Evidence map›Paper›PMID 42523677›Full record

ReviewFrontiers in endocrinology2026

The role of artificial intelligence in thyroid cytology of indeterminate nodules: from digital cytology to multimodal precision triage.

Pietro Tralongo, Mariagiovanna Ballato, Vincenzo Fiorentino, Valeria Zuccalà, Cristina Pizzimenti, Ludovica Rita Pepe, Angelica Cardile, Teresa Maria Martorana, Antonio Ieni, Maurizio Martini and 1 more

Erratum issuedAbstract readReview
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In one paragraph

Review in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Pietro TralongoDepartment of Biomedical, Dental and Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy.
Mariagiovanna BallatoDepartment of Biomedical, Dental and Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy.
Vincenzo FiorentinoDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Valeria ZuccalàDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Cristina PizzimentiPathology Unit, Papardo Hospital, Messina, Italy.
Ludovica Rita PepeDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Angelica CardileDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Teresa Maria MartoranaDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Antonio IeniDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Maurizio MartiniDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.
Guido FaddaDepartment of Human Pathology of the Adulthood and of the Developing Age "Gaetano Barresi", University of Messina, Messina, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Indeterminate thyroid cytology is among the most challenging bottlenecks in thyroid nodule management and continues to be a significant source of risk stratification ambiguity and potentially preventable diagnostic surgeries. While molecular analysis has helped refine preoperative risk stratification, especially among Bethesda III (AUS) and Bethesda IV (FN/SFN) thyroid nodules, issues remain regarding positive predictive value, availability, and subsequent malignancy risk, even among those having the "negative" molecular risk assessment. The field of artificial intelligence (AI) is presently experiencing an accelerated trajectory of expansion into thyroid diagnostic fields, extending initially from thyroid ultrasound into the realms of whole-slide cytology analysis and computational pathology. The purpose of this narrative review is to highlight the changing landscape of AI applications in the context of the workup of indeterminate thyroid nodules, focusing on thyroid cytology and decision support for indeterminate thyroid nodules. It is becoming clear from the evidence that AI has the potential to decrease subjectivity and variability in cytology/Whole-Slide Imaging (WSI) analysis, optimize the selection of candidates for biopsy in the upstream process, and optimize post-FNA evaluation by fusion of molecular analysis in the downstream process. Future application will depend upon validation, standardization, and prospectively conducted studies in patients.

Indexed as

Artificial IntelligenceCytodiagnosisThyroid GlandThyroid NeoplasmsThyroid NoduleTriageBiopsy, Fine-NeedleHumansAI-assisted analysiscytologyindeterminate nodulesthyroidwhole slide analysis

Identifiers

PMID42523677
PMCPMC13407368

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.