Machine-learning-based prediction of the effectiveness of the delivered dose by exhale-gated radiotherapy for locally advanced lung cancer: The additional value of geometric over dosimetric parameters alone

Machine-learning-based prediction of the effectiveness of the delivered dose by exhale-gated radiotherapy for locally advanced lung cancer: The additional value of geometric over dosimetric parameters alone

PurposeThis study aimed to assess interfraction stability of the delivered dose distribution by exhale-gated volumetric modulated arc therapy (VMAT) or intensity-modulated arc therapy (IMAT) for lung cancer and to determine dominant prognostic dosimetric and geometric factors.MethodsClinical target...

Full description

Bibliographic Details
Main Authors: Nika Guberina, Christoph Pöttgen, Alina Santiago, Sabine Levegrün, Sima Qamhiyeh, Toke Printz Ringbaek, Maja Guberina, Wolfgang Lübcke, Frank Indenkämpen, Martin Stuschke
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-01-01
Series:Frontiers in Oncology
Subjects:
Hausdorff-distance
cold spot
respiratory gating
planning target volume margin
lung cancer
clinical target volume
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.870432/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.870432/full

Similar Items