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      A radiomics model based on magnetic resonance imaging to predict cytokeratin 7/19 expression and liver fluke infection of hepatocellular carcinoma

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          Abstract

          Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time. A total of 134 HCC patients were included. Gadoxetic acid-enhanced magnetic resonance imaging (MRI) images of all patients were acquired. Radiomics features of the tumor were extracted and then data dimensionality was reduced. The radiomics model was established to predict liver fluke infection and the radiomics score (Radscore) was calculated. There were 11 features in the four-phase combined model. The efficiency of the combined model increased significantly compared to each single-phase MRI model. Radscore was an independent predictor of liver fluke infection. It was also significantly different between different expression of CK7/ CK19. Meanwhile, liver fluke infection was associated with CK7/CK19 expression. A cut-off value was set up and all patients were divided into high risk and low risk groups of CK7/CK19 positive expression. Radscore was also an independent predictor of these two biomarkers. Overall survival (OS) and recurrence free survival (RFS) of negative liver fluke infection group were significantly better than the positive group. OS and RFS of negative CK7 and CK19 expression were also better, though not significantly. Positive liver fluke infection and CK19 expression prediction groups harbored significantly worse OS and RFS, survival of positive CK7 expression prediction was unsatisfying as well. A radiomics model was established to predict liver fluke infection among HCC patients. This model could also predict CK7 and CK19 expression. OS and RFS could be foreseen by this model at the same time.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          Hyuna Sung, Jacques Ferlay, Rebecca Siegel … (2021)
          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

            Ahmedin Jemal, Lindsey A Torre, Rebecca Siegel … (2018)
            This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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              Radiomics: Images Are More than Pictures, They Are Data

              Robert Gillies, Paul E Kinahan, Hedvig Hricak (2015)
              This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
              Article 0 comments Cited 2052 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Tao Peng:
                ORCID: http://orcid.org/0000-0001-6133-7078
                pengtao@gxmu.edu.cn
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 16 October 2023
                Publication date PMC-release: 16 October 2023
                Publication date Collection: 2023
                Volume: 13
                Electronic Location Identifier: 17553
                Affiliations
                [1 ]GRID grid.412594.f, ISNI 0000 0004 1757 2961, Department of Hepatobiliary Surgery, , The First Affiliated Hospital of Guangxi Medical University, ; Shuang Yong Rd. 6#, Nanning, 530021 Guangxi Zhuang Autonomous Region People’s Republic of China
                [2 ]Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, ( https://ror.org/00zjgt856) Nanning, Guangxi Zhuang Autonomous Region People’s Republic of China
                [3 ]Key Laboratory of Early Prevention & Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, ( https://ror.org/00zjgt856) Nanning, Guangxi Zhuang Autonomous Region People’s Republic of China
                [4 ]GRID grid.412594.f, ISNI 0000 0004 1757 2961, Department of Radiology, , The First Affiliated Hospital of Guangxi Medical University, ; Nanning, Guangxi Zhuang Autonomous Region People’s Republic of China
                Author information
                http://orcid.org/0000-0001-6133-7078
                Article
                Publisher ID: 44773
                DOI: 10.1038/s41598-023-44773-5
                PMC ID: 10579381
                PubMed ID: 37845287
                SO-VID: 5fb54f19-50ac-4ace-9cff-181b4fae6476
                Copyright © © Springer Nature Limited 2023
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 7 August 2023
                Date accepted : 12 October 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100011827, Guangxi Medical University;
                Award ID: GKE-ZZ202213, GKE-ZZ202109 and GKE-ZZ202009
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © Springer Nature Limited 2023

                ScienceOpen disciplines: Uncategorized
                Keywords: hepatocellular carcinoma,predictive markers,prognostic markers
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: hepatocellular carcinoma, predictive markers, prognostic markers

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