Exploring the Incremental Value of Aorta Enhancement Normalization Method in Evaluating Renal Cell Carcinoma Histological Subtypes: A Multi-center Large Cohort Study.

Journal: Academic radiology
Published Date: Mar 28, 2025

Abstract

RATIONALE AND OBJECTIVES: The classification of renal cell carcinoma (RCC) histological subtypes plays a crucial role in clinical diagnosis. However, traditional image normalization methods often struggle with discrepancies arising from differences in imaging parameters, scanning devices, and multi-center data, which can impact model robustness and generalizability.

Authors

  • Zexin Huang
    Department of Radiology, Shenzhen Luohu District Traditional Chinese Medicine Hospital (Luohu Hospital Group), Shenzhen, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Hangru Mei
    Department of Urology, Southern University of Science and Technology Hospital, Shenzhen 518000, China.
  • Jiewen Liu
    Department of Pathology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen 518000, China.
  • Haoyang Zeng
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
  • Weihao Liu
    Computer School, Hubei University of Arts and Science, Longzhong Road, Xiangyang, 441053, Hubei, China.
  • Haoyuan Yuan
    Shantou University Medical College, Shantou University, Shantou, China.
  • Kai Wu
  • Hanlin Liu
    Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL, United States of America.

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