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Objectives <p>To assess the 1-year natural history of liver imaging reporting and data system (LI-RADS) 3 observations on contrast-enhanced MRI in cirrhotic patients across multiple international centers, and to identify clinical and imaging predictors of progression using multivariable and machine learning models.</p> Materials and methods <p>This retrospective study included 347 cirrhotic patients with 540 LI-RADS 3 observations from six centers across three countries, each with 12 (±3) months of follow-up MRI. Observations were reassessed using LI-RADS v2018 criteria. Generalized linear mixed-effects models and machine learning (LASSO, random forest) evaluated predictors of progression. Area under the curve (AUC) analysis assessed the predictive performance of clinical and imaging variables.</p> Results <p>Within one year, 28% of LI-RADS 3 observations progressed: 14% to LI-RADS 4 and 14% to LI-RADS 5. Independent predictors of progression included lesion size, with an odds ratio (OR: 1.12, 95% CI: 1.01–1.24), Child–Pugh Class C (OR: 8.36, 95% CI: 1.01–69.27), and alcohol-related liver disease (OR: 0.24, 95% CI: 0.06–0.94). Enhancing capsule and untreated hepatitis C virus were significant in univariable analysis. Imaging features improved predictive accuracy, increasing AUC from 0.65 to 0.72 (<i>p</i> = 0.01). A lesion size cut-off of 9.5 mm was associated with increased progression risk.</p> Conclusion <p>One in four LI-RADS 3 observations progress within one year. Lesion size, liver function, and etiology are key predictors. Integration of imaging features enhances risk stratification and supports more personalized follow-up strategies for indeterminate liver lesions.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis><i> Identifying which LI-RADS 3 liver observations progress to malignancy remains challenging; evidence from large, standardized, multicenter MRI cohorts is lacking</i>.</p> <p><Emphasis Type="BoldItalic">Findings</Emphasis><i> In this large multinational study, 28% of LI-RADS 3 observations progressed within one year; lesion size, liver dysfunction, and disease etiology were key independent predictors</i>.</p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis><i> LI-RADS 3 observations show significant progression risk, with imaging features improving prediction models and guiding surveillance strategies for early HCC detection</i>.</p> Graphical Abstract <p></p>

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A multicenter multinational retrospective study of the 1-year natural history of LI-RADS 3 observations in patients with cirrhosis

  • 期刊论文

  • 发表日期：

    2026年1月6日

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  • Luigi Asmundo,
  • Nathaniel Mercaldo,
  • Felipe Furtado,
  • Alexander Herold,
  • Amirkasra Mojtahed,
  • Mark Anderson,
  • William Bradley,
  • Mina Hesami,
  • Valeria Peña-Trujillo,
  • Antonino Andrea Blandino,
  • Roberto Cannella,
  • Federica Vernuccio,
  • Saubhagya Srivastava,
  • Manjiri Dighe,
  • Manish Dhyani,
  • Dushyant Sahani,
  • Cristiano Sgrazzutti,
  • Nicolò Brandi,
  • Matteo Renzulli,
  • Stefano Fanti,
  • Bhan Irun,
  • Giuseppe Brancatelli,
  • Angelo Vanzulli,
  • Claude Sirlin,
  • Avinash R. Kambadakone,
  • Onofrio A. Catalano

摘要

Objectives

To assess the 1-year natural history of liver imaging reporting and data system (LI-RADS) 3 observations on contrast-enhanced MRI in cirrhotic patients across multiple international centers, and to identify clinical and imaging predictors of progression using multivariable and machine learning models.

Materials and methods

This retrospective study included 347 cirrhotic patients with 540 LI-RADS 3 observations from six centers across three countries, each with 12 (±3) months of follow-up MRI. Observations were reassessed using LI-RADS v2018 criteria. Generalized linear mixed-effects models and machine learning (LASSO, random forest) evaluated predictors of progression. Area under the curve (AUC) analysis assessed the predictive performance of clinical and imaging variables.

Results

Within one year, 28% of LI-RADS 3 observations progressed: 14% to LI-RADS 4 and 14% to LI-RADS 5. Independent predictors of progression included lesion size, with an odds ratio (OR: 1.12, 95% CI: 1.01–1.24), Child–Pugh Class C (OR: 8.36, 95% CI: 1.01–69.27), and alcohol-related liver disease (OR: 0.24, 95% CI: 0.06–0.94). Enhancing capsule and untreated hepatitis C virus were significant in univariable analysis. Imaging features improved predictive accuracy, increasing AUC from 0.65 to 0.72 (p = 0.01). A lesion size cut-off of 9.5 mm was associated with increased progression risk.

Conclusion

One in four LI-RADS 3 observations progress within one year. Lesion size, liver function, and etiology are key predictors. Integration of imaging features enhances risk stratification and supports more personalized follow-up strategies for indeterminate liver lesions.

Key Points

Question Identifying which LI-RADS 3 liver observations progress to malignancy remains challenging; evidence from large, standardized, multicenter MRI cohorts is lacking.

Findings In this large multinational study, 28% of LI-RADS 3 observations progressed within one year; lesion size, liver dysfunction, and disease etiology were key independent predictors.

Clinical relevance LI-RADS 3 observations show significant progression risk, with imaging features improving prediction models and guiding surveillance strategies for early HCC detection.

Graphical Abstract