TY - JOUR
T1 - Inter- and intrafractional 4D dose accumulation for evaluating ΔNTCP robustness in lung cancer
AU - Smolders, Andreas
AU - Hengeveld, Adriaan C.
AU - Both, Stefan
AU - Wijsman, Robin
AU - Langendijk, Johannes A.
AU - Weber, Damien C.
AU - Lomax, Anthony J.
AU - Albertini, Francesca
AU - Guterres Marmitt, Gabriel
N1 - Funding Information:
This project has received funding from the European Union's Horizon 2020 Marie Skłodowska-Curie Actions under Grant Agreement No. 955956. The authors would like to thank Cosylab for providing their DIR algorithm.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/5
Y1 - 2023/5
N2 - Background and purpose: Model-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, but NTCP can be affected when the delivered treatment deviates from the plan due to delivery inaccuracies. Especially for proton therapy of lung cancer, this can be important because of tissue density changes and, with pencil beam scanning, the interplay effect between the proton beam and breathing motion.Materials and methods: In this work, we verified whether the expected benefit of proton therapy is retained despite delivery inaccuracies by reconstructing the delivered treatment using log-file based dose reconstruction and inter- and intrafractional accumulation. Additionally, the importance of two uncertain parameters for treatment reconstruction, namely deformable image registration (DIR) algorithm and α/β ratio, was assessed.Results: The expected benefit or proton therapy was confirmed in 97% of all studied cases, despite regular differences up to 2 percent point (p.p.) NTCP between the delivered and planned treatments. The choice of DIR algorithm affected NTCP up to 1.6 p.p., an order of magnitude higher than the effect of α/β ratio.Conclusion: For the patient population and treatment technique employed, the predicted clinical benefit for patients selected for proton therapy was confirmed for 97.0% percent of all cases, although the NTCP based proton selection was subject to 2 p.p. variations due to delivery inaccuracies.
AB - Background and purpose: Model-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, but NTCP can be affected when the delivered treatment deviates from the plan due to delivery inaccuracies. Especially for proton therapy of lung cancer, this can be important because of tissue density changes and, with pencil beam scanning, the interplay effect between the proton beam and breathing motion.Materials and methods: In this work, we verified whether the expected benefit of proton therapy is retained despite delivery inaccuracies by reconstructing the delivered treatment using log-file based dose reconstruction and inter- and intrafractional accumulation. Additionally, the importance of two uncertain parameters for treatment reconstruction, namely deformable image registration (DIR) algorithm and α/β ratio, was assessed.Results: The expected benefit or proton therapy was confirmed in 97% of all studied cases, despite regular differences up to 2 percent point (p.p.) NTCP between the delivered and planned treatments. The choice of DIR algorithm affected NTCP up to 1.6 p.p., an order of magnitude higher than the effect of α/β ratio.Conclusion: For the patient population and treatment technique employed, the predicted clinical benefit for patients selected for proton therapy was confirmed for 97.0% percent of all cases, although the NTCP based proton selection was subject to 2 p.p. variations due to delivery inaccuracies.
KW - DIR
KW - Lung cancer
KW - NTCP
KW - Proton therapy
KW - Robustness
U2 - 10.1016/j.radonc.2023.109488
DO - 10.1016/j.radonc.2023.109488
M3 - Article
C2 - 36706960
AN - SCOPUS:85147702983
SN - 0167-8140
VL - 182
JO - Radiotherapy and Oncology
JF - Radiotherapy and Oncology
M1 - 109488
ER -