Evaluating the diagnostic sensitivity of computed diffusion-weighted MR imaging in the detection of breast cancer

Abstract

Purpose: To evaluate the diagnostic sensitivity of computed diffusion-weighted (DW)-MR imaging for the detection of breast cancer.

Materials and methods: Local research ethics approval was obtained. A total of 61 women (median 48 years) underwent dynamic contrast enhanced (DCE)- and DW-MR between January 2011 and March 2012, including 27 with breast cancer on core biopsy and 34 normal cases. Standard ADC maps using all four b values (0, 350, 700, 1150) were used to generate computed DW-MR images at b = 1500 s/mm(2) and b = 2000 s/mm(2) . Four image sets were read sequentially by two readers: acquired b = 1150 s/mm(2) , computed b = 1500 s/mm(2) and b = 2000 s/mm(2) , and DCE-MR at an early time point. Cancer detection was rated using a five-point scale; image quality and background suppression were rated using a four-point scale. The diagnostic sensitivity for breast cancer detection was compared using the McNemar test and inter-reader agreement with a Kappa value.

Results: Computed DW-MR resulted in higher overall diagnostic sensitivity with b = 2000 s/mm(2) having a mean diagnostic sensitivity of 76% (range 49.8-93.7%) and b = 1500 s/mm(2) having a mean diagnostic sensitivity of 70.3% (range 32-97.7%) compared with 44.4% (range 25.5-64.7%) for acquired b = 1150 s/mm(2) (both p = 0.0001). Computed DW-MR images produced better image quality and background suppression (mean scores for both readers: 2.55 and 2.9 for b 1500 s/mm(2) ; 2.55 and 3.15 for b 2000 s/mm(2) , respectively) than the acquired b value 1150 s/mm(2) images (mean scores for both readers: 2.4 and 2.45, respectively).

Conclusion: Computed DW-MR imaging has the potential to improve the diagnostic sensitivity of breast cancer detection compared to acquired DW-MR. J. Magn. Reson. Imaging 2016;44:130-137.