Development and validation of a radiomics nomogram for diagnosis of malignant pleural effusion.

ABSTRACT:

Objective

We aimed to develop a radiomics nomogram based on computed tomography (CT) scan features and high-throughput radiomics features for diagnosis of malignant pleural effusion (MPE).

Methods

In this study, 507 eligible patients with PE (207 malignant and 300 benign) were collected retrospectively. Patients were divided into training (n = 355) and validation cohorts (n = 152). Radiomics features were extracted from initial unenhanced CT images. CT scan features of PE were also collected. We used the variance threshold algorithm and least absolute shrinkage and selection operator (LASSO) to select optimal features to build a radiomics model for predicting the nature of PE. Univariate and multivariable logistic regression analyzes were used to identify significant indepen

SUBMITTER: Wei M 

PROVIDER: S-EPMC10673775 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature