A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma
BackgroundIntrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the se...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.838701/full |
| _version_ | 1818872467313131520 |
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| author | Xianling Qian Xianling Qian Xianling Qian Xin Lu Xin Lu Xin Lu Xijuan Ma Ying Zhang Changwu Zhou Changwu Zhou Changwu Zhou Fang Wang Yibing Shi Mengsu Zeng Mengsu Zeng Mengsu Zeng |
| author_facet | Xianling Qian Xianling Qian Xianling Qian Xin Lu Xin Lu Xin Lu Xijuan Ma Ying Zhang Changwu Zhou Changwu Zhou Changwu Zhou Fang Wang Yibing Shi Mengsu Zeng Mengsu Zeng Mengsu Zeng |
| author_sort | Xianling Qian |
| collection | DOAJ |
| description | BackgroundIntrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime.PurposeThis study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively.MethodsA total of 163 pathologically confirmed ICC patients (training cohort: n = 130; validation cohort: n = 33) with postoperative Ga-DTPA-enhanced MR examination were enrolled, and a time-independent test cohort (n = 24) was collected for external validation. Univariate and multivariate analyses were used to determine the independent predictors of MVI status, which were then incorporated into the MVI prediction nomogram. Least absolute shrinkage and selection operator logistic regression was performed to select optimal features and construct radiomics models. The prediction performances of models were assessed by receiver operating characteristic (ROC) curve analysis. The performance of the MVI prediction nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsLarger tumor size (p = 0.003) and intrahepatic duct dilatation (p = 0.002) are independent predictors of MVI. The final radiomics model shows desirable and stable prediction performance in the training cohort (AUC = 0.950), validation cohort (AUC = 0.883), and test cohort (AUC = 0.812). The MVI prediction nomogram incorporates tumor size, intrahepatic duct dilatation, and the final radiomics model and achieves excellent predictive efficacy in training cohort (AUC = 0.953), validation cohort (AUC = 0.861), and test cohort (AUC = 0.819), fitting well in calibration curves (p > 0.05). Decision curve and clinical impact curve further confirm the clinical usefulness of the nomogram.ConclusionThe nomogram incorporating tumor size, intrahepatic duct dilatation, and the final radiomics model is a potential biomarker for preoperative prediction of the MVI status in ICC patients. |
| first_indexed | 2024-12-19T12:39:16Z |
| format | Article |
| id | doaj.art-5e1ba3f10cb74e47b8cd90c8e63aec37 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-19T12:39:16Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-5e1ba3f10cb74e47b8cd90c8e63aec372022-12-21T20:21:01ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-02-011210.3389/fonc.2022.838701838701A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic CholangiocarcinomaXianling Qian0Xianling Qian1Xianling Qian2Xin Lu3Xin Lu4Xin Lu5Xijuan Ma6Ying Zhang7Changwu Zhou8Changwu Zhou9Changwu Zhou10Fang Wang11Yibing Shi12Mengsu Zeng13Mengsu Zeng14Mengsu Zeng15Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, ChinaShanghai Institute of Medical Imaging, Shanghai, ChinaDepartment of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, ChinaShanghai Institute of Medical Imaging, Shanghai, ChinaDepartment of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, ChinaDepartment of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, ChinaDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, ChinaShanghai Institute of Medical Imaging, Shanghai, ChinaDepartment of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, ChinaDepartment of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, ChinaDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, ChinaShanghai Institute of Medical Imaging, Shanghai, ChinaDepartment of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, ChinaBackgroundIntrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime.PurposeThis study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively.MethodsA total of 163 pathologically confirmed ICC patients (training cohort: n = 130; validation cohort: n = 33) with postoperative Ga-DTPA-enhanced MR examination were enrolled, and a time-independent test cohort (n = 24) was collected for external validation. Univariate and multivariate analyses were used to determine the independent predictors of MVI status, which were then incorporated into the MVI prediction nomogram. Least absolute shrinkage and selection operator logistic regression was performed to select optimal features and construct radiomics models. The prediction performances of models were assessed by receiver operating characteristic (ROC) curve analysis. The performance of the MVI prediction nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsLarger tumor size (p = 0.003) and intrahepatic duct dilatation (p = 0.002) are independent predictors of MVI. The final radiomics model shows desirable and stable prediction performance in the training cohort (AUC = 0.950), validation cohort (AUC = 0.883), and test cohort (AUC = 0.812). The MVI prediction nomogram incorporates tumor size, intrahepatic duct dilatation, and the final radiomics model and achieves excellent predictive efficacy in training cohort (AUC = 0.953), validation cohort (AUC = 0.861), and test cohort (AUC = 0.819), fitting well in calibration curves (p > 0.05). Decision curve and clinical impact curve further confirm the clinical usefulness of the nomogram.ConclusionThe nomogram incorporating tumor size, intrahepatic duct dilatation, and the final radiomics model is a potential biomarker for preoperative prediction of the MVI status in ICC patients.https://www.frontiersin.org/articles/10.3389/fonc.2022.838701/fullintrahepatic cholangiocarcinomamicrovascular invasionprognosismagnetic resonance imagingradiomicsnomogram |
| spellingShingle | Xianling Qian Xianling Qian Xianling Qian Xin Lu Xin Lu Xin Lu Xijuan Ma Ying Zhang Changwu Zhou Changwu Zhou Changwu Zhou Fang Wang Yibing Shi Mengsu Zeng Mengsu Zeng Mengsu Zeng A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma Frontiers in Oncology intrahepatic cholangiocarcinoma microvascular invasion prognosis magnetic resonance imaging radiomics nomogram |
| title | A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma |
| title_full | A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma |
| title_fullStr | A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma |
| title_full_unstemmed | A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma |
| title_short | A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma |
| title_sort | multi parametric radiomics nomogram for preoperative prediction of microvascular invasion status in intrahepatic cholangiocarcinoma |
| topic | intrahepatic cholangiocarcinoma microvascular invasion prognosis magnetic resonance imaging radiomics nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.838701/full |
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