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Clinical and MRI features for differentiating reactive lymphoid hyperplasia from hepatocellular carcinoma in
Qiansen Lin1, Gengyun Miao2, Lishan Wang3
1Department of Radiology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, Fujian Province, China; Visiting Scholar, Department of Radiology, Zhongshan Hospital, Fudan University, No.180 Fenglin Road, Xuhui District, Shanghai 200032, China.
Purpose:
To identify clinical and MRI features and construct a diagnostic model for differentiating hepatic reactive lymphoid hyperplasia (RLH) from hepatocellular carcinoma (HCC) in non-cirrhotic patients with chronic hepatitis B virus (HBV) infection.
Materials And Methods:
A retrospective study was conducted including 31 patients with pathologically confirmed RLH and 31 propensity score-matched patients with HCC. Clinical and MRI features were compared between the two groups. Firth logistic regression analysis was performed to identify independent predictors of RLH. Receiver operating characteristic curves were used to evaluate diagnostic performance. This was a patient-based analysis, with the largest lesion per patient included. The model was derived and tested in the same matched dataset.
Results:
Low AFP, ill-defined margin, and perilesional hyperintensity on T2-weighted imaging were identified as independent predictive features for differentiating RLH from HCC. The integrated model combining these variables achieved an area under the receiver operating characteristic curve of 0.965 (95% CI: 0.884-0.995), sensitivity of 96.8% (95% CI: 83.3%-99.0%), specificity of 83.9% (95% CI: 66.3%-94.5%). The integrated model significantly outperformed AFP, tumor margin, and perilesional hyperintensity on T2-weighted imaging alone (P < 0.05).
Conclusion:
Clinical and MRI features, particularly low AFP, ill-defined margin, and perilesional hyperintensity on T2-weighted imaging, are useful for differentiating RLH from HCC in non-cirrhotic chronic HBV patients. The integrated model showed excellent diagnostic performance in this patient-based matched cohort and may help reduce unnecessary surgical intervention.
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