Hepatocellular Carcinoma in Evolution: Correlation with CEUS                     LI-RADS

Nguyen, Stephanie A; Merrill, Christina; Burrowes, David P.; Medellin, Alexandra; Wilson, Stephanie R.

doi:10.1148/rg.210149

Cited by 5 publications

(5 citation statements)

References 21 publications

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“…Even though the diagnostic performance of imaging and biopsy for small HCC is improving, the accurate diagnosis of dysplastic nodules remains challenging, especially the differential diagnosis between HGDN and well-differentiated HCC. 1,4,31 A combination of a panel of 14 histological criteria has routinely been used to classify small hepatocellular nodules into LRN, dysplastic nodules or HCC. 1 The differential diagnosis is mainly based on histological features supplemented by additional stainings, particularly reticulin staining and immunohistochemical panel (Hsp70, GS and glypican 3).…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, their management differs greatly, from monitoring for dysplastic nodules to curative treatment for HCC. 1,4,5 Telomerase reactivation is a main event in the early stages of liver carcinogenesis. 6 Telomerase reactivation enables uncontrolled cell proliferation leading to malignant transformation and HCC development.…”

Section: Introductionmentioning

confidence: 99%

“…In routine practice, the differential diagnosis between HGDN and very well‐differentiated HCC is often challenging on imaging and also biopsy. Nevertheless, their management differs greatly, from monitoring for dysplastic nodules to curative treatment for HCC 1,4,5 …”

Section: Introductionmentioning

confidence: 99%

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Differential diagnosis of small hepatocellular nodules in cirrhosis: surrogate histological criteria of TERT promoter mutations

Beaufrère,

Paisley,

et al. 2023

Histopathology

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AimsThe differential diagnosis of small hepatocellular nodules in cirrhosis between dysplastic nodules and hepatocellular carcinoma (HCC) remains challenging on biopsy. As TERT promoter (pTERT) mutations may indicate the nodules already engaged in the malignant process, the aim of this study was to identify histological criteria associated with pTERT mutations by detecting these mutations by ddPCR in small formalin‐fixed paraffin‐embedded (FFPE) hepatocellular nodules arising in cirrhosis.Methods and resultsWe built a bicentric cohort data set of 339 hepatocellular nodules < 2 cm from cirrhotic samples, divided into a test cohort of 299 resected samples and a validation cohort of 40 biopsies. Pathological review, based on the evaluation of 14 histological criteria, classified all nodules. pTERT mutations were identified by ddPCR in FFPE samples. Among the 339 nodules, ddPCR revealed pTERT mutations in 105 cases (31%), including 90 and 15 cases in the test and validation cohorts, respectively. On multivariate analysis, three histological criteria were associated with pTERT mutations in the test cohort: increased cell density (P = 0.003), stromal invasion (P = 0.036) and plate‐thickening anomalies (P < 0.001). With the combination of at least two of these major criteria, the AUC for predicting pTERT mutations was 0.84 in the test cohort (sensitivity: 86%, specificity: 83%) and 0.81 in the validation cohort (sensitivity: 87%, specificity: 76%).ConclusionsWe identified three histological criteria as surrogate markers of pTERT mutations that may be used in routine biopsy to more clearly classify small hepatocellular nodules arising in cirrhosis.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Differential diagnosis of small hepatocellular nodules in cirrhosis: surrogate histological criteria of TERT promoter mutations

Beaufrère,

Paisley,

et al. 2023

Histopathology

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“…Diagnosis and reporting of imaging features for hepatocellular carcinoma (HCC) and its pre‐cursor nodules in at risk patients demands a high level of knowledge related to hepatocarcinogenesis 1 as well as recognition of imaging features related to these nodules. Contrast‐enhanced ultrasound (CEUS) has an expanding role in the diagnostic pathway 2–5 .…”

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confidence: 99%

Synoptic Reporting of Focal Liver Masses in at Risk Patients

Lu,

Samuel,

Merrill

et al. 2023

J of Ultrasound Medicine

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ObjectivesReporting contrast‐enhanced ultrasound (CEUS) for focal liver masses in at risk patients is a challenging task. Traditionally used prose reporting (PR) is inconsistent and lacks standardization. We propose synoptic reporting (SR), encompassing algorithmic interpretation and liver imaging and reporting data system (LI‐RADS) categorization.MethodsA software worksheet from Kailo Medical (Melbourne, AU), incorporates the CEUS algorithm for liver interpretation and CEUS LI‐RADS categorization. Part 1. Feasibility of SR: twenty participants of varying experience were presented a brief lecture on SR, algorithmic approach to liver mass interpretation, and CEUS LI‐RADS categorization. Ten representative liver masses were shown as unknown cases. Participants inputted data into SR worksheets. Results and LI‐RADS category were generated solely by SR. Data were categorized as “correct” or “incorrect.” Part 2. Prospective Analysis: Ninety‐one patients for SR and 56 for PR, all were tested for completeness, efficiency, and user satisfaction.ResultsPart 1: Junior participants, pass rate 81.6%, and senior participants, pass rate 83.3% showed no difference in performance. Part 2: Completeness: SR 98.4% and PR 87.0%. Efficiency: Average total time to completion: SR 11 minutes and PR 20 minutes. User satisfaction: Ultrasound technologists, all referring physicians, and six out of seven radiologists preferred SR over PR. Major benefits cited were total time saved, consistency and accuracy in documentation, and report completeness.ConclusionsSR is a reliable and useful tool in clinical practice to report liver masses on ultrasound and assign an appropriate LI‐RADS categorization and management pathway. This ultimately improves communication with referring clinicians and leads to better patient outcomes.

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