Analysis of Waveform-Derived ORA Parameters in Early Forms of Keratoconus and Normal Corneas

PURPOSE: To evaluate the Ocular Response Analyzer (ORA; Reichert Ophthalmic Instruments, Depew, NY) performance in differentiating grades I and II keratoconus from normal corneas using 41 parameters individually and to assess the effect of analyzing all parameters together.METHODS: This study compared the mean value of 41 ORA parameters in grades I and II keratoconus with healthy age-matched control eyes. Only eyes with a central corneal thickness between 500 and 600 mu m were included. the area under the receiver operating characteristic curve was calculated for each of the 41 parameters independently and for all of the parameters together.RESULTS: This study included 136 eyes with normal corneas and 68 eyes with grades I and II keratoconus. When analyzed individually, four ORA parameters (p1area, p1area1, p2area, and p2area1) had an area under the curve greater than 0.900 for discriminating between both groups. the p2area was the parameter that achieved the largest area under the curve individually (0.931). the area under the curve increased to 0.978 when analyzing all parameters together.CONCLUSION: Alternative ORA parameters are better for differentiating grades I and II keratoconus from normal corneas than the four parameters originally available for ophthalmologists (corneal hysteresis, Goldmann-correlated intraocular pressure, corneal-compensated intraocular pressure, and corneal resistance factor). Although the ORA did not achieve 100% accuracy, the discrimination between these two groups was optimized by combining all parameters.Brazilian Study Grp Artificial Intelligence & Cor, Rio de Janeiro, BrazilAltino Ventura Fdn, Recife, PE, BrazilUniv Fed Alagoas, Maceio, BrazilInst Olhos Renato Ambrosio, Rio de Janeiro, BrazilUniversidade Federal de São Paulo, São Paulo, BrazilUniv Ciencias Saude Alagoas, Maceio, BrazilUniversidade Federal de São Paulo, São Paulo, BrazilWeb of Scienc

Enhanced Diagnostics for Corneal Ectatic Diseases: The Whats, the Whys, and the Hows

There are different fundamental diagnostic strategies for patients with ectatic corneal diseases (ECDs): screening, confirmation of the diagnosis, classification of the type of ECD, severity staging, prognostic assessment, and clinical follow-up. The conscious application of such strategies enables individualized treatments. The need for improved diagnostics of ECD is related to the advent of therapeutic refractive procedures that are considered prior to keratoplasty. Among such less invasive procedures, we include corneal crosslinking, customized ablations, and intracorneal ring segment implantation. Besides the paradigm shift in managing patients with ECD, enhancing the sensitivity to detect very mild forms of disease, and characterizing the inherent susceptibility for ectasia progression, became relevant for identifying patients at higher risk for progressive iatrogenic ectasia after laser vision correction (LVC). Moreover, the hypothesis that mild keratoconus is a risk factor for delivering a baby with Down’s syndrome potentially augments the relevance of the diagnostics of ECD. Multimodal refractive imaging involves different technologies, including Placido-disk corneal topography, Scheimpflug 3-D tomography, segmental or layered tomography with layered epithelial thickness using OCT (optical coherence tomography), and digital very high-frequency ultrasound (VHF-US), and ocular wavefront. Corneal biomechanical assessments and genetic and molecular biology tests have translated to clinical measurements. Artificial intelligence allows for the integration of a plethora of clinical data and has proven its relevance in facilitating clinical decisions, allowing personalized or individualized treatments

Multimodal diagnostics for keratoconus and ectatic corneal diseases: a paradigm shift

Abstract Different diagnostic approaches for ectatic corneal diseases (ECD) include screening, diagnosis confirmation, classification of the ECD type, severity staging, prognostic evaluation, and clinical follow-up. The comprehensive assessment must start with a directed clinical history. However, multimodal imaging tools, including Placido-disk topography, Scheimpflug three-dimensional (3D) tomography, corneal biomechanical evaluations, and layered (or segmental) tomography with epithelial thickness by optical coherence tomography (OCT), or digital very high-frequency ultrasound (dVHF-US) serve as fundamental complementary exams for measuring different characteristics of the cornea. Also, ocular wavefront analysis, axial length measurements, corneal specular or confocal microscopy, and genetic or molecular biology tests are relevant for clinical decisions. Artificial intelligence enhances interpretation and enables combining such a plethora of data, boosting accuracy and facilitating clinical decisions. The applications of diagnostic information for individualized treatments became relevant concerning the therapeutic refractive procedures that emerged as alternatives to keratoplasty. The first paradigm shift concerns the surgical management of patients with ECD with different techniques, such as crosslinking and intrastromal corneal ring segments. A second paradigm shift involved the quest for identifying patients at higher risk of progressive iatrogenic ectasia after elective refractive corrections on the cornea. Beyond augmenting the sensitivity to detect very mild (subclinical or fruste) forms of ECD, ectasia risk assessment evolved to characterize the inherent susceptibility for ectasia development and progression. Furthermore, ectasia risk is also related to environmental factors, including eye rubbing and the relational impact of the surgical procedure on the cornea

Decision taking in corneal refractive surgery

A 27-year-old woman who wants to get rid of contact lenses and spectacles was seen at our clinic. She had strabismus surgery as a child and was patched for the right eye but now shows mild nondisturbing exophoria. Infrequently, she likes to box in the sports school. Her corrected distance visual acuity at presentation in the right eye was 20/16 with -3.75 -0.75 × 50 and in the left eye 20/16 with -3.75 -1.25 × 142. Her cycloplegic refraction in the right eye was -3.75 -0.75 × 44 and in the left eye was -3.25 -1.25 × 147. The left eye is the dominant eye. The tear break-up time was 8 seconds in both eyes, and the Schirmer tear test was 7 to 10 mm in right and left eyes, respectively. Pupil sizes under mesopic conditions were 6.62 mm and 6.68 mm. The anterior chamber depth (ACD) (measured from the epithelium) in the right eye was 3.89 mm and in the left eye was 3.87 mm. The corneal thickness was 503 μm and 493 μm of the right and left eye, respectively. Corneal endothelial cell density was on average 2700 cells/mm2 for both eyes. Slitlamp biomicroscopy showed clear corneas and a normal flat iris configuration. Supplemental Figures 1 to 4 (available at http://links.lww.com/JRS/A818, http://links.lww.com/JRS/A819, http://links.lww.com/JRS/A820, and http://links.lww.com/JRS/A821) show the corneal topography and Belin-Ambrósio deviation (BAD) maps at presentation of the right eye and left eye, respectively. Would you consider this patient a candidate for corneal refractive surgery (eg, laser-assisted subepithelial keratectomy, laser in situ keratomileusis [LASIK], or small-incision lenticule extraction [SMILE] procedure)? Has your opinion changed given the recent opinion of the U.S. Food and Drug Administration (FDA) regarding LASIK?1 The patient herself is slightly favoring an implantation of a phakic intraocular lens (pIOL), as she prefers something reversible. Would you implant a pIOL, and which type of IOL, for this level of myopia? What is your diagnosis or are additional diagnostic methodologies needed to establish a diagnosis? What is your treatment advice for this patient? REFERENCES 1. U.S. Food and Drug Administration, HHS. Laser-assisted in situ keratomileusis (LASIK) lasers-patient labeling recommendations; draft guidance for industry and food and drug administration staff; availability. July 28, 2022, Federal Register; 87 FR 45334. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/laser-assisted-situ-keratomileusis-lasik-lasers-patient-labeling-recommendations Accessed January 25, 2023

Optimized artificial intelligence for enhanced ectasia detection using Scheimpflug-based corneal tomography and biomechanical data

PurposeTo optimize artificial intelligence (AI) algorithms to integrate Scheimpflug-based corneal tomography and biomechanics to enhance ectasia detection.DesignMulticenter cross-sectional case-control retrospective study.Methods3,886 unoperated eyes from 3,412 patients had Pentacam and Corvis ST (Oculus Optikgeräte GmbH; Wetzlar, Germany) examinations. The database included one eye randomly selected from 1,680 normal patients (N), and from 1,181 "bilateral" keratoconus (KC) patients, along with 551 normal topography eyes from very asymmetric ectasia patients (VAE-NT), and their 474 unoperated ectatic (VAE-E) eyes. The current TBIv1 (tomographic-biomechanical index) was tested, and an optimized AI algorithm was developed for augmenting accuracy.ResultsThe area under the receiver operating characteristic curve (AUC) of the TBIv1 for discriminating clinical ectasia (KC and VAE-E) was 0.999 (98.5% sensitivity; 98.6% specificity [cutoff 0.5]), and for VAE-NT, 0.899 (76% sensitivity; 89.1% specificity [cutoff 0.29]). A novel random forest algorithm (TBIv2), developed with 18 features in 156 trees using 10-fold cross-validation, had significantly higher AUC (0.945; DeLong, pConclusionAI optimization to integrate Scheimpflug-based corneal tomography and biomechanical assessments augments accuracy for ectasia detection, characterizing ectasia susceptibility in the diverse VAE-NT group. Some VAE patients may be true unilateral ectasia. Machine learning considering additional data, including epithelial thickness or other parameters from multimodal refractive imaging, will continuously enhance accuracy