Hepatocellular carcinoma imaging systems: why they exist, how they have evolved, and how they differ.

{"article_title":"Hepatocellular carcinoma imaging systems: why they exist, how they have evolved, and how they differ.","author":"Tang A, Cruite I, Mitchell DG, Sirlin CB","journal_title":"Abdominal radiology (New York)","issn":"2366-0058","isbn":"","publication_date":"2018 Jan","volume":"43","issue":"1","first_page":"3","page_count":"","accession_number":"28840293","doi":"10.1007\/s00261-017-1292-3","publisher":"Springer","doctype":"Journal Article","subjects":"Algorithms; Carcinoma, Hepatocellular diagnostic imaging; Diagnostic Imaging trends; Liver Neoplasms diagnostic imaging; Consensus; Contrast Media; Humans; Practice Guidelines as Topic; Radiology Information Systems standards; Sensitivity and Specificity; Societies, Medical","interest_area":["Gastroenterology"," Oncology"," Radiology"],"abstract":"Over the past 16 years, several scientific organizations have proposed systems that incorporate imaging for surveillance, diagnosis, staging, treatment, and monitoring of treatment response of hepatocellular carcinoma (HCC). These systems are needed to standardize the acquisition, interpretation, and reporting of liver imaging examinations; help differentiate benign from malignant observations; improve consistency between radiologists; and provide guidance for management of HCC. This review article discusses the historical evolution of HCC imaging systems. We indicate the features differentiating these systems, including target population, screening and surveillance algorithm, diagnostic imaging modalities, diagnostic scope, expertise and technical requirements, terminology, major and ancillary imaging features, staging and transplant eligibility, and assessment of treatment response. We highlight the potential benefits of unifying the systems, which we anticipate will enable sharing, pooling, and meta-analysis of data; facilitate multi-center trials; and accelerate dissemination of knowledge.","url":"https:\/\/search.ebscohost.com\/login.aspx?direct=true&db=mdl&AN=28840293&authtype=shib&custid=ns346513","isPdfLink":true,"isSAML":false,"additionalInfo":{"Authored_By":"Tang A, Cruite I, Mitchell DG, Sirlin CB","Journal_Info":"Publisher: Springer Country of Publication: United States NLM ID: 101674571 Publication Model: Print Cited Medium: Internet ISSN: 2366-0058 (Electronic) NLM ISO Abbreviation: Abdom Radiol (NY) Subsets: MEDLINE","Publication_Type":"Journal Article; Research Support, Non-U.S. Gov't; Review","Published_Date":"2018-01-01","Source":"Abdominal radiology (New York) [Abdom Radiol (NY)] 2018 Jan; Vol. 43 (1), pp. 3-12.","Languages":"English","Electronic_ISSN":"2366-0058","MeSH_Terms":"Algorithms*, Carcinoma, Hepatocellular\/*diagnostic imaging , Diagnostic Imaging\/*trends , Liver Neoplasms\/*diagnostic imaging, Consensus ; Contrast Media ; Humans ; Practice Guidelines as Topic ; Radiology Information Systems\/standards ; Sensitivity and Specificity ; Societies, Medical","Subjects":"Consensus, Contrast Media, Humans, Practice Guidelines as Topic, Radiology Information Systems standards, Sensitivity and Specificity, Societies, Medical, Algorithms, Carcinoma, Hepatocellular diagnostic imaging, Diagnostic Imaging trends, Liver Neoplasms diagnostic imaging","Title_Abbreviations":"Abdominal radiology (New York)","Volume":"43"},"header":{"DbId":"mdl","DbLabel":"MEDLINE Ultimate","An":"28840293","RelevancyScore":"809","PubType":"Academic Journal","PubTypeId":"academicJournal","PreciseRelevancyScore":"809.340270996094"},"plink":"https:\/\/search.ebscohost.com\/login.aspx?direct=true&site=eds-live&db=mdl&AN=28840293&authtype=shib&custid=ns346513&group=main&profile=eds","upload_link":"https:\/\/search.ebscohost.com\/login.aspx?direct=true&site=eds-live&db=mdl&AN=28840293&authtype=shib&custid=ns346513&group=main&profile=eds"}