2021
DOI: 10.15403/jgld-3212
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Deep Learning Algorithm for the Confirmation of Mucosal Healing in Crohn’s Disease, Based on Confocal Laser Endomicroscopy Images

Abstract: Background and Aims: Mucosal healing (MH) is associated with a stable course of Crohn’s disease (CD) which can be assessed by confocal laser endomicroscopy (CLE). To minimize the operator’s errors and automate assessment of CLE images, we used a deep learning (DL) model for image analysis. We hypothesized that DL combined with convolutional neural networks (CNNs) and long short-term memory (LSTM) can distinguish between normal and inflamed colonic mucosa from CLE images. Methods: The study included 54 pa… Show more

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Cited by 19 publications
(8 citation statements)
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“…Several studies (seven prospective and two retrospective) have investigated the CLE features of inflammation. These include crypt architectural abnormalities, microvascular alterations, inflammatory cell infiltration in lamina propria, and increased vascular permeability as evidenced by fluorescein leakage in lamina propria 1,3–10 . Additional markers of inflammation included evidence of microerosions and decrease in goblet cells 1 .…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Several studies (seven prospective and two retrospective) have investigated the CLE features of inflammation. These include crypt architectural abnormalities, microvascular alterations, inflammatory cell infiltration in lamina propria, and increased vascular permeability as evidenced by fluorescein leakage in lamina propria 1,3–10 . Additional markers of inflammation included evidence of microerosions and decrease in goblet cells 1 .…”
Section: Resultsmentioning
confidence: 99%
“…These include crypt architectural abnormalities, microvascular alterations, inflammatory cell infiltration in lamina propria, and increased vascular permeability as evidenced by fluorescein leakage in lamina propria. 1,[3][4][5][6][7][8][9][10] Additional markers of inflammation included evidence of microerosions and decrease in goblet cells. 1 These markers have been used for documenting mucosal healing in both ulcerative colitis (UC) and Crohn's disease (CD) (Table 1).…”
Section: Confocal Laser Endomicroscopymentioning
confidence: 99%
“…Following a recent discussion at the Stenosis Therapy and Antifibrotic Research Consortium, a four-tiered system (none, mild, moderate, and severe) was constructed to include an evaluation of the inflammatory and fibrotic components of each mural layer [ 55 ]. In this artificial intelligence era, researchers have endeavored to develop a deep learning model to evaluate intestinal fibrosis in surgical specimens for postoperative recurrence prediction [ 65 , 66 ].…”
Section: Histopathologymentioning
confidence: 99%
“…However, CLE requires accurate image interpretation, which only experienced endoscopic physicians can do. Udristoiu’s team designed the DL system can distinguish between ulcerated and healed Crohn’s disease patients in CLE pictures [ 29 ]. Still, the algorithm was unable to determine active ulcers from inactive ulcers.…”
Section: Application Of DL In Gastrointestinal Endoscopymentioning
confidence: 99%