Austin M Faught1, Lindsey Olsen2, Leah Schubert3, Chad Rusthoven3, Edward Castillo4, Richard Castillo5, Jingjing Zhang4, Thomas Guerrero4, Moyed Miften3, Yevgeniy Vinogradskiy3. 1. University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States; St. Jude Children's Research Hospital, Department of Radiation Oncology, Memphis, United States. Electronic address: austin.faught@stjude.org. 2. Memorial Hospital, Department of Radiation Oncology, Colorado Springs, United States. 3. University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States. 4. Beaumont Health System, Department of Radiation Oncology, Royal Oak, United States. 5. Emory University, Department of Radiation Oncology, Atlanta, United States.
Abstract
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring consistent plan quality across multiple planners. Knowledge-based planning (KBP) is positioned to address both concerns. MATERIAL AND METHODS: A KBP model was created from 30 previously planned functional-guided lung patients. Standard organs at risk (OAR) in lung radiotherapy and a ventilation contour delineating areas of high ventilation were included. Model validation compared dose-metrics to standard OARs and functional dose-metrics from 20 independent cases that were planned with and without KBP. RESULTS: A significant improvement was observed for KBP optimized plans in V20Gy and mean dose to functional lung (p = 0.005 and 0.001, respectively), V20Gy and mean dose to total lung minus GTV (p = 0.002 and 0.01, respectively), and mean doses to esophagus (p = 0.005). CONCLUSION: The current work developed a KBP model for functional-guided radiotherapy. Modest, but statistically significant, improvements were observed in functional lung and total lung doses.
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring consistent plan quality across multiple planners. Knowledge-based planning (KBP) is positioned to address both concerns. MATERIAL AND METHODS: A KBP model was created from 30 previously planned functional-guided lung patients. Standard organs at risk (OAR) in lung radiotherapy and a ventilation contour delineating areas of high ventilation were included. Model validation compared dose-metrics to standard OARs and functional dose-metrics from 20 independent cases that were planned with and without KBP. RESULTS: A significant improvement was observed for KBP optimized plans in V20Gy and mean dose to functional lung (p = 0.005 and 0.001, respectively), V20Gy and mean dose to total lung minus GTV (p = 0.002 and 0.01, respectively), and mean doses to esophagus (p = 0.005). CONCLUSION: The current work developed a KBP model for functional-guided radiotherapy. Modest, but statistically significant, improvements were observed in functional lung and total lung doses.
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