Interindividual Comparison of Frequency-Selective Nonlinear Blending to Conventional CT for Detection of Focal Liver Lesions Using MRI as the Reference Standard.

Abstract

BACKGROUND. Diagnosing liver lesions is challenging. CT is used for primary diagnosis, but its contrast resolution is limited. Investigating methods to improve detection of liver lesions is important. OBJECTIVE. The purpose of this study was to evaluate the effect of frequency-selective nonlinear blending on the detectability of liver lesions on CT. METHODS. A retrospective search yielded 109 patients with 356 malignant and benign liver lesions (191 principally diagnosed, 165 incidental findings) who underwent contrast-enhanced CT (CECT) in the portal venous phase and liver MRI between January 2012 and December 2017. Nonlinear blending was applied to CECT examinations, and three blinded readers independently rated the quality (5-point Likert scale) of randomly presented images. Focal lesions (n = 356) were evaluated for lesion identification and categorization to assess sensitivity. For 191 lesions (primary diagnosis), two readers evaluated CECT and nonlinear blending CT to compare lesion size and the accuracy of subjective measurements. A fourth reader performed ROI measurements for calculation of contrast-to-noise ratio (CNR), and a fifth reader reviewed MRI as the standard of reference. Statistics included interobserver agreement, quantitative comparisons of CNR, lesion size, and subjective image analyses of image quality and sensitivity for detecting liver lesions. RESULTS. Three readers rated the image quality of nonlinear blending CT (rating, 4; 10th-90th percentiles, 4-5) higher than that of CECT (rating, 2; 10th-90th percentiles, 1-3) (p < .001). CECT had good interreader agreement (interclass correlation coefficient [ICC], 0.81; 95% CI, 0.76-0.85), as did nonlinear blending CT (ICC, 0.75; 95% CI, 0.69-0.79). The median CNR of liver lesions increased with nonlinear blending (CECT, 4.18 [10th-90th percentiles, 1.67-9.06]; nonlinear blending CT, 12.49 [10th-90th percentiles, 6.18-23.39]; p < .001). Bland-Altman analysis of lesion size showed a reduction in underestimation from 2.5 (SD, 9.2) mm (95% CI, 1.2-3.9 mm) with CECT to 0.1 (SD, 3.9) mm (95% CI, -0.68 to 0.46 mm) for nonlinear blending CT (concordance correlation coefficient, 0.99). Sensitivity for detecting liver lesions increased to 86% for nonlinear blending CT. The sensitivity of CECT was 76%. CONCLUSION. Frequency-selective nonlinear blending in CECT increases image quality and CNR, increases the precision of size measurement, and increases sensitivity for detecting liver lesions. CLINICAL IMPACT. Use of nonlinear blending CT improves liver lesion detection and increases the accuracy of lesion size measurement, which is important when local ablation or liver transplant is being considered.