An MRI-Based Clinical-Perfusion Model Predicts Pathological Subtypes of Prevascular Mediastinal Tumors

An MRI-Based Clinical-Perfusion Model Predicts Pathological Subtypes of Prevascular Mediastinal Tumors

This study aimed to build machine learning prediction models for predicting pathological subtypes of prevascular mediastinal tumors (PMTs). The candidate predictors were clinical variables and dynamic contrast–enhanced MRI (DCE-MRI)–derived perfusion parameters. The clinical data and preoperative DC...

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Bibliographic Details
Main Authors: Chia-Ying Lin, Yi-Ting Yen, Li-Ting Huang, Tsai-Yun Chen, Yi-Sheng Liu, Shih-Yao Tang, Wei-Li Huang, Ying-Yuan Chen, Chao-Han Lai, Yu-Hua Dean Fang, Chao-Chun Chang, Yau-Lin Tseng
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Diagnostics
Subjects:
differential diagnosis
dynamic contrast-enhanced MRI
perfusion parameters
prevascular mediastinal tumor
machine learning
Online Access:https://www.mdpi.com/2075-4418/12/4/889

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https://www.mdpi.com/2075-4418/12/4/889

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