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1.
World J Gastroenterol ; 30(13): 1926-1933, 2024 Apr 07.
Article in English | MEDLINE | ID: mdl-38659487

ABSTRACT

Accurate preoperative diagnosis is highly important for the treatment of perivascular epithelioid cell tumors (PEComas) because PEComas are mainly benign tumors and may not require surgical intervention. By analyzing the causes, properties and clinical manifestations of PEComas, we summarize the challenges and solutions in the diagnosis of PEComas.


Subject(s)
Liver Neoplasms , Perivascular Epithelioid Cell Neoplasms , Humans , Perivascular Epithelioid Cell Neoplasms/surgery , Perivascular Epithelioid Cell Neoplasms/pathology , Perivascular Epithelioid Cell Neoplasms/diagnosis , Liver Neoplasms/surgery , Liver Neoplasms/pathology , Liver Neoplasms/diagnosis , Hepatectomy , Preoperative Care/methods , Biomarkers, Tumor/analysis , Diagnosis, Differential , Liver/pathology , Liver/surgery , Liver/diagnostic imaging
2.
Curr Med Imaging ; 2024 Feb 27.
Article in English | MEDLINE | ID: mdl-38415458

ABSTRACT

AIM: Hepatic perivascular epithelioid cell tumors (PEComa) often mimic hepatocellular carcinoma (HCC) in patients without cirrhosis. This study aimed to develop a nomogram using imaging characteristics on Gd-EOB-DTPA-enhanced MRI and to distinguish PEComa from HCC in a noncirrhotic liver. METHODS: Forty patients with non-cirrhotic Gd-EOB-DTPA-enhanced magnetic resonance imaging(MRI) were included in our study. A multivariate logistic regression model was used to select significant variables to distinguish PEComa from HCC. A nomogram was developed based on the regression model. The performance of the nomogram was assessed with respect to the ROC curve and calibration curve. Decision curve analysis (DCA) was performed to evaluate the clinical usefulness of the nomogram. RESULTS: Two significant predictors were identified: the appearance of an early draining vein and the T1D value of tumors. The ROC curve showed that the area under the curve (AUC) of the model to predict the risk of PEComa was 0.91 (95% CI: 0.80~1) and showed that the model had high specificity (92.3%) and sensitivity (88.9%). The nomogram incorporating these two predictors showed favorable calibration, which was validated using 1000 resampling procedures, and the corrected C-index of this model was 0.90. Furthermore, DCA analysis showed that the model had clinical practicability. CONCLUSION: In conclusion, the nomogram model showed favorable predictive accuracy for distinguishing PEComa from HCC in non-cirrhotic patients and may aid in clinical decision-making.

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