A deep learning-informed interpretation of why and when dose metrics outside the PTV can affect the risk of distant metastasis in SBRT NSCLC patients.

Journal: Radiation oncology (London, England)

PMID: 39334387

Abstract

PURPOSE: Recent papers suggested a correlation between the risk of distant metastasis (DM) and dose outside the PTV, though conclusions in different publications conflicted. This study resolves these conflicts and provides a compelling explanation of prognostic factors.

Authors

D Dudas

Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czechia. dudasden@fjfi.cvut.cz.
T J Dilling

Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
I El Naqa

Department of Machine Learning, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

Keywords

Aged Carcinoma, Non-Small-Cell Lung Deep Learning Female Humans Lung Neoplasms Male Middle Aged Neoplasm Metastasis Prognosis Radiosurgery Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated

External Resources

View on PubMed Access via DOI PubMed (39334387)

A deep learning-informed interpretation of why and when dose metrics outside the PTV can affect the risk of distant metastasis in SBRT NSCLC patients.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals