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

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.

Materials and methods

This retrospective study included 400 participants from 3 hospitals b

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC11884038 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature