Introduction: Ocular manifestations in several neurological pathologies accentuate the strong relationship between the eye and the brain. Retinal alterations in particular can serve as surrogates for cerebral changes. Offering a “window to the brain,” the transparent eye enables non-invasive imaging of these changes in retinal structure and vasculature. Fractal dimension (FD) reflects the overall complexity of the retinal vasculature. Changes in FD could reflect subtle changes in the cerebral vasculature that correspond to preclinical stages of neurodegenerative diseases. In this review, the potential of this retinal vessel metric to serve as a biomarker in neurodegeneration and stroke will be explored. Methods: A literature search was conducted, following the PRISMA Statement 2009 criteria, in four large bibliographic databases (Pubmed, Embase, Web Of Science and Cochrane Library) up to 12 October 2019. Articles have been included based upon their relevance. Wherever possible, level of evidence (LOE) has been assessed by means of the Oxford Centre for Evidence-based Medicine Level of Evidence classification. Results: Twenty-one studies were included for qualitative synthesis. We performed a narrative synthesis and produced summary tables of findings of included papers because methodological heterogeneity precluded a meta-analysis. A significant association was found between decreased FD and neurodegenerative disease, mainly addressing cognitive impairment (CI) and dementia. In acute, subacute as well as chronic settings, decreased FD seems to be associated with stroke. Differences in FD between subtypes of ischemic stroke remain unclear. Conclusions: This review provides a summary of the scientific literature regarding the association between retinal FD and neurodegenerative disease and stroke. Central pathology is associated with a decreased FD, as a measure of microvascular network complexity. As retinal FD reflects the global integrity of the cerebral microvasculature, it is an attractive parameter to explore. Despite obvious concerns, mainly due to a lack of methodological standardization, retinal FD remains a promising non-invasive and low-cost diagnostic biomarker for neurodegenerative and cerebrovascular disease. Before FD can be implemented in clinic as a diagnostic biomarker, the research community should strive for uniformization and standardization.

Introduction: The eye offers potential for the diagnosis of Alzheimer’s disease (AD) with retinal imaging techniques being explored to quantify amyloid accumulation and aspects of neurodegeneration. To assess these changes, this proof-of-concept study combined hyperspectral imaging and optical coherence tomography to build a classification model to differentiate between AD patients and controls. Methods: In a memory clinic setting, patients with a diagnosis of clinically probable AD (n = 10) or biomarker-proven AD (n = 7) and controls (n = 22) underwent non-invasive retinal imaging with an easy-to-use hyperspectral snapshot camera that collects information from 16 spectral bands (460–620 nm, 10-nm bandwidth) in one capture. The individuals were also imaged using optical coherence tomography for assessing retinal nerve fiber layer thickness (RNFL). Dedicated image preprocessing analysis was followed by machine learning to discriminate between both groups. Results: Hyperspectral data and retinal nerve fiber layer thickness data were used in a linear discriminant classification model to discriminate between AD patients and controls. Nested leave-one-out cross-validation resulted in a fair accuracy, providing an area under the receiver operating characteristic curve of 0.74 (95% confidence interval [0.60–0.89]). Inner loop results showed that the inclusion of the RNFL features resulted in an improvement of the area under the receiver operating characteristic curve: for the most informative region assessed, the average area under the receiver operating characteristic curve was 0.70 (95% confidence interval [0.55, 0.86]) and 0.79 (95% confidence interval [0.65, 0.93]), respectively. The robust statistics used in this study reduces the risk of overfitting and partly compensates for the limited sample size. Conclusions: This study in a memory-clinic-based cohort supports the potential of hyperspectral imaging and suggests an added value of combining retinal imaging modalities. Standardization and longitudinal data on fully amyloid-phenotyped cohorts are required to elucidate the relationship between retinal structure and cognitive function and to evaluate the robustness of the classification model.

Purpose: Hyperspectral imaging is gaining attention in the biomedical field because it generates additional spectral information to study physiological and clinical processes. Several technologies have been described; however an independent, systematic literature overview is lacking, especially in the field of ophthalmology. This investigation is the first to systematically overview scientific literature specifically regarding retinal hyperspectral imaging. Methods: A systematic literature review was conducted, in accordance with PRISMA Statement 2009 criteria, in four bibliographic databases: Medline, Embase, Cochrane Database of Systematic Reviews, and Web of Science. Results: Fifty-six articles were found that meet the review criteria. A range of techniques was reported: Fourier analysis, liquid crystal tunable filters, tunable laser sources, dual-slit monochromators, dispersive prisms and gratings, computed tomography, fiber optics, and Fabry-Perrot cavity filter covered complementary metal oxide semiconductor. We present a narrative synthesis and summary tables of findings of the included articles, because methodologic heterogeneity and diverse research topics prevented a meta-analysis being conducted. Conclusions: Application in ophthalmology is still in its infancy. Most previous experiments have been performed in the field of retinal oximetry, providing valuable information in the diagnosis and monitoring of various ocular diseases. To date, none of these applications have graduated to clinical practice owing to the lack of sufficiently large validation studies. Translational Relevance: Given the promising results that smaller studies show for hyperspectral imaging (e.g., in Alzheimer's disease), advanced research in larger validation studies is warranted to determine its true clinical potential.

Glaucoma remains a frequent serious complication following cataract surgery in children. The optimal approach to management for ‘glaucoma following cataract surgery’ (GFCS), one of the paediatric glaucoma subtypes, is an ongoing debate. This review evaluates the various management options available and aims to propose a clinical management strategy for GFCS cases. A literature search was conducted in four large databases (Cochrane, PubMed, Embase, and Web of Science), from 1995 up to December 2021. Thirty-nine studies—presenting (1) eyes with GFCS; a disease entity as defined by the Childhood Glaucoma Research Network Classification, (2) data on treatment outcomes, and (3) follow-up data of at least 6 months—were included. Included papers report on GFCS treated with angle surgery, trabeculectomy, glaucoma drainage device implantation (GDD), and cyclodestructive procedures. Medical therapy is the first-line treatment in GFCS, possibly to bridge time to surgery. Multiple surgical procedures are often required to adequately control GFCS. Angle surgery (360 degree) may be considered before proceeding to GDD implantation, since this technique offers good results and is less invasive. Literature suggests that GDD implantation gives the best chance for long-term IOP control in childhood GFCS and some studies put this technique forward as a good choice for primary surgery. Cyclodestruction seems to be effective in some cases with uncontrolled IOP. Trabeculectomy should be avoided, especially in children under the age of one year and children that are left aphakic. The authors provide a flowchart to guide the management of individual GFCS cases.

Précis: In reducing intraocular pressure (IOP), Paul (PGI) and Baerveldt (BGI) glaucoma implants are safe and effective in patients with glaucoma. Objective: To compare efficacy and safety profiles of the PGI and BGI in the treatment of medically uncontrolled glaucoma at 1 year of follow-up. Methods: Retrospective analysis of patients implanted with a PGI or BGI with a minimum of 12 months follow-up. The primary outcome was surgical success defined as IOP ≥6 and ≤18 mm Hg and at least 20% IOP reduction from baseline. Secondary outcomes included IOP measurements, number of medications, and complications. Results: Twenty-three patients implanted with PGI and 27 with BGI were included. At last visit (12 mo), mean IOP had decreased from 23.7 ± 6.9 to 0.1 ± 2.9 mm Hg in the PGI group versus 26 ± 7.3 to 10.4 ± 4.9 mm Hg with the BGI (P < 0.001 for both comparisons). Overall qualified success rates were similar between groups (PGI 91% vs BGI 89%, P = 0.784). IOP was significantly lower in the PGI at week 1 and month 1 of follow-up versus the BGI (13.6 ± 6.1 vs 20.1 ± 7.4; 14.6±3.8 vs 21.2 ± 5.8 mm Hg; P < 0.002 for both) with a lower number of medications (1.57 ± 1.47 vs 2.52 ± 1.16 at mo 1, P = 0.015). Most complications were minor and similar in both groups. Conclusion: Both PGI and BGI are safe and effective in reducing IOP in patients with glaucoma, with similar success rates.

Purpose This cross-sectional study investigates the association between retinal vessel complexity and age and studies the effects of cardiovascular health determinants. Methods Retinal vessel complexity was assessed by calculating the box-counting fractal dimension (D_f) from digital fundus photographs of 850 subjects (3–97 years). All photographs were labelled as ‘non-pathological’ by the treating ophthalmologist. Results Statistical models showed a significantly decreasing relationship between age and D_f (linear: R-squared = 0.1897, p < 0.0001; quadratic: R-squared = 0.2343, p < 0.0001; cubic: R-squared = 0.2721, p < 0.0001), with the cubic regression model offering the best compromise between accuracy and model simplicity. Multivariate cubic regression showed that age, spherical equivalent and smoking behaviour have an effect (p < 0.0001) on D_f. A significantly increasing effect of the number of pack-years on D_f was observed (effect: 0.0004, p = 0.0017), as well as a significantly decreasing effect of years since tobacco abstinence (effect: −0.0149, p < 0.0001). Conclusion We propose using a cubic trend with age, refractive error and smoking behaviour when interpreting retinal vessel complexity.