LI-RADS and transplantation: challenges and controversies

Hepatocellular Carcinoma: Optimal Radiological Evaluation before Liver Transplantation

Liver transplantation (LT) is the recommended curative-intent treatment for patients with early or intermediate-stage hepatocellular carcinoma (HCC) who are ineligible for resection. Imaging plays a central role in staging and for selecting the best LT candidates. This review will discuss recent developments in pre-LT imaging assessment, in particular LT eligibility criteria on imaging, the technical requirements and the diagnostic performance of imaging for the pre-LT diagnosis of HCC including the recent Liver Imaging Reporting and Data System (LI-RADS) criteria, the evaluation of the response to locoregional therapy, as well as the non-invasive prediction of HCC aggressiveness and its impact on the outcome of LT. We will also briefly discuss the role of nuclear medicine in the pre-LT evaluation and the emerging role of artificial intelligence models in patients with HCC.

Prospective evaluation of Gadoxetate-enhanced magnetic resonance imaging and computed tomography for hepatocellular carcinoma detection and transplant eligibility assessment with explant histopathology correlation

BACKGROUND

We aimed to prospectively compare the diagnostic performance of gadoxetic acid-enhanced MRI (EOB-MRI) and contrast-enhanced Computed Tomography (CECT) for hepatocellular carcinoma (HCC) detection and liver transplant (LT) eligibility assessment in cirrhotic patients with explant histopathology correlation.

METHODS

In this prospective, single-institution ethics-approved study, 101 cirrhotic patients were enrolled consecutively from the pre-LT clinic with written informed consent. Patients underwent CECT and EOB-MRI alternately every 3 months until LT or study exclusion. Two blinded radiologists independently scored hepatic lesions on CECT and EOB-MRI utilizing the liver imaging reporting and data system (LI-RADS) version 2018. Liver explant histopathology was the reference standard. Pre-LT eligibility accuracies with EOB-MRI and CECT as per Milan criteria (MC) were assessed in reference to post-LT explant histopathology. Lesion-level and patient-level statistical analyses were performed.

RESULTS

Sixty patients (49 men; age 33-72 years) underwent LT successfully. One hundred four non-treated HCC and 42 viable HCC in previously treated HCC were identified at explant histopathology. For LR-4/5 category lesions, EOB-MRI had a higher pooled sensitivity (86.7% versus 75.3%, p <  0.001) but lower specificity (84.6% versus 100%, p <  0.001) compared to CECT. EOB-MRI had a sensitivity twice that of CECT (65.9% versus 32.2%, p <  0.001) when all HCC identified at explant histopathology were included in the analysis instead of imaging visible lesions only. Disregarding the hepatobiliary phase resulted in a significant drop in EOB-MRI performance (86.7 to 72.8%, p <  0.001). EOB-MRI had significantly lower pooled sensitivity and specificity versus CECT in the LR5 category with lesion size < 2 cm (50% versus 79%, p = 0.002 and 88.9% versus 100%, p = 0.002). EOB-MRI had higher sensitivity (84.8% versus 75%, p <  0.037) compared to CECT for detecting < 2 cm viable HCC in treated lesions. Accuracies of LT eligibility assessment were comparable between EOB-MRI (90-91.7%, p = 0.156) and CECT (90-95%, p = 0.158).

CONCLUSION

EOB-MRI had superior sensitivity for HCC detection; however, with lower specificity compared to CECT in LR4/5 category lesions while it was inferior to CECT in the LR5 category under 2 cm. The accuracy for LT eligibility assessment based on MC was not significantly different between EOB-MRI and CECT.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03342677 , Registered: November 17, 2017.

Performance of LI-RADS Version 2018 on CT for Determining Eligibility for Liver Transplantation According to Milan Criteria in Patients at High Risk for Hepatocellular Carcinoma

Background: LI-RADS has been investigated primarily in terms of detection of hepatocellular carcinoma (HCC), with less attention given to its performance, particularly on CT, in determining eligibility for liver transplantation (LT). Objectives: To assess performance of LI-RADS version 2018 (v2018) on CT for diagnosis of HCC and determination of LT eligibility according to Milan criteria (MC). Methods: This retrospective study included 136 patients (mean age, 53.9±8.1 years; 110 men, 26 women) at high-risk for HCC who underwent liver-protocol CT within 3 months before LT between January 2010 and December 2018. Two radiologists independently reviewed CT examinations using LI-RADS v2018; OPTN classes were constructed from the LI-RADS interpretations. Histopathologic analysis of liver explants served as reference for determining presence of HCC and LT eligibility based on MC. Diagnostic performance was evaluated. Overall survival (OS) was assessed based on medical record review. Results: Based on histopathologic evaluation of liver explants in the 136 patients, 27 had no malignancy, 77 were eligible for LT due to HCC within MC, and 32 were unsuitable for LT (HCC beyond MC in 16, HCC with macrovascular invasion in 12, non-HCC malignancy in 4). LR-5 exhibited per-lesion sensitivity and PPV for HCC of 55.9% and 92.8% for reader 1, and 39.8% and 86.5% for reader 2. When considering LR-5 observations to represent HCC in assessing MC, LI-RADS had accuracy for determining LT eligibility of 92.7% for reader 1 and 85.3% for reader 2; OPTN had accuracy for determining LT eligibility of 89.0% for reader 1 and 84.4% for reader 2. Five-year OS for those within MC versus unsuitable for LT was 92.2 months versus 56.0 months for LI-RADS, 93.4 months versus 53.8 months for OPTN, and 93.3 months versus 55.1 months for histopathologic assessment of liver explants. Conclusions: LI-RADS v2018, as evaluated on CT in high-risk patients, demonstrates high PPV for HCC detection and high accuracy for determining LT eligibility based on MC. LT eligibility based on preoperative LI-RADS evaluation is associated with post-LT survival. Clinical Impact: These findings support the use of LI-RADS on CT in assessing eligibility in patients who are candidates for LT.

Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evaluate their methodological quality. The methodological quality was assessed by the Radiomics Quality Score (RQS), and the risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Twenty-two studies using CT, MRI, or PET/CT for MVI prediction were included. All were retrospective studies, and only two had an external validation cohort. The AUC values of the prediction models ranged from 0.69 to 0.94 in the test cohort. Substantial methodological heterogeneity existed, and the methodological quality was low, with an average RQS score of 10 (28% of the total). Most studies demonstrated a low or unclear risk of bias in the domains of QUADAS-2. In conclusion, a radiomics model could be an accurate and effective tool for MVI prediction in HCC patients, although the methodological quality has so far been insufficient. Future prospective studies with an external validation cohort in accordance with a standardized radiomics workflow are expected to supply a reliable model that translates into clinical utilization.

Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

Simple Summary

Microvascular invasion (MVI) is regarded as a sign of early metastasis in liver cancer and can be only diagnosed by a histopathology exam in the resected specimen. Preoperative prediction of MVI status may exert an effect on patient treatment management, for instance, to expand the resection margin. Radiomics can identify delicate imaging features from routinely used radiological images that are invisible to the naked eye and has been increasingly adopted to predict MVI. We reviewed the available radiomics models to evaluate their role in the prediction of MVI. The discriminative capacity of the models ranged from 0.69 to 0.94. Even though the studies were preliminary and the methodologic quality was suboptimal, radiomics models hold promise for the accurate and non-invasive prediction of MVI. In accordance with a standardized radiomics workflow, future prospective studies with external validation are expected to provide a reliable and robust prediction tool for clinical implementation.

Abstract

Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evaluate their methodological quality. The methodological quality was assessed by the Radiomics Quality Score (RQS), and the risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Twenty-two studies using CT, MRI, or PET/CT for MVI prediction were included. All were retrospective studies, and only two had an external validation cohort. The AUC values of the prediction models ranged from 0.69 to 0.94 in the test cohort. Substantial methodological heterogeneity existed, and the methodological quality was low, with an average RQS score of 10 (28% of the total). Most studies demonstrated a low or unclear risk of bias in the domains of QUADAS-2. In conclusion, a radiomics model could be an accurate and effective tool for MVI prediction in HCC patients, although the methodological quality has so far been insufficient. Future prospective studies with an external validation cohort in accordance with a standardized radiomics workflow are expected to supply a reliable model that translates into clinical utilization.

A retrospective single-centre analysis of the oncological impact of LI-RADS classification applied to Metroticket 2.0 calculator in liver transplantation: every nodule matters

Although the diagnostic value of Liver Imaging Reporting and Data System (LI-RADS) protocol is well recognized in clinical practice, its role in liver transplant (LT) setting is under-explored. We sought to evaluate the oncological impact of LI-RADS classification applied to Metroticket 2.0 calculator in a single-centre retrospective cohort of transplanted hepatocellular carcinoma (HCC) patients, exploring which LI-RADS subclasses need to be considered in order to grant the best Metroticket 2.0 performance. The most recent pre-LT imaging of 245 patients undergoing LT for HCC between 2005 and 2015 was retrospectively and blindly reviewed, classifying all nodules according to LI-RADS protocol. Metroticket 2.0 accuracy was subsequently tested incorporating all vital nodules identified during multi-disciplinary team (MDT) meetings attended before LI-RADS reclassification of the latest pre-LT imaging, LR-5 and LR-treatment-viable (LR-TR-V), LR-4/5 and LR-TR-V, and LR-3/4/5 and LR-TR-V nodules respectively. Considering their extremely low probability for harbouring HCC, LR-1 and LR-2 nodules were not considered in this analysis. Incorporation of all HCCs identified during MDT meetings attended before LI-RADS reclassification of the latest pre-LT imaging resulted in a Metroticket 2.0 c-index of 0.72, [95% confidence interval (CI) 0.64-0.80]. Metroticket 2.0 c-index dropped to 0.60 [95% CI: 0.48-0.72] when LI-RADS-5 and LI-RADS-TR-V (P = 0.0089) or LI-RADS-5, LI-RADS-4 and LI-RADS-TR-V (P = 0.0068) nodules were entered in the calculator. Conversely, addition of LI-RADS-3 HCCs raised the Metroticket 2.0 c-index to 0.65 [95% CI: 0.54-0.86], resulting in a not statistically significant diversion from the original performance (0.72 vs. 0.65; P = 0.08). Exclusion of LR-3 and LR-4 nodules from Metroticket 2.0 calculator resulted in a significant drop in its accuracy. Every nodule with an intermediate-to-high probability of harbouring HCC according to LI-RADS protocol seems to contribute to tumour burden and should be entered in the Metroticket 2.0 calculator in order to grant appropriate performance.

Magnetic Resonance Imaging of Liver Transplant

MR imaging increasingly has been adopted for follow-up imaging post-liver transplantation and for diagnosis of its complications. These include vascular and biliary complications as well as post-transplant malignancies. Interpretation of postoperative MR imaging should take into account the surgical technique and expected post-transplant changes. Contrast-enhanced MR imaging has high sensitivity for identification of vascular complications. MR cholangiopancreatography on the other hand is the most accurate noninvasive method for evaluation of biliary complications.