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Tytuł:
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Artificial intelligence for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging.
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Autorzy:
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Wu Q; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China; Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Chen J; Department of Pathology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Ren Y; Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River Delta, Guangzhou 510735, China; Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen 518107, China.
Qiu H; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Yuan L; Department of Science and Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Deng H; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Zhang Y; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Zheng R; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Hong H; Department of Otolaryngology-Head and Neck Surgery, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai 519020, China.
Sun Y; Department of Otorhinolaryngology-Head and Neck Surgery, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen 518107, China.
Wang X; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Huang X; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Shao C; Department of Pathology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
Lin H; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou 510060, China.
Han L; Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River Delta, Guangzhou 510735, China. Electronic address: .
Yang Q; Department of Otorhinolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China; Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China. Electronic address: .
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Źródło:
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EBioMedicine [EBioMedicine] 2021 Apr; Vol. 66, pp. 103336. Date of Electronic Publication: 2021 Apr 12.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: [Amsterdam] : Elsevier B.V., [2014]-
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MeSH Terms:
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Artificial Intelligence*
Histocytochemistry*/methods
Histocytochemistry*/standards
Nasal Polyps/*diagnosis
Adolescent ; Adult ; Aged ; Computational Biology/methods ; Deep Learning ; Female ; Humans ; Image Processing, Computer-Assisted ; Male ; Middle Aged ; Nasal Polyps/etiology ; Nasal Polyps/pathology ; Neural Networks, Computer ; Reproducibility of Results ; Software ; Young Adult
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Contributed Indexing:
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Keywords: Artificial intelligence; Cellular phenotype; Chronic rhinosinusitis; Deep learning; Nasal polyps; Whole-slide imaging
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Entry Date(s):
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Date Created: 20210415 Date Completed: 20211129 Latest Revision: 20211129
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Update Code:
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20240104
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PubMed Central ID:
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PMC8050855
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DOI:
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10.1016/j.ebiom.2021.103336
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PMID:
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33857906
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Background: artificial intelligence (AI) for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging (WSI) is lacking. We aim to establish an AI chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0) to obtain the proportion of inflammatory cells for cellular phenotyping diagnosis of nasal polyps and to explore the clinical significance of different phenotypes of nasal polyps on the WSI.
Methods: a total of 453 patients were enrolled in our study. For the development of AICEP 2.0, 179 patients (WSIs) were obtained from the Third Affiliated Hospital of Sun Yat-Sen University (3HSYSU) from January 2008 to December 2018. A total of 24,625 patches were automatically extracted from the regions of interest under a 400× HPF by Openslide and the number of inflammatory cells in these patches was counted by two pathologists. For the application of AICEP 2.0 in a prospective cohort, 158 patients aged 14-70 years old with chronic rhinosinusitis with nasal polyps (CRSwNP) who had undergone endoscopic sinus surgery at 3HSYSU from June 2020 to December 2020 were included for preoperative demographic characteristics. For the application of AICEP 2.0 in a retrospective cohort, 116 patients with CRSwNP who had undergone endoscopic sinus surgery from May 2016 to June 2017 were enrolled for the recurrence rate. The proportion of inflammatory cells of these patients on WSI was calculated by our AICEP 2.0.
Findings: for AICEP 2.0, the mean absolute errors of the ratios of eosinophils, lymphocytes, neutrophils, and plasma cells were 1.64%, 2.13%, 1.06%, and 1.22%, respectively. The four phenotypes of nasal polyps were significantly different in clinical characteristics (including asthma, itching, sneezing, total IgE, peripheral eosinophils%, tissue eosinophils%, tissue neutrophils%, tissue lymphocytes%, tissue plasma cells%, and recurrence rate; P <0.05), but there were no significant differences in age distribution, onset time, total VAS score, Lund-Kennedy score, or Lund-Mackay score. The percentage of peripheral eosinophils was positively correlated with the percentage of tissue eosinophils (r = 0.560, P <0.001) and negatively correlated with tissue lymphocytes% (r = -0.489, P <0.001), tissue neutrophils% (r = -0.225, P = 0.005), and tissue plasma cells% (r = -0.266, P = 0.001) in WSIs.
Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest.
(Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)
