Evaluation of frequency-selective non-linear blending technique on brain CT in postoperative children with Moyamoya disease

Abstract

Objective: To evaluate whether a frequency-selective non-linear blending (BC) technique can improve tissue contrast and infarct detection on non-enhanced brain CT (NECT) in postoperative Moyamoya (MMD) patients. Materials and methods: From January 2010 to December 2017, 33 children (13 boys and 20 girls; mean age 9.1 ± 3.4 years) with MMD postoperatively underwent NECT followed by diffusion MRI. We compared the contrast-to-noise ratio (CNR) between gray matter (GM) and white matter (WM) in NECT and BC images and the CNR between the infarct lesion and adjacent normal-appearing brain in NECT and BC images using a paired t-test. We assessed image noise, GM-WM differentiation, artifacts, and overall quality using a Wilcoxon signed rank test. A McNemar two-tailed test was conducted to compare the diagnostic accuracy of infarct detection. Results: The CNR between GM and WM and the CNR of the infarct was better in BC images than in NECT images (3.9 ± 1.0 vs. 1.8 ± 0.6, P < 0.001 and 3.6 ± 0.3 vs. 1.9 ± 0.2, P < 0.001), with no difference in overall image quality observed. The sensitivity and specificity of infarct detection were 55.0% and 76.9% using NECT, and 70.0% and 69.2% using BC technique. The diagnostic accuracy of NECT and BC technique was 63.6% (21/33) and 69.7% (23/33), respectively. Conclusion: This study showed that the BC technique improved CNR and maintained image quality. This technique may also be used to identify ischemic brain changes in postoperative MMD patients by improving the CNR of the infarct lesion.