Epithelium Zernike Indices and Artificial Intelligence Can Differentiate Epithelial Remodeling Between Flap and Flapless Refractive Procedures
| Autor: | Pooja Khamar, Rohit Shetty, Yash Patel, Rudy M.M.A. Nuijts, Gairik Kundu, Abhijit Sinha Roy, Rachana Chandapura, Zelda Dadachanji |
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| Přispěvatelé: | MUMC+: *AB Refractie Chirurgie Oogheelkunde (9), Oogheelkunde, MUMC+: MA UECM Oogartsen MUMC (9), RS: MHeNs - R3 - Neuroscience |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Male
Refractive error medicine.medical_treatment Keratomileusis Laser In Situ Visual Acuity Keratomileusis Surgical Flaps 0302 clinical medicine PHOTOREFRACTIVE KERATECTOMY Myopia PACHYMETRIC PARAMETERS CORNEAL-THICKNESS medicine.diagnostic_test Epithelium Corneal FEMTOSECOND Corneal topography Refraction Photorefractive keratectomy Area Under Curve symbols Female Lasers Excimer Tomography Optical Coherence Adult MYOPIC LASIK medicine.medical_specialty Materials science Zernike polynomials Corneal Stroma TOPOGRAPHY Refraction Ocular PROFILE Sensitivity and Specificity Decision Support Techniques 03 medical and health sciences symbols.namesake Young Adult Optical coherence tomography Artificial Intelligence Ophthalmology TOMOGRAPHY medicine Small incision lenticule extraction Humans STROMAL THICKNESS IN-SITU KERATOMILEUSIS Retrospective Studies Models Statistical Corneal Topography Reproducibility of Results medicine.disease 030221 ophthalmology & optometry Surgery 030217 neurology & neurosurgery |
| Zdroj: | Journal of Refractive Surgery, 36(2), 97-103. Slack, Inc. |
| ISSN: | 1081-597X |
| Popis: | PURPOSE: To evaluate epithelial Zernike indices as a differentiator of epithelial remodeling after different refractive procedures. METHODS: Optical coherence tomography (OCT) images of 22 laser in situ keratomileusis, 22 small incision lenticule extraction, 15 photorefractive keratectomy (PRK), and 17 transepithelial PRK eyes were evaluated retrospectively before and after surgery. A custom algorithm was used to calculate the epithelial Zernike indices from the three-dimensional distribution of epithelial thickness distribution. The epithelial Zernike indices were also compared with the local measurements of epithelial thickness, used conventionally from the current clinical OCT. A decision tree classifier was built, one in which flap/cap and surface procedures were classified (2G) and another in which all surgical groups were classified separately (4G). RESULTS: Local measurements of thicknesses changed significantly after all surgeries ( P < .05), but these changes were similar in magnitude between the surgical platforms ( P > .05). The surgeries not only changed the epithelial Zernike indices ( P < .05), but also resulted in differential changes in epithelial thickness distribution based on the type of surgery ( P < .05). In the 2G analyses with local measurements of epithelial thickness, the area under the curve, sensitivity, and specificity were 0.57 ± 0.07, 42.11%, and 57.89%, respectively. Further, the accuracy was limited to less than 60%. In the 2G analyses with epithelial Zernike indices, the area under the curve, sensitivity, and specificity were 0.79 ± 0.05, 86.4%, and 71.9%, respectively. Here, the accuracy was limited between 70% and 80%. Similar trends were observed with 4G analyses. CONCLUSIONS: The epithelial Zernike indices were significantly better in identifying surgery-specific three-dimensional remodeling of the thickness compared to local measurements of epithelial thickness. Further, the changes in Zernike indices were independent of the magnitude of refractive error but not the type of surgery. [ J Refract Surg . 2020;36(2):97–103.] |
| Databáze: | OpenAIRE |
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