Consistency of visual assessments of mammographic breast density from vendor-specific "for presentation" images

Mohamed Abdolell, Kaitlyn Tsuruda, Christopher B. Lightfoot, Eva Barkova, Melanie McQuaid, Judy Caines, Sian E. Iles

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Resumen

Discussions of percent breast density (PD) and breast cancer risk implicitly assume that visual assessments of PD are comparable between vendors despite differences in technology and display algorithms. This study examines the extent to which visual assessments of PD differ between mammograms acquired from two vendors. Pairs of "for presentation" digital mammography images were obtained from two mammography units for 146 women who had a screening mammogram on one vendor unit followed by a diagnostic mammogram on a different vendor unit. Four radiologists independently visually assessed PD from single left mediolateral oblique view images from the two vendors. Analysis of variance, intra-class correlation coefficients (ICC), scatter plots, and Bland-Altman plots were used to evaluate PD assessments between vendors. The mean radiologist PD for each image was used as a consensus PD measure. Overall agreement of the PD assessments was excellent between the two vendors with an ICC of 0.95 (95% confidence interval: 0.93 to 0.97). Bland-Altman plots demonstrated narrow upper and lower limits of agreement between the vendors with only a small bias (2.3 percentage points). The results of this study support the assumption that visual assessment of PD is consistent across mammography vendors despite vendor-specific appearances of "for presentation" images.

Idioma originalEnglish
Número de artículo011004
PublicaciónJournal of Medical Imaging
Volumen3
N.º1
DOI
EstadoPublished - ene. 1 2016

Nota bibliográfica

Publisher Copyright:
© The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. © The Authors.

ASJC Scopus Subject Areas

  • Radiology Nuclear Medicine and imaging

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