Statistical evaluation of dosimetric differences changes between the Modified Batho's density correction method and the Anisotropic Analytical Algorithm for clinical practice

Chaikh, Abdulhamid; Balosso, Jacques

doi:10.14319/ijcto.42.17

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…Dose differences between different dose planning algorithms, pencil beam and point kernel, is well known and have been published a number of times (23)(24)(25). In the present study we have used the recommend EUD model to compare dose calculation algorithms, as well as to evaluate radiotherapy treatment outcomes.…”

Section: Discussionmentioning

confidence: 99%

Impact of dose calculation models on radiotherapy outcomes and quality adjusted life years for lung cancer treatment: do we need to measure radiotherapy outcomes to tune the radiobiological parameters of a normal tissue complication probability model?

Chaikh¹,

Docquière²,

Bondiau³

et al. 2016

Transl. Lung Cancer Res.

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Background: The equivalent uniform dose (EUD) radiobiological model can be applied for lung cancer treatment plans to estimate the tumor control probability (TCP) and the normal tissue complication probability (NTCP) using different dose calculation models. Then, based on the different calculated doses, the quality adjusted life years (QALY) score can be assessed versus the uncomplicated tumor control probability (UTCP) concept in order to predict the overall outcome of the different treatment plans.Methods: Nine lung cancer cases were included in this study. For the each patient, two treatments plans were generated. The doses were calculated respectively from pencil beam model, as pencil beam convolution (PBC) turning on 1D density correction with Modified Batho's (MB) method, and point kernel model as anisotropic analytical algorithm (AAA) using exactly the same prescribed dose, normalized to 100% at isocentre point inside the target and beam arrangements. The radiotherapy outcomes and QALY were compared. The bootstrap method was used to improve the 95% confidence intervals (95% CI) estimation.Wilcoxon paired test was used to calculate P value.Results: Compared to AAA considered as more realistic, the PBC MB overestimated the TCP while underestimating NTCP, P<0.05. Thus the UTCP and the QALY score were also overestimated.Conclusions: To correlate measured QALY's obtained from the follow-up of the patients with calculated QALY from DVH metrics, the more accurate dose calculation models should be first integrated in clinical use. Second, clinically measured outcomes are necessary to tune the parameters of the NTCP model used to link the treatment outcome with the QALY. Only after these two steps, the comparison and the ranking of different radiotherapy plans would be possible, avoiding over/under estimation of QALY and any other clinic-biological estimates.Keywords: Point kernel; anisotropic analytical algorithm (AAA); tumor control probability (TCP)/uncomplicated tumor control probability (UTCP); normal tissue complication probability (NTCP) and quality adjusted life years (QALY)

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Section: Discussionmentioning

confidence: 99%

Impact of dose calculation models on radiotherapy outcomes and quality adjusted life years for lung cancer treatment: do we need to measure radiotherapy outcomes to tune the radiobiological parameters of a normal tissue complication probability model?

Chaikh¹,

Docquière²,

Bondiau³

et al. 2016

Transl. Lung Cancer Res.

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“…The dosimetric results from DVH and dose calculations were performed, as described previously (10). The dose was calculated using treatment planning system (TPS) Eclipse ® (Varian Medical Systems, Palo Alto, CA, USA) with analytical anisotropic algorithm (AAA) (11,12).…”

Section: Clinical Cases and Dose Calculationmentioning

confidence: 99%

Correlation between pneumonitis risk in radiation oncology and lung density measured with X-ray computed tomography

Chaikh

Balosso

2016

Quant. Imaging Med. Surg.

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Background: The risk of toxicity with radiation oncology for lung cancer limits the maximal radiation dose that can be delivered to thoracic tumors. This study aims at investigating the correlation between normal tissue complication probability (NTCP) and physical lung density by analyzing the computed tomography (CT) scan imaging used for radiotherapy dose planning.Methods: Data from CT of lung cancer patients (n=10), treated with three dimensional radiotherapy, were selected for this study. The dose was calculated using analytical anisotropic algorithm (AAA). Dose volume histograms (DVH) for healthy lung (lung excluding targets) were calculated. The NTCP for lung radiation induced pneumonitis was computed using initial radiobiological parameters from Lyman-Kutcher and Burman (LKB) model and readjusted parameters for AAA, with α/β=3. The correlation coefficient "rho" was calculated using Spearman's rank test. The bootstrap method was used to estimate the 95% confidence interval (95% CI). Wilcoxon paired test was used to calculate P values.Results: Bootstrapping simulation revealed significant difference between NTCP computed with the initial radiobiological parameters and that computed with the parameters readjusted for AAA (P=0.03). The results of simulations based on 1,000 replications showed no correlation for NTCP with density, with "rho" <0.3.Conclusions: For a given set of patients, we assessed the correlation between NTCP and lung density using bootstrap analysis. The lack of correlation could result either from a very accurate dose calculation, by AAA, whatever the lung density yielding a NTCP result only dependant of the dose and not any more of the density; or to the very limited range of natural variation of relative electronic density (0.15 to 0.20) observed in this small series of patients. Another important parameter is the bootstrap simulation with 1,000 random samplings may have underestimated the correlation, since the initial data (n=10) showed a weak correlation.Keywords: Normal tissue complication probability (NTCP); radiotherapy; bootstrap; physical density of lung and statistical concepts, to estimate the tumor control probability (TCP) as well as the normal tissue complication probability (NTCP) (2-9). Most theoretical models, that have been developed to estimate the benefits/risks balance, are based on physical dose distribution and the biological effect in normal tissue. However, the accuracy of the estimated TCP/NTCP depends on the accuracy of the assessment of the delivered dose as well as uncertainties related to the clinical data and dose calculation methods. The purpose of this paper is to evaluate and quantify the correlation between NTCP estimates and physical lung density. The NTCP was computed using dosimetric data derived from the patients' dose volume histograms (DVH) with Lyman model. Methods Clinical cases and dose calculationData from computed tomography (CT-scans) in ten lung cancer patients, treated with 3-dimensional radiotherapy, were selected for this study. The clini...

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Impact of the NTCP modeling on medical decision to select eligible patient for proton therapy: the usefulness of EUD as an indicator to rank modern photon vs proton treatment plans

Chaikh

Calugaru

Bondiau

et al. 2018

International Journal of Radiation Biology

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Treatment effectiveness assessed on NTCP reduction depends on radiobiological predictions and parameters used as inputs for in silico evaluation. Because estimates of absolute NTCP values from LKB and GN models are imprecise due to EUD ≪ TD, a reduction of the EUD value with proton plans would better predict a reduction of dose/toxicity. The EUD concept appears as a robust radiobiological surrogate of the dose distribution to select the optimal patient's plan.

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Statistical evaluation of dosimetric differences changes between the Modified Batho's density correction method and the Anisotropic Analytical Algorithm for clinical practice

Cited by 3 publications

References 19 publications

Impact of dose calculation models on radiotherapy outcomes and quality adjusted life years for lung cancer treatment: do we need to measure radiotherapy outcomes to tune the radiobiological parameters of a normal tissue complication probability model?

Impact of dose calculation models on radiotherapy outcomes and quality adjusted life years for lung cancer treatment: do we need to measure radiotherapy outcomes to tune the radiobiological parameters of a normal tissue complication probability model?

Correlation between pneumonitis risk in radiation oncology and lung density measured with X-ray computed tomography

Impact of the NTCP modeling on medical decision to select eligible patient for proton therapy: the usefulness of EUD as an indicator to rank modern photon vs proton treatment plans

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