Multicenter study on CT-based Radiomics for predicting severity and delayed recovery in <i>Mycoplasma pneumoniae</i> pneumonia.

ABSTRACT:

Objective

To develop and validate model based on clinical, imaging, and Radiomics features for predicting disease severity and delayed recovery in Mycoplasma pneumoniae pneumonia (MPP).

Methods

This multicenter retrospective study enrolled 238 patients (training cohort), 60 (testing cohort), and 278 (validation cohort). Patients were classified into non-severe MPP (NSMPP) and severe MPP (SMPP) groups based on guideline, and further stratified post-treatment into recovery or delayed recovery groups. Radiomics features were extracted from chest CT using PyRadiomics, with Least Absolute Shrinkage and Selection Operator (LASSO) regression for feature selection. Three random forest-based predictive models were developed, including Clinical-Image, Radiomics, and Integrated.

SUBMITTER: Li Q 

PROVIDER: S-EPMC12626870 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature