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Effect of Comprehensive Nursing Approach in Perioperative Stage of Patients with Hepatocellular Carcinoma Interventional Therapy. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:6862463. [PMID: 35966746 PMCID: PMC9374545 DOI: 10.1155/2022/6862463] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/03/2022] [Accepted: 07/05/2022] [Indexed: 11/17/2022]
Abstract
Objective. To examine the efficacy of a complete nursing strategy during the perioperative phase for patients undergoing interventional treatment for hepatocellular cancer. Methods. Sixty patients who were diagnosed with liver cancer and underwent interventional therapy in our hospital between February 2019 and December 2021 were recruited in this trial. All study subjects were numbered according to the time when the patients first came to our hospital, and were equally divided into a comprehensive group and a conventional group based on the odd and even number of the last number, with 30 cases in each group. Those in the conventional group received conventional nursing care, whereas patients in the comprehensive group received comprehensive nursing care. Before and after the nursing intervention, the quality of life, pain, and patient satisfaction in both groups were compared. Results. The quality of survival scores, including physical, emotional, role, social, and cognitive function scores of patients in the comprehensive group, were significantly higher than those in the conventional group (
); there was no statistically significant difference in numeric rating scales (NRS) scores between the two groups compared before treatment (
). After treatment, the NRS scores of patients in the study group were significantly lower than those of patients in the control group (
); before the intervention, the difference between the emotional state scores of patients in the two groups was not significant and not statistically significant (
), while the emotional state of patients in both groups improved after the intervention, and the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS) scores of patients in the comprehensive group were lower than those in the conventional group (
); the total incidence of adverse reactions in the comprehensive group (10.00%) was significantly lower than that in the conventional group (46.67%) (
); and the total satisfaction of patients in the comprehensive group (93.33%) was significantly higher than that of patients in the conventional group (73.33%) (
). Conclusion. The intervention of a comprehensive nursing approach in the perioperative period for patients with liver cancer is remarkable as it can relieve patients' psychological burden and pain, ensure a smooth operation, improve patients' postoperative quality of life, and also help to reduce the risk of postoperative adverse reactions, effectively enhancing patients’ satisfaction, and thus deserves to be promoted in clinical practice.
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He Z, Bao K, Zhang J, Ju D, Luo M, Liu L, Gao X. Multifunctional nanoparticles for targeted delivery of apoptin plasmid in cancer treatment. E-POLYMERS 2022. [DOI: 10.1515/epoly-2022-0020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Abstract
The systemic toxicity and low efficacy of traditional chemotherapy for hepatocellular carcinoma (HCC) result in poor clinical outcomes. This study was designed to achieve targeted delivery of apoptin plasmid (AP) to liver tumors and killing of cancer cells using multifunctional nanoparticles (MFNPs) having sustained-release properties. The MFNPs featuring a distinct core-shell structure were prepared using poly(lactic-glycolic acid)-ε-polylysine copolymer and loaded with AP by adsorption. Specific targeting of liver tumor cells was achieved by biotinylation of the nanoparticles (NPs), while an improvement in lysosomal escape and nuclear localization enhanced the tumor cell killing capability of AP. Blank MFNPs exhibited good biocompatibility while AP-loaded NPs were found to exert strong inhibitory effects on both tumor cells in vitro and solid tumors in vivo. Taken together, these findings demonstrate a promising route for the development of tumor-targeted NPs which may lead to improved therapeutic strategies for treating HCC.
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Affiliation(s)
- Zhuanxia He
- School of Biomedical Engineering and Technology, Tianjin Medical University , Tianjin 300070 , China
| | - Ke Bao
- School of Biomedical Engineering and Technology, Tianjin Medical University , Tianjin 300070 , China
| | - Jiawei Zhang
- School of Biomedical Engineering and Technology, Tianjin Medical University , Tianjin 300070 , China
| | - Dandan Ju
- School of Biomedical Engineering and Technology, Tianjin Medical University , Tianjin 300070 , China
| | - Mingyan Luo
- School of Biomedical Engineering and Technology, Tianjin Medical University , Tianjin 300070 , China
| | - Liyan Liu
- College of Science, Civil Aviation University of China , Tianjin 300300 , China
| | - Xiujun Gao
- School of Biomedical Engineering and Technology, Tianjin Medical University , No. 22, Meteorological Station Road , Tianjin 300070 , China
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Sun R, Fang L, Lv X, Fang J, Wang Y, Chen D, Wang L, Chen J, Qi Y, Tang Z, Zhang J, Tian Y. In vitro and in vivo evaluation of self-assembled chitosan nanoparticles selectively overcoming hepatocellular carcinoma via asialoglycoprotein receptor. Drug Deliv 2021; 28:2071-2084. [PMID: 34595970 PMCID: PMC8491732 DOI: 10.1080/10717544.2021.1983077] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the major causes of cancer-related mortality worldwide. Nowadays, liver-targeting drug delivery system has been proven as a promising strategy for overcoming HCC. Asialoglycoprotein receptor (ASGPR) is an ideal receptor for liver targeting, which is mainly expressed on hepatocytes. In this study, we developed several novel liver-targeting chitosan nanoparticles to selectively overcome HCC via ASGPR. Chitosan nanoparticles (Gly-CS-VE, Gal-Gly-CS-VE, Gly-CS-DCA, and Gal-Gly-CS-DCA) were prepared by grafting hydrophilic group (glycidol, Gly), hydrophobic group (deoxycholic acid, DCA or vitamin E succinate, VE), and ASGPR recognizing group (galactose, Gal). Subsequently, their characterizations were measured by 1H NMR, FT-IR, TEM, and DLS. Doxorubicin (DOX) was loaded in nanoparticles and released out in a pH-dependent manner. Most importantly, the galactosylated Gal-Gly-CS-VE and Gal-Gly-CS-DCA nanoparticles exhibited significantly stronger in vitro cell internalization, cytotoxicity, anti-migration capabilities and in vivo anticancer efficacies than the corresponding Gly-CS-VE and Gly-CS-DCA nanoparticles, as well as free DOX. Finally, the four chitosan nanoparticles exhibited good biocompatibility without causing any obvious histological damage to the major organs. Overall, the galactosylated chitosan nanoparticles were proven to be promising pharmaceutical formulations for selectively overcoming HCC, with great potential for clinical applications.
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Affiliation(s)
- Rensong Sun
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Linlin Fang
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Xia Lv
- Collage of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Jiani Fang
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Yuting Wang
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Dapeng Chen
- Laboratory Animal Center, Dalian Medical University, Dalian, China
| | - Liang Wang
- Laboratory Animal Center, Dalian Medical University, Dalian, China
| | - Jun Chen
- Laboratory Animal Center, Dalian Medical University, Dalian, China
| | - Yan Qi
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Zeyao Tang
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Jianbin Zhang
- Collage of Pharmacy, Dalian Medical University, Dalian, China
| | - Yan Tian
- Collage of Pharmacy, Dalian Medical University, Dalian, China
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4
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Aslam A, Kamath A, Spieler B, Maschiocchi M, Sabottke CF, Chernyak V, Lewis SC. Assessing locoregional treatment response to Hepatocellular Carcinoma: comparison of hepatobiliary contrast agents to extracellular contrast agents. Abdom Radiol (NY) 2021; 46:3565-3578. [PMID: 33856509 DOI: 10.1007/s00261-021-03076-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 03/22/2021] [Accepted: 03/27/2021] [Indexed: 12/17/2022]
Abstract
Cross-sectional imaging with contrast-enhanced magnetic resonance imaging (MRI) is routinely performed in patients with hepatocellular carcinoma (HCC) to assess tumor response to locoregional therapy (LRT). Current response assessment algorithms, such as the Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA), allow assessment using conventional gadolinium-based extracellular contrast agents (ECA) for accurate tumor response assessment following LRT. MRI with hepatobiliary agents (HBA) allows an acquisition of hepatobiliary phase (HBP), which is proven to increase sensitivity for detection of observations in at-risk patients, particularly for findings < 2 cm. The use of HBA is not yet incorporated into the TRA; however, it is increasingly used in clinical practice. Few published studies have evaluated the performance of LI-RADS TRA by applying ancillary features related to HBP that has resulted in category adjustment, enabling more sensitive and unequivocal diagnosis. This may help timely management of viable cases, without a significant loss of specificity in comparison with the ECA-based LI-RADS TRA assessment. In this review, we will describe and compare the imaging appearance of treated HCC on MRI using extracellular and hepatobiliary contrast agents and discuss emerging evidence and pitfalls in the assessment of tumor response following LRT with HBA.
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Affiliation(s)
- Anum Aslam
- Department of Radiology, University of Michigan Health System, 1500 E. Medical Center Dr, Ann Arbor, MI, 48109-5030, USA.
| | - Amita Kamath
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine At Mount Sinai, New York, NY, USA
| | - Bradley Spieler
- Department of Radiology, Louisiana State University Health Sciences Center, 1542 Tulane Avenue, Rm 343, New Orleans, LA, 70112, USA
| | - Mark Maschiocchi
- Umass Memorial Medical Center- University Campus, 55 Lake Avenue North, Worcester, MA, 01655, USA
| | - Carl F Sabottke
- Department of Medical Imaging, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Victoria Chernyak
- Department of Radiology and Urology, Albert Einstein College of Medicine, New York, 10467, USA
| | - Sara C Lewis
- Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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5
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Zou ZM, Chang DH, Liu H, Xiao YD. Current updates in machine learning in the prediction of therapeutic outcome of hepatocellular carcinoma: what should we know? Insights Imaging 2021; 12:31. [PMID: 33675433 PMCID: PMC7936998 DOI: 10.1186/s13244-021-00977-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 02/15/2021] [Indexed: 12/24/2022] Open
Abstract
With the development of machine learning (ML) algorithms, a growing number of predictive models have been established for predicting the therapeutic outcome of patients with hepatocellular carcinoma (HCC) after various treatment modalities. By using the different combinations of clinical and radiological variables, ML algorithms can simulate human learning to detect hidden patterns within the data and play a critical role in artificial intelligence techniques. Compared to traditional statistical methods, ML methods have greater predictive effects. ML algorithms are widely applied in nearly all steps of model establishment, such as imaging feature extraction, predictive factor classification, and model development. Therefore, this review presents the literature pertaining to ML algorithms and aims to summarize the strengths and limitations of ML, as well as its potential value in prognostic prediction, after various treatment modalities for HCC.
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Affiliation(s)
- Zhi-Min Zou
- Department of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, 410011, China
| | - De-Hua Chang
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, 69120, Heidelberg, Germany
| | - Hui Liu
- Department of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, 410011, China
| | - Yu-Dong Xiao
- Department of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, 410011, China.
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Aslam A, Do RKG, Chernyak V, Mendiratta-Lala M. LI-RADS Imaging Criteria for HCC Diagnosis and Treatment: Emerging Evidence. CURRENT HEPATOLOGY REPORTS 2020; 19:437-447. [DOI: 10.1007/s11901-020-00546-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/07/2020] [Indexed: 01/07/2025]
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7
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Aslam A, Do RKG, Kambadakone A, Spieler B, Miller FH, Gabr AM, Charalel RA, Kim CY, Madoff DC, Mendiratta-Lala M. Hepatocellular carcinoma Liver Imaging Reporting and Data Systems treatment response assessment: Lessons learned and future directions. World J Hepatol 2020; 12:738-753. [PMID: 33200013 PMCID: PMC7643220 DOI: 10.4254/wjh.v12.i10.738] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 08/07/2020] [Accepted: 09/17/2020] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of morbidity and mortality worldwide, with rising clinical and economic burden as incidence increases. There are a multitude of evolving treatment options, including locoregional therapies which can be used alone, in combination with each other, or in combination with systemic therapy. These treatment options have shown to be effective in achieving remission, controlling tumor progression, improving disease free and overall survival in patients who cannot undergo resection and providing a bridge to transplant by debulking tumor burden to downstage patients. Following locoregional therapy (LRT), it is crucial to provide treatment response assessment to guide management and liver transplant candidacy. Therefore, Liver Imaging Reporting and Data Systems (LI-RADS) Treatment Response Algorithm (TRA) was created to provide a standardized assessment of HCC following LRT. LI-RADS TRA provides a step by step approach to evaluate each lesion independently for accurate tumor assessment. In this review, we provide an overview of different locoregional therapies for HCC, describe the expected post treatment imaging appearance following treatment, and review the LI-RADS TRA with guidance for its application in clinical practice. Unique to other publications, we will also review emerging literature supporting the use of LI-RADS for assessment of HCC treatment response after LRT.
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Affiliation(s)
- Anum Aslam
- Department of Radiology, University of Michigan, Ann Arbor, MI 48019, United States.
| | - Richard Kinh Gian Do
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, United States
| | - Avinash Kambadakone
- Abdominal Imaging and Interventional Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Bradley Spieler
- Department of Radiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112, United States
| | - Frank H Miller
- Department of Radiology, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States
| | - Ahmed M Gabr
- Department of Interventional Radiology, OHSU and Tanta University, Egypt, Portland, OR 97239, United States
| | - Resmi A Charalel
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, United States
| | - Charles Y Kim
- Department of Radiology, Duke University Medical Center, Duke University, Durham, NC 27710, United States
| | - David C Madoff
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Mishal Mendiratta-Lala
- School of Medicine, 1500 East Medical Center Drive, University of Michigan, Ann Arbor, MI 48109, United States
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Xu G, Zhu Y, Liu H, Liu Y, Zhang X. LncRNA MIR194-2HG Promotes Cell Proliferation and Metastasis via Regulation of miR-1207-5p/TCF19/Wnt/β-Catenin Signaling in Liver Cancer. Onco Targets Ther 2020; 13:9887-9899. [PMID: 33116574 PMCID: PMC7547811 DOI: 10.2147/ott.s264614] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/05/2020] [Indexed: 01/05/2023] Open
Abstract
Purpose LncRNAs play an important role in tumorigenesis and cancer progression in liver cancer. Although many lncRNAs have been reported, the role of MIR194-2HG and the underlying mechanism mediated by it are still largely unknown in HCC. This study aimed to investigate the biological role and mechanism of MIR194-2HG in liver cancer. Materials and Methods The expression of MIR194-2HG was determined in liver cancer tissues and cells by RT-qPCR. The overall survival rate of MIR194-2HG was analyzed by Kaplan–Meier survival analysis. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, and Transwell assays were carried out to detect cell migration and invasion. Western blotting was used to quantify the levels of all proteins. The regulatory mechanism of the MIR194-2HG/miR-1207-5p/TCF19 axis in liver cancer was investigated by dual-luciferase activity reporter assay, Kaplan-Meier survival analysis, and Western blotting. Results MIR194-2HG was upregulated in liver cancer tissues and cell lines. Liver cancer patients with higher expression of MIR194-2HG revealed poor overall survival compared with those who had lower expression of MIR194-2HG. MIR194-2HG promoted the proliferation, migration, and invasion of HepG2 and Huh7 cells by acting as a ceRNA mechanism for the miR-1207-5p/TCF19 axis to activate the Wnt/β-catenin signaling pathway. Conclusion MIR194-2HG acts in an oncogenic role and activates the Wnt/β-catenin signaling pathway via a miR-1207-5p/TCF19 axis-mediated mechanism, which provides a novel avenue for diagnostic or therapeutic interventions in liver cancer.
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Affiliation(s)
- Guoping Xu
- Department of Medical Imaging, The Second Hospital of Tianjin Medical University, Tianjin 300211, People's Republic of China
| | - Yungang Zhu
- Graduate School of Tianjin Medical University, Tianjin Medical University, Tianjin 300070, People's Republic of China
| | - Huijia Liu
- Department of Medical Imaging, The Second Hospital of Tianjin Medical University, Tianjin 300211, People's Republic of China
| | - Yingying Liu
- Department of Medical Imaging, The Second Hospital of Tianjin Medical University, Tianjin 300211, People's Republic of China
| | - Xuening Zhang
- Department of Medical Imaging, The Second Hospital of Tianjin Medical University, Tianjin 300211, People's Republic of China
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Zhang Y, Wang J, Li H, Zheng T, Jiang H, Li M, Song B. Performance of LI-RADS version 2018 CT treatment response algorithm in tumor response evaluation and survival prediction of patients with single hepatocellular carcinoma after radiofrequency ablation. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:388. [PMID: 32355832 PMCID: PMC7186681 DOI: 10.21037/atm.2020.03.120] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 03/02/2020] [Indexed: 02/05/2023]
Abstract
BACKGROUND The Liver Imaging Reporting and Data System treatment response algorithm (LI-RADS TRA) was developed to evaluate the tumor response of patients with hepatocellular carcinoma (HCC) after locoregional treatments. This study aimed to evaluate the performance of LI-RADS computed tomography (CT) TRA version 2018 in tumor response assessment and survival prediction of patients with single HCC after radiofrequency ablation (RFA). METHODS Forty patients who underwent RFA for single HCC between 2010 and 2016 were included in this retrospective study. The overall survival (OS) data from all the patients after the first therapy was collected. Two readers independently assessed the pretreatment (within 7 d) and posttreatment (within 90 d after RFA) CT manifestations using the LI-RADS version 2018 CT TRA. Inter-reader agreement was assessed. Another radiologist re-evaluated any divergent results and came to the final conclusion. The performance of LI-RADS version 2018 CT TRA for tumor response assessment and predicting survival of patients with single HCC after RFA was evaluated. RESULTS Interobserver agreement was moderate between the 2 readers [κ=0.602, 95% confidence interval (CI): 0.390-0.814] when using LI-RADS version 2018 TRA to evaluate tumor response for patients with single HCC after RFA. Patients classified as LR-TR viable had significantly lower OS than those classified as LR-TR nonviable (P=0.005) and LR-TR equivocal (P=0.036). However, the OS between LR-TR nonviable and LR-TR equivocal did not differ significantly (P=0.901). CONCLUSIONS LI-RADS version 2018 CT TRA can be applied to predict viable or nonviable HCC after RFA. Patients with LR-TR viable had significantly lower OS than those with LR-TR nonviable and LR-TR equivocal. More research is needed to validate the performance of LI-RADS version 2018 TRA in HCC tumor response evaluation, to better grasp the use of the tie-breaking rule, and to improve the accuracy of prediction for tumor viability.
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Affiliation(s)
- Yun Zhang
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, China
| | - Jinju Wang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital, Chengdu 610041, China
| | - Hui Li
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital, Chengdu 610041, China
| | - Tianying Zheng
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, China
| | - Hanyu Jiang
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, China
| | - Mou Li
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, China
| | - Bin Song
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, China
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