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Factors Predicting a Need for Treatment Replanning with Proton Radiotherapy for Lung Cancer

C Teng

C Teng*, G Janssens , C Ainsley , B Teo , G Valdes , B Burgdorf , A Berman , W Levin , Y Xiao , L Lin , P Gabriel , C Simone II , T Solberg , University of Pennsylvania, Philadelphia, PA


TU-H-CAMPUS-JeP3-4 (Tuesday, August 2, 2016) 5:30 PM - 6:00 PM Room: ePoster Theater

Purpose: Proton dose distribution is sensitive to tumor regression and tissue and normal anatomy changes. Replanning is sometimes necessary during treatment to ensure continue tumor coverage or avoid overtreatment of organs at risk (OARs). We investigated action thresholds for replanning and identified both dosimetric and non-dosimetric metrics that would predict a need for replan.

Methods: All consecutive lung cancer patients (n = 188) who received definitive proton radiotherapy and had more than two evaluation CT scans at the Roberts Proton Therapy Center (Philadelphia, USA) from 2011 to 2015 were included in this study. The cohort included a variety of tumor sizes, locations, histology, beam angles, as well as radiation-induced tumor and lung change. Dosimetric changes during therapy were characterized by changes in the dose volume distribution of PTV, ITV, and OARs (heart, cord, esophagus, brachial plexus and lungs). Tumor and lung change were characterized by changes in sizes, and in the distribution of Hounsfield numbers and water equivalent thickness (WET) along the beam path. We applied machine learning tools to identify both dosimetric and non-dosimetric metrics that predicted a replan.

Results: Preliminary data showed that clinical indicators (n = 54) were highly correlated; thus, a simple indicator may be derived to guide the action threshold for replanning. Additionally, tumor regression alone could not predict dosimetric changes in OARs; it required further information about beam angles and tumor locations.

Conclusion: Both dosimetric and non-dosimetric factors are predictive of the need for replanning during proton treatment.

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