Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Mar 6, 2025

Abstract

BACKGROUND: Apart from rare cases such as lymphomas, germ cell tumors, neuroendocrine neoplasms, and thymic hyperplasia, thymic mass lesions (TMLs) are typically categorized into cysts, and thymomas. However, the classification results cannot be determined in advance and can only be confirmed through postoperative pathology. Therefore, the objective of this study is to rely on clinical parameters and radiomic features extracted from chest computed tomography (CT) scans to facilitate the preoperative classification of TMLs. The model development specifically focused on thymic cysts and thymomas, as these are the most commonly encountered anterior mediastinal tumors in clinical practice.

Authors

  • Yan Zhu
    Department of Chemistry, Xixi Campus, Zhejiang University, Hangzhou, 310028, China. Electronic address: zhuyan@zju.edu.cn.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Aichao Ruan
    Thoracic Surgical Department, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, PR China.
  • Zhiyu Peng
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Zhenzhong Zhang
    Thoracic Surgical Department, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, PR China. zhang_zhenzhong@outlook.com.

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