Added‑value of ancillary imaging features for differentiating hepatocellular carcinoma from intrahepatic mass‑forming cholangiocarcinoma on Gd‑BOPTA‑enhanced MRI in LI‑RADS M
Zheng W, Huang H, She D, Xiong M, Chen X, Lin X, Cao D
Abdom Radiol 2022 Mar;47:957-968. doi: 10.1007/s00261-021-03380-6
The Liver Imaging Reporting and Data System (1) is an imaging-based diagnostic system applicable in patients at high risk of hepatocellular carcinoma (HCC) (2). In LI-RADS, each liver observation is assigned a category that reflects probability of malignancy (2). LI-RADS M (LR-M) is a category for liver lesions that are definitely or probably malignant, but not specific for hepatocellular carcinoma (HCC) (1, 3). LR-M primarily aims to maintain the high specificity of LR-5 without sacrificing sensitivity to diagnose hepatic malignancies (1). HCC and intrahepatic mass-forming cholangiocarcinoma (IMCC) are the two predominant types in the LR-M group (4).
In this study, the authors aimed to identify reliable imaging features on Gd-BOPTA-enhanced MRI and determine the value of adding ancillary imaging features to distinguish HCC and IMCC in LR-M patients. Data were retrospectively collected from consecutive patients with pathologically proven HCC or IMCC. The inclusion criteria were as follows: a) pathologically proven HCC or IMCC by surgical resection or liver puncture; b) patients underwent Gd-BOPTA-enhanced MRI within three months before surgery or liver puncture; and c) patients were suitable for the LI-RADS categorization system according to the LI-RADS v2018 criteria. Among the remaining potentially eligible patients, only patients with liver lesions classified as LR-M were included, resulting in a final population of 116 patients with HCC (n= 82) and IMCC (n=34).
The LI-RADS imaging features were independently analyzed by two radiologists (with 11 and 5 years of experience in abdominal imaging). If the observations were classified to LR-M, the two readers would evaluate ancillary imaging features simultaneously.
Multivariable logistic regression analysis was performed to identify independent predictors to diagnose HCC among LR-M observations.
HCCs showed significantly more often an enhancing capsule (59.8%), while in IMCCs targetoid appearance on DWI (29.4%) and HBP (73.5%) were more common. Among the ancillary imaging features blood product in mass, fat in mass, mosaic architecture, round margin, intratumoral septa and small-scale central HBP hyperintensity were significantly more frequent in HCC. Peritumoral biliary dilatation and cloud-like enhancement on HBP were significantly more frequent in IMCC.
In the multivariable logistic regression analysis enhancing capsule, intratumoral septa and small-scale central HBP hyperintensity were identified as independent predictors for HCC over IMCC. The model where ancillary imaging features were added demonstrated a significantly superior AUC (0.918 vs. 0.845, p=0.021) and sensitivity (91.5% vs. 79.3%), but lower specificity (79.4% vs. 85.3%) compared to the model without ancillary imaging features for diagnosing HCC.
This study is of interest as it brings light into the wide category of LR-M. Among the large number of ancillary features only two were identified as independent predictors, which may be easily assessed in addition to the major features and LR-M characteristics.
Limitations of this study are the exclusion of other non-HCC malignancies and the rather small study population. Since most patients had hepatitis B viral infection and Child–Pugh class A the results have limited generalizability. Furthermore, the results may not be transferable to Gd-EOB-DTPA enhanced liver MRI.
Nevertheless, ancillary imaging features have shown potential in the differentiation of LI-RADS M lesions in this study. Further studies including a larger study population, other non-HCC malignancies (i.e. combined HCC-ICC), and different contrast agents are needed to prove applicability and eventual incorporation in the LI-RADS classification.
References:
- Tang A, Bashir MR, Corwin MT, et al.Evidence Supporting LI-RADS Major Features for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review. Radiology. 2018;286(1):29-48.
- Chernyak V, Santillan CS, Papadatos D, Sirlin CB. LI-RADS((R)) algorithm: CT and MRI. Abdom Radiol (NY). 2018;43(1):111-26.
- (2018). RAACoR;Pages. Accessed at https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS/CT-MRI-LI-RADS-v2018.
- Fowler KJ, Potretzke TA, Hope TA, et al.LI-RADS M (LR-M): definite or probable malignancy, not specific for hepatocellular carcinoma. Abdom Radiol (NY). 2018;43(1):149-57.
Lisa Jungblut is a fourth-year radiology resident at the University Hospital Zurich. During her residency she has spent 12 months as research scholar and has been involved in several research studies centered on chest imaging.
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