000117380 001__ 117380
000117380 005__ 20230519145546.0
000117380 0247_ $$2doi$$a10.1167/TVST.10.9.32
000117380 0248_ $$2sideral$$a127073
000117380 037__ $$aART-2021-127073
000117380 041__ $$aeng
000117380 100__ $$0(orcid)0000-0001-5186-1837$$aConsejo A.$$uUniversidad de Zaragoza
000117380 245__ $$aDetection of subclinical keratoconus with a validated alternative method to corneal densitometry
000117380 260__ $$c2021
000117380 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117380 5203_ $$aPurpose: To enhance the current standards of subclinical keratoconus screening based on the statistical modeling of the pixel intensity distribution of Scheimpflug images. Methods: Scheimpflug corneal tomographies corresponding to 25 corneal meridians of 60 participants were retrospectively collected and divided into three groups: controls (20 eyes), subclinical keratoconus (20 eyes), and clinical keratoconus (20 eyes). Only right eyes were selected. After corneal segmentation, pixel intensities of the stromal tissue were statistically modeled using a Weibull probability density function from which parameter a (pixel brightness) was derived. Further, data were transformed to polar coordinates, smoothed, and interpolated to build a map of the corneal a parameter. The discriminative power of the method was analyzed using receiver operating characteristic curves. Results: The proposed platform-independent method achieved a higher performance in discriminating subclinical keratoconus from control eyes (90.0% sensitivity, 95.0% specificity, 0.97 area under the curve [AUC]) than the standard method (Belin–Ambrósio enhanced ectasia display), which uses only corneal morphometry (85.0% sensitivity, 85.0% specificity, 0.80 AUC). Conclusions: Analysis of light backscatter at the cornea successfully discriminates subclinical keratoconus from control eyes, upgrading the results previously reported in the literature. Translational Relevance: The proposed methodology has the potential to support clinicians in the detection of keratoconus before showing clinical signs. © 2021 The Authors.
000117380 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000117380 590__ $$a3.048$$b2021
000117380 592__ $$a0.9$$b2021
000117380 594__ $$a3.5$$b2021
000117380 591__ $$aOPHTHALMOLOGY$$b30 / 62 = 0.484$$c2021$$dQ2$$eT2
000117380 593__ $$aOphthalmology$$c2021$$dQ1
000117380 593__ $$aBiomedical Engineering$$c2021$$dQ1
000117380 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117380 700__ $$aJiménez-García M.
000117380 700__ $$aIssarti I.
000117380 700__ $$aRozema J.J.
000117380 7102_ $$12002$$2385$$aUniversidad de Zaragoza$$bDpto. Física Aplicada$$cÁrea Física Aplicada
000117380 773__ $$g10, 9 (2021), 7212 [9 pp]$$pTransl. vis. sci. technol.$$tTranslational Vision Science and Technology$$x2164-2591
000117380 8564_ $$s2092765$$uhttps://zaguan.unizar.es/record/117380/files/texto_completo.pdf$$yVersión publicada
000117380 8564_ $$s2916186$$uhttps://zaguan.unizar.es/record/117380/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117380 909CO $$ooai:zaguan.unizar.es:117380$$particulos$$pdriver
000117380 951__ $$a2023-05-18-15:44:04
000117380 980__ $$aARTICLE