A radiomics model enables prediction venous sinus invasion in meningioma.

ABSTRACT:

Objective

Preoperative prediction of meningioma venous sinus invasion would facilitate the selection of surgical approaches and predicting the prognosis. To predict venous sinus invasion in meningiomas, we used radiomic signatures to construct a model based on preoperative contrast-enhanced T1-weighted (T1C) and T2-weighted (T2) magnetic resonance imaging.

Methods

In total, 599 patients with pathologically confirmed meningioma were retrospectively enrolled. For each patient enrolled in this study, 1595 radiomic signatures were extracted from T1C and T2 image sequences. Pearson correlation analysis and recursive feature elimination were used to select the most relevant signatures extracted from different image sequences, and logistic regression algorithms were used to build a

SUBMITTER: Wang L 

PROVIDER: S-EPMC10424646 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature