Using adaptive optics to optimize the spherical aberration of eyes implanted with EDOF and enhanced monofocal intraocular lenses.

PURPOSE: To assess the effect of change in ocular spherical aberration (SA) with adaptive optics on visual acuity (VA) at different defocus after implantation of extended depth-of-focus (EDOF) and enhanced monofocal intraocular lenses (IOLs). SETTINGS: Narayana Nethralaya Eye Hospital, Bangalore, India. DESIGN: Prospective, longitudinal, observational. METHODS: 80 eyes (40 patients) that had cataract surgery were included in the study. 40 eyes were implanted with Eyhance EDOF IOLs and the remaining with Vivity EDOF IOLs. Baseline ocular aberrations were measured with a visual adaptive optics aberrometer, then the optimal SA was determined by increasing it in steps of -0.01 µm up to -0.1 µm until the maximum improvement in near distance VA was observed for a given eye. Then the defocus curve for each eye was measured after modifying the ocular SA by magnitude equal to optimal SA. RESULTS: Most of the eyes accepted a negative induced SA of -0.05 µm (Eyhance group: 67.6%; Vivity group, 45.2%). In the Eyhance group (dominant eyes), VA improved at -2 diopters (D) ( P < .02) only and degraded at 0 D, +0.5 D, and +1 D defocus ( P < .05). In the Vivity group, the VA remained unchanged at all defocus ( P > .05). In the Eyhance group (nondominant eyes), VA improved at -3.5 D defocus only and degraded at +1.5 D and +2 D defocus ( P < .05). In the Vivity group, VA improved at -2.5 D defocus ( P < .05) only. CONCLUSIONS: A negative induced SA of -0.05 µm in implanted eyes was optimal for a slight improvement in distance-corrected near and intermediate VA without any significant decrease in baseline distance-corrected VA.

Artificial intelligence-based stratification of demographic, ocular surface high-risk factors in progression of keratoconus.

Purpose: The purpose of this study was to identify and analyze the clinical and ocular surface risk factors influencing the progression of keratoconus (KC) using an artificial intelligence (AI) model. Methods: This was a prospective analysis in which 450 KC patients were included. We used the random forest (RF) classifier model from our previous study (which evaluated longitudinal changes in tomographic parameters to predict "progression" and "no progression") to classify these patients. Clinical and ocular surface risk factors were determined through a questionnaire, which included presence of eye rubbing, duration of indoor activity, usage of lubricants and immunomodulator topical medications, duration of computer use, hormonal disturbances, use of hand sanitizers, immunoglobulin E (IgE), and vitamins D and B12 from blood investigations. An AI model was then built to assess whether these risk factors were linked to the future progression versus no progression of KC. The area under the curve (AUC) and other metrics were evaluated. Results: The tomographic AI model classified 322 eyes as progression and 128 eyes as no progression. Also, 76% of the cases that were classified as progression (from tomographic changes) were correctly predicted as progression and 67% of cases that were classified as no progression were predicted as no progression based on clinical risk factors at the first visit. IgE had the highest information gain, followed by presence of systemic allergies, vitamin D, and eye rubbing. The clinical risk factors AI model achieved an AUC of 0.812. Conclusion: This study demonstrated the importance of using AI for risk stratification and profiling of patients based on clinical risk factors, which could impact the progression in KC eyes and help manage them better.

Tear biomarkers in dry eye disease: Progress in the last decade.

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-1ß (IL-1ß), 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.

Impact of crossplay between ocular aberrations and depth of focus in topo-guided laser-assisted in situ keratomileusis outcomes.

Purpose: To develop a nomogram in cases with mismatch between subjective and Topolyzer cylinder, and based on the magnitude of the mismatch, customize a treatment plan to attain good visual outcomes post-laser-assisted in situ keratomileusis (LASIK) surgery. Methods: The patients were evaluated preoperatively using corneal tomography with Pentacam. Five optimal corneal topography scans were obtained from the Topolyzer Vario were used for planning the LASIK treatment. For the nomogram purpose, the patients were divided into three categories based on the difference between the subjective cylinder and Topolyzer (corneal) cylinder. The first group (group 1) consisted of eyes of patients, where the difference was less than or equal to 0.4 D. The second group (group 2) consisted of eyes, where the difference was more than 0.4 D and the subjective cylinder was lesser than the Topolyzer cylinder. The third group (group 3) included eyes where the difference was more than 0.4 D but the subjective cylinder was greater than the Topolyzer cylinder. LASIK was performed with the WaveLight FS 200 femtosecond laser and WaveLight EX500 excimer laser. Assessment of astigmatism correction for the three groups was done using Aplins vector analysis. For comparison of proportions, Chi-square test was used. A P value less than 0.05 was considered statistically significant. Results: The UDVA was statistically significantly different when compared between groups 1 and 2 (P = 0.02). However, the corrected distance visual acuity (CDVA) was similar among all the three groups (P = 0.1). Group 3 showed an increase of residual cylinder by -0.25 D, which was significant at intermediate and near reading distances (P < 0.05). Group 3 showed significantly higher target-induced astigmatism (TIA) compared to groups 1 and 2 (P = 0.01). The mean surgically induced astigmatism (SIA) was the least in group 2, which was statistically significant (P < 0.01). Conclusion: The outcomes for distance vision using our nomogram postoperatively were excellent, but further refinement for improving the near vision outcomes is required.

Phase retardation and corneal sublayer thickness repeatability using ultrahigh-resolution polarization-sensitive OCT.

PURPOSE: To assess phase retardation and corneal sublayer thickness repeatability using ultrahigh-resolution polarization-sensitive optical coherence tomography (PS-OCT). SETTING: Narayana Nethralaya Eye Hospital, Bangalore. DESIGN: Observational. METHODS: In this study, all eyes were imaged using a custom-built ultrahigh-resolution PS-OCT and high-resolution hybrid OCT (MS-39). The repeatability of phase retardation en face maps and corneal sublayer thickness profiles was evaluated. The reflectivity and phase retardation were calculated from the 2 orthogonal polarization channels to generate en face maps of phase retardation and corneal sublayer thicknesses. 3 consecutive measurements of all participants were acquired for each eye. For each measurement, the participant was asked to sit back and was realigned again. The repeatability was assessed using the intraclass correlation coefficient (ICC). RESULTS: The study included 20 healthy eyes of 20 participants. The phase retardation en face maps showed preferential arrangement of collagen fibrils with least retardation in the apex and maximum retardation in the periphery. The phase retardation showed excellent repeatability (ICC >0.95) in all zones. The Bowman layer and stromal layer thicknesses were measured with excellent repeatability (ICC >0.93 and >0.99, respectively). Significant differences ( P < .05) in stromal layer thickness were observed between MS-39 and PS-OCT. The repeatability of epithelial thickness measurements was better with PS-OCT than MS-39. CONCLUSIONS: The combinational assessment of corneal birefringence and sublayer thicknesses shows the advanced potential of ultrahigh-resolution PS-OCT in routine clinical practice over current OCT devices.

Mapping of corneal birefringence in thin and asymmetric keratoconus corneas with ultrahigh-resolution polarization-sensitive OCT.

PURPOSE: To evaluate phase retardation (PR) across healthy eyes and eyes with thin corneas (<500 µm) and with asymmetric and bilateral keratoconus (KC). SETTING: Narayana Nethralaya Eye Hospital, Bangalore, India. DESIGN: Observational cross-sectional. METHODS: There were 4 eye groups: healthy eyes (Group 1; n = 10 eyes), eyes with thin corneas and no clinical disease (Group 2; n = 10 eyes), eyes with asymmetric KC (Group 3; n = 5 eyes), and eyes with clinical KC (Group 4; n = 15 eyes). All eyes were imaged with polarization-sensitive optical coherence tomography (PS-OCT), MS-39, and Corvis-ST. Using PS-OCT, PR was analyzed in annular regions. The anterior (A-E) and Bowman (E-B) wavefront aberrations, epithelial Zernike indices (EZI), total corneal thickness, Corvis biomechanical index (CBI), total biomechanical index (TBI), and Belin-Ambrósio overall deviation index (BAD-D) were analyzed. RESULTS: Only CBI, TBI, BAD-D, A-E and E-B aberrations, EZI, and total corneal thickness distributions of Groups 1 (n =10), 2 (n =10), and 3 (n =5) were similar ( P > .05) but not CCT ( P < .05). PR distributions clearly showed that the eyes in Groups 1, 2, and 3 had a normal corneal birefringence unlike Group 4 (n = 10) eyes ( P < .05). The PR map was similar to the preferred orientations of collagen fibers seen in X-ray diffraction ex vivo studies of corneal stroma. CONCLUSIONS: PR distributions may eliminate the uncertainty associated with the stromal status of thin and asymmetric KC corneas. Group 2 and 3 eyes appeared as healthy because of normal corneal birefringence at the time of imaging, but a longitudinal follow-up of these eyes with PS-OCT may assist in early detection of onset of disease.

Artificial Intelligence Efficiently Identifies Regional Differences in the Progression of Tomographic Parameters of Keratoconic Corneas.

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.].

Early Corneal and Epithelial Remodeling Differences Identified by OCT Imaging and Artificial Intelligence Between Two Transepithelial PRK Platforms.

PURPOSE: To analyze corneal and epithelial remodeling differences between SmartSurfACE reverse transepithelial PRK (SCHWIND eye-tech-solutions) and Streamlight (Alcon Laboratories, Inc) transepithelial PRK procedure using optical coherence tomography (OCT) and artificial intelligence (AI). METHODS: This was a prospective, interventional, and longitudinal study. A contralateral eye study was conducted in which one eye was assigned to the SmartSurfACE group and the fellow eye was assigned to the Streamlight group. OCT was performed preoperatively and 1, 3, and 6 months after surgery. Uncorrected (UDVA) and corrected (CDVA) distance visual acuity and residual refractive error was measured only preoperatively and at 3 and 6 months. From OCT, curvature and aberrations of the air-epithelium (A-E) interface, epithelium-Bowman's layer (E-B) interface, and epithelium Zernike indices (EZI) were derived. Pain was evaluated at 1 day postoperatively using the Wong-Baker scale. RESULTS: Both groups had similar UDVA, CDVA, residual refractive error, and changes in A-E and E-B curvatures at 3 and 6 months postoperatively (P > .05). However, many parameters indicated that the Streamlight group underwent a greater change in A-E aberrations, E-B aberrations, and EZI than the SmartSurfACE group postoperatively (P < .05). The EZI indicated a greater level of epithelial thickness distortion in the Streamlight group than in the SmartSurfACE group (P < .05). Using AI, the EZI were most indicative of remodeling differences between the two groups. Further, the pain was significantly greater at 1 day in the Streamlight group (P < .05). CONCLUSIONS: Early remodeling differences existed because the Streamlight procedure removed a greater amount of epithelium than the SmartSurfACE procedure. However, the visual and refractive outcomes were comparable. [J Refract Surg. 2020;36(10):678-686.].

Accuracy of OCT Curvature and Aberrations of Bowman's Layer: A Prospective Comparison With Physical Removal of Epithelium.

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.].

Status of Residual Refractive Error, Ocular Aberrations, and Accommodation After Myopic LASIK, SMILE, and TransPRK.

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.].