SU‐E‐T‐633: Predictive Factors Influencing Low‐Dose Conformality in Lung SBRT

L. Appenzoller, C. Robinson, K. Moore

Research output: Contribution to journalArticlepeer-review


Purpose: The purpose of this study is to evaluate the impact of PTV volume, lung density, PTV shape, and proximity of an organ at risk (OAR) on lung SBRT low‐dose conformality. Methods: A phantom study was performed in the Phillips Pinnacle treatment planning system by varying the above parameters and calculating a low‐dose conformality metric, V50/V100 (ratio of the volume of the 50% isodose to the prescription isodose). To ensure consistency between data, the high‐dose conformality index (ratio of the volume of the prescription isodose to the PTV volume) was held fixed at 1.00 +\− 0.05. Seven equally‐weighted coplanar beams were delivered to a cylindrical phantom with a centrally located PTV (unit density ITV with 5mm margin). The spherical PTV volumes varied from 13–163 cc and lung density varied from 0.10–0.30 g/cm3. To assess the influence of a non‐spherical PTV shape on V50/V100, the study was repeated with elliptically‐shaped PTVs (aspect ratios ranging from 1:2 to 2:1 in the superior/inferior direction) while holding the PTV volume constant at 50 cc. Finally, the effect of a non‐spherical dose distribution on V50/V100 was evaluated by applying unequal beam weights as would be used to protect adjacent OARs. Results: V50/V100 shows strong negative correlation with mean lung density and PTV volume. Non‐ spherical PTVs and dose distributions show weaker correlation to V50/V100 except at extreme aspect ratios and low lung densities. A quantitative predictive model for low‐dose conformality was developed based on a combination power law model for PTV volume and linear model for lung density. Conclusion:. This work confirms that, in addition to known effects of PTV volume, lung density also plays a significant role in determining low‐dose conformality for lung SBRT. Future investigations on aggregate clinical data will likely observe a similar predictive model.

Original languageEnglish
Number of pages1
JournalMedical physics
Issue number6
StatePublished - Jun 2011


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