A prior knowledge-guided convolutional neural network model for predicting fetal brain age from MRI during second and third trimesters.

ABSTRACT:

Background

This study aimed to evaluate the efficacy of a convolutional neural network (CNN) model in estimating fetal brain age from MRI scans during second and third trimesters.

Methods

A total of 407 T2-weighted MRI including 2310 stacks in the axial, sagittal, and coronal planes were used. The average fetal brain age was 30.7 weeks (ranging from 22 to 39 weeks). The reference standard gestational age was based on ultrasonography measurements during the first trimester. A prior knowledge-guided CNN model was utilized for brain age prediction. The relationship between the predicted brain age and the reference standard was assessed using Lin's concordance correlation coefficient (ρc) and determination coefficient (R²) score. The results of fetal brain age predict

SUBMITTER: Zhu F 

PROVIDER: S-EPMC12699803 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature