Enhanced gray-white matter differentiation on non-enhanced CT using a frequency selective non-linear blending.

ABSTRACT

INTRODUCTION: The aim if this study is to find out if contrast between gray (GM) and white matter (WM) on non-enhanced brain CT (NECT) can be enhanced by using a frequency selective non-linear blending. METHODS: Thirty consecutive patients (40 % female; mean age 67.73 ± 12.71 years), who underwent NECT of the brain, were retrospectively included in this study. Brain scan readings were performed by two radiologists independently, for NECT and subsequently the images were read using a new frequency selective non-linear blending algorithm (best contrast, BC). Optimal settings of BC for enhanced delineation of anatomical structures were set at an averaged center of 30 HU, averaged delta of 5 HU, and a slope of 5. For contrast-to-noise ratio calculation (CNR), gray and white matter attenuation values were measured for both NECT and BC in different anatomical structures. RESULTS: CNR increase in the gray matter was 5.91 ± 2.45 for the cortical gray matter and 4.41 ± 1.82 for the basal ganglia. The contrast ratio between cortical gray and white matter was 1.87 and 1.7 (basal ganglia/WM) for BC quantification vs. 1.43 (cortex/WM) and 1.33 (basal ganglia/WM) for standard NECT (both p < 0.0001). Improved CNR did not depend on the anatomical structures measured. CONCLUSION: Frequency selective non-linear blending allows better discrimination between WM and GM and therefore may enhance diagnostic accuracy of NECT.