A narrative review on the application of artificial intelligence in renal ultrasound.

Journal: Frontiers in oncology
Published Date: Mar 1, 2024

Abstract

Kidney disease is a serious public health problem and various kidney diseases could progress to end-stage renal disease. The many complications of end-stage renal disease. have a significant impact on the physical and mental health of patients. Ultrasound can be the test of choice for evaluating the kidney and perirenal tissue as it is real-time, available and non-radioactive. To overcome substantial interobserver variability in renal ultrasound interpretation, artificial intelligence (AI) has the potential to be a new method to help radiologists make clinical decisions. This review introduces the applications of AI in renal ultrasound, including automatic segmentation of the kidney, measurement of the renal volume, prediction of the kidney function, diagnosis of the kidney diseases. The advantages and disadvantages of the applications will also be presented clinicians to conduct research. Additionally, the challenges and future perspectives of AI are discussed.

Authors

  • Tong Xu
    Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xian-Ya Zhang
    Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Na Yang
    Department of Ultrasound, Affiliated Hospital of Jilin Medical College, Jilin, China.
  • Fan Jiang
    Department of Medical Ultrasound, The Second Hospital of Anhui Medical University, Hefei, China.
  • Gong-Quan Chen
    Department of Medical Ultrasound, Minda Hospital of Hubei Minzu University, Enshi, China.
  • Xiao-Fang Pan
    Health Medical Department, Dalian Municipal Central Hospital, Dalian, China.
  • Yue-Xiang Peng
    Department of Ultrasound, Wuhan Third Hospital, Tongren Hospital of Wuhan University, Wuhan, China.
  • Xin-Wu Cui
    Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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