Abstract #4021

An Automated Approach for the Optimised Estimation of Breast Density with Dixon Methods

Rosie Goodburn¹, Evanthia Kousi¹, Alison Macdonald², Veronica Morgan², Erica Scurr², Martin O Leach¹, Mamatha Reddy³, Louise Wilkinson³, Elizabeth O'Flynn², Romney Pope², Robin Wilson², Steven Allen², and Maria A Schmidt¹

¹CRUK Cancer Imaging Centre, The Institute of Cancer Research and Royal Marsden Foundation Trust, London, United Kingdom, Sutton, United Kingdom, ²The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom, ³St George's University Hospitals NHS Foundation Trust, London, United Kingdom

In Breast MRI, Dixon fat-water separation techniques have been invaluable for the measurement of breast-density in studies of breast cancer risk. A fundamental source of error in Dixon methods arises from differences in the signal intensity from water and fat, associated with differences in proton density and relaxation times. We propose an automated method to introduce a scaling factor that minimizes these errors. We demonstrate our method in a group of 14 subjects, imaged at 3T with different levels of T1-weighting.

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