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Modifying LI-RADS on Gadoxetate Disodium-Enhanced MRI: A Secondary Analysis of a Prospective Observational Study.
Jiang, Hanyu; Song, Bin; Qin, Yun; Konanur, Meghana; Wu, Yuanan; McInnes, Matthew D F; Lafata, Kyle J; Bashir, Mustafa R.
Afiliação
  • Jiang H; Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Song B; Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.
  • Qin Y; Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Konanur M; Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Wu Y; Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.
  • McInnes MDF; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Lafata KJ; Departments of Radiology and Epidemiology, University of Ottawa, Ottawa, Ontario, Canada.
  • Bashir MR; Clinical Epidemiology Program, The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
J Magn Reson Imaging ; 56(2): 399-412, 2022 08.
Article em En | MEDLINE | ID: mdl-34994029
BACKGROUND: The Liver Imaging Reporting and Data System (LI-RADS) is widely used for diagnosing hepatocellular carcinoma (HCC), however, with unsatisfactory sensitivity, complex ancillary features, and inadequate integration with gadoxetate disodium (EOB)-enhanced MRI. PURPOSE: To modify LI-RADS (mLI-RADS) on EOB-MRI. STUDY TYPE: Secondary analysis of a prospective observational study. POPULATION: Between July 2015 and September 2018, 224 consecutive high-risk patients (median age, 51 years; range, 26-83; 180 men; training/testing sets: 169/55 patients) with 742 (median size, 13 mm; interquartile range, 7-27; 498 HCCs) LR-3/4/5 observations. FIELD STRENGTH/SEQUENCE: 3.0 T T2 -weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar, and 3D T1 -weighted gradient echo sequences. ASSESSMENT: Three radiologists (with 5, 5, and 10 years of experience in liver MR imaging, respectively) blinded to the reference standard (histopathology or imaging follow-up) reviewed all MR images independently. In the training set, the optimal LI-RADS version 2018 (v2018) features selected by Random Forest analysis were used to develop mLI-RADS via decision tree analysis. STATISTICAL TESTS: In an independent testing set, diagnostic performances of mLI-RADS, LI-RADS v2018, and the Korean Liver Cancer Association (KLCA) guidelines were computed using a generalized estimating equation model and compared with McNemar's test. A two-tailed P < 0.05 was statistically significant. RESULTS: Five features (nonperipheral "washout," restricted diffusion, nonrim arterial phase hyperenhancement [APHE], mild-moderate T2 hyperintensity, and transitional phase hypointensity) constituted mLI-RADS, and mLR-5 was nonperipheral washout coupled with either nonrim APHE or restricted diffusion. In the testing set, mLI-RADS was significantly more sensitive (72%) and accurate (80%) than LI-RADS v2018 (sensitivity, 61%; accuracy 74%; both P < 0.001) and the KLCA guidelines (sensitivity, 64%; accuracy 74%; both P < 0.001), without sacrificing positive predictive value (mLI-RADS, 94%; LI-RADS v2018, 94%; KLCA guidelines, 92%). DATA CONCLUSION: In high-risk patients, the EOB-MRI-based mLI-RADS was simpler and more sensitive for HCC than LI-RADS v2018 while maintaining high positive predictive value. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Idioma: En Ano de publicação: 2022 Tipo de documento: Article