Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.

ABSTRACT:

Background

The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity.

Methods

A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain β coefficients, construct predictive models and nomogram incorporating MRI morphological features in the training cohort, and validated in the validation cohort. The discrimination, calibration, and decision curve analysis of the nomogram were performed. The diagnosis efficacy, area under the curve (AUC) an

SUBMITTER: Zheng T 

PROVIDER: S-EPMC10885392 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature