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Updated: Mar 2, 2026
Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
Published on: June 7, 2015
TU-E-BRB-03: Biological Dose Optimization for SBRT of Lung Cancer: One Size Does Not Fit All
Purpose:
Given the differences in tumor size and location, encountered in lung SBRT, we hypothesize that 'one dose fractionation regimen does not fit all', i.e. that there is a role for patient-specific dose prescription based on optimization of biological models.
Methods:
Sixty one NSCLC patients (tumor volume 46.5+/-47.3 cc) treated with stereotactic body radiotherapy (48 Gy in 4fx) were retrospectively studied. Clinically treated plans were generated using Brainlab's Pencil Beam (PB-BL), and then recalculated with fixed MUs using Anisotropic Analytic Algorithm (AAA), Pencil Beam (PB-EC), Monte Carlo (MC) and Collapsed-Cone-Convolution (CCC). DVHs were exported to calculate TCP (Poisson) and NTCP (Lyman-Kutcher-Burman). TCP/NTCP model parameters were utilized from published data. For each dose distribution two dose response curves were generated by scaling the prescription dose and assuming a linear relationship between the prescription dose and entire 3D dose distribution. In addition, associations were assessed between changes in each algorithm's TCP relative to PB-BL, target diameter, and local density (density of the 70% isodose covering the PTV).
Results:
For PB-BL, mean TCP was 99.6%±0.9%, whereas for same MUs, mean TCP for PB-EC, AAA, CC and MC plans were 96.5±14.3%, 74.6±31.6%, 74.4±32.4% and 76.8±32.0%, respectively. With the same prescription dose for all plans, TCP values changed to 98.1±8.7%, 96.5±15.3%, 77.5±28.6%, 85.4±25.8% and 92.9±20.1% for PB-BL, PB-EC, AAA, and CCC, MC, respectively, indicating that AAA and CCC dose distributions are likely less homogeneous relative to MC. The TCP improvement was 12.3%, 8.9% and 4.4% for AAA, CCC and MC-based plans when the average NTCP before optimization was set as the upper limit for lung toxicity.
Conclusions:
This work supports patient-specific dose prescription strategies, based on biological optimization, for lung SBRT. However, further investigation is warranted. Acknowledgement: supported in part by a grant from Varian Medical Systems.
