Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study

Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study

The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions in 36 patients were evaluated. Quantita...

Full description

Bibliographic Details
Main Authors: Noriyuki Fujima, Yukie Shimizu, Daisuke Yoshida, Satoshi Kano, Takatsugu Mizumachi, Akihiro Homma, Koichi Yasuda, Rikiya Onimaru, Osamu Sakai, Kohsuke Kudo, Hiroki Shirato
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Cancers
Subjects:
magnetic resonance imaging
machine learning
diffusion
perfusion
texture analysis
squamous cell carcinoma of the head and neck
Online Access:https://www.mdpi.com/2072-6694/11/6/800

Internet

https://www.mdpi.com/2072-6694/11/6/800

Similar Items