@article{f45397bd95cb4977a87b8bc4b9cd2e6b,
title = " LI-RADS {\textregistered} ancillary features on CT and MRI ",
abstract = "The Liver Imaging Reporting and Data System (LI-RADS) uses an algorithm to assign categories that reflect the probability of hepatocellular carcinoma (HCC), non-HCC malignancy, or benignity. Unlike other imaging algorithms, LI-RADS utilizes ancillary features (AFs) to refine the final category. AFs in LI-RADS v2017 are divided into those favoring malignancy in general, those favoring HCC specifically, and those favoring benignity. Additionally, LI-RADS v2017 provides new rules regarding application of AFs. The purpose of this review is to discuss ancillary features included in LI-RADS v2017, the rationale for their use, potential pitfalls encountered in their interpretation, and tips on their application.",
keywords = "Ancillary features, Benignity, Hepatocellular carcinoma, Imaging features, Malignancy, Review article",
author = "Victoria Chernyak and An Tang and Milana Flusberg and Demetri Papadatos and Bijan Bijan and Yuko Kono and Cynthia Santillan",
note = "Funding Information: Acknowledgements. This work was supported by [1] the Fonds de recherche du Qu{\'e}bec—Sant{\'e} (Career Award#26993), and New Researcher Startup Grant from the Centre de Recherche du Centre Hospitalier de l{\textquoteright}Universit{\'e} de Montr{\'e}al (CRCHUM) to An Tang. Funding Information: This work was supported by [1] the Fonds de recherche du Qu?bec?Sant? (Career Award#26993), and New Researcher Startup Grant from the Centre de Recherche du Centre Hospitalier de l?Universit? de Montr?al (CRCHUM) to An Tang. V Chernyak, M. Flusberg, D. Papadatos, B. Bijan, C. Santillan: None. A. Tang, MD, MSc: Advisory board member of Imagia Cybernetics. Y. Kono: Research Grant support: Toshiba Medical Systems Co.; Contrast agent support: Lantheus Medical Imaging Inc.; Equipment support: GE Healthcare; Equipment support: Philips Ultrasound. Publisher Copyright: {\textcopyright} 2017, Springer Science+Business Media, LLC.",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/s00261-017-1220-6",
language = "English (US)",
volume = "43",
pages = "82--100",
journal = "Abdominal Radiology",
issn = "2366-004X",
publisher = "Springer New York",
number = "1",
}