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Leah Portnow, MD








BWPO Physician, Radiologist




Leah H. Portnow, MD; Lina Choridah, MD; Kardinah Kardinah, MD; Triwulan Handarini, MD; Ruud Pijnappel, MD; A.M.J. Bluekens, MD, PhD; L.E.M Duijm, MD, PhD; Peter K. Schoub, MD; Pam Smilg, MD; Liat Malek, MD; Jessica Leung, MD; Sughra Raza, MD

International Inter-observer Variability of Breast Density Assessment

I am a breast imaging radiologist at Brigham and Women’s Hospital and Dana-Farber/Brigham Cancer Center, and an Instructor at Harvard Medical School. My research interests include evaluating breast biopsy markers, breast density assessment and risk management, and multidisciplinary collaboration in axillary management and neoadjuvant response to treatment. I also have an avid interest in medical training, involving fellows and residents in research, leading to Cum Laude citations for RSNA educational exhibits and mentored manuscripts. It is important to participate in this symposium to showcase my work contributions in medicine as a woman-physician, with my project emphasizing global, diverse women populations.


Breast density may vary based on ethnicity, resulting in different density category distributions globally. We questioned whether radiologists skew mammographic density categorization according to BI-RADS®-based expectations versus local population/cultural influences. We evaluated variability in mammographic density categorization among radiologists practicing in Indonesia, the Netherlands, South Africa, and the USA.


200 screening mammograms performed from September-December 2017 were reviewed from four global locations for a total of 800. Three radiologists in each location/“team” provided consensus density assessments using BI-RADS®. Inter-reader agreement was compared using Gwet’s AC2 across all four density categories and Gwet’s AC1 for not-dense versus dense combined categories. Variability of distribution was calculated using the Stuart-Maxwell test across all four density categories, McNemar’s test for not-dense vs dense, and logistic regression for readers from a particular country on their own 200 mammograms versus other teams.


For all 800 mammograms, inter-reader agreement across four density categories is 0.86 and not-dense vs dense categories is 0.66. Density category assessment distribution was significantly different when comparing teams in pairs and source readers vs other teams combined (p<0.001).


When comparing readers from four geographical locations, despite almost-perfect/substantial agreement of density categorization, distribution across density categories is significantly different.