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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Detalles Bibliográficos
Autores principales: Lin, Chia-Ying, Yen, Yi-Ting, Huang, Li-Ting, Chen, Tsai-Yun, Liu, Yi-Sheng, Tang, Shih-Yao, Huang, Wei-Li, Chen, Ying-Yuan, Lai, Chao-Han, Fang, Yu-Hua Dean, Chang, Chao-Chun, Tseng, Yau-Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026802/
https://www.ncbi.nlm.nih.gov/pubmed/35453937
http://dx.doi.org/10.3390/diagnostics12040889

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026802/
https://www.ncbi.nlm.nih.gov/pubmed/35453937
http://dx.doi.org/10.3390/diagnostics12040889

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