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      A Nomogram Based on Combining Clinical Features and Contrast Enhanced Ultrasound LI-RADS Improves Prediction of Microvascular Invasion in Hepatocellular Carcinoma

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          Abstract

          Purposes

          To establish a predictive model incorporating clinical features and contrast enhanced ultrasound liver imaging and reporting and data system (CEUS LI-RADS) for estimation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.

          Methods

          In the retrospective study, 127 HCC patients from two hospitals were allocated as training cohort (n=98) and test cohorts (n=29) based on cutoff time-point, June 2020. Multivariate regression analysis was performed to identify independent indicators for developing predictive nomogram models. The area under receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. Corresponding sensitivities and specificities of different models at the cutoff nomogram value were compared.

          Results

          In the training cohort, clinical information (larger tumor size, higher AFP level) and CEUS LR-M were significantly correlated with the presence of MVI (all p<0.05). By incorporating clinical information and CEUS LR-M, the predictive model (LR-M+Clin) achieved a desirable diagnostic performance (AUC=0.80 and 0.84) in both cohorts at nomogram cutoff score value of 89. The sensitivity of LR-M+Clin when predicting MVI in HCC patients was higher than that of the clinical model alone (86.7% vs. 46.7%, p=0.027), while specificities were 78.6% and 85.7% (p=0.06), respectively, in the test cohort. In addition, LR-M+Clin exhibited similar AUC and specificity, but a significantly higher sensitivity (86.7%) than those of LR-M alone and LR-5(No)+Clin (both sensitivities=73.3%, both p=0.048).

          Conclusion

          The predictive model incorporating CEUS LR-M and clinical features was able to predict the MVI status of HCC and is a potential reliable preoperative tool for informing treatment.

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          Most cited references31

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          Predicting survival after liver transplantation in patients with hepatocellular carcinoma beyond the Milan criteria: a retrospective, exploratory analysis.

          Vincenzo Mazzaferro, Josep Llovet, Rosalba Miceli … (2009)
          Patients undergoing liver transplantation for hepatocellular carcinoma within the Milan criteria (single tumour
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            Nomogram for Preoperative Estimation of Microvascular Invasion Risk in Hepatitis B Virus-Related Hepatocellular Carcinoma Within the Milan Criteria.

            Zhengqing Lei, Jun. Li, Dong Wu … (2016)
            The presence of microvascular invasion (MVI) decreases surgical outcomes of hepatocellular carcinoma (HCC). An accurate preoperative prediction of MVI can help surgeons to better choose surgical procedures, but accuracy is still difficult to achieve.
            Article 0 comments Cited 278 times – based on 0 reviews     Review now
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              Prognostic and Therapeutic Implications of Microvascular Invasion in Hepatocellular Carcinoma

              Derek Erstad, Kenneth Tanabe (2019)
              Article 0 comments Cited 177 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Journal
                Journal ID (nlm-ta): Front Oncol
                Journal ID (iso-abbrev): Front Oncol
                Journal ID (publisher-id): Front. Oncol.
                Title: Frontiers in Oncology
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 2234-943X
                Publication date (Electronic): 08 July 2021
                Publication date Collection: 2021
                Volume: 11
                Electronic Location Identifier: 699290
                Affiliations
                [1] 1 Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine , Hangzhou, China
                [2] 2 Department of In-Patient Ultrasound, The Second Affiliated Hospital of Harbin Medical University , Harbin, China
                Author notes

                Edited by: Po-Hsiang Tsui, Chang Gung University, Taiwan

                Reviewed by: Chuan Hu, Qingdao University Medical College, China; Xin-Wu Cui, Huazhong University of Science and Technology, China

                *Correspondence: Xianli Zhou, hrbzhouxl@ 123456163.com ; Pintong Huang, huangpintong@ 123456zju.edu.cn

                †These authors have contributed equally to this work

                This article was submitted to Cancer Imaging and Image-directed Interventions, a section of the journal Frontiers in Oncology

                Article
                DOI: 10.3389/fonc.2021.699290
                PMC ID: 8297520
                PubMed ID: 34307168
                SO-VID: f14db50f-f5fa-4e0b-8b61-ea9d559cda0c
                Copyright © Copyright © 2021 Zhou, Sun, Jiang, Wu, Li, Zhang, Zhang, Cao, Sun, Jiang, Liu, Zhou and Huang
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 23 April 2021
                Date accepted : 22 June 2021
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 31, Pages: 10, Words: 4588
                Funding
                Funded by: National Key Research and Development Program of China 10.13039/501100012166
                Award ID: 2018YFC0115900
                Categories
                Subject: Oncology
                Subject: Original Research

                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: hepatocellular carcinoma,nomogram,liver imaging and reporting and data system,contrast enhanced ultrasound,microvascular invasion
                Data availability:
                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: hepatocellular carcinoma, nomogram, liver imaging and reporting and data system, contrast enhanced ultrasound, microvascular invasion

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