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Diagnostic performance of MR for hepatocellular carcinoma based on LI-RADS v2018, compared with v2017.
Ren, A-Hong; Zhao, Peng-Fei; Yang, Da-Wei; Du, Jing-Bo; Wang, Zhen-Chang; Yang, Zheng-Han.
Afiliación
  • Ren AH; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, P.R. China.
  • Zhao PF; Department of Radiology, People's Hospital of Beijing DaXing District, Capital Medical University, Beijing, P.R. China.
  • Yang DW; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, P.R. China.
  • Du JB; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, P.R. China.
  • Wang ZC; Department of Radiology, People's Hospital of Beijing DaXing District, Capital Medical University, Beijing, P.R. China.
  • Yang ZH; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, P.R. China.
J Magn Reson Imaging ; 50(3): 746-755, 2019 09.
Article en En | MEDLINE | ID: mdl-30648327
ABSTRACT

BACKGROUND:

The Liver Imaging Reporting and Data System (LI-RADS) is widely adopted for noninvasive diagnosis of hepatocellular carcinoma (HCC). It's updated to version 2018 recently, with some major changes compared with v2017. However, the diagnostic performance of LI-RADS v2018 and its difference with v2017 are yet to be validated.

PURPOSE:

To compare the diagnostic performances of LI-RADS on MR for diagnosing HCC between v2017 and v2018. STUDY TYPE Retrospective.

SUBJECTS:

In all, 181 patients with 217 hepatic observations (146 HCCs, 16 non-HCC malignancies and 55 benign lesions) with liver MRI and pathological or follow-up imaging diagnoses. FIELD STRENGTH/SEQUENCE 1.5 T or 3 T MRI. Dual-echo T1 WI, T2 WI, diffusion-weighted imaging, and a liver acquisition with volume acceleration. Assessment Images were independently interpreted by three radiologists, and then in consensus for observations with different LR categories, according to LI-RADS v2017 and v2018, separately. STATISTICAL TESTS Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), and Youden index.

RESULTS:

When adopting LR-5 as a predictor of HCC, the sensitivity (80.8% vs. 71.2%), NPV (69.6% vs. 60.7%), and accuracy (83.9% vs. 77.9%) were all increased for LI-RADS v2018 compared with v2017, with a greater Youden index (0.709 vs. 0.627). However, the diagnostic performances of MRI for diagnosing HCC were not changed while adopting LR-4/5 as a predictor. The threshold growths of 76% (19/25) observations in v2017 were revised to subthreshold growth in v2018, and 16 LR-4 observations in v2017 were changed to LR-5 based on v2018. DATA

CONCLUSION:

The diagnostic performance of LI-RADS v2018 for diagnosing HCC is superior to v2017, with a greater sensitivity, NPV, and accuracy. The revisions in v2018 mainly affect the categorization when adopting LR-5 as a predictor of HCC. LEVEL OF EVIDENCE 4 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2019;50746-755.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Sistemas de Información Radiológica / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Sistemas de Información Radiológica / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2019 Tipo del documento: Article