Simplifying CT/MRI LI-RADS v2018 Maintains Diagnostic Performance: An Individual Participant Data Meta-Analysis
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E Lam1, M M G Leeflang2, R G Adamo1
1Faculty of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
Background:
The Liver Imaging Reporting and Data System (LI-RADS) diagnostic algorithm assesses hepatocellular carcinoma (HCC) probability of liver observations in high-risk individuals, but complexity may limit its adoption.
Purpose:
To evaluate whether LI-RADS v2018 can be simplified without impairing diagnostic performance by removing threshold growth (TG) and reducing size cut-offs.
Study Type:
Retrospective meta-analysis.
Population:
Eight thousand five hundred eighty-two patients (mean age: 59 ± 11 years; 6610 male) at risk for HCC with CT/MRI (986 CT, 6554 MRI, and 1042 CT/MRI).
Field Strength/Sequence:
Field strength: 1.5T and 3.0T; sequences varied by institution per LI-RADS technical requirements.
Assessment:
LI-RADS v2018 using major features only was compared with seven simplifications removing TG and/or applying single size cut-offs (≥ 10, ≥ 15, and ≥ 20 mm) in individual participant data (IPD) of 64 studies (29 institutions, 11 countries) from the LI-RADS Living Systematic Review and IPD Meta-analysis Project. Risk of bias was assessed with QUADAS-2.
Statistical Tests:
Summary receiver operating characteristic curves estimated area under the curve (AUC) across LR-3 to LR-5; LR-5 sensitivity, specificity, and positive predictive value (PPV) were estimated using a one-step bivariate mixed-effects model. Differences were assessed by cluster bootstrap. p < 0.05 indicated significance, uncorrected for multiple comparisons.
Results:
Nine thousand four hundred six observations were included. Excluding TG with a 10-mm cut-off showed AUC similar to LI-RADS v2018 (0.80 vs. 0.81, p = 0.44) and significantly higher LR-5 sensitivity (73.8% vs. 71.8%) with similar specificity (72.5% vs. 73.7%, p = 0.13) and PPV (97.8% vs. 97.8%, p = 0.73). Removing TG with 15-mm and 20-mm cut-offs had significantly lower AUC than v2018 (-0.03 [95% CI: -0.041, -0.019]; -0.043 [-0.054, -0.032], respectively) and sensitivity (-13.2% [95% CI: -14.5%, -12.0%]; -30.1% [-31.7%, -28.5%], respectively). Of the 64 studies, 17 had low-risk of bias, and 56 had low applicability concerns.
Conclusion:
Simplifying LI-RADS v2018 by removing TG and using a 10-mm size cut-off preserved diagnostic table AUC while improving LR-5 sensitivity without loss of specificity or PPV.
Protocol Registration:
Open Science Framework (https://osf.io/cjwgp).
Evidence Level:
3.
Technical Efficiency:
Stage 2.