How to utilize LR-M features of the LI-RADS to improve the diagnosis of combined hepatocellular-cholangiocarcinoma on gadoxetate-enhanced MRI?

Choi

et al. 2020

Liver International

Background and Aims:The Liver Imaging Reporting and Data System (LI-RADS) category M (LR-M) was introduced to preserve the high specificity of LI-RADS algorithm for diagnosing hepatocellular carcinoma (HCC). We aimed to systematically determine the probability of the LR-M for HCC and non-HCC malignancy, and to determine the sources of heterogeneity between reported results. Methods:Original studies reporting the probability of LR-M for HCC and non-HCC malignancy on magnetic resonance imaging (MRI) were identified in MEDLINE and EMBASE. The meta-analytic pooled percentages of HCC and non-HCC in LR-M were calculated. Meta-regression analysis was performed to explore study heterogeneity.The meta-analytic frequency of each LR-M imaging feature was determined. Results:We found 10 studies reporting the diagnostic performance of LR-M (1819 lesions in 1631 patients), and six reporting the frequency of LR-M imaging features.The pooled percentages of HCC and non-HCC malignancy for LR-M were 28.2% (95% confidence interval [CI], 23.8%-33.1%; I 2 = 83%) and 69.6% (95% CI, 64.6%-74.1%; I 2 = 83%) respectively. The study type and MRI scanner field strength were significantly associated with study heterogeneity (P ≤ .04). Of the seven imaging features, rim arterial phase hyperenhancement showed the highest frequency in both non-HCC (48.9%; 95% CI, 43.0%-54.8%) and HCC groups (9.8%; 95% CI, 6.9%-13.6%). Conclusions:The LR-M category most commonly included non-HCC malignancy but also included 28.2% of HCC. Substantial study heterogeneity was noted, and it was significantly associated with study type and MRI scanner field strength. In addition, the frequency of LR-M imaging features was variable. K E Y W O R D Shepatocellular carcinoma; liver imaging reporting and data system; magnetic resonance imaging; systematic review; meta-analysis,

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Liver imaging reporting and data system category M: A systematic review and meta‐analysis

Choi

et al. 2020

Liver International

Magnetic Resonance Imaging

Hepatocellular Carcinoma With Atypical Imaging Features: Review of the Morphologic Hepatocellular Carcinoma Subtypes With Radiology‐Pathology Correlation

Bello

Zaid

Lui

et al. 2021

Hepatocellular carcinoma (HCC) is the fastest growing cause of cancer death in the United States with the incidence rate more than doubling in 20 years. HCC is unique since a noninvasive diagnosis can be achieved with imaging alone when specific clinical criteria and imaging characteristics are met, obviating the need for tissue sampling. However, HCC is a highly heterogeneous neoplasm. Atypical HCC subtypes vary significantly in their morphology, which can be attributed to specific histologic and molecular features, and can cause deviations from the classic imaging characteristics. The different morphologic subtypes of HCC frequently present a diagnostic challenge for radiologists and pathologists since their imaging and pathologic features can overlap with those of non-HCC malignancies. Identifying an atypical subtype can have important clinical implications. Liver transplant, albeit a scarce and limited resource, is the optimal treatment for conventional HCC, potentially curing both the tumor and the underlying pre-malignant condition. Some HCC subtypes as well as mimickers are associated with unacceptably high recurrence and poor outcome after transplant, and there remains limited data on the role and prognosis of liver transplantation for treatment of rare HCC subtypes. Other subtypes tend to recur later than classic HCC, potentially requiring a different follow-up scheme. This review will discuss the appearance of different HCC subtypes in relation to their histopathologic features.

Magnetic Resonance Imaging

Best Practice for MRI Diagnostic Accuracy Research With Lessons and Examples from the LI‐RADS Individual Participant Data Group

van der Pol,

Costa,

Lam

et al. 2023

Medical imaging diagnostic test accuracy research is strengthened by adhering to best practices for study design, data collection, data documentation, and study reporting. In this review, key elements of such research are discussed, and specific recommendations provided for optimizing diagnostic accuracy study execution to improve uniformity, minimize common sources of bias and avoid potential pitfalls. Examples are provided regarding study methodology and data collection practices based on insights gained by the liver imaging reporting and data system (LI‐RADS) individual participant data group, who have evaluated raw data from numerous MRI diagnostic accuracy studies for risk of bias and data integrity. The goal of this review is to outline strategies for investigators to improve research practices, and to help reviewers and readers better contextualize a study's findings while understanding its limitations.Level of Evidence5Technical EfficacyStage 3