Epithelium Zernike Indices and Artificial Intelligence Can Differentiate Epithelial Remodeling Between Flap and Flapless Refractive Procedures.
Adult
Area Under Curve
Artificial Intelligence
Corneal Stroma
/ surgery
Corneal Topography
Decision Support Techniques
Epithelium, Corneal
/ physiology
Female
Humans
Keratomileusis, Laser In Situ
/ methods
Lasers, Excimer
/ therapeutic use
Male
Models, Statistical
Myopia
/ physiopathology
Photorefractive Keratectomy
/ methods
Refraction, Ocular
/ physiology
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity
Surgical Flaps
Tomography, Optical Coherence
Visual Acuity
/ physiology
Young Adult
Journal
Journal of refractive surgery (Thorofare, N.J. : 1995)
ISSN: 1938-2391
Titre abrégé: J Refract Surg
Pays: United States
ID NLM: 9505927
Informations de publication
Date de publication:
01 Feb 2020
01 Feb 2020
Historique:
received:
18
04
2019
accepted:
02
01
2020
entrez:
8
2
2020
pubmed:
8
2
2020
medline:
15
12
2020
Statut:
ppublish
Résumé
To evaluate epithelial Zernike indices as a differentiator of epithelial remodeling after different refractive procedures. 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). 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. 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.].
Identifiants
pubmed: 32032430
doi: 10.3928/1081597X-20200103-01
doi:
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
97-103Informations de copyright
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