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Correlation of dose computed using different algorithms with local control following stereotactic ablative radiotherapy (SABR)-based treatment of non-small-cell lung cancer

Abstract Purpose To retrospectively compute dose distributions for lung cancer patients treated with SABR, and to correlate dose distributions with outcome using a tumor control probability (TCP) model. Methods Treatment plans for 133 NSCLC patients treated using 12 Gy/fxn × 4 (BED = 106 Gy), and pl...

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Published in:Radiotherapy and oncology 2013-12, Vol.109 (3), p.498-504
Main Authors: Chetty, Indrin J, Devpura, Suneetha, Liu, Dezhi, Chen, Daiquan, Li, Haisen, Wen, Ning (Winston), Kumar, Sanath, Fraser, Correen, Siddiqui, M. Salim, Ajlouni, Munther, Movsas, Benjamin
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Language:English
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Summary:Abstract Purpose To retrospectively compute dose distributions for lung cancer patients treated with SABR, and to correlate dose distributions with outcome using a tumor control probability (TCP) model. Methods Treatment plans for 133 NSCLC patients treated using 12 Gy/fxn × 4 (BED = 106 Gy), and planned using a pencil-beam (1D-equivalent-path-length, EPL-1D) algorithm were retrospectively re-calculated using model-based algorithms (including convolution/superposition, Monte Carlo). 4D imaging was performed to manage motion. TCP was computed using the Marsden model and associations between dose and outcome were inferred. Results Mean D95 reductions of 20% (max. = 33%) were noted with model-based algorithms (relative to EPL-1D) for the smallest tumors (PTV < 20 cm3 ), corresponding to actual delivered D95 BEDs of ∼60–85 Gy. For larger tumors (PTV > 100 cm3 ), D95 reductions were ∼10% (BED > 100 Gy). Mean lung doses (MLDs) were 15% lower for model-based algorithms for PTVs < 20 cm3 . No correlation between tumor size and 2-year local control rate was observed clinically, consistent with TCP calculations, both of which were ∼90% across all PTV bins. Conclusion Results suggest that similar control rates might be achieved for smaller tumors using lower BEDs relative to larger tumors. However, more studies with larger patient cohorts are necessary to confirm this possible finding.
ISSN:0167-8140
1879-0887
DOI:10.1016/j.radonc.2013.10.012