Predicting radiation esophagitis after lung cancer radiotherapy using dose-volume, radiomic and dosiomic features: an external validation study
This study evaluates the effectiveness of combining clinical data, dose-volume histograms, and radiomic features to predict radiation esophagitis in lung cancer patients. The research suggests that integrating advanced imaging features may improve predictive accuracy compared to traditional methods alone.
Why it matters
Improving the prediction of side effects in radiotherapy can help clinicians adjust treatment plans to enhance patient safety and quality of life.
Scientific Reports ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in