PURPOSE: The aim of the study is to assess the predictive power of DCE-MRI semi-quantitative parameters during treatment of breast cancer, for disease-free (DFS) and overall survival (OS). MATERIALS AND METHODS: Forty-nine women (age range, 28-84 years; mean, 50.6 years) with breast cancer underwent dynamic contrast enhancement MRI at 1.0T imaging, using 2D FLASH sequences. Time intensity curves (TICs) were obtained from the regions showing maximal enhancement in subtraction images. Semi-quantitative parameters (TICs; maximal relative enhancement within the first minute, E (max/1); maximal relative enhancement of the entire study, E(max); steepest slope of the contrast enhancement curve; and time to peak enhancement) derived from the DCE-MRI data. These parameters were then compared with presence of recurrence or metastasis, DFS and OS by using Cox regression (proportional hazards model) analysis, linear discriminant analysis. RESULTS: The results from of the 49 patients enrolled into the survival analysis demonstrated that traditional prognostic parameters (tumor size and nodal metastasis) and semi-quantitative parameters (E(max/1), and steepest slope) demonstrated significant differences in survival intervals (p<0.05). Further Cox regression (proportional hazards model) survival analysis revealed that semi-quantitative parameters contributed the greatest prediction of both DFS, OS in the resulting models (for E(max/1): p=0.013, hazard ratio 1.022; for stepest slope: p=0.004, hazard ratio 1.584). CONCLUSION: This study shows that DCE-MRI has utility predicting survival analysis with breast cancer patients.
PURPOSE: The aim of the study is to assess the predictive power of DCE-MRI semi-quantitative parameters during treatment of breast cancer, for disease-free (DFS) and overall survival (OS). MATERIALS AND METHODS: Forty-nine women (age range, 28-84 years; mean, 50.6 years) with breast cancer underwent dynamic contrast enhancement MRI at 1.0T imaging, using 2D FLASH sequences. Time intensity curves (TICs) were obtained from the regions showing maximal enhancement in subtraction images. Semi-quantitative parameters (TICs; maximal relative enhancement within the first minute, E (max/1); maximal relative enhancement of the entire study, E(max); steepest slope of the contrast enhancement curve; and time to peak enhancement) derived from the DCE-MRI data. These parameters were then compared with presence of recurrence or metastasis, DFS and OS by using Cox regression (proportional hazards model) analysis, linear discriminant analysis. RESULTS: The results from of the 49 patients enrolled into the survival analysis demonstrated that traditional prognostic parameters (tumor size and nodal metastasis) and semi-quantitative parameters (E(max/1), and steepest slope) demonstrated significant differences in survival intervals (p<0.05). Further Cox regression (proportional hazards model) survival analysis revealed that semi-quantitative parameters contributed the greatest prediction of both DFS, OS in the resulting models (for E(max/1): p=0.013, hazard ratio 1.022; for stepest slope: p=0.004, hazard ratio 1.584). CONCLUSION: This study shows that DCE-MRI has utility predicting survival analysis with breast cancerpatients.
Authors: Daniel I Golden; Jafi A Lipson; Melinda L Telli; James M Ford; Daniel L Rubin Journal: J Am Med Inform Assoc Date: 2013-06-19 Impact factor: 4.497
Authors: J Jayender; K G Vosburgh; E Gombos; A Ashraf; D Kontos; S C Gavenonis; F A Jolesz; K Pohl Journal: Proc IEEE Int Symp Biomed Imaging Date: 2012-07-12
Authors: Baishali Chaudhury; Mu Zhou; Dmitry B Goldgof; Lawrence O Hall; Robert A Gatenby; Robert J Gillies; Bhavika K Patel; Robert J Weinfurtner; Jennifer S Drukteinis Journal: J Magn Reson Imaging Date: 2015-04-17 Impact factor: 4.813
Authors: Jagadeesan Jayender; Eva Gombos; Sona Chikarmane; Donnette Dabydeen; Ferenc A Jolesz; Kirby G Vosburgh Journal: Comput Med Imaging Graph Date: 2013-05-19 Impact factor: 4.790