Comparison of pencil beam–based homogeneous vs inhomogeneous target dose planning for stereotactic body radiotherapy of peripheral lung tumors through Monte Carlo–based recalculation

Dosimetric differences between local failure and local controlled non-small cell lung cancer patients treated with stereotactic body radiotherapy: A matched-pair study

INTRODUCTION

Concerns were raised about the accuracy of pencil beam (PB) calculation and potential underdosing of medically inoperable non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT). From our institutional series, we designed a matched-pair study where each local failure and controlled patient was matched based upon several clinical factors, to investigate the dose difference between the matched-pair.

METHODS

Eighteen pairs of NSCLC patients, treated with 50 Gy in five fractions, were selected. These patients were matched based on treatment intent, tumour size, histology and clinical follow-up. All PB calculated clinical plans were retrospectively recalculated with a MC algorithm. The D₉₉ and D_Mean of the gross tumour volume (GTV) and D₉₅ and D_Mean of the planning tumour volume (PTV) from PB and Monte Carlo (MC) calculation were compared between local failures and controls using the Mann-Whitney test.

RESULTS

The mean PB calculated D95 of PTV was 50.4 Gy for both failures and controls (P = 0.85), indicating no planning differences between the groups. From MC calculations, the mean (±SD) of GTV D₉₉ , GTV D_Mean , PTV D₉₅ , PTV D_Mean were 47.6 ± 2.6/46.3 ± 2.4, 50.4 ± 2.1/49.8 ± 1.6, 44.4 ± 2.7/43.6 ± 3.1, 48.7 ± 2.4/48.2 ± 2.4 Gy for failure/controlled groups, respectively, and there was no significant difference between two groups (all P > 0.1). The dose differences between MC and PB calculations were in agreement with other literatures and there was no significant difference between two groups.

CONCLUSIONS

While PB algorithms may overestimate tumour doses relative to MC algorithms, our matched-pair study did not find dose differences between local failure and local controlled cases.

Frontiers in planning optimization for lung SBRT

Emerging data are showing the safety and the efficacy of Stereotactic Body Radiation therapy (SBRT) in lung cancer management. In this context, the very high doses delivered to the Planning Target Volume, make the planning phase essential for achieving high dose levels conformed to the shape of the target in order to have a good prognosis for tumor control and to avoid an overdose in relevant healthy adjacent tissue. In this non-systematic review we analyzed the technological and the physics aspects of SBRT planning for lung cancer. In particular, the aims of the study were: (i) to evaluate prescription strategies (homogeneous or inhomogeneous), (ii) to outline possible geometrical solutions by comparing the dosimetric results (iii) to describe the technological possibilities for a safe and effective treatment, (iv) to present the issues concerning radiobiological planning and the automation of the planning process.

Target dose conversion modeling from pencil beam (PB) to Monte Carlo (MC) for lung SBRT

BACKGROUND

A challenge preventing routine clinical implementation of Monte Carlo (MC)-based lung SBRT is the difficulty of reinterpreting historical outcome data calculated with inaccurate dose algorithms, because the target dose was found to decrease to varying degrees when recalculated with MC. The large variability was previously found to be affected by factors such as tumour size, location, and lung density, usually through sub-group comparisons. We hereby conducted a pilot study to systematically and quantitatively analyze these patient factors and explore accurate target dose conversion models, so that large-scale historical outcome data can be correlated with more accurate MC dose without recalculation.

METHODS

Twenty-one patients that underwent SBRT for early-stage lung cancer were replanned with 6MV 360° dynamic conformal arcs using pencil-beam (PB) and recalculated with MC. The percent D95 difference (PB-MC) was calculated for the PTV and GTV. Using single linear regression, this difference was correlated with the following quantitative patient indices: maximum tumour diameter (MaxD); PTV and GTV volumes; minimum distance from tumour to soft tissue (dmin); and mean density and standard deviation of the PTV, GTV, PTV margin, lung, and 2 mm, 15 mm, 50 mm shells outside the PTV. Multiple linear regression and artificial neural network (ANN) were employed to model multiple factors and improve dose conversion accuracy.

RESULTS

Single linear regression with PTV D95 deficiency identified the strongest correlation on mean-density (location) indices, weaker on lung density, and the weakest on size indices, with the following R(2) values in decreasing orders: shell2mm (0.71), PTV (0.68), PTV margin (0.65), shell15mm (0.62), shell50mm (0.49), lung (0.40), dmin (0.22), GTV (0.19), MaxD (0.17), PTV volume (0.15), and GTV volume (0.08). A multiple linear regression model yielded the significance factor of 3.0E-7 using two independent features: mean density of shell2mm (P = 1.6E-7) and PTV volume (P = 0.006). A 4-feature ANN model slightly improved the modeling accuracy.

CONCLUSION

Quantifiable density features were proposed, replacing simple central/peripheral location designation, which showed strong correlations with PB-to-MC target dose conversion magnitude, followed by lung density and target size. Density in the immediate outer and inner areas of the PTV showed the strongest correlations. A multiple linear regression model with one such feature and PTV volume established a high significance factor, improving dose conversion accuracy.