Radiomics based on diffusion tensor imaging and 3D T1-weighted MRI for essential tremor diagnosis.

ABSTRACT:

Background

Due to the absence of biomarkers, the misdiagnosis of essential tremor (ET) with other tremor diseases and enhanced physiologic tremor is very common in practice. Combined radiomics based on diffusion tensor imaging (DTI) and three-dimensional T1-weighted imaging (3D-T1) with machine learning (ML) give a most promising way to identify essential tremor (ET) at the individual level and further reveal the potential imaging biomarkers.

Methods

Radiomics features were extracted from 3D-T1 and DTI in 103 ET patients and 103 age-and sex-matched healthy controls (HCs). After data dimensionality reduction and feature selection, five classifiers, including the support vector machine (SVM), random forest (RF), logistic regression (LR), extreme gradient boosting (XGBoost) and

SUBMITTER: Xu B 

PROVIDER: S-EPMC11387670 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature