Complication probability models for radiation-induced heart valvular dysfunction

Do heart-lung interactions play a role?

Laura Cella, Giuseppe Palma, Joseph O. Deasy, Jung Hun Oh, Raffaele Liuzzi, Vittoria D'Avino, Manuel Conson, Novella Pugliese, Marco Picardi, Marco Salvatore, Roberto Pacelli

Research output: Contribution to journalArticle

17 Citations (Scopus)

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.

Original languageEnglish
Article numbere111753
JournalPLoS One
Volume9
Issue number10
DOIs
Publication statusPublished - Oct 31 2014

Fingerprint

Area Under Curve
lungs
heart
Radiation
Lung
Cardiac Volume
dosage
Conformal Radiotherapy
Tissue
Heart Valves
Hodgkin Disease
ROC Curve
Hodgkin disease
heart valves
Survivors
Thorax
Maximum likelihood estimation
Databases
Radiotherapy
radiotherapy

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Cella, L., Palma, G., Deasy, J. O., Oh, J. H., Liuzzi, R., D'Avino, V., ... Pacelli, R. (2014). Complication probability models for radiation-induced heart valvular dysfunction: Do heart-lung interactions play a role? PLoS One, 9(10), [e111753]. https://doi.org/10.1371/journal.pone.0111753

Complication probability models for radiation-induced heart valvular dysfunction : Do heart-lung interactions play a role? / Cella, Laura; Palma, Giuseppe; Deasy, Joseph O.; Oh, Jung Hun; Liuzzi, Raffaele; D'Avino, Vittoria; Conson, Manuel; Pugliese, Novella; Picardi, Marco; Salvatore, Marco; Pacelli, Roberto.

In: PLoS One, Vol. 9, No. 10, e111753, 31.10.2014.

Research output: Contribution to journalArticle

Cella, L, Palma, G, Deasy, JO, Oh, JH, Liuzzi, R, D'Avino, V, Conson, M, Pugliese, N, Picardi, M, Salvatore, M & Pacelli, R 2014, 'Complication probability models for radiation-induced heart valvular dysfunction: Do heart-lung interactions play a role?', PLoS One, vol. 9, no. 10, e111753. https://doi.org/10.1371/journal.pone.0111753
Cella, Laura ; Palma, Giuseppe ; Deasy, Joseph O. ; Oh, Jung Hun ; Liuzzi, Raffaele ; D'Avino, Vittoria ; Conson, Manuel ; Pugliese, Novella ; Picardi, Marco ; Salvatore, Marco ; Pacelli, Roberto. / Complication probability models for radiation-induced heart valvular dysfunction : Do heart-lung interactions play a role?. In: PLoS One. 2014 ; Vol. 9, No. 10.
@article{477ae60f48844f409a1399247a8915c0,
title = "Complication probability models for radiation-induced heart valvular dysfunction: Do heart-lung interactions play a role?",
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.",
author = "Laura Cella and Giuseppe Palma and Deasy, {Joseph O.} and Oh, {Jung Hun} and Raffaele Liuzzi and Vittoria D'Avino and Manuel Conson and Novella Pugliese and Marco Picardi and Marco Salvatore and Roberto Pacelli",
year = "2014",
month = "10",
day = "31",
doi = "10.1371/journal.pone.0111753",
language = "English",
volume = "9",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "10",

}

TY - JOUR

T1 - Complication probability models for radiation-induced heart valvular dysfunction

T2 - Do heart-lung interactions play a role?

AU - Cella, Laura

AU - Palma, Giuseppe

AU - Deasy, Joseph O.

AU - Oh, Jung Hun

AU - Liuzzi, Raffaele

AU - D'Avino, Vittoria

AU - Conson, Manuel

AU - Pugliese, Novella

AU - Picardi, Marco

AU - Salvatore, Marco

AU - Pacelli, Roberto

PY - 2014/10/31

Y1 - 2014/10/31

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84910000530&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84910000530&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0111753

DO - 10.1371/journal.pone.0111753

M3 - Article

VL - 9

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 10

M1 - e111753

ER -