Literature DB >> 26119393

Classifying CT/MR findings in patients with suspicion of hepatocellular carcinoma: Comparison of liver imaging reporting and data system and criteria-free Likert scale reporting models.

Yu-Dong Zhang1, Fei-Peng Zhu1, Xun Xu1, Qing Wang1, Chen-Jiang Wu1, Xi-Sheng Liu1, Hai-Bin Shi1.   

Abstract

PURPOSE: To compare the Liver Imaging Reporting and Data System (LI-RADS) and a criteria-free Likert scale (LS) reporting models for classifying computed tomography/magnetic resonance imaging (CT/MR) findings of suspicious hepatocellular carcinoma (HCC).
MATERIALS AND METHODS: Imaging data of 281 hepatic nodules in 203 patients were retrospectively included. Imaging characteristics including diameter, arterial hyperenhancement, washout, and capsule were reviewed independently by two groups of readers using LI-RADS and LS (range, score 1-5). LS is primarily based on the overall impression of image findings without using fixed criteria. Interreader agreement (IRA), intraclass agreement (ICA), and diagnostic performance were determined by Fleiss, Cohen's kappa (κ), and logistic regression, respectively.
RESULTS: There were 167 contrast-enhanced CT (CECT) versus 114 MR data. Overall, IRA was moderate (κ = 0.47, 0.52); IRA was moderate-to-good for arterial hyperenhancement, washout, and capsule (κ = 0.56-0.69); excellent for diameter and tumor embolus (κ = 0.99). Overall, ICA between LI-RADS and LS was moderate (κ = 0.44-0.50); ICA was good for scores 1-2 (κ = 0.71-0.90), moderate for scores 3 and 5 (κ = 0.41-0.52), but very poor for score 4 (κ = 0.11-0.19). LI-RADS produced significantly lower accuracy (78.6% vs. 87.2%) and sensitivity (72.1% vs. 92.8%), higher specificity (97.3% vs. 71.2%) and positive likelihood ratio (+LR: 26.32 vs. 3.23) in diagnosis of HCC. CECT produced relatively low IRA, ICA, and diagnostic ability against MR.
CONCLUSION: There were substantial variations in liver observations between LI-RADS and LS. Further study is needed to investigate ICA between CECT and MR.
© 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  HCC; LI-RADS; Likert scale; interreader agreement; intraclass agreement

Mesh:

Year:  2015        PMID: 26119393     DOI: 10.1002/jmri.24987

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  13 in total

1.  Longitudinal evolution of CT and MRI LI-RADS v2014 category 1, 2, 3, and 4 observations.

Authors:  Cheng William Hong; Charlie C Park; Adrija Mamidipalli; Jonathan C Hooker; Soudabeh Fazeli Dehkordy; Saya Igarashi; Mohanad Alhumayed; Yuko Kono; Rohit Loomba; Tanya Wolfson; Anthony Gamst; Paul Murphy; Claude B Sirlin
Journal:  Eur Radiol       Date:  2019-02-26       Impact factor: 5.315

2.  Liver Imaging Reporting and Data System on CT and gadoxetic acid-enhanced MRI with diffusion-weighted imaging.

Authors:  Dong Ik Cha; Kyung Mi Jang; Seong Hyun Kim; Tae Wook Kang; Kyoung Doo Song
Journal:  Eur Radiol       Date:  2017-04-03       Impact factor: 5.315

3.  Interobserver and intermodality agreement of standardized algorithms for non-invasive diagnosis of hepatocellular carcinoma in high-risk patients: CEUS-LI-RADS versus MRI-LI-RADS.

Authors:  Barbara Schellhaas; Matthias Hammon; Deike Strobel; Lukas Pfeifer; Christian Kielisch; Ruediger S Goertz; Alexander Cavallaro; Rolf Janka; Markus F Neurath; Michael Uder; Hannes Seuss
Journal:  Eur Radiol       Date:  2018-04-19       Impact factor: 5.315

4.  Does a combined CT and MRI protocol enhance the diagnostic efficacy of LI-RADS in the categorization of hepatic observations? A prospective comparative study.

Authors:  Mohammad Abd Alkhalik Basha; Mohamad Zakarya AlAzzazy; Ayman F Ahmed; Hala Y Yousef; Samar Mohamad Shehata; Dena Abd El Aziz El Sammak; Talaat Fathy; Ahmed Ali Obaya; Eman H Abdelbary
Journal:  Eur Radiol       Date:  2018-01-24       Impact factor: 5.315

5.  Characterization of liver nodules in patients with chronic liver disease by MRI: performance of the Liver Imaging Reporting and Data System (LI-RADS v.2018) scale and its comparison with the Likert scale.

Authors:  Andrea Esposito; Valentina Buscarino; Dario Raciti; Elena Casiraghi; Matteo Manini; Pietro Biondetti; Laura Forzenigo
Journal:  Radiol Med       Date:  2019-10-05       Impact factor: 3.469

6.  Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features.

Authors:  Clinton J Wang; Charlie A Hamm; Lynn J Savic; Marc Ferrante; Isabel Schobert; Todd Schlachter; MingDe Lin; Jeffrey C Weinreb; James S Duncan; Julius Chapiro; Brian Letzen
Journal:  Eur Radiol       Date:  2019-05-15       Impact factor: 5.315

7.  Reduced field of view echo-planar imaging diffusion tensor MRI for pediatric spinal tumors.

Authors:  Lily H Kim; Edward H Lee; Michelle Galvez; Murat Aksoy; Stefan Skare; Rafael O'Halloran; Michael S B Edwards; Samantha J Holdsworth; Kristen W Yeom
Journal:  J Neurosurg Spine       Date:  2019-07-05

8.  LI-RADS v2017 categorisation of HCC using CT: Does moderate to severe fatty liver affect accuracy?

Authors:  Seung Soo Kim; Jeong Ah Hwang; Hyeong Cheol Shin; Seo-Youn Choi; Tae Wook Kang; Sung Shick Jou; Woong Hee Lee; Suyeon Park; Nam Hun Heo
Journal:  Eur Radiol       Date:  2018-08-02       Impact factor: 5.315

Review 9.  Evidence Supporting LI-RADS Major Features for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review.

Authors:  An Tang; Mustafa R Bashir; Michael T Corwin; Irene Cruite; Christoph F Dietrich; Richard K G Do; Eric C Ehman; Kathryn J Fowler; Hero K Hussain; Reena C Jha; Adib R Karam; Adrija Mamidipalli; Robert M Marks; Donald G Mitchell; Tara A Morgan; Michael A Ohliger; Amol Shah; Kim-Nhien Vu; Claude B Sirlin
Journal:  Radiology       Date:  2017-11-21       Impact factor: 11.105

Review 10.  Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients.

Authors:  Victoria Chernyak; Kathryn J Fowler; Aya Kamaya; Ania Z Kielar; Khaled M Elsayes; Mustafa R Bashir; Yuko Kono; Richard K Do; Donald G Mitchell; Amit G Singal; An Tang; Claude B Sirlin
Journal:  Radiology       Date:  2018-09-25       Impact factor: 11.105

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.