The expansion of wavefront-sensing techniques redefined the meaning of refractive error in clinical ophthalmology. Clinical aberrometers provide detailed measurements of the eye's wavefront aberration. The distribution and contribution of each higher-order aberration to the overall wavefront aberration in the individual eye can now be accurately determined and predicted. Using corneal or ocular wavefront sensors, studies have measured the interindividual and age-related changes in the wavefront aberration in the normal population with the goal of optimizing refractive surgery outcomes for the individual. New objective optical-quality metrics would lead to better use and interpretation of newly available information on aberrations in the eye. However, the first metrics introduced, based on sets of Zernike polynomials, is not completely suitable to depict visual quality because they do not directly relate to the quality of the retinal image. Thus, several approaches to describe the real, complex optical performance of human eyes have been implemented. These include objective metrics that quantify the quality of the optical wavefront in the plane of the pupil (ie, pupil-plane metrics) and others that quantify the quality of the retinal image (ie, image-plane metrics). These metrics are derived by wavefront aberration information from the individual eye. This paper reviews the more recent knowledge of the wavefront aberration in human eyes and discusses the image-quality and optical-quality metrics and predictors that are now routinely calculated by wavefront-sensor software to describe the optical and image quality in the individual eye.

Adaptive optics (AO) is a technology used to improve the performance of optical systems by reducing the effects of optical aberrations. The direct visualization of the photoreceptor cells, capillaries and nerve fiber bundles represents the major benefit of adding AO to retinal imaging. Adaptive optics is opening a new frontier for clinical research in ophthalmology, providing new information on the early pathological changes of the retinal microstructures in various retinal diseases. We have reviewed AO technology for retinal imaging, providing information on the core components of an AO retinal camera. The most commonly used wavefront sensing and correcting elements are discussed. Furthermore, we discuss current applications of AO imaging to a population of healthy adults and to the most frequent causes of blindness, including diabetic retinopathy, age-related macular degeneration and glaucoma. We conclude our work with a discussion on future clinical prospects for AO retinal imaging.

Purpose: To investigate the distribution of cone density and spacing as well as the preferred packing arrangement of the cone mosaic as a function of retinal eccentricity. Methods: An adaptive optics retinal camera ( rtx1 , www.imagine-eyes.com ) was used to obtain images of the parafoveal cone mosaic in nineteen healthy volunteers. Cone density and spacing were estimated for each subject (both eyes) using a sampling window of 80 × 80 pixels, at 250‐, 450‐, 650‐ and 1100‐μm eccentricities from the fovea along the nasal and temporal retina of both eyes. The inter‐subject and intra‐subject variation of cone density and spacing were calculated via C oefficient of V ariation ( CoV ). Cone packing arrangement was assessed using V oronoi analysis; calculations were done over 1024 × 128 pixels image sections of the cone mosaic across the horizontal meridian from 200‐ to 1050‐μm eccentricities. Results: The inter‐subject variation of parafoveal cone density ranged between 10% and 15% ( p  < 0.001) and the intra‐subject variation of cone density was lower than 8% in all subjects, except for two. The cone spacing values showed a moderate inter‐subject (CoV<7%; p < 0.001) and a low intra‐subject variation (CoV<4% in all subjects, except for two cases). In the parafoveal region, 40–50% of cones were hexagonally arranged; the percentage of non‐hexagonal V oronoi tiles increased at greater eccentricities. Conclusion: The use of multiple and complementary metric descriptors allows for a more detailed description of packing distribution and preferred arrangement of cone photoreceptors across the parafoveal retina.

Purpose: To evaluate the parafoveal cone density in patients with Type 1 diabetes mellitus (DM1). Methods: Adaptive optics retinal images of the photoreceptor mosaic were acquired from 11 DM1 patients (study group) and 11 age-matched healthy subjects (control group). Cone density was analyzed, along the horizontal and vertical meridian, at 230-µm, 350-µm, and 460-µm eccentricity from the fovea. Central retinal thickness was measured using a Spectralis spectral-domain optical coherence tomography. A multiple regression model was performed to determine the relationships between the explanatory variables (age, glycohemoglobin level, presence of diabetic retinopathy, duration of diabetes, and central retinal thickness) and cone density. Results: Patients had a diagnosis of DM1 in the past 9 years to 21 years. Of these, five patients had a diagnosis of no diabetic retinopathy and six had mild nonproliferative diabetic retinopathy. On average, cone density was 10% lower in the study than in the control group at each retinal eccentricity along the horizontal and vertical meridians (analysis of variance, P < 0.001). The central retinal thickness was thicker in DM1 eyes than in the control eyes (278 ± 20 µm and 260 ± 13 µm; P < 0.05). The model explained 61% (P < 0.01) of the variance of cone density in the population, with the variables representing an abnormal glucose metabolism, that is, a higher glycohemoglobin level, the presence of diabetic retinopathy, and a chronic diabetes, having the highest influence on cone density decline. Conclusion: A subtle decrease of parafoveal cone density was found in DM1 patients in comparison with age-matched control subjects via high-resolution adaptive optics retinal imaging. The cone density decline was moderately associated with a disturbance in the glucose metabolism.

Purpose. To investigate the biomechanics of the anterior human corneal stroma using atomic force microscopy (AFM). Methods. AFM measurements were performed in liquid on the anterior stroma of human corneas, after gently removing the epithelium, using an atomic force microscope in the force spectroscopy mode. Rectangular silicon cantilevers with tip radius of 10 nm and spring elastic constants of 25- and 33-N/m were used. Each specimen was subjected to increasing loads up to a maximum of 2.7 μN with scan speeds ranging between 3- and 95-μm/s. The anterior stromal hysteresis during the extension–retraction cycle was quantified as a function of the application load and scan rate. The elastic modulus of the anterior stroma was determined by fitting force curve data to the Sneddon model. Results. The anterior stroma exhibited significant viscoelasticity at micrometric level: asymmetry in the curve loading–unloading response with considerable hysteresis dependent both on the application load and scan rate (P < 0.01). The mean elastic modulus ranged between 1.14 and 2.63 MPa and was constant over the range of indentation depths between 1.0 and 2.7 μm in the stroma. Conclusions. At microscale level, the mechanical response of the most anterior stroma is complex and nonlinear. The microstructure (fibers' packing, number of cross-links, water content) and the combination of elastic (collagen fibers) and viscous (matrix) components of the tissue influence the type of viscoelastic response. Efforts in modeling the biomechanics of human corneal tissue at micrometric level are needed.