changchun 130600, China.
  • Hongyan Chen
    Department of Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
  • Qiujie Ni
    Department of Ultrasound, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Fei Wang
    Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States.
  • Jingjing You
    Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Zhe Jin
    Zhejiang University, College of Computer Science and Technology, Hangzhou, China.
  • WenLe He
    Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
  • Jie Sun
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, People's Republic of China.
  • Dexing Yang
    Department of Pathology, The People's Hospital of Wenshan Prefecture, Wenshan, Yunnan, China.
  • Lijuan Liu
    New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
  • Boling Cao
    Department of Ultrasound, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), Zhuhai, Guangdong, China.
  • Xiao Zhang
    Merck & Co., Inc., Rahway, NJ, USA.
  • Yingjia Li
    Department of Ultrasound, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou, Guangdong Province, P. R. China. lyjia@smu.edu.cn.
  • Shuixing Zhang
    Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, PR China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, Guangdong, PR China. Electronic address: shui7515@126.com.
  • Bin Zhang
    Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Keywords

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