How much can AI see in early pregnancy: A multi-center study of fetus head characterization in week 10-14 in ultrasound using deep learning.

Journal: Computer methods and programs in biomedicine
PMID: 36272307

Abstract

PURPOSE: To investigate if artificial intelligence can identify fetus intracranial structures in pregnancy week 11-14; to provide an automated method of standard and non-standard sagittal view classification in obstetric ultrasound examination METHOD AND MATERIALS: We proposed a newly designed scheme based on deep learning (DL) - Fetus Framework to identify nine fetus intracranial structures: thalami, midbrain, palate, 4th ventricle, cisterna magna, nuchal translucency (NT), nasal tip, nasal skin, and nasal bone. Fetus Framework was trained and tested on a dataset of 1528 2D sagittal-view ultrasound images from 1519 females collected from Shenzhen People's Hospital. Results from Fetus Framework were further used for standard/non-standard (S-NS) plane classification, a key step for NT measurement and Down Syndrome assessment. S-NS classification was also tested with 156 images from the Longhua branch of Shenzhen People's Hospital. Sensitivity, specificity, and area under the curve (AUC) were evaluated for comparison among Fetus Framework, three classic DL models, and human experts with 1-, 3- and 5-year ultrasound training. Furthermore, 4 physicians with more than 5 years of experience conducted a reader study of diagnosing fetal malformation on a dataset of 316 standard images confirmed by the Fetus framework and another dataset of 316 standard images selected by physicians. Accuracy, sensitivity, specificity, precision, and F1-Score of physicians' diagnosis on both sets are compared.

Authors

  • Qi Lin
    Shandong University, School of Mechanical, Electrical and Information Engineering, Weihai, 264209, China. Electronic address: 202100800115@mail.sdu.edu.cn.
  • Yuli Zhou
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Siyuan Shi
    Department of Ultrasound, The Second Clinical Medical Collegeļ¼ŒJinan University, Guangdong, China.
  • Yujuan Zhang
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Shaoli Yin
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Xuye Liu
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Qihui Peng
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Shaoting Huang
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Yitao Jiang
    Illuminate, LLC, Shenzhen, Guangdong, China; Microport Prophecy, Shanghai, China.
  • Chen Cui
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China; University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Ruilian She
    Department of Obstetric, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, China. Electronic address: zhe.ruilian@szhospital.com.
  • Jinfeng Xu
    Department of Ultrasound, The Second Clinical Medical Collegeļ¼ŒJinan University, Guangdong, China.
  • Fajin Dong
    Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.

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