LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MRI for early recurrence risk stratification after curative resection

Wei, Hong; Jiang, Hanyu; Zheng, Ting; Zhang, Zhen; Yang, Caiwei; Zheng, Yi; Duan, Ting; Song, Bin

doi:10.1007/s00330-020-07303-9

Cited by 36 publications

(39 citation statements)

References 31 publications

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“…It may be induced by impaired hepatocyte function (45,46) or Kupffer cells injury in tumorous arterioportal shunts (46) because of portal branches obstruction by cancer embolus (i.e., MVI). Controversially, this radiologic feature is paucity of robustness for identifying MVI, RFS or OS in different studies (6,7,15,45,(47)(48)(49). Thus, this equivocal finding needs further study.…”

Section: Discussionmentioning

confidence: 98%

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An excellent nomogram predicts microvascular invasion that cannot independently stratify outcomes of small hepatocellular carcinoma

et al. 2021

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Background: Whether microvascular invasion is a prognosis factor for small hepatocellular carcinoma (sHCC) is controversial, and a preoperatively predictive model based on gadoxetate disodium (Gd-EOB-DTPA) MRI is clinically needed for MVI in sHCC. Methods: Between March 2012 and September 2020, 455 consecutive patients with pathologically confirmed HCC ≤3 cm who underwent hepatectomy and preoperative Gd-EOB-DTPA MRI were retrospectively enrolled. Univariate and multivariate logistic regression combined with cox regression were conducted to find the confounding factors in the cohorts. Propensity score matching (PSM) was employed to balance the biases between MVI and non-MVI groups. Nomogram with C-index visualized the predictive model of MVI. Results: Multivariate logistic regression identified that 5 characteristics (AFP, tumor size, tumor margin, peritumoral enhancement, radiologic capsule) were markedly associated with MVI of sHCC and incorporated into the nomogram with excellent predictive performance in the training (AUC/C-index: 0.884/0.874, n=288), validation (AUC/C-index: 0.845/0.828, n=123) and test cohorts (AUC/C-index: 0.903/0.954, n=44). Before PSM, histologic MVI independently affected tumor recurrence (hazard ratio:1.555, 95% CI: 1.055-2.293, P=0.026). However, due to the confounder of tumor size, there was a significant bias between MVI-positive and MVI-negative groups (propensity score: 0.249±0.105 vs. 0.179±0.106, P<0.001). Meanwhile, the frequency of MVI significantly increased as tumor size growing (P<0.001). After PSM, 70 of 79 MVI cases matched with 171 non-MVI (total 332), and no biases were observed between the two groups (propensity score: 0.238±0.104 vs. 0.217±0.109, P=0.186). Although the median recurrence time in non-MVI sHCC was still longer than that in MVI group (74.3 vs. 43.0 months, P=0.063), MVI was not an independent risk factor for RFS in sHCC. Additionally, MVI was not independently vulnerable to mortality in our population.Conclusions: A preoperative model, mainly based on the peritumoral hallmarks of Gd-EOB-DTPA MRI, showed an excellent performance to predict the occurrence of MVI. Nevertheless, MVI was a potential but not an independent risk factor for recurrence and mortality in sHCC ≤3 cm.

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Section: Discussionmentioning

confidence: 98%

“…According (20,47). Previous study indicated (20) that mosaic architecture independently identified MVI and fat deposition independently predicted recurrence in LR-5 HCC after hepatectomy.…”

Section: Discussionmentioning

confidence: 99%

An excellent nomogram predicts microvascular invasion that cannot independently stratify outcomes of small hepatocellular carcinoma

et al. 2021

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“…Other studies have shown that imaging features defined by LI-RADS as well as LI-RADS categories may stratify risk, predict response to treatment, and inform overall prognosis. 47 , 51 , 53 , 55 , 56 In a study including HCCs, iCCA, and cHCC-CCA, the LI-RADS category was independently correlated with overall survival and recurrence-free survival. 48 In that study, observations categorized as LR-4 or LR-5 had better outcomes than observations categorized as LR-M, regardless of their final histopathologic diagnosis.…”

Section: Future Directionsmentioning

confidence: 99%

“…HCCs that are hyperintense on hepatobiliary phase images have better prognosis, while HCCs with high tumor-to-liver signal ratio or with peritumoral hypointensity on hepatobiliary phase images are associated with worse molecular features, more aggressive behavior, and higher recurrence rates. 50 , 52 , 53 Arterial phase imaging features may help to predict molecular differentiation and biologic behavior. In one study, the presence of irregular rim enhancement on arterial phase images was associated with worse histologic features, such as macrotrabecular pattern, immunomarkers of stemness, and microvascular invasion, and, therefore, worse outcomes.…”

Section: Future Directionsmentioning

confidence: 99%

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Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma

Cunha¹,

Chernyak²,

Fowler³

et al. 2021

JHC

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Hepatocellular carcinoma (HCC) is a leading cause of mortality worldwide and a major healthcare burden in most societies. Computed tomography (CT) and magnetic resonance imaging (MRI) play a pivotal role in the medical care of patients with or at risk for hepatocellular carcinoma (HCC). When stringent imaging criteria are fulfilled, CT and MRI allow for diagnosis, staging, and assessment of response to treatment, without the need for invasive workup, and can inform clinical decision making. Owing to the central role of these imaging modalities in HCC management, standardization is essential to facilitate proper imaging technique, accurate interpretation, and clear communication among all stakeholders in both the clinical practice and research settings. The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system that provides standardization across the continuum of HCC imaging, including ordinal probabilistic approach for reporting that directs individualized management. This review discusses the up-to-date role of CT and MRI in HCC imaging from the LI-RADS perspective. It also provides a glimpse into the future by discussing how advances in knowledge and technology are likely to enrich the LI-RADS approach.

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The Organ Procurement and Transplantation Network hepatocellular carcinoma classification: Alignment with Liver Imaging Reporting and Data System, current gaps, and future direction

Kierans¹,

Chernyak

Mendiratta‐Lala

et al. 2022

Liver Transpl

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The Organ Procurement and Transplantation Network (OPTN) updated its allocation policy for liver transplantation to align with the Liver Imaging Reporting and Data System (LI-RADS) for the diagnosis of hepatocellular carcinoma (HCC). LI-RADS computed tomography/magnetic resonance imaging algorithm had achieved congruency with the American Association for the Study of Liver Diseases (AASLD) HCC Practice Guidance in 2018, and therefore, alignment of OPTN, LI-RADS, and AASLD unifies HCC diagnostic approaches. The two changes to the OPTN HCC classification are adoption of LI-RADS terminology or lexicon for HCC major imaging features as well as the modification of OPTN Class-5A through the adoption of LI-RADS-5 criteria. However, despite this significant milestone, the OPTN allocation policy may benefit from further refinements such as adoption of treatment response assessment criteria after locoregional therapy and categorization criteria for lesions with atypical imaging appearances that are not specific for HCC. In this review, we detail the changes to the OPTN HCC classification to achieve alignment with LI-RADS, discuss current limitations of the OPTN classification, and explore future directions.

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LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MRI for early recurrence risk stratification after curative resection

Cited by 36 publications

References 31 publications

An excellent nomogram predicts microvascular invasion that cannot independently stratify outcomes of small hepatocellular carcinoma

An excellent nomogram predicts microvascular invasion that cannot independently stratify outcomes of small hepatocellular carcinoma

Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma

The Organ Procurement and Transplantation Network hepatocellular carcinoma classification: Alignment with Liver Imaging Reporting and Data System, current gaps, and future direction

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