Background Histopathological interpretation is crucial for diagnosing inflammatory bowel disease (IBD), distinguishing between Crohn's Disease (CD), Ulcerative Colitis (UC), IBD-Unclassified (IBD-U), and Non-IBD colitis (NIBDC). However, interobserver variability and limited expertise can reduce diagnostic accuracy. Large Language Models (LLMs) such as GPT-5 may offer clinical support in interpreting histology reports.Methods We analyzed 100 real-life histological reports from ileo-colonoscopies, equally representing CD, UC, IBD-U, and NIBDC, collected across five Italian healthcare centers, including both IBD-specialized and non-specialized hospitals. A reference standard was established by an expert pathologist. Independent classifications were generated by GPT-5, five gastrointestinal pathologists, five IBD-expert gastroenterologists (GIs), and five non-expert GIs. Diagnostic performance (accuracy, recall, precision, F1-score), agreement with the reference standard (Cohen's kappa), and inter-rater reliability (Fleiss' kappa) were assessed.Results GPT-5 achieved the highest agreement with the reference standard with the highest accuracy (76.0%), compared to pathologists (68.6%), IBD-experts (69.2%), and non-experts (63.2%). Agreement with the reference standard was substantial for GPT-5 (kappa = 0.671) and moderate for human groups (kappa = 0.508-0.588). GPT-5 showed perfect recall for CD and UC, high recall for NIBDC (96.0%), but poor performance for IBD-U (recall 8.0%, F1-score 14.3%). Fleiss' kappa indicated moderate agreement among pathologists and IBD-experts, and fair agreement among non-experts.Conclusion GPT-5 demonstrated reliable performance in interpreting IBD histological reports, exhibiting high accuracy and strong agreement with the reference standard. While unreliable for IBD-U, GPT-5 may serve as a supportive tool in histopathological interpretation of IBD, particularly in centers with limited access to expert pathologists or IBD-specialists.

Maida, M., Vitello, A., Macaluso, F.S., Daperno, M., Mocci, G., Rispo, A., et al. (2026). Performance of GPT-5 in the Interpretation of IBD Histopathology Reports. UNITED EUROPEAN GASTROENTEROLOGY JOURNAL, 14(1), 1-7 [10.1002/ueg2.70161].

Performance of GPT-5 in the Interpretation of IBD Histopathology Reports

Marasco G.
;
Facciorusso A.;
2026

Abstract

Background Histopathological interpretation is crucial for diagnosing inflammatory bowel disease (IBD), distinguishing between Crohn's Disease (CD), Ulcerative Colitis (UC), IBD-Unclassified (IBD-U), and Non-IBD colitis (NIBDC). However, interobserver variability and limited expertise can reduce diagnostic accuracy. Large Language Models (LLMs) such as GPT-5 may offer clinical support in interpreting histology reports.Methods We analyzed 100 real-life histological reports from ileo-colonoscopies, equally representing CD, UC, IBD-U, and NIBDC, collected across five Italian healthcare centers, including both IBD-specialized and non-specialized hospitals. A reference standard was established by an expert pathologist. Independent classifications were generated by GPT-5, five gastrointestinal pathologists, five IBD-expert gastroenterologists (GIs), and five non-expert GIs. Diagnostic performance (accuracy, recall, precision, F1-score), agreement with the reference standard (Cohen's kappa), and inter-rater reliability (Fleiss' kappa) were assessed.Results GPT-5 achieved the highest agreement with the reference standard with the highest accuracy (76.0%), compared to pathologists (68.6%), IBD-experts (69.2%), and non-experts (63.2%). Agreement with the reference standard was substantial for GPT-5 (kappa = 0.671) and moderate for human groups (kappa = 0.508-0.588). GPT-5 showed perfect recall for CD and UC, high recall for NIBDC (96.0%), but poor performance for IBD-U (recall 8.0%, F1-score 14.3%). Fleiss' kappa indicated moderate agreement among pathologists and IBD-experts, and fair agreement among non-experts.Conclusion GPT-5 demonstrated reliable performance in interpreting IBD histological reports, exhibiting high accuracy and strong agreement with the reference standard. While unreliable for IBD-U, GPT-5 may serve as a supportive tool in histopathological interpretation of IBD, particularly in centers with limited access to expert pathologists or IBD-specialists.
2026
Maida, M., Vitello, A., Macaluso, F.S., Daperno, M., Mocci, G., Rispo, A., et al. (2026). Performance of GPT-5 in the Interpretation of IBD Histopathology Reports. UNITED EUROPEAN GASTROENTEROLOGY JOURNAL, 14(1), 1-7 [10.1002/ueg2.70161].
Maida, M.; Vitello, A.; Macaluso, F. S.; Daperno, M.; Mocci, G.; Rispo, A.; Calabrese, G.; Decarli, N. L.; Laschi, L.; Fattorini, C.; Locci, G.; Sordo...espandi
File in questo prodotto:
File Dimensione Formato  
1M.pdf

accesso aperto

Tipo: Versione (PDF) editoriale / Version Of Record
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 881.38 kB
Formato Adobe PDF
881.38 kB Adobe PDF Visualizza/Apri
ueg270161-sup-0001-suppl-data.docx

accesso aperto

Tipo: File Supplementare
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 295.04 kB
Formato Microsoft Word XML
295.04 kB Microsoft Word XML Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1039370
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact