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Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?

Cella L, Palma G, Deasy JO, Oh JH, Liuzzi R, D'Avino V, Conson M, Pugliese N, Picardi M, Salvatore M, Pacelli R - PLoS ONE (2014)

Bottom Line: Bootstrap result showed that the parameter fits for lung-LKB were extremely robust.A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70).A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biostructure and Bioimaging, National Council of Research (CNR), Naples, Italy; Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy.

ABSTRACT

Purpose: The purpose of this study is to compare different normal tissue complication probability (NTCP) models for predicting heart valve dysfunction (RVD) following thoracic irradiation.

Methods: All patients from our institutional Hodgkin lymphoma survivors database with analyzable datasets were included (n = 90). All patients were treated with three-dimensional conformal radiotherapy with a median total dose of 32 Gy. The cardiac toxicity profile was available for each patient. Heart and lung dose-volume histograms (DVHs) were extracted and both organs were considered for Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) NTCP model fitting using maximum likelihood estimation. Bootstrap refitting was used to test the robustness of the model fit. Model performance was estimated using the area under the receiver operating characteristic curve (AUC).

Results: Using only heart-DVHs, parameter estimates were, for the LKB model: D50 = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D50 = 32.4 Gy, s = 0.99 and γ = 0.42. AUC values were 0.67 for LKB and 0.66 for RS, respectively. Similar performance was obtained for models using only lung-DVHs (LKB: D50 = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D50 = 24.4 Gy, s = 0.99, γ = 2.12, AUC = 0.66). Bootstrap result showed that the parameter fits for lung-LKB were extremely robust. A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70). However, the best performance was obtained using the previously determined multivariate regression model including maximum heart dose with increasing risk for larger heart and smaller lung volumes (AUC = 0.82).

Conclusions: The risk of radiation induced valvular disease cannot be modeled using NTCP models only based on heart dose-volume distribution. A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint.

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Related in: MedlinePlus

Likelihood estimation values plotted as a function of lung LKB parameters.a) m and D50 for a fixed value of n = 0.01; b) D50 and n for a fixed value of m = 0.19; c) n and m for a fixed value of D50 = 33.2; d) NTCP bundle of curves showing 95% confidence interval for the model fit. The red point corresponds to the optimum LLH. Abbreviation- LKB: Lyman-Kutcher-Burman, D50: uniform dose given to the entire organ volume that results in 50% complication probability, NTCP: Normal Tissue Complication Probability, LLH: Log-likelihood.
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pone-0111753-g003: Likelihood estimation values plotted as a function of lung LKB parameters.a) m and D50 for a fixed value of n = 0.01; b) D50 and n for a fixed value of m = 0.19; c) n and m for a fixed value of D50 = 33.2; d) NTCP bundle of curves showing 95% confidence interval for the model fit. The red point corresponds to the optimum LLH. Abbreviation- LKB: Lyman-Kutcher-Burman, D50: uniform dose given to the entire organ volume that results in 50% complication probability, NTCP: Normal Tissue Complication Probability, LLH: Log-likelihood.

Mentions: Maximum likelihood estimations for the LKB and RS parameters obtained using lungs DVHs are provided in Table 1 along with 95% CI. Iso-likelihood contours and NTCP curve bundle for LKB model are illustrated in figure 3a–d.


Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?

Cella L, Palma G, Deasy JO, Oh JH, Liuzzi R, D'Avino V, Conson M, Pugliese N, Picardi M, Salvatore M, Pacelli R - PLoS ONE (2014)

Likelihood estimation values plotted as a function of lung LKB parameters.a) m and D50 for a fixed value of n = 0.01; b) D50 and n for a fixed value of m = 0.19; c) n and m for a fixed value of D50 = 33.2; d) NTCP bundle of curves showing 95% confidence interval for the model fit. The red point corresponds to the optimum LLH. Abbreviation- LKB: Lyman-Kutcher-Burman, D50: uniform dose given to the entire organ volume that results in 50% complication probability, NTCP: Normal Tissue Complication Probability, LLH: Log-likelihood.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4216137&req=5

pone-0111753-g003: Likelihood estimation values plotted as a function of lung LKB parameters.a) m and D50 for a fixed value of n = 0.01; b) D50 and n for a fixed value of m = 0.19; c) n and m for a fixed value of D50 = 33.2; d) NTCP bundle of curves showing 95% confidence interval for the model fit. The red point corresponds to the optimum LLH. Abbreviation- LKB: Lyman-Kutcher-Burman, D50: uniform dose given to the entire organ volume that results in 50% complication probability, NTCP: Normal Tissue Complication Probability, LLH: Log-likelihood.
Mentions: Maximum likelihood estimations for the LKB and RS parameters obtained using lungs DVHs are provided in Table 1 along with 95% CI. Iso-likelihood contours and NTCP curve bundle for LKB model are illustrated in figure 3a–d.

Bottom Line: Bootstrap result showed that the parameter fits for lung-LKB were extremely robust.A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70).A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biostructure and Bioimaging, National Council of Research (CNR), Naples, Italy; Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy.

ABSTRACT

Purpose: The purpose of this study is to compare different normal tissue complication probability (NTCP) models for predicting heart valve dysfunction (RVD) following thoracic irradiation.

Methods: All patients from our institutional Hodgkin lymphoma survivors database with analyzable datasets were included (n = 90). All patients were treated with three-dimensional conformal radiotherapy with a median total dose of 32 Gy. The cardiac toxicity profile was available for each patient. Heart and lung dose-volume histograms (DVHs) were extracted and both organs were considered for Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) NTCP model fitting using maximum likelihood estimation. Bootstrap refitting was used to test the robustness of the model fit. Model performance was estimated using the area under the receiver operating characteristic curve (AUC).

Results: Using only heart-DVHs, parameter estimates were, for the LKB model: D50 = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D50 = 32.4 Gy, s = 0.99 and γ = 0.42. AUC values were 0.67 for LKB and 0.66 for RS, respectively. Similar performance was obtained for models using only lung-DVHs (LKB: D50 = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D50 = 24.4 Gy, s = 0.99, γ = 2.12, AUC = 0.66). Bootstrap result showed that the parameter fits for lung-LKB were extremely robust. A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70). However, the best performance was obtained using the previously determined multivariate regression model including maximum heart dose with increasing risk for larger heart and smaller lung volumes (AUC = 0.82).

Conclusions: The risk of radiation induced valvular disease cannot be modeled using NTCP models only based on heart dose-volume distribution. A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint.

Show MeSH
Related in: MedlinePlus