Accuracy of Liver Surface Nodularity Quantification on MDCT as a Noninvasive Biomarker for Staging Hepatic Fibrosis.

Academic Article

Abstract

  • OBJECTIVE: The purpose of this study was to investigate objective semiautomated measurement of liver surface nodularity on MDCT for prediction of underlying hepatic fibrosis (stages F0-F4). MATERIALS AND METHODS: Contrast-enhanced abdominal MDCT scans were assessed with an independently validated semiautomated surface nodularity tool. A series of 10 or more consecutive ROI measurements along the anterior aspect of the liver totaling a length of 80 cm or more were made with the left lateral segment as the default. All intermediate stages of fibrosis (F1-F3) were based on liver biopsy results within 1 year of MDCT. RESULTS: The study participants were 367 patients (191 men, 176 women; mean age, 51.1 years) divided into a healthy (F0) control group (n = 118) and patients with fibrosis in stages F1 (n = 47), F2 (n = 38), F3 (n = 67), and F4, which constituted cirrhosis (n = 97). MDCT-based liver surface nodularity scores increased with stage of fibrosis: F0, 2.01 ± 0.28; F1, 2.34 ± 0.39; F2, 2.37 ± 0.39; F3, 2.88 ± 0.68; and F4, 4.11 ± 0.95. For discriminating significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (≥ F4), the ROC AUCs were 0.902, 0.932, and 0.959, respectively. The sensitivity and specificity for significant fibrosis (≥ F2; liver surface nodularity threshold, 2.38) were 80.2% and 80.0%, for advanced fibrosis (≥ F3; liver surface nodularity threshold, 2.53) were 89.0% and 84.2%, and for cirrhosis (≥ F4; liver surface nodularity threshold, 2.81) were 97.9% and 84.8%. CONCLUSION: Objective quantification of liver surface nodularity at MDCT allows accurate discrimination between stages of hepatic fibrosis, especially at more advanced levels. Although the results are comparable to those of elastography, this simple semiautomated biomarker can be measured retrospectively without additional equipment or patient time.
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    Keywords

  • CT, biomarker, cirrhosis, elastography, hepatic fibrosis, Biomarkers, Female, Humans, Liver, Liver Cirrhosis, Male, Middle Aged, Multidetector Computed Tomography, Pattern Recognition, Automated, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Severity of Illness Index
  • Digital Object Identifier (doi)

    Author List

  • Pickhardt PJ; Malecki K; Kloke J; Lubner MG
  • Start Page

  • 1194
  • End Page

  • 1199
  • Volume

  • 207
  • Issue

  • 6