Biomicroscopy versus optical coherence tomography screening of epiretinal membranes in patients undergoing cataract surgery.

PURPOSE: The purpose of the study is the evaluation and comparison of the relative incidence of epiretinal membrane in patients undergoing cataract surgery diagnosed with biomicroscopy versus those diagnosed with optical coherence tomography imaging (Stratus). METHODS: This prospective study evaluated 146 eyes of patients referred for cataract surgery. Considering biomicroscopic fundus appearance assessed by two examiners and OCT, the following findings were considered to indicate positivity for epiretinal membranes: biomicroscopic evidence of cellophane macular reflex, biomicroscopic evidence of macular pucker, and OCT thickening of the vitreoretinal interface with or without loss of the foveal depression. Positivity (metamorphopsia) to original Amsler test was also noted. RESULTS: Patient mean age was 72.8 ± 9.1 years. Optical coherence tomography revealed 17 eyes with macular pucker (11.6%) and 21 with cellophane macular reflex (14.4%) and, hence, a total of 38 eyes with epiretinal membrane (26%; confidence interval, 18.9-33.1%). Biomicroscopy evaluation overlooked 14 affected eyes, or 9.6% of the eyes examined. False negatives, that is, eyes affected by epiretinal membrane (cellophane macular reflex or macular pucker) and not detected biomicroscopically were 36.8% (confidence interval, 21.5-52.2.7%) and false positives were 1.9% (confidence interval, 0-4%). Amsler test was positive in 7 (18.4%) of the 38 affected eyes. CONCLUSION: This study finds that patients undergoing cataract surgery may present with epiretinal membrane that are better detected by optical coherence tomography rather than by biomicroscopy. Optical coherence tomography was more sensitive both for eyes with cellophane macular reflex and for those with macular pucker. The use of this instrument before surgery can therefore be considered.

Stochastic geometric models, and related statistical issues in tumour-induced angiogenesis.

In the modelling and statistical analysis of tumor-driven angiogenesis it is of great importance to handle random closed sets of different (though integer) Hausdorff dimensions, usually smaller than the full dimension of the relevant space. Here an original approach is reported, based on random generalized densities (distributions) á la Dirac-Schwartz, and corresponding mean generalized densities. The above approach also suggests methods for the statistical estimation of geometric densities of the stochastic fibre system that characterize the morphology of a real vascular system. A quantitative description of the evolution of tumor-driven angiogenesis requires the mathematical modelling of a strongly coupled system of a stochastic branching-and-growth process of fibres, modelling the network of blood vessels, and a family of underlying fields, modelling biochemical signals. Methods for reducing complexity include homogenization at mesoscales, thus leading to hybrid models (deterministic at the larger scale, and stochastic at lower scales); in tumor-driven angiogenesis the two scales can be bridged by introducing a mesoscale at which one locally averages the microscopic branching-and-growth process, in presence of a sufficiently large number of vessels (fibers).

Multimodal imaging and diagnosis of myopic choroidal neovascularization in Caucasians.

PURPOSE: To investigate myopic choroidal neovascularization (mCNV) by fluorescein angiography (FA), spectral-domain optical coherence tomography (SD-OCT), near-infrared (NIR) reflectance, and autofluorescence (AF). METHODS: This retrospective study included 65 eyes of 62 Caucasian patients with a mean age of 66.72 years (95% confidence interval [CI] 63-70 years) and a mean refraction of -9.72 diopters (95% CI -8.74 to -10.70 diopters). RESULTS: Most of the mCNV cases were foveal-juxtafoveal (60/65, 92.3%), with thickening of the corresponding retina (62/65, 95.3%) and leakage on FA (44/65, 67.6%). No retinal fluid was detectable in 32 (49.2%) eyes and there was no hemorrhage in 25 (38.4%) eyes. Papillary chorioretinal atrophy was evident in 58 (89.2%), a shadowing effect in 48 (73.8%), and an epiretinal membrane in 38 (58.4%) eyes. If an area of macular chorioretinal atrophy was present, mCNV frequently developed adjacent to it and was hyperfluorescent rather than with leakage (P⩽0.001). In eyes with edema or hemorrhage, hyper-reflective foci were more frequent (P⩽0.005). NIR and AF features were indeterminable in 19 (29.2%) and 27 (41.5%) eyes, respectively. The predominant feature was black or grayish on NIR (34/65, 52.3%) and patchy (hypo- and hyperfluorescence was observed) on AF (25/65, 38.4%). FA and SD-OCT correctly detected mCNV in 49 (75.3%) and 48 (73.8%) eyes, respectively, whereas NIR and AF exhibited limited diagnostic sensitivity. Doubtful diagnosis was associated with hyperfluorescent mCNV (P⩽0.001), absence of retinal fluid and epiretinal membrane (P⩽0.05), and presence of macular chorioretinal atrophy (P⩽0.01). CONCLUSION: Tomographic, angiographic, AF, and NIR features of mCNV are described in this study. Combination of SD-OCT and FA is recommendable for diagnosis.

Randomness in self-organized phenomena. A case study: retinal angiogenesis.

This note presents a review of recent work by the authors on angiogenesis, as a case study for analyzing the role of randomness in the formation of biological patterns. The mathematical description of the formation of new vessels is presented, based on a system of stochastic differential equations, coupled with a branching process, both of them driven by a set of relevant chemotactic underlying fields. A discussion follows about the possible reduction of complexity of the above approach, by mean field approximations of the underlying fields. The crucial role of randomness at the microscale is observed in order to obtain nontrivial realistic vessel networks.

Stochastic modelling of tumour-induced angiogenesis.

A major source of complexity in the mathematical modelling of an angiogenic process derives from the strong coupling of the kinetic parameters of the relevant stochastic branching-and-growth of the capillary network with a family of interacting underlying fields. The aim of this paper is to propose a novel mathematical approach for reducing complexity by (locally) averaging the stochastic cell, or vessel densities in the evolution equations of the underlying fields, at the mesoscale, while keeping stochasticity at lower scales, possibly at the level of individual cells or vessels. This method leads to models which are known as hybrid models. In this paper, as a working example, we apply our method to a simplified stochastic geometric model, inspired by the relevant literature, for a spatially distributed angiogenic process. The branching mechanism of blood vessels is modelled as a stochastic marked counting process describing the branching of new tips, while the network of vessels is modelled as the union of the trajectories developed by tips, according to a system of stochastic differential equations à la Langevin.

An interacting particle system modelling aggregation behavior: from individuals to populations.

In this paper we investigate the stochastic modelling of a spatially structured biological population subject to social interaction. The biological motivation comes from the analysis of field experiments on a species of ants which exhibits a clear tendency to aggregate, still avoiding overcrowding. The model we propose here provides an explanation of this experimental behavior in terms of "long-ranged" aggregation and "short-ranged" repulsion mechanisms among individuals, in addition to an individual random dispersal described by a Brownian motion. Further, based on a "law of large numbers", we discuss the convergence, for large N, of a system of stochastic differential equations describing the evolution of N individuals (Lagrangian approach) to a deterministic integro-differential equation describing the evolution of the mean-field spatial density of the population (Eulerian approach).