Evidence map›Paper›PMID 42722940›Full record

ArticleAnnals of surgical oncology2026

Concordance Between a Generative Artificial Intelligence Model and a Hepatobiliary Multidisciplinary Team in Hepatocellular Carcinoma Management: A Retrospective Study.

Cristina Ciulli, Emanuele Scarpa, Pasquale Chiacchio, Alessandro Fogliati, Mauro Alessandro Scotti, Antonio Ciaccio, Antonio Rovere, Christian Cotsoglou, Rita Niespolo, Federica Elisei and 4 more

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Article in Annals of surgical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Cristina Ciulli *General Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.ORCID http://orcid.org/0000-0003-0911-5114
Emanuele Scarpa *University of Milano-Bicocca, Milano, Italy.ORCID http://orcid.org/0009-0008-4196-3889
Pasquale ChiacchioUniversity of Milano-Bicocca, Milano, Italy.
Alessandro FogliatiGeneral Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Mauro Alessandro ScottiGeneral Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Antonio CiaccioGastroenterology, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Antonio RovereRadiology, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Christian CotsoglouGeneral Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Rita NiespoloRadiotherapy, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Federica EliseiNuclear Medicine, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Michele Pietro ApriglianoAnesthesiology, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Lorenzo RipamontiGeneral Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.
Mattia GaranciniGeneral Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy. mattia.garancini@irccs-sangerardo.it.
Fabrizio RomanoGeneral Surgery Department, IRCCS San Gerardo dei Tintori di Monza Foundation, Monza, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe management of hepatocellular carcinoma (HCC) relies on decisions formulated by a multidisciplinary team (MDT). Generative artificial intelligence (AI) models are increasingly explored as decision-support tools. This study aimed to assess the level of agreement between AI-generated recommendation and expert MDT decisions in HCC management.

methodsA retrospective cohort of 100 HCC patients discussed at a hepatobiliary MDT between January 2023 and February 2025 was retrospectively included. Anonymized case summaries, excluding MDT conclusion, were submitted to a large language AI model (ChatGPT-4). Recommendations were categorized using the following four-level progressive concordance scale: (1) treatment aim (curative vs palliative), (2) treatment extent (locoregional vs systemic), (3) treatment modality (e.g., resection, ablation, embolization), and (4) specific technique. Concordance levels 1 and 2 were classified as low concordance (LC), whereas levels 3 and 4 were classified as high concordance (HC).

resultsIn 81 % of the cases, HC between AI-generated and MDT recommendations was observed, with 53 % showing complete agreement on treatment technique. In 19 % of the cases, LC was identified and associated with older patient age (p = 0.001). In most discordant cases, discrepancies reflected the MDT's preference for more aggressive, tailored interventions.

conclusionsIn HCC management, AI demonstrated a high level of agreement with expert MDT decisions, suggesting its potential role as a complementary decision-support tool. However, limitations persist for elderly patients and borderline clinical scenarios, in which individualized human judgment remains essential.

Indexed as

AIGenerative artificial intelligenceHCCHepatocellular carcinomaMDTMultidisciplinary team

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