CT Radiomics and Machine-Learning Models for Predicting Tumor-Stroma Ratio in Patients With Pancreatic Ductal Adenocarcinoma

PurposeTo develop and validate a machine learning classifier based on multidetector computed tomography (MDCT), for the preoperative prediction of tumor–stroma ratio (TSR) expression in patients with pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsIn this retrospective study, 227 patien...

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Autores principales:	Yinghao Meng, Hao Zhang, Qi Li, Fang Liu, Xu Fang, Jing Li, Jieyu Yu, Xiaochen Feng, Mengmeng Zhu, Na Li, Guodong Jing, Li Wang, Chao Ma, Jianping Lu, Yun Bian, Chengwei Shao
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	pancreatic neoplasm carcinoma prognosis tumor-stroma ratio multidetector computed tomography radiomics Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/97a9274c27c04a598c8643a72ca74334
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CT Radiomics and Machine-Learning Models for Predicting Tumor-Stroma Ratio in Patients With Pancreatic Ductal Adenocarcinoma

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