A Deep Learning--Based Approach to Estimate Paneth Cell Granule Area in Celiac Disease.
Context.--Changes in Paneth cell numbers can be associated with chronic inflammatory diseases of the gastrointestinal tract. So far, no consensus has been achieved on the number of Paneth cells and their relevance to celiac disease (CD). Objectives.--To compare crypt and Paneth cell granule areas be...
| Publicado en: | Archives of Pathology & Laboratory Medicine Vol. 148; no. 7; pp. 828 - 836 |
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| Autores principales: | , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
College of American Pathologists
Jul2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=178199651&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 178199651 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00039985 1FS jtl: Archives of Pathology & Laboratory Medicine issn: 00039985 maglogo: N pubinfo: dt: Jul2024 vid: 148 iid: 7 pid: 2550 pub: College of American Pathologists place: Northfield, Illinois artinfo: ui: 178199651 178199651 178199651 10.5858/arpa.2023-0074-OA 178199651 ppf: 828 ppct: 8 formats: fmt: @attributes: type: P tig: atl: A Deep Learning--Based Approach to Estimate Paneth Cell Granule Area in Celiac Disease. aug: au: Alharbi, Ebtihal Rajaram, Ajay Côté, Kevin Farag, Mina Maleki, Farhad Zu-Hua Gao Maedler-Kron, Chelsea Marcus, Victoria Fiset, Pierre Olivier affil: Department of Pathology, McGill University, Montreal, Quebec, Canada sug: subj: Deep Learning Epithelial Cells Celiac Disease Intestinal Mucosa Human Staining and Labeling Methods Duodenum Biopsy Data Analysis Software Descriptive Statistics Hyperplasia Cell Physiology Workflow ab: Context.--Changes in Paneth cell numbers can be associated with chronic inflammatory diseases of the gastrointestinal tract. So far, no consensus has been achieved on the number of Paneth cells and their relevance to celiac disease (CD). Objectives.--To compare crypt and Paneth cell granule areas between patients with CD and those without CD (non-CD) using an artificial intelligence--based solution. Design.--Hematoxylin--eosin--stained sections of duodenal biopsies from 349 patients at the McGill University Health Centre were analyzed. Of these, 185 had a history of CD and 164 were controls. Slides were digitized, and NoCodeSeg, a code-free workflow using opensource software (QuPath, DeepMIB), was implemented to train deep learning models to segment crypts and Paneth cell granules. The total area of the entire analyzed tissue, epithelium, crypts, and Paneth cell granules was documented for all slides, and comparisons were performed. Results.--A mean intersection-over-union score of 88.76% and 91.30% was achieved for crypt areas and Paneth cell granule segmentations, respectively. On normalization to total tissue area, the crypt to total tissue area in CD was increased and the Paneth cell granule area to total tissue area decreased when compared to non-CD controls. Conclusions.--Crypt hyperplasia was confirmed in CD compared to non-CD controls. The area of Paneth cell granules, an indirect measure of Paneth cell function, decreased with increasing severity of CD. More importantly, our study analyzed complete hematoxylin-eosin slide sections using an efficient and easy to use codingfree artificial intelligence workflow. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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