PURPOSE: To develop an artificial intelligence (AI) model to effectively assess local versus global progression of keratoconus using multiple tomographic parameters. METHODS: This was a retrospective review of medical records of patients diagnosed as having keratoconus. A total of 1,884 Pentacam (Oculus Optikgeräte GmbH) scans of 366 eyes (296 patients) were analyzed. Based on an increase in maximum anterior curvature (Kmax), the eyes were classified as actual “progression” and “no progression.” The corresponding changes in other Pentacam parameters were incorporated to train and cross-validate (five-fold) the AI models. Three AI models were trained (an increase in Kmax by A = 0.75 diopters [D], B = 1.00 D, and C = 1.25 D). The area under the curve (AUC), sensitivity, specificity, and classification accuracy, along with other metrics, were evaluated. RESULTS: The AUC, sensitivity, specificity, and classification accuracy were 0.90, 85%, 82%, and 83%, respectively, for Model A; 0.91, 86%, 82%, and 88%, respectively, for Model B; and 0.93, 89%, 81%, and 91%, respectively, for Model C. All models also predicted that 60% to 62% of the actual progression eyes had concomitant progression-associated changes in the other Pentacam parameters (global progression). However, there was discordance between increase in Kmax and concomitant associated changes in the other parameters in 38.8% to 40% of the eyes (local progression). CONCLUSIONS: The AI models identified the eyes where the increase in Kmax and corresponding progression-associated changes in the other parameters were in agreement. These eyes may require corneal cross-linking earlier than the rest. [ J Refract Surg . 2021;37(4):240–248.]

Dry eye disease (DED) is a commonly occurring, multifactorial disease characterized by reduced tear film stability and hyperosmolarity at the ocular surface, leading to discomfort and visual compromise. DED is driven by chronic inflammation and its pathogenesis involves multiple ocular surface structures such as the cornea, conjunctiva, lacrimal glands, and meibomian glands. The tear film secretion and its composition are regulated by the ocular surface in orchestration with the environment and bodily cues. Thus, any dysregulation in ocular surface homeostasis causes an increase in tear break-up time (TBUT), osmolarity changes, and reduction in tear film volume, all of which are indicators of DED. Tear film abnormalities are perpetuated by underlying inflammatory signaling and secretion of inflammatory factors, leading to the recruitment of immune cells and clinical pathology. Tear-soluble factors such as cytokines and chemokines are the best surrogate markers of disease severity and can also drive the altered profile of ocular surface cells contributing to the disease. Soluble factors can thus help in disease classification and planning treatment strategies. Our analysis suggests increased levels of cytokines namely interleukin-1β (IL-1β), IL-2, IL-4, IL-6, IL-9, IL-12, IL-17A, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α); chemokines (CCL2, CCL3, CCL4, CXCL8); MMP-9, FGF, VEGF-A; soluble receptors (sICAM-1, sTNFR1), neurotrophic factors (NGF, substance P, serotonin) and IL1RA and reduced levels of IL-7, IL-17F, CXCL1, CXCL10, EGF and lactoferrin in DED. Due to the non-invasive sample collection and ease of quantitively measuring soluble factors, tears are one of the best-studied biological samples to molecularly stratify DED patients and monitor their response to therapy. In this review, we evaluate and summarize the soluble factors profiles in DED patients from the studies conducted over the past decade and across various patient groups and etiologies. The use of biomarker testing in clinical settings will aid in the advancement of personalized medicine and represents the next step in managing DED.

PURPOSE: To analyze residual refractive error, ocular aberrations, and visual acuity (VA) during accommodation simultaneously with ocular aberrometry in eyes after laser-assisted in situ keratomileusis (LASIK), small incision lenticule extraction (SMILE), and transepithelial photorefractive keratectomy (TransPRK). METHODS: Ocular aberrometry (Tracey Technologies, Houston, TX) was performed 3 months after LASIK (n = 95), SMILE (n = 73), and TransPRK (n = 35). While measuring the aberrations, VA was measured at distance (20 ft), intermediate (60 cm), and near (40 cm) targets. The examinations were done monocularly. A parallel group of age-matched normal eyes (n = 50) with 20/20 Snellen distance VA also underwent aberrometry. RESULTS: Distribution of residual spherical error of LASIK eyes matched the normal eyes the best, followed by SMILE and TransPRK. However, the distribution of cylindrical error of the SMILE eyes was distinctly different from the rest ( P < .05). The SMILE eyes tended to be undercorrected by approximately 0.25 diopters (D) on average at all reading targets compared to LASIK eyes ( P < .05). The undercorrection was greater when the magnitude of the preoperative cylinder exceeded 0.75 D ( P < .05). The VA of LASIK and SMILE eyes was similar to normal eyes at all targets, but the TransPRK eyes were marginally inferior ( P < .05). Only the ocular defocus changed differentially between the study groups during accommodation and the magnitude of change was least for TransPRK eyes ( P < .05). However, postoperative near and intermediate accommodation of LASIK eyes were similar to normal eyes, followed by SMILE eyes and then TransPRK eyes. CONCLUSIONS: The refractive and aberrometric status of the LASIK eyes was closest to the normal eyes. The SMILE procedure may benefit from slight overcorrection of the preoperative refractive cylinder. [ J Refract Surg. 2019;35(10):624–631.]

PURPOSE: To compare optical coherence tomography (OCT) and Scheimpflug curvature and aberrations of the Bowman's layer before and after removal of the epithelium. METHODS: Bowman's layer was mapped with OCT (Optovue Inc., Irvine, CA) before and after removal of the epithelium in normal eyes undergoing photorefractive keratectomy (n = 14) and keratoconic eyes undergoing corneal cross-linking (n = 25). The anterior corneal surface before removal and the underlying Bowman's layer after removal of the epithelium were also mapped with Pentacam (Oculus Optikgeräte, Wetzlar, Germany), and the surface aberrations with ray tracing were computed. RESULTS: The agreement of OCT curvatures before and after removal of the epithelium was excellent (intraclass correlation coefficient [ICC] = 0.9). A similar trend was seen between OCT and Pentacam after removal of the epithelium. The agreement of surface wavefront aberrations of the Bowman's layer before and after removal of the epithelium was excellent (ICC = 0.9) between the devices for keratoconic eyes. However, this agreement was relatively inferior in normal eyes (ICC < 0.5). CONCLUSIONS: The virtual OCT curvature and aberrations of the Bowman's layer agreed well with its actual magnitudes on removal of the epithelium in the keratoconic eyes. In normal eyes, the agreement was inferior for aberrations but not for curvature. [ J Refract Surg . 2020;36(3):193–198.]