Correlation Of Clinical Outcome, Radiobiological Modeling Of Tumor Control, Normal Tissue Complication Probability In Lung Cancer Patients Treated With Sbrt Using Monte Carlo Calculation Algorithm

Purpose/Background We analyzed the predictive value of non-x-ray voxel Monte Carlo (XVMC)-based modeling of tumor control probability (TCP) and normal tissue complication probability (NTCP) in patients treated with stereotactic body radiotherapy (SBRT) using the XVMC dose calculation algorithm. Materials/Methods We conducted an IRB-approved retrospective analysis in patients with lung tumors treated with XVMC-based lung SBRT. For TCP, we utilized tumor size-adjusted biological effective dose (s-BED) TCP modeling validated in non-MC dose calculated SBRT to: (1) verify modeling as a function of s-BED in patients treated with XVMC-based SBRT; and (2) evaluate the predictive potential of different PTV dosimetric parameters (mean dose, minimum dose, max dose, prescription dose, D95, D98, and D99) for incorporation into the TCP model. Correlation between observed local control and TCPs was assessed by Pearson's correlation coefficient. For NTCP, Lyman NTCP Model was utilized to predict grade 2 pneumonitis and rib fracture. Results Eighty-four patients with 109 lung tumors were treated with XVMC-based SBRT to total doses of 40 to 60 Gy in 3 to 5 fractions. Median follow-up was 17 months. The 2-year local and local-regional control rates were 91% and and 78%, respectievly. All estimated TCPs correlated significantly with 2-year actuarial local control rates (P < 0.05). Significant corelations between TCPs and tumor control rate according to PTV dosimetric parameters were observed. D99 parameterization demonstrated the most robust correlation between observed and predicted tumor control. The incidences of grade 2 pneumonitis and rib fracture vs. predicted were 1% vs. 3% and 10% vs. 13%, respectively. Conclusion Our TCP results using a XVMC-based dose calculation algorithm are encouraging and yield validation to previously described TCP models using non-XVMC dose methods. Furthermore, D99 as potential predictive parameter in the TCP model demonstrated better correlation with clinical outcome.