Literature DB >> 16427214

The impact of heterogeneity correction on dosimetric parameters that predict for radiation pneumonitis.

Daniel T Chang1, Kenneth R Olivier, Christopher G Morris, Chihray Liu, James F Dempsey, Rashmi K Benda, Jatinder R Palta.   

Abstract

PURPOSE: To determine if heterogeneity correction significantly affects commonly measured dosimetric parameters predicting pulmonary toxicity in patients receiving radiation for lung cancer. METHODS AND MATERIALS: Sixty-eight patients treated for lung cancer were evaluated. The conformal treatment technique mostly employed anteroposterior/posterior-anterior fields and off-cord obliques. The percent total lung volume receiving 20 Gy or higher (V20) and mean lung dose (MLD) were correlated with the incidence of radiation pneumonitis. Parameters from both heterogeneity-corrected and heterogeneity-uncorrected plans were used to assess this risk.
RESULTS: Univariate analysis revealed a significant correlation between the development of radiation pneumonitis and both V20 and MLD. A best-fit line to a plot of V20 from the homogeneous plan against the corresponding V20 heterogeneous value produced a slope of 1.00 and zero offset, indicating no difference between the two parameters. For MLD, a similarly significant correlation is seen between the heterogeneous and homogeneous parameters, indicating a 4% difference when correcting for heterogeneity. A significant correlation was also observed between the MLD and V20 parameters (p < 0.0001).
CONCLUSIONS: A high degree of correlation exists between heterogeneity-corrected and heterogeneity-uncorrected dosimetric parameters for lung and the risk of developing pneumonitis. Either V20 or MLD predicts the pneumonitis risk with similar effect.

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Mesh:

Year:  2006        PMID: 16427214     DOI: 10.1016/j.ijrobp.2005.09.047

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  13 in total

Review 1.  Prediction of radiation pneumonitis in lung cancer patients: a systematic review.

Authors:  Xiao-Jing Zhang; Jian-Guo Sun; Jie Sun; Hua Ming; Xin-Xin Wang; Lei Wu; Zheng-Tang Chen
Journal:  J Cancer Res Clin Oncol       Date:  2012-07-29       Impact factor: 4.553

2.  Combining multiple models to generate consensus: application to radiation-induced pneumonitis prediction.

Authors:  Shiva K Das; Shifeng Chen; Joseph O Deasy; Sumin Zhou; Fang-Fang Yin; Lawrence B Marks
Journal:  Med Phys       Date:  2008-11       Impact factor: 4.071

3.  Investigation of the support vector machine algorithm to predict lung radiation-induced pneumonitis.

Authors:  Shifeng Chen; Sumin Zhou; Fang-Fang Yin; Lawrence B Marks; Shiva K Das
Journal:  Med Phys       Date:  2007-10       Impact factor: 4.071

4.  Analysis of clinical and dosimetric factors associated with severe acute radiation pneumonitis in patients with locally advanced non-small cell lung cancer treated with concurrent chemotherapy and intensity-modulated radiotherapy.

Authors:  Anhui Shi; Guangying Zhu; Hao Wu; Rong Yu; Fuhai Li; Bo Xu
Journal:  Radiat Oncol       Date:  2010-05-12       Impact factor: 3.481

5.  Impact of tissue heterogeneity corrections in stereotactic body radiation therapy treatment plans for lung cancer.

Authors:  Tania De La Fuente Herman; Heather Gabrish; Terence S Herman; Maria T Vlachaki; Salahuddin Ahmad
Journal:  J Med Phys       Date:  2010-07

6.  Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy.

Authors:  Gilmer Valdes; Timothy D Solberg; Marina Heskel; Lyle Ungar; Charles B Simone
Journal:  Phys Med Biol       Date:  2016-07-27       Impact factor: 3.609

7.  A neural network model to predict lung radiation-induced pneumonitis.

Authors:  Shifeng Chen; Sumin Zhou; Junan Zhang; Fang-Fang Yin; Lawrence B Marks; Shiva K Das
Journal:  Med Phys       Date:  2007-09       Impact factor: 4.071

8.  Analysis of radiation pneumonitis risk using a generalized Lyman model.

Authors:  Susan L Tucker; H Helen Liu; Zhongxing Liao; Xiong Wei; Shulian Wang; Hekun Jin; Ritsuko Komaki; Mary K Martel; Radhe Mohan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008-10-01       Impact factor: 7.038

9.  Effect of normal lung definition on lung dosimetry and lung toxicity prediction in radiation therapy treatment planning.

Authors:  Weili Wang; Yaping Xu; Matthew Schipper; Martha M Matuszak; Timothy Ritter; Yue Cao; Randall K Ten Haken; Feng-Ming Spring Kong
Journal:  Int J Radiat Oncol Biol Phys       Date:  2013-08-01       Impact factor: 7.038

10.  Using patient data similarities to predict radiation pneumonitis via a self-organizing map.

Authors:  Shifeng Chen; Sumin Zhou; Fang-Fang Yin; Lawrence B Marks; Shiva K Das
Journal:  Phys Med Biol       Date:  2007-12-19       Impact factor: 3.609

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