{"title":"Gd-EOB-DTPA 增强核磁共振成像显示非肝硬化肝脏中的肝绒毛膜癌与肝细胞癌:诊断挑战。","authors":"Ruixia Ma, Shi-Ting Feng, Xiaoqi Zhou, Meichen Chen, Jifei Wang, Zhi Dong","doi":"10.2174/0115734056269369231213102554","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hepatic Pecoma versus Hepatocellular Carcinoma In The Noncirrhotic Liver on Gd-EOB-DTPA-Enhanced MRI: A Diagnostic Challenge.\",\"authors\":\"Ruixia Ma, Shi-Ting Feng, Xiaoqi Zhou, Meichen Chen, Jifei Wang, Zhi Dong\",\"doi\":\"10.2174/0115734056269369231213102554\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aim: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":54215,\"journal\":{\"name\":\"Current Medical Imaging Reviews\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Medical Imaging Reviews\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/0115734056269369231213102554\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Medical Imaging Reviews","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115734056269369231213102554","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Hepatic Pecoma versus Hepatocellular Carcinoma In The Noncirrhotic Liver on Gd-EOB-DTPA-Enhanced MRI: A Diagnostic Challenge.
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.
期刊介绍:
Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques.
The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.