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2000
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603

Abstract

Background

It remains unknown whether the parameters obtained using the Stretched Exponential Model (SEM) and Fractional Order Calculus (FROC) models can help distinguish Hepatocellular Carcinoma (HCC) from Intrahepatic Cholangiocarcinoma (ICC).

Objective

This study aimed to evaluate the application value of the parameters of the 3.0T Magnetic Resonance Imaging (MRI) high-order SEM and FROC diffusion model in differentiating HCC and ICC.

Methods

Patients with pathologically confirmed HCC and ICC were prospectively enrolled. Diffusion-weighted imaging scans with multiple b-values were acquired 2 weeks before the surgery. The original MRI images were fitted using the mono-exponential model, SEM, and FROC, and several parameters were obtained for the analysis.

Results

In total, 74 patients with HCC and 21 with ICC were included in the study. Significant differences between the HCC and ICC groups were noted in the Apparent Diffusion Coefficient (ADC: = 0.007), Distributed Diffusion Coefficient (DDC: < 0.001), and Diffusion coefficient (D: < 0.001), as each value was significantly lower in the HCC than in the ICC group. The area under the receiver operating characteristic curve of ADC, DDC, and D was 0.694, 0.812, and 0.825, respectively, and the most effective corresponding cut-off values were 1.135 μm2/ms, 1.477 μm2/ms, and 1.104 μm2/ms, respectively.

Conclusion

The diffusion parameters DDC from the SEM and D from the FROC model have been found to be more effective in discriminating HCC and ICC than the ADC from the mono-exponential model. Combining these quantitative parameters can improve the MRI’s diagnostic accuracy, providing useful information for the preoperative differential diagnosis between HCC and ICC.

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2025-04-16
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