PURPOSE: To better understand the dose dependence of radiation therapy (RT)-induced changes in regional lung perfusion and tissue density, using a manual method to reduce inaccuracies that might be present in previously described automated methods. MATERIALS AND METHODS: Patients who were to receive RT for tumors in and around the thorax, wherein portions of healthy lung would be incidentally irradiated, were prospectively studied. Changes in regional perfusion and tissue density were assessed by comparison of pre- and post-RT single photon emission computed tomography (SPECT), lung perfusion scans and computed tomography (CT) scans, respectively. The three-dimensional dose distribution was calculated on the pre-RT CT scan and correlated to the other scans via image registration. Study volumes were defined by hand and individually visualized on pre- and post-RT scans. The manually generated dose response data were compared to data generated using automated methods. The relationship between CT density and SPECT perfusion was also determined. RESULTS: Thirteen patients with lung cancer were evaluated for changes in tissue density and 11 patients were evaluated for changes in regional perfusion at 12 months post-RT. In general, density increases with increasing regional dose, with marked changes at >60 Gy. Regional perfusion decreases with increasing regional dose. In the low dose regions, relative perfusion increases by 35% on average. Manually measured dose responses correlated well with those determined automatically. The relationship between regional perfusion and CT density indicates a wide range of perfusion over a narrow range of CT density, with markedly reduced perfusion at CT densities of > -600 and < -900 H. CONCLUSIONS: The manually generated CT density dose response data broadly agree with data previously generated using automated methods. The manually generated perfusion dose response data are in fairly good agreement with automated data, lending credibility to the accuracy of the automated methods. Regional perfusion is markedly diminished where CT density is outside the range of normal lung tissue.
PURPOSE: To better understand the dose dependence of radiation therapy (RT)-induced changes in regional lung perfusion and tissue density, using a manual method to reduce inaccuracies that might be present in previously described automated methods. MATERIALS AND METHODS:Patients who were to receive RT for tumors in and around the thorax, wherein portions of healthy lung would be incidentally irradiated, were prospectively studied. Changes in regional perfusion and tissue density were assessed by comparison of pre- and post-RT single photon emission computed tomography (SPECT), lung perfusion scans and computed tomography (CT) scans, respectively. The three-dimensional dose distribution was calculated on the pre-RT CT scan and correlated to the other scans via image registration. Study volumes were defined by hand and individually visualized on pre- and post-RT scans. The manually generated dose response data were compared to data generated using automated methods. The relationship between CT density and SPECT perfusion was also determined. RESULTS: Thirteen patients with lung cancer were evaluated for changes in tissue density and 11 patients were evaluated for changes in regional perfusion at 12 months post-RT. In general, density increases with increasing regional dose, with marked changes at >60 Gy. Regional perfusion decreases with increasing regional dose. In the low dose regions, relative perfusion increases by 35% on average. Manually measured dose responses correlated well with those determined automatically. The relationship between regional perfusion and CT density indicates a wide range of perfusion over a narrow range of CT density, with markedly reduced perfusion at CT densities of > -600 and < -900 H. CONCLUSIONS: The manually generated CT density dose response data broadly agree with data previously generated using automated methods. The manually generated perfusion dose response data are in fairly good agreement with automated data, lending credibility to the accuracy of the automated methods. Regional perfusion is markedly diminished where CT density is outside the range of normal lung tissue.
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
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
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
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