Integrated radiomics, dose-volume histogram criteria and clinical features for early prediction of saliva amount reduction after radiotherapy in nasopharyngeal cancer patients

Integrated radiomics, dose-volume histogram criteria and clinical features for early prediction of saliva amount reduction after radiotherapy in nasopharyngeal cancer patients

Abstract Purpose Previously, the evaluation of xerostomia depended on subjective grading systems, rather than the accurate saliva amount reduction. Our aim was to quantify acute xerostomia with reduced saliva amount, and apply radiomics, dose-volume histogram (DVH) criteria and clinical features to...

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Bibliographic Details
Main Authors: Lang Zhou, Wanjia Zheng, Sijuan Huang, Xin Yang
Format: Article
Language:English
Published: Springer 2022-12-01
Series:Discover Oncology
Subjects:
Acute xerostomia
Saliva amount prediction
Machine learning
Feature importance
Online Access:https://doi.org/10.1007/s12672-022-00606-x

Internet

https://doi.org/10.1007/s12672-022-00606-x

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