Evidence map›Paper›PMID 40726356›Full record

ArticleNeuropathology : official journal of the Japanese Society of Neuropathology2025

Diagnostic Performance of ChatGPT-4.0 in Histopathological Analysis of Gliomas: A Single Institution Experience.

Manuel Mazzucchelli, Serena Salzano, Rosario Caltabiano, Gaetano Magro, Francesco Certo, Giuseppe Barbagallo, Giuseppe Broggi

Abstract read
In one paragraph

Article in Neuropathology : official journal of the Japanese Society of Neuropathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Diagnostic Performance of ChatGPT-4.0 in Histopathological Analysis of Gliomas: A Single Institution Experience.Neuropathology : official journal of the Japanese Society of Neuropathology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Manuel MazzucchelliDepartment of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Anatomic Pathology, University of Catania, Catania, Italy.ORCID https://orcid.org/0009-0004-8288-8521
Serena SalzanoDepartment of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Anatomic Pathology, University of Catania, Catania, Italy.ORCID https://orcid.org/0009-0005-3669-8759
Rosario CaltabianoDepartment of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Anatomic Pathology, University of Catania, Catania, Italy.ORCID https://orcid.org/0000-0001-8591-8010
Gaetano MagroDepartment of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Anatomic Pathology, University of Catania, Catania, Italy.
Francesco CertoDepartment of Neurological Surgery, Policlinico "G. Rodolico-S. Marco", University Hospital, Catania, Italy.
Giuseppe BarbagalloDepartment of Neurological Surgery, Policlinico "G. Rodolico-S. Marco", University Hospital, Catania, Italy.
Giuseppe BroggiDepartment of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Anatomic Pathology, University of Catania, Catania, Italy.ORCID https://orcid.org/0000-0003-2576-6523

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to evaluate the performance of ChatGPT-4.0 as a diagnostic support tool for pathologists in identifying different types of gliomas based on histopathological data and to compare its performance with that of another artificial intelligence tool (Gemini 2.5 Pro). A retrospective analysis was performed on 25 cases with histopathological descriptions. The dataset, anonymized for patient confidentiality, included clinical details such as age, sex, and site, along with two histological images for each case, obtained from the archive files of the Anatomic Pathology section, Department of Medical, Surgical Sciences and Advanced Technologies "G.F. Ingrassia" University of Catania, Italy. ChatGPT-4.0 was tasked with generating diagnoses, which were classified as correct, similar, or different when compared to the pathologists' conclusions and the diagnoses provided by Gemini. ChatGPT-4.0 achieved a diagnostic accuracy of 88%, correctly identifying 22 out of 25 cases. No significant differences in diagnostic performance were observed between male and female patients. The AI performed exceptionally well in diagnosing glioblastomas, with a 100% accuracy rate, while two oligodendrogliomas and one astrocytoma IDH-mutant G3 were misdiagnosed. A comparative evaluation with Gemini 2.5 Pro was also conducted, although its contribution was limited to a qualitative comparison based on the same dataset. ChatGPT-4.0 demonstrated moderate accuracy in the histopathological diagnosis of gliomas, with little variability depending on glioma subtype. While its performance highlights potential for future integration into clinical workflows, significant improvements are required to ensure its reliability and effectiveness in diagnostic applications. Trial Registration: ce 165/2015/PO.

Indexed as

Artificial IntelligenceBrain NeoplasmsGliomaAdultAgedFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedRetrospective StudiesYoung Adultartificial intelligencecentral nervous system tumorsChatGPTGeminineuropathology

Identifiers

PMID40726356
PMCPMC12305399

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.