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Li Y, Li P, Ma J, Wang Y, Tian Q, Yu J, Zhang Q, Shi H, Zhou W, Huang G. Preoperative Three-Dimensional Morphological Tumor Features Predict Microvascular Invasion in Hepatocellular Carcinoma. Acad Radiol 2024; 31:1862-1869. [PMID: 37989682 DOI: 10.1016/j.acra.2023.10.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 10/28/2023] [Accepted: 10/30/2023] [Indexed: 11/23/2023]
Abstract
RATIONALE AND OBJECTIVES The study was designed to evaluate microvascular invasion (MVI) using three-dimensional (3D) morphological indicators prior to surgery. MATERIALS AND METHODS This retrospective study included 156 patients with hepatocellular carcinoma (HCC) at our hospital from 2017 to 2018. Through thin-layer CT scanning and 3D reconstruction, the tumor surface inclination angles can be quantitatively analyzed to determine the surface irregularity rate (SIR), which serves as a comprehensive assessment method for tumor irregularity based on preoperative 3D morphological evaluation. Univariate and multivariate logistic regression analyses were employed to investigate the correlation with MVI. RESULTS The SIR was related to MVI (OR: 10.667, P < 0.001). Multivariate logistic regression analysis showed that the SIR was an independent risk factor for MVI. The area under the receiver operating characteristic curve (ROC) of prediction model composed of the morphological indicator SIR was 0.831 (95% confidence interval: 0.759-0.895). CONCLUSION The preoperative 3D morphological indicator SIR of a tumor is an accurate predictor of MVI, providing a valuable tool in clinical decision-making.
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Affiliation(s)
- Yumeng Li
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.)
| | - Pengpeng Li
- Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.)
| | - Junjie Ma
- Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China (J.M.)
| | - Yuanyuan Wang
- Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.)
| | - Qiyu Tian
- Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.)
| | - Jian Yu
- Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.)
| | - Qinghui Zhang
- Shenzhen Yorktal Digital Medical Imaging Technology Company Ltd, Shenzhen, China (Q.Z.)
| | - Huazheng Shi
- Shanghai Universal cloud Medical Imaging Diagnostic Center, Shanghai, China (H.S.)
| | - Weiping Zhou
- Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.)
| | - Gang Huang
- Eastern Hepatobiliary Surgery Hospital, No. 700, Moyu North Road, Jiading District, Shanghai, China (Y.L., P.L., Y.W., Q.T., J.Y., W.Z., G.H.).
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Zhang J, Dong W, Liu W, Fu J, Liao T, Li Y, Huo L, Jia N. Preoperative evaluation of MRI features and inflammatory biomarkers in predicting microvascular invasion of combined hepatocellular cholangiocarcinoma. Abdom Radiol (NY) 2024; 49:710-721. [PMID: 38112787 PMCID: PMC10909765 DOI: 10.1007/s00261-023-04130-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/07/2023] [Accepted: 11/12/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE Microvascular invasion (MVI) is a significant prognostic factor in combined hepatocellular cholangiocarcinoma (cHCC-CCA). However, its diagnosis relies on postoperative histopathologic analysis. This study aims to identify preoperative inflammatory biomarkers and MR-imaging features that can predict MVI in cHCC-CCA. METHODS This retrospective study enrolled 119 patients with histopathologically confirmed cHCC-CCA between January 2016 and December 2021. Two radiologists, unaware of the clinical data, independently reviewed all MR image features. Univariable and multivariable analyses were performed to determine the independent predictors for MVI among inflammatory biomarkers and MRI characteristics. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance. RESULTS Multivariable logistic regression analysis identified four variables significantly associated with MVI (p < 0.05), including two inflammatory biomarkers [albumin-to-alkaline phosphatase ratio (AAPR) and aspartate aminotransferase-to-neutrophil ratio index (ANRI)] and two MRI features (non-smooth tumor margin and arterial phase peritumoral enhancement). A combined model for predicting MVI was constructed based on these four variables, with an AUC of 0.802 (95% CI 0.719-0.870). The diagnostic efficiency of the combined model was higher than that of the imaging model. CONCLUSION Inflammatory biomarkers and MRI features could be potential predictors for MVI in cHCC-CCA. The combined model, derived from inflammatory biomarkers and MRI features, showed good performance in preoperatively predicting MVI in cHCC-CCA patients.
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Affiliation(s)
- Juan Zhang
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Wei Dong
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Wanmin Liu
- Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Jiazhao Fu
- Department of Organ Transplantation, Changhai Hospital, First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Tian Liao
- Department of Ultrasound, Changsha Hospital of Traditional Chinese Medicine, Changsha, China
| | - Yinqiao Li
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Lei Huo
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
| | - Ningyang Jia
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
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Chen S, Wan L, Zhao R, Peng W, Liu X, Li L, Zhang H. Nomogram based on preoperative clinical and MRI features to estimate the microvascular invasion status and the prognosis of solitary intrahepatic mass-forming cholangiocarcinoma. Abdom Radiol (NY) 2024; 49:425-436. [PMID: 37889266 DOI: 10.1007/s00261-023-04079-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/28/2023]
Abstract
PURPOSE To develop a nomogram based on preoperative clinical and magnetic resonance imaging (MRI) features for the microvascular invasion (MVI) status in solitary intrahepatic mass-forming cholangiocarcinoma (sIMCC) and to evaluate whether it could predict recurrence-free survival (RFS). METHODS We included 115 cases who experienced MRI examinations for sIMCC with R0 resection. The preoperative clinical and MRI features were extracted. Independent predictors related to MVI+ were evaluated by stepwise multivariate logistic regression, and a nomogram was constructed. A receiver operating characteristic (ROC) curve was used to assess the predictive ability. All patients were classified into high- and low-risk groups of MVI. Then, the correlations of the nomogram with RFS in patents with sIMCC were analyzed by Kaplan-Meier method. RESULTS The occurrence rate of MVI+ was 38.3% (44/115). The preoperative independent predictors of MVI+ were carbohydrate antigen 19-9 > 37 U/ml, tumor size > 5 cm, and an ill-defined tumor boundary. Integrating these predictors, the nomogram exerted a favorable diagnostic performance with areas under the ROC curve of 0.767 (95% confidence interval [CI] 0.654-0.881) in the development cohort, and 0.760 (95% CI 0.591-0.929) in the validation cohort. In the RFS analysis, significant differences were observed between the high- and low-risk MVI groups (6-month RFS rates: 64.5% vs. 78.8% and 46.7% vs. 82.4% in the development and validation cohorts, respectively) (P < 0.05). CONCLUSIONS A nomogram based on clinical and MRI features is a potential biomarker of MVI and may be a potent method to classify the risk of recurrence in patients with sIMCC.
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Affiliation(s)
- Shuang Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China
| | - Lijuan Wan
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China
| | - Rui Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China
| | - Wenjing Peng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China
| | - Xiangchun Liu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China
| | - Lin Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China
| | - Hongmei Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Panjiayuan nanli, Chaoyang district, Beijing, 100021, China.
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Shen K, Mo W, Wang X, Shi D, Qian W, Sun J, Yu R. A convenient scoring system to distinguish intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis based on magnetic resonance imaging features. Eur Radiol 2023; 33:8986-8998. [PMID: 37392232 PMCID: PMC10667410 DOI: 10.1007/s00330-023-09873-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 04/17/2023] [Accepted: 05/10/2023] [Indexed: 07/03/2023]
Abstract
OBJECTIVES To develop and validate a diagnostic scoring system to differentiate intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM). METHODS A total of 366 patients (263 in the training cohort, 103 in the validation cohort) who underwent MRI examination with pathologically proven either IMCC or CRLM from two centers were included. Twenty-eight MRI features were collected. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors for distinguishing IMCC from solitary CRLM. The independent predictors were weighted over based on regression coefficients to build a scoring system. The overall score distribution was divided into three groups to show the diagnostic probability of CRLM. RESULTS Six independent predictors, including hepatic capsular retraction, peripheral hepatic enhancement, vessel penetrating the tumor, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, and rim enhancement at the portal venous phase were included in the system. All predictors were assigned 1 point. At a cutoff of 3 points, AUCs for this score model were 0.948 and 0.903 with sensitivities of 96.5% and 92.0%, specificities of 84.4% and 71.7%, positive predictive values of 87.7% and 75.4%, negative predictive values of 95.4% and 90.5%, and accuracies of 90.9% and 81.6% for the training and validation cohorts, respectively. An increasing trend was shown in the diagnostic probability of CRLM among the three groups based on the score. CONCLUSIONS The established scoring system is reliable and convenient for distinguishing IMCC from solitary CRLM using six MRI features. CLINICAL RELEVANCE STATEMENT A reliable and convenient scoring system was developed to differentiate between intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis using six MRI features. KEY POINTS • Characteristic MRI features were identified to distinguish intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM). • A model to distinguish IMCC from solitary CRLM was created based on 6 features, including hepatic capsular retraction, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, rim enhancement at the portal venous phase, peripheral hepatic enhancement, and vessel penetrating the tumor.
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Affiliation(s)
- Keren Shen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Weixing Mo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Xiaojie Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Dan Shi
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Wei Qian
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Jihong Sun
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China
| | - Risheng Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
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Chen S, Zhu Y, Wan L, Zou S, Zhang H. Predicting the microvascular invasion and tumor grading of intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance imaging radiomics and morphological features. Quant Imaging Med Surg 2023; 13:8079-8093. [PMID: 38106327 PMCID: PMC10722063 DOI: 10.21037/qims-23-11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 09/12/2023] [Indexed: 12/19/2023]
Abstract
Background Preoperative diagnosis of microvascular invasion (MVI) and tumor grading of intrahepatic mass-forming cholangiocarcinoma (IMCC) using imaging findings can facilitate patient treatment decision-making. This study was conducted to establish and validate nomograms based on magnetic resonance imaging (MRI) radiomics and morphological features for predicting the MVI and tumor grading of IMCC before radical hepatectomy. Methods A total of 235 patients with resected IMCC at the Chinese Academy of Medical Sciences and Peking Union Medical College were divided into a training set (n=167) and a validation set (n=68), retrospectively. Clinical data and MRI morphological features were recorded. Univariate and multivariate analyses were conducted to identify the significant features for the prediction of MVI and tumor grading. Radiomics features were extracted from T2-weighted imaging fat-suppressed and diffusion-weighted imaging (DWI). Radiomics signatures (rad_scores) were built based on the least absolute shrinkage and selection operator (LASSO) method. Then, the nomograms were constructed by combining the rad_scores and the significant clinical or MRI morphologic features. The predictive performances for MVI and tumor grading were evaluated by the area under the receiver operating characteristic curve (AUC), calibration, and clinical utility. Results Totals of 16 and 9 radiomics features were selected to build the rad_scores for the prediction of MVI and tumor grading for the training and validation set, respectively. The nomogram for the prediction of MVI comprised the morphologic features including number of tumors, tumor margin, and rad_score. For the prediction of tumor grading, the nomogram comprised the number of tumors, tumor necrosis, and rad_score. The best discriminations were observed in the training and validation sets for the MVI nomogram [AUCs of 0.874, 95% confidence interval (CI): (0.822-0.926) and 0.869 (0.783-0955)] and tumor grading nomogram [AUCs of 0.827 (0.763-0.891) and 0.848 (0.759-0.937)]. Decision curve analysis (DCA) further confirmed the clinical utilities of the nomograms. Conclusions Nomograms based on MRI radiomics and morphological features can effectively predict the individualized risks of MVI and tumor grading for IMCC.
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Affiliation(s)
- Shuang Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yumeng Zhu
- Beijing No. 4 High School International Campus, Beijing, China
| | - Lijuan Wan
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuangmei Zou
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongmei Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Ma X, Qian X, Wang Q, Zhang Y, Zong R, Zhang J, Qian B, Yang C, Lu X, Shi Y. Radiomics nomogram based on optimal VOI of multi-sequence MRI for predicting microvascular invasion in intrahepatic cholangiocarcinoma. LA RADIOLOGIA MEDICA 2023; 128:1296-1309. [PMID: 37679641 PMCID: PMC10620280 DOI: 10.1007/s11547-023-01704-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 08/11/2023] [Indexed: 09/09/2023]
Abstract
OBJECTIVE Microvascular invasion (MVI) is a significant adverse prognostic indicator of intrahepatic cholangiocarcinoma (ICC) and affects the selection of individualized treatment regimens. This study sought to establish a radiomics nomogram based on the optimal VOI of multi-sequence MRI for predicting MVI in ICC tumors. METHODS 160 single ICC lesions with MRI scanning confirmed by postoperative pathology were randomly separated into training and validation cohorts (TC and VC). Multivariate analysis identified independent clinical and imaging MVI predictors. Radiomics features were obtained from images of 6 MRI sequences at 4 different VOIs. The least absolute shrinkage and selection operator algorithm was performed to enable the derivation of robust and effective radiomics features. Then, the best three sequences and the optimal VOI were obtained through comparison. The MVI prediction nomogram combined the independent predictors and optimal radiomics features, and its performance was evaluated via the receiver operating characteristics, calibration, and decision curves. RESULTS Tumor size and intrahepatic ductal dilatation are independent MVI predictors. Radiomics features extracted from the best three sequences (T1WI-D, T1WI, DWI) with VOI10mm (including tumor and 10 mm peritumoral region) showed the best predictive performance, with AUCTC = 0.987 and AUCVC = 0.859. The MVI prediction nomogram obtained excellent prediction efficacy in both TC (AUC = 0.995, 95%CI 0.987-1.000) and VC (AUC = 0.867, 95%CI 0.798-0.921) and its clinical significance was further confirmed by the decision curves. CONCLUSION A nomogram combining tumor size, intrahepatic ductal dilatation, and the radiomics model of MRI multi-sequence fusion at VOI10mm may be a predictor of preoperative MVI status in ICC patients.
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Affiliation(s)
- Xijuan Ma
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, No. 199 Jiefang South Road, Quanshan District, Xuzhou, 221009, Jiangsu, People's Republic of China
| | - Xianling Qian
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
| | - Qing Wang
- Graduate Department, Bengbu Medical College, Bengbu, 233000, Anhui, People's Republic of China
| | - Yunfei Zhang
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
- Central Research Institute, United Imaging Healthcare, No. 2258 Chengbei Rd, Shanghai, 201807, People's Republic of China
| | - Ruilong Zong
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, No. 199 Jiefang South Road, Quanshan District, Xuzhou, 221009, Jiangsu, People's Republic of China
| | - Jia Zhang
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, No. 199 Jiefang South Road, Quanshan District, Xuzhou, 221009, Jiangsu, People's Republic of China
| | - Baoxin Qian
- Huiying Medical Technology, Huiying Medical Technology Co., Ltd, Room A206, B2, Dongsheng Science and Technology Park, Haidian District, Beijing City, 100192, People's Republic of China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China
| | - Xin Lu
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China.
- Department of Cancer Center, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Shanghai, 200032, People's Republic of China.
- Department of Radiology, Shanghai Geriatric Medical Center, No. 2560 Chunshen Rd, Shanghai, 201104, People's Republic of China.
| | - Yibing Shi
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, No. 199 Jiefang South Road, Quanshan District, Xuzhou, 221009, Jiangsu, People's Republic of China.
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Yu L, Dai MG, Lu WF, Wang DD, Ye TW, Xu FQ, Liu SY, Liang L, Feng DJ. Preoperative prediction model for microvascular invasion in HBV-related intrahepatic cholangiocarcinoma. BMC Surg 2023; 23:239. [PMID: 37592274 PMCID: PMC10433593 DOI: 10.1186/s12893-023-02139-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 08/04/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND AND AIMS Preoperative prediction of microvascular invasion (MVI) using a noninvasive method remain unresolved, especially in HBV-related in intrahepatic cholangiocarcinoma (ICC). This study aimed to build and validate a preoperative prediction model for MVI in HBV-related ICC. METHODS Patients with HBV-associated ICC undergoing curative surgical resection were identified. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors of MVI in the training cohort. Then, a prediction model was built by enrolling the independent risk factors. The predictive performance was validated by receiver operator characteristic curve (ROC) and calibration in the validation cohort. RESULTS Consecutive 626 patients were identified and randomly divided into the training (418, 67%) and validation (208, 33%) cohorts. Multivariate analysis showed that TBIL, CA19-9, tumor size, tumor number, and preoperative image lymph node metastasis were independently associated with MVI. Then, a model was built by enrolling former fiver risk factors. In the validation cohort, the performance of this model showed good calibration. The area under the curve was 0.874 (95% CI: 0.765-0.894) and 0.729 (95%CI: 0.706-0.751) in the training and validation cohort, respectively. Decision curve analysis showed an obvious net benefit from the model. CONCLUSION Based on clinical data, an easy model was built for the preoperative prediction of MVI, which can assist clinicians in surgical decision-making and adjuvant therapy.
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Affiliation(s)
- Liang Yu
- Department of Radiology, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Zhejiang, Hangzhou, China
| | - Mu-Gen Dai
- Department of Gastroenterology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
| | - Wen-Feng Lu
- Department of Hepatobiliary Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Medical University, Shanghai, China
| | - Dong-Dong Wang
- Department of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery , General Surgery, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Zhejiang, Hangzhou, China
| | - Tai-Wei Ye
- Department of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery , General Surgery, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Zhejiang, Hangzhou, China
| | - Fei-Qi Xu
- Department of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery , General Surgery, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Zhejiang, Hangzhou, China
| | - Si-Yu Liu
- Department of Gastroenterology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Department of Laboratory Medicine, The Key Laboratory of Imaging Diagnosis and Minimally Invasive Interventional Research of Zhejiang Province, Zhejiang University Lishui Hospital, Lishui, Zhejiang, China
| | - Lei Liang
- Department of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery , General Surgery, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Zhejiang, Hangzhou, China
| | - Du-Jin Feng
- Department of Clinical Laboratory, Laboratory Medicine Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Zhejiang, 310014, Hangzhou, China.
- Department of Laboratory Medicine Center, Zhejiang Center for Clinical Laboratories, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
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Jiang C, Yuan Y, Gu B, Ahn E, Kim J, Feng D, Huang Q, Song S. Preoperative prediction of microvascular invasion and perineural invasion in pancreatic ductal adenocarcinoma with 18F-FDG PET/CT radiomics analysis. Clin Radiol 2023:S0009-9260(23)00219-2. [PMID: 37365115 DOI: 10.1016/j.crad.2023.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 04/23/2023] [Accepted: 05/13/2023] [Indexed: 06/28/2023]
Abstract
AIM To develop and validate a predictive model based on 2-[18F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron-emission tomography (PET)/computed tomography (CT) radiomics features and clinicopathological parameters to preoperatively identify microvascular invasion (MVI) and perineural invasion (PNI), which are important predictors of poor prognosis in patients with pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS Preoperative 18F-FDG PET/CT images and clinicopathological parameters of 170 patients in PDAC were collected retrospectively. The whole tumour and its peritumoural variants (tumour dilated with 3, 5, and 10 mm pixels) were applied to add tumour periphery information. A feature-selection algorithm was employed to mine mono-modality and fused feature subsets, then conducted binary classification using gradient boosted decision trees. RESULTS For MVI prediction, the model performed best on a fused subset of 18F-FDG PET/CT radiomics features and two clinicopathological parameters, with an area under the receiver operating characteristic curve (AUC) of 83.08%, accuracy of 78.82%, recall of 75.08%, precision of 75.5%, and F1-score of 74.59%. For PNI prediction, the model achieved best prediction results only on the subset of PET/CT radiomics features, with AUC of 94%, accuracy of 89.33%, recall of 90%, precision of 87.81%, and F1 score of 88.35%. In both models, 3 mm dilation on the tumour volume produced the best results. CONCLUSIONS The radiomics predictors from preoperative 18F-FDG PET/CT imaging exhibited instructive predictive efficacy in the identification of MVI and PNI status preoperatively in PDAC. Peritumoural information was shown to assist in MVI and PNI predictions.
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Affiliation(s)
- C Jiang
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China; Department of Nuclear Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Y Yuan
- Biomedical and Multimedia Information Technology Research Group, School of Computer Science, University of Sydney, Sydney, Australia
| | - B Gu
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - E Ahn
- Discipline of Information Technology, College of Science & Engineering, James Cook University, Australia
| | - J Kim
- Biomedical and Multimedia Information Technology Research Group, School of Computer Science, University of Sydney, Sydney, Australia
| | - D Feng
- Biomedical and Multimedia Information Technology Research Group, School of Computer Science, University of Sydney, Sydney, Australia
| | - Q Huang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
| | - S Song
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.
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Zhang J, Dong W, Li Y, Fu J, Jia N. Prediction of microvascular invasion in combined hepatocellular-cholangiocarcinoma based on preoperative contrast-enhanced CT and clinical data. Eur J Radiol 2023; 163:110839. [PMID: 37121101 DOI: 10.1016/j.ejrad.2023.110839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/11/2023] [Accepted: 04/14/2023] [Indexed: 05/02/2023]
Abstract
OBJECTIVE Microvascular invasion (MVI) is significantly associated with prognosis in combined hepatocellular-cholangiocarcinoma (cHCC-CCA) patients. The study aimed to explore the value of preoperative contrast-enhanced CT (CECT) features and clinical data in predicting MVI of cHCC-CCA. METHODS A total of 33 patients with MVI-positive and 27 with MVI-negative were enrolled, and underwent preoperative CECT imaging from January 2016 to December 2021. Preoperative clinical data and CECT imaging features were retrospectively analyzed. Univariable and multivariable logistic regression analysis were performed to identify potential predictors of MVI in cHCC-CCA. The diagnostic performance was evaluated by the receiver operating characteristic (ROC) curve and its area under the curve (AUC) value. RESULTS The mean age of the patients was 54.0 ± 10.3 years, and 53 of the 60 patients (88.3%) were male. Preoperative imaging features on CECT (non-smooth contour and arterial phase peritumoral enhancement) and clinical data (hepatitis B virus (HBV) infection and protein induced by vitamin K absence or antagonist-II (PIVKA-II)) were highly distinct between those in MVI-positive group and MVI-negative group. On multivariable logistic analysis, arterial phase peritumoral enhancement (odds ratio (OR), 6.514; 95% confidence interval (CI), 1.588-26.728, p = 0.012) and high serum PIVKA-II level (OR, 6.810; 95% CI, 1.796-25.820, p = 0.005) were independent predictors associated with MVI of cHCC-CCA. The combination of these two predictors had high sensitivity (31/33, 93.9%; 95% CI, 80.4% - 98.3%) in the prediction of MVI with an area under the receiver operating characteristic (ROC) curve of 0.763 (95% CI, 0.635-0.863). CONCLUSIONS The findings indicated that arterial phase peritumoral enhancement on preoperative CECT and high serum PIVKA-II level were identified as potential predictors for MVI in cHCC-CCA patients.
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Affiliation(s)
- Juan Zhang
- Department of Radiology, Eastern Hepatobilliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai 200438, China
| | - Wei Dong
- Department of Pathology, Eastern Hepatobilliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai 200438, China
| | - Yinqiao Li
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Jiazhao Fu
- Department of Organ Transplantation, Changhai Hospital, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China.
| | - Ningyang Jia
- Department of Radiology, Eastern Hepatobilliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai 200438, China.
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10
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Chen S, Wan L, Zhao R, Peng W, Li Z, Zou S, Zhang H. Predictive factors of microvascular invasion in patients with intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance images. Abdom Radiol (NY) 2023; 48:1306-1319. [PMID: 36872324 DOI: 10.1007/s00261-023-03847-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 03/07/2023]
Abstract
PURPOSE The aim of this retrospective study was to develop and validate a preoperative nomogram for predicting microvascular invasion (MVI) in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) based on magnetic resonance imaging (MRI). METHODS In this retrospective study, 224 consecutive patients with clinicopathologically confirmed IMCC were enrolled. Patients whose data were collected from February 2010 to December 2020 were randomly divided into the training (131 patients) and internal validation (51 patients) datasets. The data from January 2021 to November 2021 (42 patients) were allocated to the time-independent validation dataset. Univariate and multivariate forward logistic regression analyses were used to identify preoperative MRI features that were significantly related to MVI, which were then used to develop the nomogram. We used the area under the receiver operating characteristic curve (AUC) and calibration curve to evaluate the performance of the nomogram. RESULTS Interobserver agreement of MRI qualitative features was good to excellent, with κ values of 0.613-0.882. Multivariate analyses indicated that the following variables were independent predictors of MVI: multiple tumours (odds ratio [OR]) = 4.819, 95% confidence interval [CI] 1.562-14.864, P = 0.006), ill-defined margin (OR = 6.922, 95% CI 2.883-16.633, P < 0.001), and carbohydrate antigen 19-9 (CA 19-9) > 37 U/ml (OR = 2.890, 95% CI 1.211-6.897, P = 0.017). A nomogram incorporating these factors was established using well-fitted calibration curves. The nomogram showed good diagnostic efficacy for MVI, with AUC values of 0.838, 0.819, and 0.874 for the training, internal validation, and time-independent validation datasets, respectively. CONCLUSION A nomogram constructed using independent factors, namely the presence of multiple tumours, ill-defined margins, and CA 19-9 > 37 U/ml could predict the presence of MVI. This can facilitate personalised therapeutic strategy and clinical management in patients with IMCC.
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Affiliation(s)
- Shuang Chen
- Department of Diagnostic Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Lijuan Wan
- Department of Diagnostic Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Rui Zhao
- Department of Diagnostic Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Wenjing Peng
- Department of Diagnostic Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Zhuo Li
- Department of Pathology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
| | - Shuangmei Zou
- Department of Pathology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
| | - Hongmei Zhang
- Department of Diagnostic Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
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11
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A Bayesian Network Prediction Model for Microvascular Invasion in Patients with Intrahepatic Cholangiocarcinoma: A Multi-institutional Study. World J Surg 2023; 47:773-784. [PMID: 36607391 DOI: 10.1007/s00268-022-06867-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2022] [Indexed: 01/07/2023]
Abstract
BACKGROUND Microvascular invasion (MVI) has been reported to be an independent prognostic factor of recurrence and poor overall survival in patients with intrahepatic cholangiocarcinoma (ICC). This study aimed to explore the preoperative independent risk factors of MVI and establish a Bayesian network (BN) prediction model to provide a reference for surgical diagnosis and treatment. METHODS A total of 531 patients with ICC who underwent radical resection between 2010 and 2018 were used to establish and validate a BN model for MVI. The BN model was established based on the preoperative independent variables. The ROC curves and confusion matrix were used to assess the performance of the model. RESULTS MVI was an independent risk factor for relapse-free survival (RFS) (P < 0.05). MVI has a correlation with postoperative recurrence, early recurrence (< 6 months), median RFS and median overall survival (all P < 0.05). The preoperative independent risk variables of MVI included obstructive jaundice, prognostic nutritional index, CA19-9, tumor size, and major vascular invasion, which were used to establish the BN model. The AUC of the BN model was 78.92% and 83.01%, and the accuracy was 70.85% and 77.06% in the training set and testing set, respectively. CONCLUSION The BN model established based on five independent risk variables for MVI is an effective and practical model for predicting MVI in patients with ICC.
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12
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Chen P, Yang Z, Zhang H, Huang G, Li Q, Ning P, Yu H. Personalized intrahepatic cholangiocarcinoma prognosis prediction using radiomics: Application and development trend. Front Oncol 2023; 13:1133867. [PMID: 37035147 PMCID: PMC10076873 DOI: 10.3389/fonc.2023.1133867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 03/13/2023] [Indexed: 04/11/2023] Open
Abstract
Radiomics was proposed by Lambin et al. in 2012 and since then there has been an explosion of related research. There has been significant interest in developing high-throughput methods that can automatically extract a large number of quantitative image features from medical images for better diagnostic or predictive performance. There have also been numerous radiomics investigations on intrahepatic cholangiocarcinoma in recent years, but no pertinent review materials are readily available. This work discusses the modeling analysis of radiomics for the prediction of lymph node metastasis, microvascular invasion, and early recurrence of intrahepatic cholangiocarcinoma, as well as the use of deep learning. This paper briefly reviews the current status of radiomics research to provide a reference for future studies.
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Affiliation(s)
- Pengyu Chen
- Department of Hepatobiliary Surgery, Henan University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Zhenwei Yang
- Department of Hepatobiliary Surgery, Henan University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Haofeng Zhang
- Department of Hepatobiliary Surgery, People’s Hospital of Zhengzhou University, Zhengzhou, China
| | - Guan Huang
- Department of Hepatobiliary Surgery, People’s Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingshan Li
- Department of Hepatobiliary Surgery, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Peigang Ning
- Department of Radiology, People’s Hospital of Zhengzhou University, Zhengzhou, China
| | - Haibo Yu
- Department of Hepatobiliary Surgery, Henan University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
- Department of Hepatobiliary Surgery, People’s Hospital of Zhengzhou University, Zhengzhou, China
- Department of Hepatobiliary Surgery, Henan Provincial People’s Hospital, Zhengzhou, China
- *Correspondence: Haibo Yu,
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13
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Chen Y, Lu Q, Zhu Y, Huang B, Dong Y, Wang W. Prediction of Microvascular Invasion in Combined Hepatocellular-Cholangiocarcinoma Based on Pre-operative Clinical Data and Contrast-Enhanced Ultrasound Characteristics. ULTRASOUND IN MEDICINE & BIOLOGY 2022; 48:1190-1201. [PMID: 35397928 DOI: 10.1016/j.ultrasmedbio.2022.02.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 01/27/2022] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
The goal of the study described here was to define the predictive value of pre-operative clinical information and contrast-enhanced ultrasound (CEUS) imaging characteristics in combined hepatocellular-cholangiocarcinoma (CHC) patients with microvascular invasion (MVI). Seventy-six patients with pathologically confirmed CHC were enrolled in this study, comprising 18 patients with MVI-positive status and 58 with MVI-negative CHC nodules. The pre-operative clinical data and CEUS imaging features were retrospectively analyzed. Univariate and multivariate analyses were performed to identify the potential predictors of MVI in CHC. Recurrence-free survival (RFS) after hepatectomy was compared between patients with different MVI status using the log-rank test and Kaplan-Meier survival curves. Univariate analysis indicated that the following parameters of patients with CHC significantly differed between the MVI-positive and MVI-negative groups (p<0.05): tumor size, α-fetoprotein ≥400 ng/mL, enhancement patterns in arterial phase and marked washout during the portal venous phase on CEUS. On multivariate logistic regression analysis, only the CEUS characteristics of heterogeneous enhancement (odds ratio = 6.807; 95% confidence interval [CI]: 1.099, 42.147; p = 0.039) and marked washout (odds ratio = 4.380; 95% CI: 1.050,18.270; p = 0.043) were identified as independent predictors of MVI in CHC. The combination of the two risk factors in predicting MVI achieved a better diagnostic performance than each parameter alone, with an area under the receiver operating characteristic curve of 0.736 (0.622, 0.830). After hepatectomy, CHC patients with MVI exhibited earlier recurrence compared with those without MVI (hazard ratio = 1.859; 95% CI: 0.8699-3.9722, p = 0.046). The CEUS imaging features of heterogeneous enhancement in the arterial phase and marked washout during the portal venous phase were the potential predictors of MVI in CHC. Aside from that, CHC patients with MVI had an earlier recurrence rate than those without MVI after surgery.
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Affiliation(s)
- Yanling Chen
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qing Lu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuli Zhu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Beijian Huang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Institute of Ultrasound Medicine and Engineering, Fudan University, Shanghai, China
| | - Yi Dong
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Wenping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Institute of Ultrasound Medicine and Engineering, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
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14
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Xing LH, Zhuo LY, Wang JN, Zhang Y, Zhu FY, Wang C, Yin XP, Gao BL. Values of MRI Imaging Presentations in the Hepatobiliary Phase, DWI and T2WI Sequences in Predicting Pathological Grades of Intrahepatic Mass-Forming Cholangiocarcinoma. Front Oncol 2022; 12:867702. [PMID: 35747789 PMCID: PMC9209728 DOI: 10.3389/fonc.2022.867702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/18/2022] [Indexed: 11/16/2022] Open
Abstract
Objective To retrospectively investigate the value of various MRI image menifestations in the hepatobiliary phase (HBP), DWI and T2WI sequences in predicting the pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC). Materials and Methods Forty-three patients of IMCCs confirmed by pathology were enrolled including 25 cases in well- or moderately-differentiated group and 18 cases in poorly-differentiated group. All patients underwent DWI, T2WI and HBP scan. The Chi square test was used to compare the differences in the general information. Logistic regression analysis was used to analyze the risk factors in predicting the pathological grade of IMCCs. Results The maximal diameter of the IMCC lesion was < 3 cm in 11 patients, between 3 cm and 6 cm in 15, and > 6 cm in 17. Sixteen cases had intrahepatic metastasis, including 5 in the well- or moderately-differentiated group and 11 in the poorly-differentiated group. Seventeen (39.5%) patients presented with target signs in the DWI sequence, including 9 in the well- or moderately-differentiated group and 8 in the poorly-differentiated group. Twenty (46.5%) patients presented with target signs in the T2WI sequence, including 8 in the well- or moderately-differentiated group and 12 in the poorly-differentiated group. Nineteen cases (54.3%) had a complete hypointense signal ring, including 13 in the well- or moderately-differentiated group and 6 in the poorly-differentiated group. Sixteen (45.7%) cases had an incomplete hypointense signal ring, including 5 in the well- or moderately-differentiated group and 11 in the poorly-differentiated group. The lesion size, intrahepatic metastasis, T2WI signal, and integrity of a hypointense signal ring in HBP were statistically significantly different between two gourps. T2WI signal, presence or non-presence of intrahepatic metastasis, and integrity of hypointense signal ring were the independent influencing factors for pathological grade of IMCC. Conclusion Target sign in T2WI sequence, presence of intrahepatic metastasis and an incomplete hypointense-signal ring in HBP are more likely to be present in poorly-differentiated IMCCs.
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Affiliation(s)
- Li-Hong Xing
- Affiliated Hospital of Hebei University/ School of Clinical Medicine of Hebei University, Baoding, China
| | - Li-Yong Zhuo
- Computed Tomography (CT)/Magnetic Resonance Imaging (MRI) Room, Affiliated Hospital of Hebei University, Baoding, China
| | - Jia-Ning Wang
- Computed Tomography (CT)/Magnetic Resonance Imaging (MRI) Room, Affiliated Hospital of Hebei University, Baoding, China
| | - Yan Zhang
- Department of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, China
| | - Feng-Ying Zhu
- Computed Tomography (CT)/Magnetic Resonance Imaging (MRI) Room, Affiliated Hospital of Hebei University, Baoding, China
| | - Chu Wang
- Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China
| | - Xiao-Ping Yin
- Computed Tomography (CT)/Magnetic Resonance Imaging (MRI) Room, Affiliated Hospital of Hebei University, Baoding, China
- *Correspondence: Xiao-Ping Yin, ;
| | - Bu-Lang Gao
- Computed Tomography (CT)/Magnetic Resonance Imaging (MRI) Room, Affiliated Hospital of Hebei University, Baoding, China
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15
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Aung TM, Ciin MN, Silsirivanit A, Jusakul A, Lert-Itthiporn W, Proungvitaya T, Roytrakul S, Proungvitaya S. Serum Angiopoietin-Like Protein 4: A Potential Prognostic Biomarker for Prediction of Vascular Invasion and Lymph Node Metastasis in Cholangiocarcinoma Patients. Front Public Health 2022; 10:836985. [PMID: 35392474 PMCID: PMC8980351 DOI: 10.3389/fpubh.2022.836985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 02/23/2022] [Indexed: 11/26/2022] Open
Abstract
Cholangiocarcinoma (CCA) is a tumor arising from cholangiocytes lining the bile ducts. Vascular invasion and lymph node metastasis are important prognostic factors for disease staging as well as clinical therapeutic decisions for CCA patients. In the present study, we applied CCA sera proteomic analysis to identify a potential biomarker for prognosis of CCA patients. Then, using bioinformatics tools, we identified angiopoietin-like protein 4 (ANGPTL4) which expressed highest signal intensity among candidate proteins in proteomic analysis of CCA sera. Expression of ANGPTL4 in CCA tissues was determined using immunohistochemistry. The results showed that ANGPTL4 was stained at higher level in CCA cells when compared with normal cholangiocytes. The high expression of ANGPTL4 was associated with lymph node metastasis and advanced tumor stage (p = 0.013 and p = 0.031, respectively). Furthermore, serum ANGPTL4 levels in CCA and healthy control (HC) were analyzed using a dot blot assay. And it was found that ANGPTL4 level was significantly higher in CCA than HC group (p < 0.0001). ROC curve analysis revealed that serum ANGPTL4 level was effectively distinguished CCA from healthy patients (cutoff = 0.2697 arbitrary unit (AU), 80.0% sensitivity, 72.7% specificity, AUC = 0.825, p < 0.0001). Serum ANGPTL4 level was associated with vascular invasion and lymph node metastasis (p = 0.0004 and p = 0.006), so that it differentiated CCA with vascular invasion from CCA without vascular invasion (cutoff = 0.5526 AU, 64.9% sensitivity, 92.9% specificity, AUC = 0.751, p = 0.006) and it corresponded to CCA with/without lymph node metastasis (cutoff = 0.5399 AU, 71.4% sensitivity, 70.8% specificity, AUC = 0.691, p = 0.01) by ROC analysis. Serum ANGPTL4 levels showed superior predictive efficiency compared with CA 19-9 and CEA for vascular invasion and lymph node metastasis. In addition, serum ANGPTL4 level was an independent predictive indicator by multivariate regression analysis. In conclusion, serum ANGPTL4 could be a novel prognostic biomarker for prediction of vascular invasion and lymph node metastasis of CCA patients.
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Affiliation(s)
- Tin May Aung
- Faculty of Associated Medical Sciences, Centre of Research and Development of Medical Diagnostic Laboratories (CMDL), Khon Kaen University, Khon Kaen, Thailand
| | - Mang Ngaih Ciin
- Faculty of Associated Medical Sciences, Centre of Research and Development of Medical Diagnostic Laboratories (CMDL), Khon Kaen University, Khon Kaen, Thailand
| | - Atit Silsirivanit
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand.,Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Apinya Jusakul
- Faculty of Associated Medical Sciences, Centre of Research and Development of Medical Diagnostic Laboratories (CMDL), Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
| | - Worachart Lert-Itthiporn
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand.,Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Tanakorn Proungvitaya
- Faculty of Associated Medical Sciences, Centre of Research and Development of Medical Diagnostic Laboratories (CMDL), Khon Kaen University, Khon Kaen, Thailand
| | - Sittiruk Roytrakul
- Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Siriporn Proungvitaya
- Faculty of Associated Medical Sciences, Centre of Research and Development of Medical Diagnostic Laboratories (CMDL), Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
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16
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Qian X, Lu X, Ma X, Zhang Y, Zhou C, Wang F, Shi Y, Zeng M. A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma. Front Oncol 2022; 12:838701. [PMID: 35280821 PMCID: PMC8907475 DOI: 10.3389/fonc.2022.838701] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 01/24/2022] [Indexed: 02/06/2023] Open
Abstract
Background Intrahepatic 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. Purpose This study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively. Methods A 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. Results Larger 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. Conclusion The 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.
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Affiliation(s)
- Xianling Qian
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xin Lu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xijuan Ma
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Ying Zhang
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Changwu Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fang Wang
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Yibing Shi
- Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
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17
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Gao W, Wang W, Song D, Wang K, Lian D, Yang C, Zhu K, Zheng J, Zeng M, Rao S, Wang M. A
Multiparametric
Fusion Deep Learning Model Based on
DCE‐MRI
for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma. J Magn Reson Imaging 2022; 56:1029-1039. [PMID: 35191550 DOI: 10.1002/jmri.28126] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 02/11/2022] [Accepted: 02/11/2022] [Indexed: 12/22/2022] Open
Affiliation(s)
- Wenyu Gao
- Digital Medical Research Center School of Basic Medical Sciences, Fudan University Shanghai 200032 China
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention Shanghai 200032 China
| | - Wentao Wang
- Department of Radiology Cancer center, Zhongshan Hospital, Fudan University China
- Shanghai Institute of Medical Imaging Shanghai China
| | - Danjun Song
- Liver Cancer Institute, Zhongshan Hospital, Fudan University Shanghai China
- Department of Interventional Radiology Zhejiang Cancer Hospital Hangzhou Zhejiang China
| | - Kang Wang
- Digital Medical Research Center School of Basic Medical Sciences, Fudan University Shanghai 200032 China
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention Shanghai 200032 China
| | - Danlan Lian
- Department of Radiology Xiamen Branch, Zhongshan Hospital, Fudan University Xiamen China
| | - Chun Yang
- Department of Radiology Cancer center, Zhongshan Hospital, Fudan University China
| | - Kai Zhu
- Liver Cancer Institute, Zhongshan Hospital, Fudan University Shanghai China
| | - Jiaping Zheng
- Department of Interventional Radiology Zhejiang Cancer Hospital Hangzhou Zhejiang China
| | - Mengsu Zeng
- Department of Radiology Cancer center, Zhongshan Hospital, Fudan University China
- Shanghai Institute of Medical Imaging Shanghai China
| | - Sheng‐xiang Rao
- Department of Radiology Cancer center, Zhongshan Hospital, Fudan University China
- Shanghai Institute of Medical Imaging Shanghai China
| | - Manning Wang
- Digital Medical Research Center School of Basic Medical Sciences, Fudan University Shanghai 200032 China
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention Shanghai 200032 China
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18
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Xiang F, Wei S, Liu X, Liang X, Yang L, Yan S. Radiomics Analysis of Contrast-Enhanced CT for the Preoperative Prediction of Microvascular Invasion in Mass-Forming Intrahepatic Cholangiocarcinoma. Front Oncol 2021; 11:774117. [PMID: 34869018 PMCID: PMC8640186 DOI: 10.3389/fonc.2021.774117] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 11/02/2021] [Indexed: 12/13/2022] Open
Abstract
Background Microvascular invasion (MVI) has been shown to be closely associated with postoperative recurrence and metastasis in patients with intrahepatic cholangiocarcinoma (ICC). We aimed to develop a radiomics prediction model based on contrast-enhanced CT (CECT) to distinguish MVI in patients with mass-forming ICC. Methods 157 patients were included and randomly divided into training (n=110) and test (n=47) datasets. Radiomic signatures were built based on the recursive feature elimination support vector machine (Rfe-SVM) algorithm. Significant clinical-radiologic factors were screened, and a clinical model was built by multivariate logistic regression. A nomogram was developed by integrating radiomics signature and the significant clinical risk factors. Results The portal phase image radiomics signature with 6 features was constructed and provided an area under the receiver operating characteristic curve (AUC) of 0.804 in the training and 0.769 in the test datasets. Three significant predictors, including satellite nodules (odds ratio [OR]=13.73), arterial hypo-enhancement (OR=4.31), and tumor contour (OR=4.99), were identified by multivariate analysis. The clinical model using these predictors exhibited an AUC of 0.822 in the training and 0.756 in the test datasets. The nomogram combining significant clinical factors and radiomics signature achieved satisfactory prediction efficacy, showing an AUC of 0.886 in the training and 0.80 in the test datasets. Conclusions Both CECT radiomics analysis and radiologic factors have the potential for MVI prediction in mass-forming ICC patients. The nomogram can further improve the prediction efficacy.
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Affiliation(s)
- Fei Xiang
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shumei Wei
- Department of Pathology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xingyu Liu
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoyuan Liang
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lili Yang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Sheng Yan
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Chen Y, Liu H, Zhang J, Wu Y, Zhou W, Cheng Z, Lou J, Zheng S, Bi X, Wang J, Guo W, Li F, Wang J, Zheng Y, Li J, Cheng S, Zeng Y, Liu J. Prognostic value and predication model of microvascular invasion in patients with intrahepatic cholangiocarcinoma: a multicenter study from China. BMC Cancer 2021; 21:1299. [PMID: 34863147 PMCID: PMC8645153 DOI: 10.1186/s12885-021-09035-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 11/16/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND At present, hepatectomy is still the most common and effective treatment method for intrahepatic cholangiocarcinoma (ICC) patients. However, the postoperative prognosis is poor. Therefore, the prognostic factors for these patients require further exploration. Whether microvascular invasion (MVI) plays a crucial role in the prognosis of ICC patients is still unclear. Moreover, few studies have focused on preoperative predictions of MVI in ICC patients. METHODS Clinicopathological data of 704 ICC patients after curative resection were retrospectively collected from 13 hospitals. Independent risk factors were identified by the Cox or logistic proportional hazards model. In addition, the survival curves of the MVI-positive and MVI-negative groups before and after matching were analyzed. Subsequently, 341 patients from a single center (Eastern Hepatobiliary Hospital) in the above multicenter retrospective cohort were used to construct a nomogram prediction model. Then, the model was evaluated by the index of concordance (C-Index) and the calibration curve. RESULTS After propensity score matching (PSM), Child-Pugh grade and MVI were independent risk factors for overall survival (OS) in ICC patients after curative resection. Major hepatectomy and MVI were independent risk factors for recurrence-free survival (RFS). The survival curves of OS and RFS before and after PSM in the MVI-positive groups were significantly different compared with those in the MVI-negative groups. Multivariate logistic regression results demonstrated that age, gamma-glutamyl transpeptidase (GGT), and preoperative image tumor number were independent risk factors for the occurrence of MVI. Furthermore, the prediction model in the form of a nomogram was constructed, which showed good prediction ability for both the training (C-index = 0.7622) and validation (C-index = 0.7591) groups, and the calibration curve showed good consistency with reality. CONCLUSION MVI is an independent risk factor for the prognosis of ICC patients after curative resection. Age, GGT, and preoperative image tumor number were independent risk factors for the occurrence of MVI in ICC patients. The prediction model constructed further showed good predictive ability in both the training and validation groups with good consistency with reality.
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Affiliation(s)
- Yifan Chen
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, 350025, Fujian Province, People's Republic of China
| | - Hongzhi Liu
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, 350025, Fujian Province, People's Republic of China
| | - Jinyu Zhang
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, 350025, Fujian Province, People's Republic of China
| | - Yijun Wu
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, 350025, Fujian Province, People's Republic of China
| | - Weiping Zhou
- Department of Hepatobiliary Surgery III, Eastern Hepatobiliary Surgery Hospital, Secondary Military Medical University, Shanghai, China
| | - Zhangjun Cheng
- Department of Hepatobiliary Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China
| | - Jianying Lou
- Department of Hepatobiliary Surgery, The Second Hospital Affiliated to Zhejiang University, Hangzhou, China
| | - Shuguo Zheng
- Department of Hepatobiliary Surgery, The Southwest Hospital Affiliated to the Army Medical University, Chongqing, China
| | - Xinyu Bi
- Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Jianming Wang
- Department of Hepatobiliary Surgery, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science & Technology, Wuhan, China
| | - Wei Guo
- Department of Hepatobiliary Surgery, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing, China
| | - Fuyu Li
- Department of Hepatobiliary Surgery, The West China Hospital of Sichuan University, Chengdu, China
| | - Jian Wang
- Department of Hepatobiliary Surgery, Renji Hospital Affiliated to Shanghai Jiaotong University, Shanghai, China
| | - Yamin Zheng
- Department of Hepatobiliary Surgery, Xuanwu Hospital Affiliated to Capital Medical University, Beijing, China
| | - Jingdong Li
- Department of Hepatobiliary Surgery, The Affiliated Hospital of Chuanbei Medical University, Nanchong, China
| | - Shi Cheng
- Department of Hepatobiliary Surgery, Tiantan Hospital Affiliated to Capital Medical University, Beijing, China
| | - Yongyi Zeng
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, 350025, Fujian Province, People's Republic of China. .,Liver Diseases Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
| | - Jingfeng Liu
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, 350025, Fujian Province, People's Republic of China.
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Li Q, Che F, Wei Y, Jiang HY, Zhang Y, Song B. Role of noninvasive imaging in the evaluation of intrahepatic cholangiocarcinoma: from diagnosis and prognosis to treatment response. Expert Rev Gastroenterol Hepatol 2021; 15:1267-1279. [PMID: 34452581 DOI: 10.1080/17474124.2021.1974294] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Intrahepatic cholangiocarcinoma is the second most common liver cancer. Desmoplastic stroma may be revealed as distinctive histopathologic findings favoring intrahepatic cholangiocarcinoma. Meanwhile, a range of imaging manifestations is often accompanied with rich desmoplastic stroma in intrahepatic cholangiocarcinoma, which can indicate large bile duct ICC, and a higher level of cancer-associated fibroblasts with poor prognosis and weak treatment response. AREAS COVERED We provide a comprehensive review of current state-of-the-art and recent advances in the imaging evaluation for diagnosis, staging, prognosis and treatment response of intrahepatic cholangiocarcinoma. In addition, we discuss precursor lesions, cells of origin, molecular mutation, which would cause the different histological classification. Moreover, histological classification and tumor microenvironment, which are related to the proportion of desmoplastic stroma with many imaging manifestations, would be also discussed. EXPERT OPINION The diagnosis, prognosis, treatment response of intrahepatic cholangiocarcinoma may be revealed as the presence and the proportion of desmoplastic stroma with a range of imaging manifestations. With the utility of radiomics and artificial intelligence, imaging is helpful for ICC evaluation. Multicentre, large-scale, prospective studies with external validation are in need to develop comprehensive prediction models based on clinical data, imaging findings, genetic parameters, molecular, metabolic, and immune biomarkers.
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Affiliation(s)
- Qian Li
- Department of Radiology, Sichuan University West China Hospital, Chengdu, China
| | - Feng Che
- Department of Radiology, Sichuan University West China Hospital, Chengdu, China
| | - Yi Wei
- Department of Radiology, Sichuan University West China Hospital, Chengdu, China
| | - Han-Yu Jiang
- Department of Radiology, Sichuan University West China Hospital, Chengdu, China
| | - Yun Zhang
- Department of Radiology, Sichuan University West China Hospital, Chengdu, China
| | - Bin Song
- Department of Radiology, Sichuan University West China Hospital, Chengdu, China
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21
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Alikhanov R, Dudareva A, Trigo MÁ, Serrablo A. Vascular Resection for Intrahepatic Cholangiocarcinoma: Current Considerations. J Clin Med 2021; 10:jcm10173829. [PMID: 34501276 PMCID: PMC8432051 DOI: 10.3390/jcm10173829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 08/23/2021] [Accepted: 08/23/2021] [Indexed: 11/16/2022] Open
Abstract
Intrahepatic cholangiocarcinoma (iCCA) accounts for approximately 10% of all primary liver cancers. Surgery is the only potentially curative treatment, even in cases of macrovascular invasion. Since resection offers the only curative chance, even extended liver resection combined with complex vascular or biliary reconstruction of the surrounding organs seems justified to achieve complete tumour removal. In selected cases, the major vascular resection is the only change to try getting the cure. The best results are achieved by the referral centre with a wide experience in complex liver surgery, such as ALPPS procedure, IVC resection, and ante-situ and ex-situ resections. However, despite aggressive surgery, tumour recurrence occurs frequently and long-term oncological results are very poor. This suggests that significant progress in prognosis cannot be expected by surgery alone. Instead, multimodal treatment including neoadjuvant chemotherapy, radiotherapy, and subsequent adjuvant treatment for iCCA seem to be necessary to improve results.
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Affiliation(s)
- Ruslan Alikhanov
- Department of Liver and Pancreatic Surgery, Department of Transplantation, Moscow Clinical Scientific Centre, 111123 Moscow, Russia;
| | - Anna Dudareva
- Department of Vascular Surgery, Moscow Clinical Scientific Centre, 111123 Moscow, Russia;
| | - Miguel Ángel Trigo
- Department of Pathology, Miguel Servet University Hospital, 50009 Zaragoza, Spain;
| | - Alejandro Serrablo
- HPB Surgical Division, Miguel Servet University Hospital, 50009 Zaragoza, Spain
- Correspondence:
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22
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Zhou C, Wang Y, Ma L, Qian X, Yang C, Zeng M. Combined hepatocellular carcinoma-cholangiocarcinoma: MRI features correlated with tumor biomarkers and prognosis. Eur Radiol 2021; 32:78-88. [PMID: 34279688 DOI: 10.1007/s00330-021-08188-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES To determine how MRI features are correlated to biomarkers, and to the prognostic factors for recurrence-free survival (RFS) and overall survival (OS) in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) patients. METHODS The study enrolled 160 cHCC-CCA patients pathologically confirmed according to the 2019 WHO classification. The preoperative MRI features and clinical data were retrospectively evaluated and compared between patients grouped by AFP or CA19-9 level and with pathological findings. The RFS and OS of cHCC-CCA patients were estimated using Kaplan-Meier survival curves and compared using the log-rank test. Moreover, predictors of RFS and OS were investigated using Cox regression analyses. RESULTS One hundred and sixty patients (mean age, males vs. females: 55.7 ± 10.2 years vs. 54.9 ± 14.0 years) were evaluated. The incidence of nodule-in-nodule architecture, mosaic architecture, intratumoral hemorrhage, hepatic capsule retraction, arterial phase peritumoral enhancement, and portal vein thrombus was significantly higher in patients with AFP > 20 ng/ml (all p < 0.05). Multivariate Cox regression analysis indicated that age (HR 1.031, p = 0.03), CA19-9 > 37 U/ml (HR 1.880, p = 0.04), arterial phase peritumoral enhancement (HR 2.287, p = 0.01), and delayed enhancement (HR 0.377, p = 0.02) were independent predictors of poor RFS, while arterial phase peripheral enhancement (HR 2.391, p = 0.04) was an independent predictor of poor OS. CONCLUSIONS cHCC-CCA imaging features are complex and not correlated with AFP or CA19-9. Age, CA19-9 > 37 U/ml, arterial phase peritumoral enhancement, and delayed enhancement are independent predictors of poor RFS. Arterial phase peripheral enhancement is an independent predictor of poor OS. KEY POINTS • The imaging features of combined hepatocellular carcinoma-cholangiocarcinoma are complex and are not correlated with the alpha fetoprotein or CA19-9 levels. • Age, CA19-9 > 37 U/ml, arterial phase peritumoral enhancement, and delayed enhancement are independent predictors of poor recurrence-free survival in combined hepatocellular carcinoma-cholangiocarcinoma patients. • Arterial phase peripheral enhancement is an independent predictor of poor overall survival in patients with combined hepatocellular carcinoma-cholangiocarcinoma.
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Affiliation(s)
- Changwu Zhou
- Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Yi Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Li Ma
- Shanghai Institute of Medical Imaging, Shanghai, China
| | - Xianling Qian
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Shanghai, China. .,Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
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Zhang HM, Wen DG, Wang Y, Bao YG, Yuan Y, Chen YT, Song B. Arterial Spin Labeling MRI for Predicting Microvascular Invasion of T1 Staging Renal Clear Cell Carcinoma Preoperatively. Front Oncol 2021; 11:644975. [PMID: 34084743 PMCID: PMC8168533 DOI: 10.3389/fonc.2021.644975] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/09/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a valuable factor for T1 staging renal clear cell carcinoma (ccRCC) operation strategy decision, which is confirmed histopathologically post-operation. This study aimed to prospectively evaluate the performance of arterial spin labeling (ASL) MRI for predicting MVI of T1 staging ccRCC preoperatively. METHODS 16 volunteers and 39 consecutive patients were enrolled. MRI examinations consisted of ASL (three post label delays separately) of the kidney, followed by T1 and T2-weighted imaging. Two sessions of ASL were used to evaluate the reproducibility on volunteers. Renal blood flow of renal cortex, medulla, the entire and solid part of the tumor were measured on ASL images. Conventional imaging features were extracted. MVI and WHO/ISUP classification were evaluated histopathologically. A paired t-test was used to compare the renal cortex and medulla between ASL 1 and ASL 2. The reproducibility was assessed using the intraclass correlation. Differences in mean perfusion between the entire and the solid parts of tumors with or without MVI were assessed separately using Student's t test. The diagnostic performance was assessed. Logistic regression analysis was used to indicate the independent prediction index for MVI. RESULTS The two sessions of ASL showed no significant difference between the mean cortex values of RBF. The cortical RBF measurements demonstrated good agreement. 12 ccRCCs presented with MVI histopathologically. Mean perfusion of the solid part of tumors with MVI were 536.4 ± 154.8 ml/min/100 g (PLD1), 2912.5 ± 939.3 ml/min/100 g (PLD2), 3280.3 ± 901.2 ml/min/100 g (PLD3). Mean perfusion of the solid part of tumors without MVI were 453.5 ± 87.2 ml/min/100 g (PLD1), 1043.6 ± 695.8 ml/min/100 g (PLD2), 1577.6 ± 1085.8 ml/min/100 g (PLD3). These two groups have significant difference at all the PLDs (p < 0.05). The RBF of PLD1 of the solid part of tumor perfusion showed well diagnostic performance for predicting MVI: sensitivity 75%, specificity 100%, positive predictive value 66.7%, and negative predictive value 95.7%. The maximum diameter of the tumor, ill-defined margin, and the solid part of tumor perfusion were the independent prediction index for MVI. CONCLUSION ASL MR imaging has good reproducibility for renal cortex, and good diagnostic performance for predicting MVI for ccRCC.
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Affiliation(s)
- Han-Mei Zhang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Da-Guang Wen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Wang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi-Ge Bao
- Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuan Yuan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yun-Tian Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Lu WF, Chen PQ, Yan K, Wu YC, Liang L, Yuan JY, Fu Y, Zhang HB. Synergistic impact of resection margin and microscopic vascular invasion for patients with HBV-related intrahepatic cholangiocarcinoma. Expert Rev Gastroenterol Hepatol 2021; 15:575-582. [PMID: 33899638 DOI: 10.1080/17474124.2021.1913053] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVES The resection margin (RM) status and microscopic vascular invasion (MVI) are known prognostic factors for intrahepatic cholangiocarcinoma (ICC). An enhanced understanding of their impact on long-term prognosis is required to improve oncological outcomes. METHODS A total of 711 consecutive patients who underwent curative liver resection for hepatitis B virus-related ICC were retrospectively analyzed. The different impact of the RM status (narrow, <1 cm, or wide, ≥1 cm) and MVI (positive, +, or negative, -) on overall survival (OS) and recurrence-free survival (RFS) were analyzed. RESULTS The 1-, 3-, and 5-year OS rates were 67.6%, 42.5%, and 33.2% in wide RM & MVI (-), 58.0%, 36.1%, and 26.5% in narrow RM & MVI (-), 51.0%, 27.0%, and 24.3% in wide RM & MVI (+), and 39.0%, 20.4% and 14.3% in narrow RM & MVI (+) (p < 0.001). Multivariate analysis showed that RM & MVI were independent risk factors for the OS and RFS. CONCLUSION Combined analysis of RM and MVI can better stratify the risks of postoperative death and recurrence in patients with HBV-related ICC, which may help subsequent adjuvant therapy and closer follow-up.
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Affiliation(s)
- Wen-Feng Lu
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
| | - Pei-Qin Chen
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
| | - Kai Yan
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
| | - Ye-Chen Wu
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
| | - Lei Liang
- Department of Hepatobiliary, Pancreatic and Minimal Invasive Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Jian-Yong Yuan
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
| | - Yong Fu
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
| | - Hai-Bin Zhang
- Department of Hepatic Surgery V, Shanghai Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China
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Radiomics signature on dynamic contrast-enhanced MR images: a potential imaging biomarker for prediction of microvascular invasion in mass-forming intrahepatic cholangiocarcinoma. Eur Radiol 2021; 31:6846-6855. [PMID: 33638019 DOI: 10.1007/s00330-021-07793-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 01/22/2021] [Accepted: 02/15/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVE To develop a radiomics signature based on dynamic contrast-enhanced (DCE) MR images for preoperative prediction of microvascular invasion (MVI) in patients with mass-forming intrahepatic cholangiocarcinoma (IMCC). METHODS One hundred twenty-six patients with surgically resected single IMCC (34 MVI-positive and 92 MVI-negative) were enrolled and allocated to training and validation cohorts (7:3 ratio). Findings of clinical characteristics and MR features were analyzed. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator (LASSO) regression algorithm in the training cohort. The prediction performance of radiomics signature was evaluated by receiver operating characteristics curve (ROC) analysis. Internal validation was performed on an independent cohort containing 38 patients. RESULTS Larger tumor size and higher radiomics score were positively correlated with MVI in both training cohort (p < 0.001, < 0.001, respectively) and validation cohort (p = 0.008, 0.001, respectively). The radiomics signature, consisting of seven wavelet features, showed optimal prediction performance in both training (AUC = 0.873) and validation cohorts (AUC = 0.850). CONCLUSION A radiomics signature derived from DCE-MRI of the liver can be a reliable imaging biomarker for predicting MVI of IMCC, which could aid in tailoring treatment strategies. KEY POINTS • The radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging can be a useful tool to preoperatively predict MVI of IMCC. • Larger tumor size is positively correlated with MVI of IMCC.
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