Radiobiological impact of dose calculation algorithms on biologically optimized IMRT lung stereotactic body radiation therapy plans

Liang, Xiaoying; Peñagarícano, José; Zheng, Dandan; Morrill, Steven; Zhang, X.; Corry, Peter M.; Griffin, Robert J.; Han, Eun Young; Hardee, Matthew E.; Ratanatharathom, V.

doi:10.1186/s13014-015-0578-2

Cited by 28 publications

(30 citation statements)

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“…Recently, biological constraints, such as generalized equivalent uniform dose (gEUD), tumor control probability (TCP) and normal tissue complication probability (NTCP), have been used in IMRT planning process [4]. Biological parameters, which applied in biological models to predict the biological effect of tumor and normal tissues, have more direct correlation with treatment outcome than physical parameters [5–10]. Research shows that, with similar target coverage, biological optimization could spare more organs at risk (OARs) than physical optimization [11–18].…”

Section: Introductionmentioning

confidence: 99%

An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma

et al. 2017

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BackgroundFor cervical carcinoma cases, this study aimed to evaluate the quality of intensity-modulated radiation therapy (IMRT) plans optimized by biological constraints. Furthermore, a new integrated strategy in biological planning module was proposed and verified.MethodsTwenty patients of advanced stage cervical carcinoma were enrolled in this study. For each patient, dose volume optimization (DVO), biological model optimization (BMO) and integrated strategy optimization (ISO) plans were created using same treatment parameters. Different biological models were also used for organ at risk (OAR) in BMO plans, which include the LKB and Poisson models. Next, BMO plans were compared with their corresponding DVO plans, in order to evaluate BMO plan quality. ISO plans were also compared with DVO and BMO plans, in order to verify the performance of the integrated strategy.ResultsBMO plans produced slightly inhomogeneity and less coverage of planning target volume (PTV) (V95=96.79, HI = 0.10: p < 0.01). However, the tumor control probability (TCP) value, both from DVO and BMO plans, were comparable. For the OARs, BMO plans produced lower normal tissue complication probability (NTCP) of rectum (NTCP = 0.11) and bladder (NTCP = 0.14) than in the corresponding DVO plans (NTCP = 0.19 and 0.18 for rectum and bladder; p < 0.01 for rectum and p = 0.03 for bladder). V95, D98, CI and HI values that were produced by ISO plans (V95 = 98.31, D98 = 54.18Gy, CI = 0.76, HI = 0.09) were greatly better than BMO plans (V95 = 96.79, D98 = 53.42Gy, CI = 0.71, HI = 0.10) with significant differences. Furthermore, ISO plans produced lower NTCP values of rectum (NTCP = 0.14) and bladder (NTCP = 0.16) than DVO plans (NTCP = 0.19 and 0.18 for rectum and bladder, respectively) with significant differences.ConclusionsBMO plans produced lower NTCP values of OARs compared to DVO plans for cervical carcinoma cases, and resulted in slightly less target coverage and homogeneity. The integrated strategy, proposed in this study, could improve the coverage, conformity and homogeneity of PTV greater than the BMO plans, as well as reduce the NTCP values of OARs greater than the DVO plans.

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Section: Introductionmentioning

confidence: 99%

An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma

et al. 2017

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“…It should be stated that there are large uncertainties in the currently used biological models and associated parameters, so the application of results from conventional to SBRT approach ( 56 ) or from a dose algorithms to another ( 57 ) should be performed with caution.…”

Section: Discussionmentioning

confidence: 99%

Radiobiological Optimization in Lung Stereotactic Body Radiation Therapy: Are We Ready to Apply Radiobiological Models?

et al. 2018

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Lung tumors are often associated with a poor prognosis although different schedules and treatment modalities have been extensively tested in the clinical practice. The complexity of this disease and the use of combined therapeutic approaches have been investigated and the use of high dose-rates is emerging as effective strategy. Technological improvements of clinical linear accelerators allow combining high dose-rate and a more conformal dose delivery with accurate imaging modalities pre- and during therapy. This paper aims at reporting the state of the art and future direction in the use of radiobiological models and radiobiological-based optimizations in the clinical practice for the treatment of lung cancer. To address this issue, a search was carried out on PubMed database to identify potential papers reporting tumor control probability and normal tissue complication probability for lung tumors. Full articles were retrieved when the abstract was considered relevant, and only papers published in English language were considered. The bibliographies of retrieved papers were also searched and relevant articles included. At the state of the art, dose–response relationships have been reported in literature for local tumor control and survival in stage III non-small cell lung cancer. Due to the lack of published radiobiological models for SBRT, several authors used dose constraints and models derived for conventional fractionation schemes. Recently, several radiobiological models and parameters for SBRT have been published and could be used in prospective trials although external validations are recommended to improve the robustness of model predictive capability. Moreover, radiobiological-based functions have been used within treatment planning systems for plan optimization but the advantages of using this strategy in the clinical practice are still under discussion. Future research should be directed toward combined regimens, in order to potentially improve both local tumor control and survival. Indeed, accurate knowledge of the relevant parameters describing tumor biology and normal tissue response is mandatory to correctly address this issue. In this context, the role of medical physicists and the AAPM in the development of radiobiological models is crucial for the progress of developing specific tool for radiobiological-based optimization treatment planning.

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“…More recent studies showed that AAA overestimates the PTV dose and TCP compared to Acuros-XB using Poisson model with LQ. The difference can be reached up to 5.8% for TCP, while both algorithms yield very similar normal tissue complication probability (NTCP) on lung pneumonitis based on the LKB model parameter (28,29). However, the more advanced algorithms such as AAA, Acrous-XB, collapsed cone and MC would be recommended to better calculate the dose for tumor and to avoid the over/under estimating TCP/NTCP outcome.…”

Section: Precaution To Use Tcp In Order To Rank and Optimize Radiothementioning

confidence: 99%

The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices

Chaikh¹,

Balosso²

2017

Transl. Lung Cancer Res.

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Background: To apply the equivalent uniform dose (EUD) radiobiological model to estimate the tumor control probability (TCP) scores for treatment plans using different radiobiological parameter settings, and to evaluate the correlation between TCP and physical quality indices of the treatment plans.Methods: Ten radiotherapy treatment plans for lung cancer were generated. The dose distributions were calculated using anisotropic analytical algorithm (AAA). Dose parameters and quality indices derived from dose volume histograms (DVH) for target volumes were evaluated. The predicted TCP was computed using EUD model with tissue-specific parameter (a=−10). The assumed radiobiological parameter setting for adjuvant therapy [tumor dose to control 50% of the tumor (TCD 50 ) =36.5 Gy and γ 50 =0.72] and curative intent (TCD 50 =51.24 Gy and γ 50 =0.83) were used. The bootstrap method was used to estimate the 95% confidence interval (95% CI). The coefficients (ρ) from Spearman's rank test were calculated to assess the correlation between quality indices with TCP. Wilcoxon paired test was used to calculate P value.Results: The 95% CI of TCP were 70.6-81.5 and 46.6-64.7, respectively, for adjuvant radiotherapy and curative intent. The TCP outcome showed a positive and good correlation with calculated dose to 95% of the target volume (D95%) and minimum dose (Dmin). Consistently, TCP correlate negatively with heterogeneity indices.Conclusions: This study confirms that more relevant and robust radiobiological parameters setting should be integrated according to cancer type. The positive correlation with quality indices gives chance to improve the clinical out-come by optimizing the treatment plans to maximize the Dmin and D95%. This attempt to increase the TCP should be carried out with the respect of dose constraints for organs at risks. However, the negative correlation with heterogeneity indices shows that the optimization of beam arrangements could be also useful. Attention should be paid to obtain an appropriate optimization of initial plans, when comparing and ranking radiotherapy plans using TCP models, to avoid over or underestimated for TCP outcome.

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Radiobiological impact of dose calculation algorithms on biologically optimized IMRT lung stereotactic body radiation therapy plans

Cited by 28 publications

References 50 publications

An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma

An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma

Radiobiological Optimization in Lung Stereotactic Body Radiation Therapy: Are We Ready to Apply Radiobiological Models?

The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices

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