Literature DB >> 11208849

Can we predict radiation-induced changes in pulmonary function based on the sum of predicted regional dysfunction?

M Fan1, L B Marks, D Hollis, G G Bentel, M S Anscher, G Sibley, R E Coleman, R J Jaszczak, M T Munley.   

Abstract

PURPOSE: To determine whether changes in whole-lung pulmonary function test (PFT) values are related to the sum of predicted radiation therapy (RT)-induced changes in regional lung perfusion. PATIENTS AND METHODS: Between 1991 and 1998, 96 patients (61% with lung cancer) who were receiving incidental partial lung irradiation were studied prospectively. The patients were assessed with pre- and post-RT PFTs (forced expiratory volume in one second [FEV1] and diffusion capacity for carbon monoxide [DLCO]) for at least a 6-month follow-up period, and patients were excluded if it was determined that intrathoracic recurrence had an impact on lung function. The maximal declines in PFT values were noted. A dose-response model based on RT-induced reduction in regional perfusion (function) was used to predict regional dysfunction. The predicted decline in pulmonary function was calculated as the weighted sum of the predicted regional injuries: equation [see text] where Vd is the volume of lung irradiated to dose d, and Rd is the reduction in regional perfusion anticipated at dose d.
RESULTS: The relationship between the predicted and measured reduction in PFT values was significant for uncorrected DLCO (P = .005) and borderline significant for DLCO (P = .06) and FEV1 (P = .08). However, the correlation coefficients were small (range,.18 to.30). In patients with lung cancer, the correlation coefficients improved as the number of follow-up evaluations increased (range,.43 to.60), especially when patients with hypoperfusion in the lung adjacent to a central mediastinal/hilar thoracic mass were excluded (range,.59 to.91).
CONCLUSION: The sum of predicted RT-induced changes in regional perfusion is related to RT-induced changes in pulmonary function. In many patients, however, the percentage of variation explained is small, which renders accurate predictions difficult.

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Year:  2001        PMID: 11208849     DOI: 10.1200/JCO.2001.19.2.543

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  17 in total

Review 1.  Imaging for assessment of radiation-induced normal tissue effects.

Authors:  Robert Jeraj; Yue Cao; Randall K Ten Haken; Carol Hahn; Lawrence Marks
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-03-01       Impact factor: 7.038

2.  Does transforming growth factor-beta1 predict for radiation-induced pneumonitis in patients treated for lung cancer?

Authors:  Elizabeth S Evans; Zafer Kocak; Su-Min Zhou; Daniel A Kahn; Hong Huang; Donna R Hollis; Kim L Light; Mitchell S Anscher; Lawrence B Marks
Journal:  Cytokine       Date:  2006-09-18       Impact factor: 3.861

3.  Dose-mass inverse optimization for minimally moving thoracic lesions.

Authors:  I B Mihaylov; E G Moros
Journal:  Phys Med Biol       Date:  2015-04-24       Impact factor: 3.609

4.  Protective effect of ulinastatin in patients with non-small cell lung cancer after radiation therapy: a randomized, placebo-controlled study.

Authors:  Pengtao Bao; Weiguo Zhao; Yun Li; Yu Liu; Yi Zhou; Changting Liu
Journal:  Med Oncol       Date:  2014-12-12       Impact factor: 3.064

5.  Functional dose-volume histograms for predicting radiation pneumonitis in locally advanced non-small cell lung cancer treated with late-course accelerated hyperfractionated radiotherapy.

Authors:  Dongqing Wang; Baosheng Li; Zhongtang Wang; Jian Zhu; Hongfu Sun; Jian Zhang; Yong Yin
Journal:  Exp Ther Med       Date:  2011-06-29       Impact factor: 2.447

Review 6.  Imaging radiation-induced normal tissue injury.

Authors:  Mike E Robbins; Judy K Brunso-Bechtold; Ann M Peiffer; Christina I Tsien; Janet E Bailey; Lawrence B Marks
Journal:  Radiat Res       Date:  2012-02-21       Impact factor: 2.841

Review 7.  Radiation-related treatment effects across the age spectrum: differences and similarities or what the old and young can learn from each other.

Authors:  Matthew J Krasin; Louis S Constine; Debra L Friedman; Lawrence B Marks
Journal:  Semin Radiat Oncol       Date:  2010-01       Impact factor: 5.934

8.  Lung perfusion imaging can risk stratify lung cancer patients for the development of pulmonary complications after chemoradiation.

Authors:  Isis W Gayed; Joe Chang; E Edmund Kim; Rodolfo Nuñez; Beth Chasen; H Helen Liu; Katsuhiro Kobayashi; Yujing Zhang; Zhongxing Liao; Salman Gohar; Melinda Jeter; Louise Henderson; William Erwin; Ritsuko Komaki
Journal:  J Thorac Oncol       Date:  2008-08       Impact factor: 15.609

9.  Analysis of single nucleotide polymorphisms and radiation sensitivity of the lung assessed with an objective radiologic endpoin.

Authors:  Chris R Kelsey; Isabel L Jackson; Scott Langdon; Kouros Owzar; Jessica Hubbs; Zeljko Vujaskovic; Shiva Das; Lawrence B Marks
Journal:  Clin Lung Cancer       Date:  2013-01-10       Impact factor: 4.785

10.  Association between RT-induced changes in lung tissue density and global lung function.

Authors:  Jinli Ma; Junan Zhang; Sumin Zhou; Jessica L Hubbs; Rodney J Foltz; Donna R Hollis; Kim L Light; Terence Z Wong; Christopher R Kelsey; Lawrence B Marks
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008-12-10       Impact factor: 7.038

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