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Diagnostic Efficacy of Non-Contrast Liver Magnetic Resonance Imaging with Multiparametric Sequences in Hepatocellular Carcinoma

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Current guidelines recommend recommended the use of contrast-enhanced dynamic magnetic resonance imaging (MRI) for the diagnosis of hepatocellular carcinoma (HCC). However, some patients cannot undergo MRI examination because of the risk of nephrogenic systemic fibrosis due to renal functional impairment (eGFR <30 mL/min/1.73 m2). This study aimed to explore the feasibility of using non-contrast-enhanced multiparametric (mp) MRI to improve the diagnostic accuracy of hepatocellular carcinoma (HCC). This study included 60 patients with HCC (aged 30–85 years; 39 females and 21 males). All imaging examinations were performed on a 3-Tesla MRI system. The following MR pulse sequences were used: transverse T2/transverse (TRA)/fat suppression (FS), T1/GRE/TRA, diffusion-weighted image, 2D susceptibility-weighted imaging (SWI), T1/3D/volumetric interpolated breath-hold examination (VIBE)/FS, and contrast-enhanced T1/3D/VIBE/FS dynamic MRI. All images were reviewed and all datasets analyzed by two gastrointestinal radiologists with more than 10 years of experience. The observers were aware of the suspected HCC lesions but blinded to the number and size of the lesions. The differences in accuracy were compared using the paired-sample t-test. The diagnostic accuracy rate for HCC using the non-contrast-enhanced mpMRI and the contrast-enhanced T1/3D/VIBE/FS dynamic MRI was 91.7% and 96.6%, respectively. The diagnostic accuracy of non-contrast-enhanced mpMRI was significant compared with the contrast-enhanced T1/3D/VIBE/FS dynamic MRI. After the Wilcoxon signed-rank test, the two-tailed probability reached 0.643, demonstrating no significant difference between the groups. The use of non-contrast-enhanced mp sequences can effectively improve the diagnostic accuracy of HCC in patients who cannot undergo contrast-enhanced dynamic MRI.

Keywords: ACCURACY; HEPATOCELLULAR CARCINOMA; MULTIPARAMETRIC SEQUENCES

Document Type: Research Article

Publication date: 01 January 2019

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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