G. Magazzù, S. Aquilina, C. Barbara, R. Bondin, I. Brusca, J. Bugeja, M. Camilleri, D. Cascio, S. Costa, C. Cuzzupè, A. Duca, M. Fregapane, V. Gentile, A. Giuliano, A. Grifò, A. Grima, A. Ieni, G. Li Calzi, F. Maisano, G. Melita, S. Pallio, I. Panasiti, S. Pellegrino, C. Romano, S. Sorce, M. E. Tabacchi, V. Taormina, D. Tegolo, A. Tortora, C. Valenti, C. Vella, G. Raso

Recognizing the Emergent and Submerged Iceberg of the Celiac Disease: ITAMA Project - Global Strategy Protocol

Medical Imaging Analysis and Diagnostics Software Engineering Artificial Intelligence

Coeliac disease (CD) is frequently underdiagnosed with a consequent heavy burden in terms of morbidity and health care costs. Diagnosis of CD is based on the evaluation of symptoms and anti-transglutaminase antibodies IgA (TGA-IgA) levels, with values above a tenfold increase being the basis of the biopsy-free diagnostic approach suggested by present guidelines. This study showcased the largest screening project for CD carried out to date in school children (n=20,000) aimed at assessing the diagnostic accuracy of minimally invasive finger prick point-of-care tests (POCT) which, combined with conventional celiac serology and the aid of an artificial intelligence-based system, may eliminate the need for intestinal biopsy. Moreover, this study delves deeper into the “coeliac iceberg” in an attempt to identify people with disorders who may benefit from a gluten-free diet, even in the absence of gastrointestinal symptoms, abnormal serology and histology. This was achieved by looking for TGA-IgA mucosal deposits in duodenal biopsy. This large European multidisciplinary health project paves the way to an improved quality of life for patients by reducing the costs for diagnosis due to delayed findings of CD and to offer business opportunities in terms of diagnostic tools and support.

This article is authored also by Synbrain data scientists and collaborators. READ THE FULL ARTICLE