Purpose: Setup uncertainty is a known challenge for stereotactic body radiotherapy planning. Using the internal target volume-based robust optimization was proposed as a more accurate way than the conventional planning target volume-based optimization when considering the robustness criteria. In this study, we aim to investigate the feasibility of internal target volume-based robust optimization in stereotactic body radiotherapy planning using 4-dimensional computed tomography and develop a novel dose–volume histogram band width metric to quantitatively evaluate robustness. Method and Materials: A total of 50 patients with early stage non-small cell lung cancer, who underwent stereotactic body radiotherapy, were retrospectively selected. Each of the 50 patients had 2 stereotactic body radiotherapy plans: one with the conventional planning target volume-based optimization and the other with patient-specific robustly optimized internal target volume and with a uniform 5 mm setup error. These were compared with the planning target volume-based optimization method based on both plan quality and robustness. The quality was evaluated using dosimetric parameters and radiobiology parameters, such as high-dose spillage ( V 90%RX, conformity index), intermediate-dose spillage (dose falloff products), low-dose spillage (normal tissue: V 50%RX), and lung tissue complication probability. The robustness was evaluated under a uniform 3 to 5 mm setup errors with a novel proposed metric: dose–volume histogram band width. Results: When compared with planning target volume-based optimization plans, the internal target volume-based robust optimization plans have better conformity of internal target volume coverage (conformity index: 1.17 vs 1.27, P < .001), intermediate-dose spillage (dose falloff product: 129 vs 167, P < .001), low-dose spillage in normal tissue ( V 50%RX: 0.8% vs 1.5%, P < .05), and lower risk of radiation pneumonitis (lung tissue complication probability: 4.2% vs 5.5%, P < .001). For the robustness, dose–volume histogram band width analysis shows that the average values in internal target volume, D 95%, D 98%, and D 99%, of internal target volume-based robust optimization are smaller than that of planning target volume-based optimization (unit cGy) under 3-, 4-, and 5-mm setup uncertainties (3-mm setup uncertainty: 42 vs 73 cGy; 4-mm setup uncertainty: 88 vs 176 cGy; 5-mm setup uncertainty: 229 vs 490 cGy), which might indicate that internal target volume-based robust optimization harbored a greater robustness regardless of the setup errors. Conclusions: Internal target volume-based robust optimization may have clinical potential in offering better plan quality in both target and organs at risk and lower risk of radiation pneumonitis. In addition, the proposed internal target volume-based robust optimization may demonstrate robustness regardless of different setup uncertainties in the stereotactic body radiotherapy planning. Registration: Retrospective study with local ethics committee approval.
Evaluation of dose-volume histogram prediction for organ-at risk and planning target volume based on machine learning