BACKGROUND: Volumetric breast composition analysis represents a useful tool for assessing changes in breast composition over time. However, no data exist on the reproducibility of this method in serial mammograms. PURPOSE: To assess the reproducibility of two volumetric breast composition parameters, breast percent density (PD) and fibroglandular tissue volume (FTV), in consecutive mammograms. MATERIAL AND METHODS: Volumetric breast composition analysis to determine PD and FTV was performed in two consecutive unilateral mammograms of 211 patients. All mammograms were obtained on the same digital mammography unit within a maximum interval of 24 months. Volumetric data for analysis for both examinations were available for 174 patients. Thirty-two patients had successful volumetric analysis of additional consecutive examinations on a second digital mammography unit. Inter-examination correlation of measurements and absolute differences were analyzed. Bland-Altman analysis was performed to compare readings from different mammography units. RESULTS: Mean FTV remained constant over the study period. A reduction in PD of 0.5% and a mean increase in breast volume (BV) of 3% were observed. FTV measurements obtained on the same mammography unit were significantly more reproducible than PD measurements (Pearson correlation coefficients of 0.947 and 0.920, respectively; P < 0.05). A 15% difference between mean absolute volume measurements (FTV and BV) obtained on different mammography units was observed (P ≤ 0.001), while mean PD was close to the expected value. CONCLUSION: Volumetric breast composition analysis is highly reproducible in serial mammograms in normal women. FTV is a more reproducible parameter than PD, indicating that absolute quantification of breast parenchyma may be preferable to the measurement of relative parameters such as PD. However, a disadvantage of using FTV is that it is susceptible to systematic differences when measurements are obtained on different imaging platforms.
BACKGROUND: Volumetric breast composition analysis represents a useful tool for assessing changes in breast composition over time. However, no data exist on the reproducibility of this method in serial mammograms. PURPOSE: To assess the reproducibility of two volumetric breast composition parameters, breast percent density (PD) and fibroglandular tissue volume (FTV), in consecutive mammograms. MATERIAL AND METHODS: Volumetric breast composition analysis to determine PD and FTV was performed in two consecutive unilateral mammograms of 211 patients. All mammograms were obtained on the same digital mammography unit within a maximum interval of 24 months. Volumetric data for analysis for both examinations were available for 174 patients. Thirty-two patients had successful volumetric analysis of additional consecutive examinations on a second digital mammography unit. Inter-examination correlation of measurements and absolute differences were analyzed. Bland-Altman analysis was performed to compare readings from different mammography units. RESULTS: Mean FTV remained constant over the study period. A reduction in PD of 0.5% and a mean increase in breast volume (BV) of 3% were observed. FTV measurements obtained on the same mammography unit were significantly more reproducible than PD measurements (Pearson correlation coefficients of 0.947 and 0.920, respectively; P < 0.05). A 15% difference between mean absolute volume measurements (FTV and BV) obtained on different mammography units was observed (P ≤ 0.001), while mean PD was close to the expected value. CONCLUSION: Volumetric breast composition analysis is highly reproducible in serial mammograms in normal women. FTV is a more reproducible parameter than PD, indicating that absolute quantification of breast parenchyma may be preferable to the measurement of relative parameters such as PD. However, a disadvantage of using FTV is that it is susceptible to systematic differences when measurements are obtained on different imaging platforms.
Authors: Mohamed Abdolell; Kaitlyn Tsuruda; Christopher B Lightfoot; Eva Barkova; Melanie McQuaid; Judy Caines; Sian E Iles Journal: J Med Imaging (Bellingham) Date: 2015-10-30
Authors: Ernest U Ekpo; Mark F McEntee; Mary Rickard; Patrick C Brennan; Jyotsna Kunduri; Delgermaa Demchig; Claudia Mello-Thoms Journal: Br J Radiol Date: 2016-02-16 Impact factor: 3.039
Authors: Maureen Sanderson; Heather O'Hara; Nia Foderingham; William D Dupont; Xiao-Ou Shu; Neeraja Peterson; Alecia M Fair; Anthony C Disher Journal: Cancer Causes Control Date: 2014-11-25 Impact factor: 2.506