CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis.
Christian B van der PolMatthew D F McInnesJean-Paul SalamehBrooke LevisVictoria ChernyakClaude B SirlinMustafa R BashirBrian C AllenLauren M B BurkeJin-Young ChoiSang Hyun ChoiAlejandro FornerTyler J FraumAlice GiamperoliHanyu JiangIjin JooZhen KangAndrea Siobhan KieransHyo-Jin KangGaurav KhatriJung Hoon KimMyeong Jin KimSo Yeon KimYeun-Yoon KimHee Jin KwonJeong Min LeeChristopher SongKatrina A McGintyLorenzo MulazzaniChang Moo KangPiscaglia FabioJoanna PodgórskaCaecilia S ReinerMaxime RonotGrzegorz RosiakSong BinJi Soo SongAn TangEleonora TerziJin WangWei WangStephanie R WilsonTakeshi YokooPublished in: Radiology (2021)
Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study design flaws. Conclusion Most Liver Imaging Reporting and Data System major features had different independent associations with hepatocellular carcinoma; for CT/MRI, arterial phase hyperenhancement and washout had the strongest associations, whereas threshold growth had no association. © RSNA, 2021 Online supplemental material is available for this article.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- diffusion weighted
- computed tomography
- magnetic resonance
- diffusion weighted imaging
- ion batteries
- contrast enhanced ultrasound
- dual energy
- systematic review
- case control
- electronic health record
- big data
- machine learning
- high resolution
- solid state
- deep learning
- case report
- chronic kidney disease
- randomized controlled trial
- end stage renal disease
- newly diagnosed
- image quality
- artificial intelligence
- emergency department
- photodynamic therapy
- sensitive detection
- meta analyses
- convolutional neural network
- quantum dots
- mass spectrometry
- patient reported outcomes