Abstract
Background: Accurate characterization of small (3 cm) hepatocellular carcinoma (sHCC) and dysplastic nodules (DNs) in cirrhotic liver is challenging. We aimed to investigate whether texture analysis (TA) based on T2-weighted images (T2WI) is superior to qualitative diagnosis using gadoxetic acid-enhanced MR imaging (Gd-EOB-MRI) and diffusion-weighted imaging (DWI) for distinguishing sHCC from DNs in cirrhosis.Materials and methods: Sixty-eight patients with 73 liver nodules (46 HCCs, 27 DNs) pathologically confirmed by operation were included. For imaging diagnosis, three sets of images were reviewed by two experienced radiologists in consensus: a Gd-EOB-MRI set, a DWI set, and a combined set (combination of Gd-EOB-MRI and DWI). For TA, 279 texture features resulting from T2WI were extracted for each lesion. The performance of each approach was evaluated by a receiver operating characteristic analysis. The area under the receiver operating characteristic curve (Az), sensitivity, specificity, and accuracy were determined.Results: The performance of TA (Az = 0.96) was significantly higher than that of imaging diagnosis using Gd-EOB-MRI set (Az = 0.86) or DWI set (Az = 0.80) alone in differentiation of sHCC from DNs (P = 0.008 and 0.025, respectively). The combination of Gd-EOB-MRI and DWI showed a greater sensitivity (95.6%) but reduced specificity (66.7%). The specificity of TA (92.6%) was significantly higher than that of the combined set (P < 0.001), but no significant difference was observed in sensitivity (97.8 vs. 95.6%, P = 0.559).Conclusion: TA-based T2WI showed a better classification performance than that of qualitative diagnosis using Gd-EOB-MRI and DW imaging in differentiation of sHCCs from DNs in cirrhotic liver. TA-based MRI may become a potential imaging biomarker for the early differentiation HCCs from DNs in cirrhosis.
Highlights
Hepatocellular carcinoma (HCC) is one of the most common malignancies; almost 80% of HCC occurs in patients with cirrhosis [1, 2]
Texture subsets based on mutual information (MI) and Fisher coefficients were frequently derived from the co-occurrence matrix, whereas texture features created using the POE + ACC method were frequently derived from wavelet (Table 5)
In terms of feature classification, principal component analysis (PCA) and linear discriminant analysis (LDA) resulted in an equivalent misclassification rate of 4.1–6.8 and 4.1–5.5%, respectively (Table 6)
Summary
Hepatocellular carcinoma (HCC) is one of the most common malignancies; almost 80% of HCC occurs in patients with cirrhosis [1, 2]. Based on the criteria of the American Association for the Study of Liver Diseases, arterial enhancement followed by later (portal or equilibrium phase) washout is defined as a conclusive diagnosis for HCC [7]. This typical enhancement pattern is not always presented, especially for some well-differentiated or small HCCs [8, 9]. Accurate characterization of small (3 cm) hepatocellular carcinoma (sHCC) and dysplastic nodules (DNs) in cirrhotic liver is challenging. We aimed to investigate whether texture analysis (TA) based on T2-weighted images (T2WI) is superior to qualitative diagnosis using gadoxetic acid-enhanced MR imaging (Gd-EOB-MRI) and diffusion-weighted imaging (DWI) for distinguishing sHCC from DNs in cirrhosis
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