Radiomic Analysis for Pretreatment Prediction of Recurrence Post-Radiotherapy in Cervical Squamous Cell Carcinoma Cancer

Radiomic Analysis for Pretreatment Prediction of Recurrence Post-Radiotherapy in Cervical Squamous Cell Carcinoma Cancer

Background: The current study aims to predict the recurrence of cervical cancer patients treated with radiotherapy from radiomics features on pretreatment T1- and T2-weighted MR images. Methods: A total of 89 patients were split into model training (63 patients) and model testing (26 patients). The...

Full description

Bibliographic Details
Main Authors: Daisuke Kawahara, Ikuno Nishibuchi, Masashi Kawamura, Takahito Yoshida, Iemasa Koh, Katsuyuki Tomono, Masaki Sekine, Haruko Takahashi, Yutaka Kikuchi, Yoshiki Kudo, Yasushi Nagata
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Diagnostics
Subjects:
radiotherapy
machine learning
cervix cancer
Online Access:https://www.mdpi.com/2075-4418/12/10/2346

Internet

https://www.mdpi.com/2075-4418/12/10/2346

Similar Items