MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures

MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures

ObjectiveVertebral compression fractures (VCFs) represent a prevalent clinical problem, yet distinguishing acute benign variants from malignant pathological fractures constitutes a persistent diagnostic dilemma. To develop and validate a MRI-based nomogram combining clinical and deep learning radiom...

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Bibliographic Details
Main Authors: Wenhua Liang, Hong Yu, Lisha Duan, Xiaona Li, Ming Wang, Bing Wang, Jianling Cui
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Oncology
Subjects:
radiomics
2.5D deep learning
feature fusion
vertebral compression fractures
nomogram
magnetic resonance imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1603672/full
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https://www.frontiersin.org/articles/10.3389/fonc.2025.1603672/full

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