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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. MAT...

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Autores principales: Sood, Sumit S., Pokhrel, Damodar, Badkul, Rajeev, TenNapel, Mindi, McClinton, Christopher, Kimler, Bruce, Wang, Fen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592969/
https://www.ncbi.nlm.nih.gov/pubmed/32794632
http://dx.doi.org/10.1002/acm2.13004
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author Sood, Sumit S.
Pokhrel, Damodar
Badkul, Rajeev
TenNapel, Mindi
McClinton, Christopher
Kimler, Bruce
Wang, Fen
author_facet Sood, Sumit S.
Pokhrel, Damodar
Badkul, Rajeev
TenNapel, Mindi
McClinton, Christopher
Kimler, Bruce
Wang, Fen
author_sort Sood, Sumit S.
collection PubMed
description 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.
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spelling pubmed-75929692020-11-02 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 Sood, Sumit S. Pokhrel, Damodar Badkul, Rajeev TenNapel, Mindi McClinton, Christopher Kimler, Bruce Wang, Fen J Appl Clin Med Phys Radiation Oncology Physics 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. John Wiley and Sons Inc. 2020-08-14 /pmc/articles/PMC7592969/ /pubmed/32794632 http://dx.doi.org/10.1002/acm2.13004 Text en © 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Sood, Sumit S.
Pokhrel, Damodar
Badkul, Rajeev
TenNapel, Mindi
McClinton, Christopher
Kimler, Bruce
Wang, Fen
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592969/
https://www.ncbi.nlm.nih.gov/pubmed/32794632
http://dx.doi.org/10.1002/acm2.13004
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