New artificial intelligence index based on Scheimpflug corneal tomography to distinguish subclinical keratoconus from healthy corneas

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dc.contributor.authorAlmeida, Gildásio Castello
dc.contributor.authorGuido, Rodrigo Capobianco [UNESP]
dc.contributor.authorBalarin Silva, Henrique Monteiro
dc.contributor.authorBrandão, Cinara Cássia
dc.contributor.authorDe Mattos, Luiz Carlos
dc.contributor.authorLopes, Bernardo T.
dc.contributor.authorMachado, Aydano Pamponet
dc.contributor.authorAmbrósio, Renato
dc.contributor.institutionFaculty of Medicine of São José do Rio Preto
dc.contributor.institutionBase Hospital of São José do Rio Preto
dc.contributor.institutionVisum Eye Center
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionRio Claro Eye Institute
dc.contributor.institutionUniversity of Liverpool
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionFederal University of Alagoas
dc.contributor.institutionFederal University the State of Rio de Janeiro
dc.date.accessioned2023-07-29T13:24:01Z
dc.date.available2023-07-29T13:24:01Z
dc.date.issued2022-10-01
dc.description.abstractPurpose: To assess the efficiency of an index derived from multiple logistic regression analysis (MLRA) to measure differences in corneal tomography findings between subclinical keratoconus (KC) in 1 eye, corneal ectasia, and healthy corneas. Setting: 2 private Brazilian ophthalmological centers. Design: Multicenter case-control study. Methods: This study included 187 eyes with very asymmetric ectasia and with normal corneal topography and tomography (VAE-NTT) in the VAE-NTT group, 2296 eyes with healthy corneas in the control group (CG), and 410 eyes with ectasia in the ectasia group. An index, termed as Boosted Ectasia Susceptibility Tomography Index (BESTi), was derived using MLRA to identify a cutoff point to distinguish patients in the 3 groups. The groups were divided into 2 subgroups with an equal number of patients: validation set and external validation (EV) set. Results:2893 patients with 2893 eyes were included. BESTi had an area under the curve (AUC) of 0.91 with 86.02% sensitivity (Se) and 83.97% specificity (Sp) between CG and the VAE-NTT group in the EV set, which was significantly greater than those of the Belin-Ambrósio Deviation Index (BAD-D) (AUC: 0.81; Se: 66.67%; Sp: 82.67%; P <.0001) and Pentacam random forest index (PRFI) (AUC: 0.87; Se: 78.49%; Sp: 79.88%; P =.021). Conclusions: BESTi facilitated early detection of ectasia in subclinical KC and demonstrated higher Se and Sp than PRFI and BAD-D for detecting subclinical KC.en
dc.description.affiliationFaculty of Medicine of São José do Rio Preto, São José do Rio Preto
dc.description.affiliationBase Hospital of São José do Rio Preto, São José do Rio Preto
dc.description.affiliationVisum Eye Center, São José do Rio Preto
dc.description.affiliationDepartment of Computer Science and Statistics Institute of Biosciences Letters and Exact Sciences São Paulo State University at São José do Rio Preto
dc.description.affiliationRio Claro Eye Institute, Rio Claro
dc.description.affiliationDepartment of Civil Engineering and Industrial Design School of Engineering University of Liverpool
dc.description.affiliationDepartment of Ophthalmology Federal University of São Paulo
dc.description.affiliationComputing Institute Federal University of Alagoas
dc.description.affiliationDepartment of Ophthalmology Federal University the State of Rio de Janeiro
dc.description.affiliationUnespDepartment of Computer Science and Statistics Institute of Biosciences Letters and Exact Sciences São Paulo State University at São José do Rio Preto
dc.format.extent1168-1174
dc.identifierhttp://dx.doi.org/10.1097/j.jcrs.0000000000000946
dc.identifier.citationJournal of Cataract and Refractive Surgery, v. 48, n. 10, p. 1168-1174, 2022.
dc.identifier.doi10.1097/j.jcrs.0000000000000946
dc.identifier.issn1873-4502
dc.identifier.issn0886-3350
dc.identifier.scopus2-s2.0-85139535442
dc.identifier.urihttp://hdl.handle.net/11449/247723
dc.language.isoeng
dc.relation.ispartofJournal of Cataract and Refractive Surgery
dc.sourceScopus
dc.titleNew artificial intelligence index based on Scheimpflug corneal tomography to distinguish subclinical keratoconus from healthy corneasen
dc.typeArtigo
unesp.author.orcid0000-0001-9785-8756 0000-0001-9785-8756 0000-0001-9785-8756[1]
unesp.author.orcid0000-0002-0924-8024[2]
unesp.author.orcid0000-0002-4836-3113[4]
unesp.author.orcid0000-0002-8572-8177[5]
unesp.author.orcid0000-0002-8489-3621 0000-0002-8489-3621[6]
unesp.author.orcid0000-0003-1188-131X 0000-0003-1188-131X[7]
unesp.author.orcid0000-0001-6919-4606 0000-0001-6919-4606[8]

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