Prediction of central lymph node metastasis in patients with papillary thyroid microcarcinoma by gradient-boosting decision tree model based on ultrasound radiomics and clinical features.

ABSTRACT:

Background

In recent years, the study of radiomics in thyroid diseases has developed rapidly. This study aimed to establish a preoperative radiomics prediction model for central compartment lymph node metastases (CLNMs) in papillary thyroid microcarcinoma (PTMC) patients using gradient-boosting decision tree (GBDT) model and evaluate the performance of the model.

Methods

A total of 274 patients with PTMC admitted for thyroid surgery at China-Japan Union Hospital of Jilin University from January 2020 to July 2022 were retrospectively analyzed. Patients were randomized into training and validation cohorts according to a ratio of 8:2. Radiomics features were extracted from the ultrasound (US) images of PTMC lesions. The open-source software Pyradiomics was used to extract radio

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC10788563 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature