An ultrasound-based histogram analysis model for prediction of tumour stroma ratio in pleomorphic adenoma of the salivary gland.

ABSTRACT:

Objectives

Preoperative identification of different stromal subtypes of pleomorphic adenoma (PA) of the salivary gland is crucial for making treatment decisions. We aimed to develop and validate a model based on histogram analysis (HA) of ultrasound (US) images for predicting tumour stroma ratio (TSR) in salivary gland PA.

Methods

A total of 219 PA patients were divided into low-TSR (stroma-low) and high-TSR (stroma-high) groups and enrolled in a training cohort (n = 151) and a validation cohort (n = 68). The least absolute shrinkage and selection operator regression algorithm was used to screen the most optimal clinical, US, and HA features. The selected features were entered into multivariable logistic regression analyses for further selection of independent predictors. Di

SUBMITTER: Su HZ 

PROVIDER: S-EPMC11056798 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature