The development of artificial intelligence in the histological diagnosis of Inflammatory Bowel Disease (IBD-AI).
Dig Liver Dis
; 2024 Jun 08.
Article
en En
| MEDLINE
| ID: mdl-38853093
ABSTRACT
BACKGROUND:
Inflammatory bowel disease (IBD) includes Crohn's Disease (CD) and Ulcerative Colitis (UC). Correct diagnosis requires the identification of precise morphological features such basal plasmacytosis. However, histopathological interpretation can be challenging, and it is subject to high variability.AIM:
The IBD-Artificial Intelligence (AI) project aims at the development of an AI-based evaluation system to support the diagnosis of IBD, semi-automatically quantifying basal plasmacytosis.METHODS:
A deep learning model was trained to detect and quantify plasma cells on a public dataset of 4981 annotated images. The model was then tested on an external validation cohort of 356 intestinal biopsies of CD, UC and healthy controls. AI diagnostic performance was calculated compared to human gold standard.RESULTS:
The system correctly found that CD and UC samples had a greater prevalence of basal plasma cells with mean number of PCs within ROIs of 38.22 (95 % CI 31.73, 49.04) for CD, 55.16 (46.57, 65.93) for UC, and 17.25 (CI 12.17, 27.05) for controls. Overall, OR=4.968 (CI 1.835, 14.638) was found for IBD compared to normal mucosa (CD +59 %; UC +129 %). Additionally, as expected, UC samples were found to have more plasma cells in colon than CD cases.CONCLUSION:
Our model accurately replicated human assessment of basal plasmacytosis, underscoring the value of AI models as a potential aid IBD diagnosis.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
Dig Liver Dis
Asunto de la revista:
GASTROENTEROLOGIA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Italia