PURPOSE: The aim of this study was to assess the impact of patient-specific factors, left ventricle (LV) volume, and treatment set-up errors on the rate of perfusion defects 6 to 60 months post-radiation therapy (RT) in patients receiving tangential RT for left-sided breast cancer. METHODS AND MATERIALS: Between 1998 and 2005, a total of 153 patients were enrolled onto an institutional review board-approved prospective study and had pre- and serial post-RT (6-60 months) cardiac perfusion scans to assess for perfusion defects. Of the patients, 108 had normal pre-RT perfusion scans and available follow-up data. The impact of patient-specific factors on the rate of perfusion defects was assessed at various time points using univariate and multivariate analysis. The impact of set-up errors on the rate of perfusion defects was also analyzed using a one-tailed Fisher's Exact test. RESULTS: Consistent with our prior results, the volume of LV in the RT field was the most significant predictor of perfusion defects on both univariate (p = 0.0005 to 0.0058) and multivariate analysis (p = 0.0026 to 0.0029). Body mass index (BMI) was the only significant patient-specific factor on both univariate (p = 0.0005 to 0.022) and multivariate analysis (p = 0.0091 to 0.05). In patients with very small volumes of LV in the planned RT fields, the rate of perfusion defects was significantly higher when the fields set-up "too deep" (83% vs. 30%, p = 0.059). The frequency of deep set-up errors was significantly higher among patients with BMI > or =25 kg/m2 compared with patients of normal weight (47% vs. 28%, p = 0.068). CONCLUSIONS: BMI > or =25 kg/m2 may be a significant risk factor for cardiac toxicity after RT for left-sided breast cancer, possibly because of more frequent deep set-up errors resulting in the inclusion of additional heart in the RT fields. Further study is necessary to better understand the impact of patient-specific factors and set-up errors on the development of RT-induced perfusion defects.
PURPOSE: The aim of this study was to assess the impact of patient-specific factors, left ventricle (LV) volume, and treatment set-up errors on the rate of perfusion defects 6 to 60 months post-radiation therapy (RT) in patients receiving tangential RT for left-sided breast cancer. METHODS AND MATERIALS: Between 1998 and 2005, a total of 153 patients were enrolled onto an institutional review board-approved prospective study and had pre- and serial post-RT (6-60 months) cardiac perfusion scans to assess for perfusion defects. Of the patients, 108 had normal pre-RT perfusion scans and available follow-up data. The impact of patient-specific factors on the rate of perfusion defects was assessed at various time points using univariate and multivariate analysis. The impact of set-up errors on the rate of perfusion defects was also analyzed using a one-tailed Fisher's Exact test. RESULTS: Consistent with our prior results, the volume of LV in the RT field was the most significant predictor of perfusion defects on both univariate (p = 0.0005 to 0.0058) and multivariate analysis (p = 0.0026 to 0.0029). Body mass index (BMI) was the only significant patient-specific factor on both univariate (p = 0.0005 to 0.022) and multivariate analysis (p = 0.0091 to 0.05). In patients with very small volumes of LV in the planned RT fields, the rate of perfusion defects was significantly higher when the fields set-up "too deep" (83% vs. 30%, p = 0.059). The frequency of deep set-up errors was significantly higher among patients with BMI > or =25 kg/m2 compared with patients of normal weight (47% vs. 28%, p = 0.068). CONCLUSIONS: BMI > or =25 kg/m2 may be a significant risk factor for cardiac toxicity after RT for left-sided breast cancer, possibly because of more frequent deep set-up errors resulting in the inclusion of additional heart in the RT fields. Further study is necessary to better understand the impact of patient-specific factors and set-up errors on the development of RT-induced perfusion defects.
Authors: Eugene Chung; James R Corbett; Jean M Moran; Kent A Griffith; Robin B Marsh; Mary Feng; Reshma Jagsi; Marc L Kessler; Edward C Ficaro; Lori J Pierce Journal: Int J Radiat Oncol Biol Phys Date: 2012-09-27 Impact factor: 7.038
Authors: Lanea Keller; Randi Cohen; Dennis M Sopka; Tianyu Li; Linna Li; Penny R Anderson; Barbara L Fowble; Gary M Freedman Journal: Pract Radiat Oncol Date: 2013-01-05
Authors: Frank Lohr; Felix Heggemann; Theano Papavassiliu; Mostafa El-Haddad; Oliver Tomé; Dietmar Dinter; Barbara Dobler; Uta Kraus-Tiefenbacher; Martin Borggrefe; Frederik Wenz Journal: Strahlenther Onkol Date: 2009-04-16 Impact factor: 3.621
Authors: Alexandra J Stewart; Desmond A O'Farrell; Robert A Cormack; Jorgen L Hansen; Atif J Khan; Subhakar Mutyala; Phillip M Devlin Journal: Radiat Oncol Date: 2008-11-19 Impact factor: 3.481