8. Conclusions

The optical system of the eye imposes a limit for retinal imaging. If the eye's wavefront aberrations are completely corrected across the pupil, significant improvement in the eye's optical quality is gained. Such improvement has been shown to be valuable in recent clinical applications of adaptive optics retinal imaging [110–114, 152, 154].

Over the last ten years, advances in understanding of the eye's aberrations have moved the wave aberration theory from an academic concept to an engineering level that is central to improving ophthalmic technologies. In the first experiment using a fundus camera equipped with adaptive optics, Liang et al.[20] were able to image individual cones in the living human retina. Since this seminal paper, adaptive optics for retinal imaging applications has entered the field of clinical research. The ability to image the photoreceptor layer, the retinal micro-vasculature and the nerve fiber bundles in vivo now provides the opportunity to better understand the pathological processes leading to visual impairment [72–90, 129–131, 163–170]. The future of AO retinal imaging promises early detection of degenerative retinal diseases and monitoring the efficacy of treatments at a cellular level. In retinal diseases, early detection and treatment are essential to prevent the occurrence of serious damage and visual loss. It has been shown that it is possible to take images, with cellular resolution, in exactly the same retinal area over days, months and years [85, 110, 171]. The ability to longitudinally track disease progression serves as the foundation for an imaging-based approach to track treatment response with greater sensitivity and on a much shorter time scale than current outcome measures such as visual acuity and visual field sensitivity can allow. As novel treatments to slow disease progression in both inherited and acquired retinal degenerations are developed, it will be critical to evaluate the effect treatments have on individual photoreceptor cells. It is expected that AO high-resolution imaging tools will allow clinicians to track retinal disease and the efficacy of therapy with great accuracy, helping to accelerate the search for new strategies of secondary prevention to avoid serious visual loss.

High cost and system complexity currently hinder the wide adoption of AO technology in clinical ophthalmology. Most AO retinal cameras have been designed and constructed for the best imaging performance possible, with the exclusion of all other factors, including size, cost, complexity, ease-of-use, time required to obtain, process, and analyze the retinal images, etc. This is delaying the transition of AO from the research lab to the clinic. Nevertheless, important progress has been made in this regard during recent years [6, 172]: with reports of significant performance improvement of AO methods and systems for a growing number of ophthalmic applications, demand for a “commercial” AO instrument will increase and its cost should probably decrease. A compact, simplified AO instrument that can be used by ophthalmologists will facilitate the introduction of this technology into clinical practice and the development of new methodologies to detect and treat retinal diseases. Four companies have developed an AO prototype as a clinical viable tool at the time of this review (Boston Micromachines Corporation; Canon, Inc.; Imagine Eyes; and Physical Sciences, Inc.).

Another current drawback of AO imaging is the time required to obtain, process and analyze the retinal images: the continuous advances in the development of automated and reliable methods to evaluate the retinal micro-structures, including cell photoreceptors, vessels and nerve fiber bundles [82–85, 113, 114, 128, 129, 131, 163–165] is however expected to resolve this issue soon. Accurate automated routines are indeed mandatory when large quantities of data need to be analyzed. A number of research groups are evaluating methods of analysis and interpretation of AO retinal images, such as cone density and spacing and packing regularity of the cone mosaic. Functional features of the cone mosaic can be used to capture additional information that cannot be described by the above metrics, such as the variation of cell brightness between adjacent domains of healthy and abnormal cones [153]. Continuing efforts to develop new image analysis metrics will increase the clinical utility of AO retinal imaging.