Interreader Reliability of LI-RADS Version 2014 Algorithm and Imaging Features for Diagnosis of Hepatocellular
Kathryn J Fowler1, An Tang1, Cynthia Santillan1
1From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.).
Abstract:
Purpose To determine in a large multicenter multireader setting the interreader reliability of Liver Imaging Reporting and Data System (LI-RADS) version 2014 categories, the major imaging features seen with computed tomography (CT) and magnetic resonance (MR) imaging, and the potential effect of reader demographics on agreement with a preselected nonconsecutive image set. Materials and Methods Institutional review board approval was obtained, and patient consent was waived for this retrospective study. Ten image sets, comprising 38-40 unique studies (equal number of CT and MR imaging studies, uniformly distributed LI-RADS categories), were randomly allocated to readers. Images were acquired in unenhanced and standard contrast material-enhanced phases, with observation diameter and growth data provided. Readers completed a demographic survey, assigned LI-RADS version 2014 categories, and assessed major features. Intraclass correlation coefficient (ICC) assessed with mixed-model regression analyses was the metric for interreader reliability of assigning categories and major features. Results A total of 113 readers evaluated 380 image sets. ICC of final LI-RADS category assignment was 0.67 (95% confidence interval [CI]: 0.61, 0.71) for CT and 0.73 (95% CI: 0.68, 0.77) for MR imaging. ICC was 0.87 (95% CI: 0.84, 0.90) for arterial phase hyperenhancement, 0.85 (95% CI: 0.81, 0.88) for washout appearance, and 0.84 (95% CI: 0.80, 0.87) for capsule appearance. ICC was not significantly affected by liver expertise, LI-RADS familiarity, or years of postresidency practice (ICC range, 0.69-0.70; ICC difference, 0.003-0.01 [95% CI: -0.003 to -0.01, 0.004-0.02]. ICC was borderline higher for private practice readers than for academic readers (ICC difference, 0.009; 95% CI: 0.000, 0.021). Conclusion ICC is good for final LI-RADS categorization and high for major feature characterization, with minimal reader demographic effect. Of note, our results using selected image sets from nonconsecutive examinations are not necessarily comparable with those of prior studies that used consecutive examination series. © RSNA, 2017.
