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

Authors: Cella, L.; Palma, G.; Deasy, J. O.; Oh, J. H.; Liuzzi, R.; D'Avino, V.; Conson, M.; Pugliese, N.; Picardi, M.; Salvatore, M.; Pacelli, R.
Article 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.
Keywords: controlled study; major clinical study; area under the curve; radiation dose; sensitivity and specificity; radiation injury; hodgkin disease; mathematical model; probability; cardiotoxicity; radiation hazard; fractionation; computer assisted radiotherapy; predictive value; receiver operating characteristic; heart volume; lung volume; radiological parameters; valvular heart disease; dose volume histogram; human; article; heart valve dysfunction; lyman kutcher burman model; normal tissue complication probability model; relative seriality model
Journal Title: PLoS ONE
Volume: 9
Issue: 10
ISSN: 1932-6203
Publisher: Public Library of Science  
Date Published: 2014-10-31
Start Page: e111753
Language: English
DOI: 10.1371/journal.pone.0111753
PROVIDER: scopus
PMCID: PMC4216137
PUBMED: 25360627
Notes: Export Date: 1 December 2014 -- Source: Scopus
Citation Impact
MSK Authors
  1. Jung Hun Oh
    152 Oh
  2. Joseph Owen Deasy
    410 Deasy