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Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
- Source :
- PLoS ONE, PloS one 9 (2014). doi:10.1371/journal.pone.0111753, info:cnr-pdr/source/autori:Cella, Laura; Palma, Giuseppe; Deasy, Joseph O.; Oh, Jung Hun; Liuzzi, R.; D'Avino, Vittoria; Conson, Manuel; Pugliese, Novella; Picardi, Marco N.; Salvatore., Marco; Pacelli, Roberto/titolo:Complication probability models for radiation-induced heart valvular dysfunction: Do heart-lung interactions play a role?/doi:10.1371%2Fjournal.pone.0111753/rivista:PloS one/anno:2014/pagina_da:/pagina_a:/intervallo_pagine:/volume:9, PLoS ONE, Vol 9, Iss 10, p e111753 (2014)
- Publication Year :
- 2014
- Publisher :
- Public Library of Science, 2014.
-
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.
- Subjects :
- Multivariate statistics
Medical Physics
medicine.medical_treatment
Cancer Treatment
lcsh:Medicine
Radiation induced
Bioinformatics
Hematologic Cancers and Related Disorders
Mathematical and Statistical Techniques
Medicine and Health Sciences
Lung volumes
Probability Estimation
lcsh:Science
Lung
Likelihood Functions
Multidisciplinary
Maximum Likelihood Estimation
Radiology and Imaging
Physics
Models, Cardiovascular
Hematology
Heart Valves
medicine.anatomical_structure
Oncology
Physical Sciences
Lymphomas
Statistics (Mathematics)
Research Article
Radiation Therapy
Research and Analysis Methods
Multivariate Data Analysis
medicine
Confidence Intervals
Humans
Heart valve
Statistical Methods
Radiation Injuries
Probability
Receiver operating characteristic
business.industry
Hodgkin Lymphoma
lcsh:R
Cancers and Neoplasms
Dose-Response Relationship, Radiation
Radiation therapy
Radiation Effects
ROC Curve
lcsh:Q
Nuclear medicine
business
Complication
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 9
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....88dbb93229fcbc6f31bbd9de4a2872d5
- Full Text :
- https://doi.org/10.1371/journal.pone.0111753