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Objective <p>Aims to evaluate the potential of contrast-enhanced magnetic resonance imaging (MRI) in distinguishing steatohepatitic hepatocellular carcinoma (SH-HCC) from small(diameter &lt; 2&#xa0;cm) non-otherwise specified hepatocellular carcinoma.</p> Methods <p>This retrospective study included 32 patients with SH-HCC and 241 patients with sNOS-HCC who underwent resection between January 2017 and June 2022. The clinical, pathological, and MRI features of these patients were compared. Logistic regression analysis was employed to identify independent predictors of SH-HCC and to develop a nomogram for differentiating SH-HCC from sNOS-HCC. Model discrimination was assessed by calculating the area under the ROC curve (AUC), while calibration curves and decision curve analysis (DCA) were performed to evaluate calibration accuracy and clinical utility, respectively.</p> Results <p>Univariate and multivariate analyses identified T2DM (OR = 3.025; 95%CI:1.059, 8.634; <i>p</i> = 0.039), HBV infection (OR = 0.293; 95%CI:0.095, 0.900; <i>p</i> = 0.032), elevated TBil (OR = 1.065; 95%CI: 1.015, 1.117; <i>p</i> = 0.010), T1WI opposed-phase signal drop (OR = 4.217; 95%CI: 1.177, 15.107; <i>p</i> = 0.027), and diffuse intratumoral fat (OR = 6.255; 95%CI: 2.024, 19.337; <i>p</i> = 0.001) as independent predictors for SH-HCC. These five variables were used to establish the nomogram, which had a C-index of 0.873 (95% CI: 0.844–0.902). The ROC analysis revealed that the AUC of this model was 0.886, with a sensitivity of 84.4% and a specificity of 84.3%. It not only demonstrated excellent discriminatory ability but also had a high negative predictive value (NPV = 97.6%).</p> Conclusion <p>The integration of MRI imaging features—specifically, diffuse intratumoral fat and T1WI opposed-phase signal drop—with key clinical factors, including T2DM, HBV infection, and elevated TBil, demonstrates robust diagnostic performance in the preoperative differentiation of SH-HCC from sNOS-HCC. This multimodal model not only achieves high discriminatory accuracy but also yields a markedly high negative predictive value.</p>

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Contrast-enhanced MRI for identifying the steatohepatitic hepatocellular carcinoma from small hepatocellular carcinoma

  • 期刊论文

  • 发表日期：

    2025年11月10日

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  • Jiachen Liu,
  • Xiurong Ding,
  • Yanyan Zhang,
  • Hongjun Li

摘要

Objective

Aims to evaluate the potential of contrast-enhanced magnetic resonance imaging (MRI) in distinguishing steatohepatitic hepatocellular carcinoma (SH-HCC) from small(diameter < 2 cm) non-otherwise specified hepatocellular carcinoma.

Methods

This retrospective study included 32 patients with SH-HCC and 241 patients with sNOS-HCC who underwent resection between January 2017 and June 2022. The clinical, pathological, and MRI features of these patients were compared. Logistic regression analysis was employed to identify independent predictors of SH-HCC and to develop a nomogram for differentiating SH-HCC from sNOS-HCC. Model discrimination was assessed by calculating the area under the ROC curve (AUC), while calibration curves and decision curve analysis (DCA) were performed to evaluate calibration accuracy and clinical utility, respectively.

Results

Univariate and multivariate analyses identified T2DM (OR = 3.025; 95%CI:1.059, 8.634; p = 0.039), HBV infection (OR = 0.293; 95%CI:0.095, 0.900; p = 0.032), elevated TBil (OR = 1.065; 95%CI: 1.015, 1.117; p = 0.010), T1WI opposed-phase signal drop (OR = 4.217; 95%CI: 1.177, 15.107; p = 0.027), and diffuse intratumoral fat (OR = 6.255; 95%CI: 2.024, 19.337; p = 0.001) as independent predictors for SH-HCC. These five variables were used to establish the nomogram, which had a C-index of 0.873 (95% CI: 0.844–0.902). The ROC analysis revealed that the AUC of this model was 0.886, with a sensitivity of 84.4% and a specificity of 84.3%. It not only demonstrated excellent discriminatory ability but also had a high negative predictive value (NPV = 97.6%).

Conclusion

The integration of MRI imaging features—specifically, diffuse intratumoral fat and T1WI opposed-phase signal drop—with key clinical factors, including T2DM, HBV infection, and elevated TBil, demonstrates robust diagnostic performance in the preoperative differentiation of SH-HCC from sNOS-HCC. This multimodal model not only achieves high discriminatory accuracy but also yields a markedly high negative predictive value.