Enrico Pellegrini

Novel VAMPIRE algorithms for quantitative analysis of the retinal vasculature

This paper summarizes three recent, novel algorithms developed within VAMPIRE, namely optic disc and macula detection, arteryvein classification, and enhancement of binary vessel masks, and their performance assessment. VAMPIRE is an international collaboration growing a suite of software tools to allow efficient quantification of morphological properties of the retinal vasculature in large collections of fundus camera images. VAMPIRE measurements are currently mostly used in biomarker research, i.e., investigating associations between the morphology of the retinal vasculature and a number of clinical and cognitive conditions.

Blood vessel segmentation and width estimation in ultra-wide field scanning laser ophthalmoscopy

Features of the retinal vasculature, such as vessel widths, are considered biomarkers for systemic disease. The aim of this work is to present a supervised approach to vessel segmentation in ultra-wide field of view scanning laser ophthalmoscope (UWFoV SLO) images and to evaluate its performance in terms of segmentation and vessel width estimation accuracy. The results of the proposed method are compared with ground truth measurements from human observers and with existing state-of-the-art techniques developed for fundus camera images that we optimized for UWFoV SLO images. Our algorithm is based on multi-scale matched filters, a neural network classifier and hysteresis thresholding. After spline-based refinement of the detected vessel contours, the vessel widths are estimated from the binary maps. Such analysis is performed on SLO images for the first time. The proposed method achieves the best results, both in vessel segmentation and in width estimation, in comparison to other automatic techniques.

The application of retinal fundus camera imaging in dementia: A systematic review

The ease of imaging the retinal vasculature, and the evolving evidence suggesting this microvascular bed might reflect the cerebral microvasculature, presents an opportunity to investigate cerebrovascular disease and the contribution of microvascular disease to dementia with fundus camera imaging.

Application of the ordered logit model to optimising Frangi filter parameters for segmentation of perivascular spaces

Segmentation of perivascular spaces (PVS) from brain magnetic resonance images (MRI) is important for understanding the brains lymphatic system and its relationship with neurological diseases. The Frangi filter might be a valuable tool for this purpose. However, its parameters need to be adjusted in response to the variability in the scanners parameters and study protocols. Knowing the neuroradiological ratings of the PVS, we used the ordered logit model to optimise Frangi filter parameters. The PVS volume obtained significantly and strongly correlated with neuroradiological assessments (Spearmans ρ=0.75, p < 0.001), suggesting that the ordered logit model could be a good alternative to conventional optimisation frameworks for segmenting PVS on MRI.

Peripheral Retinal Imaging Biomarkers for Alzheimer's Disease: A Pilot Study

Purpose: To examine whether ultra-widefield (UWF) retinal imaging can identify biomarkers for Alzheimer’s disease (AD) and its progression. Methods: Images were taken using a UWF scanning laser ophthalmoscope (Optos P200C AF) to determine phenotypic variations in 59 patients with AD and 48 healthy controls at baseline (BL). All living participants were invited for a follow-up (FU) after 2 years and imaged again (if still able to participate). All participants had blood taken for genotyping at BL. Images were graded for the prevalence of age-related macular degeneration-like pathologies and retinal vascular parameters. Comparison between AD patients and controls was made using the Student t test and the χ2 test. Results: Analysis at BL revealed a significantly higher prevalence of a hard drusen phenotype in the periphery of AD patients (14/55; 25.4%) compared to controls (2/48; 4.2%) [χ2 = 9.9, df = 4, p = 0.04]. A markedly increased drusen number was observed at the 2-year FU in patients with AD compared to controls. There was a significant increase in venular width gradient at BL (zone C: 8.425 × 10–3 ± 2.865 × 10–3 vs. 6.375 × 10–3 ± 1.532 × 10–3, p = 0.008; entire image: 8.235 × 10–3 ± 2.839 × 10–3 vs. 6.050 × 10–3 ± 1.414 × 10–3, p = 0.004) and a significant decrease in arterial fractal dimension in AD at BL (entire image: 1.250 ± 0.086 vs. 1.304 ± 0.089, p = 0.049) with a trend for both at FU. Conclusions: UWF retinal imaging revealed a significant association between AD and peripheral hard drusen formation and changes to the vasculature beyond the posterior pole, at BL and after clinical progression over 2 years, suggesting that monitoring pathological changes in the peripheral retina might become a valuable tool in AD monitoring.

Towards Standardization of Quantitative Retinal Vascular Parameters: Comparison of SIVA and VAMPIRE Measurements in the Lothian Birth Cohort 1936

Purpose Semiautomated software applications derive quantitative retinal vascular parameters from fundus camera images. However, the extent of agreement between measurements from different applications is unclear. We evaluate the agreement between retinal measures from two software applications, the Singapore “I” Vessel Assessment (SIVA) and the Vessel Assessment and Measurement Platform for Images of the Retina (VAMPIRE), and examine respective associations between retinal and systemic outcomes. Method Fundus camera images from 665 Lothian Birth Cohort 1936 participants were analyzed with SIVA and VAMPIRE. Intraclass correlation coefficients (ICC) and Bland-Altman plots assessed agreement between retinal parameters: measurements of vessel width, fractal dimension, and tortuosity. Retinal–systemic variable associations were assessed with Pearsons correlation, and intersoftware correlation magnitude differences were examined with Williamss test. Results ICC values indicated poor to limited agreement for all retinal parameters (0.159–0.410). Bland-Altman plots revealed proportional bias in the majority, and systematic bias in all measurements. SIVA and VAMPIRE measurements were associated most consistently with systemic variables relating to blood pressure (SIVA rs from −0.122 to −0.183; VAMPIRE rs from −0.078 to −0.177). Williamss tests indicated significant differences in the magnitude of association between retinal and systemic variables for 7 of 77 comparisons (P < 0.05). Conclusions Agreement between two common software applications was poor. Further studies are required to determine whether associations with systemic variables are software-dependent. Translational Relevance Standardization of the measurement of retinal vascular parameters is warranted to ensure that they are reliable and application-independent. This would be an important step towards realizing the potential of the retina as a source of imaging-derived biomarkers that are clinically useful.

Investigating post-processing of scanning laser ophthalmoscope images for unsupervised retinal blood vessel detection

We explore post-processing of scanning laser ophthalmoscope (SLO) images for the automatic detection of retinal blood vessels. The retinal vasculature is first enhanced using morphological and Gaussian matched filters before a thresholding technique produces a binary vessel map. Such permutations of post-processing techniques are commonly used to achieve unsupervised classification of the vasculature in fundus images, and it is the purpose of this study to investigate their applicability to SLO imaging. We compare the results of vascular detection as performed on SLO and fundus images.

A Graph Cut Approach to Artery/Vein Classification in Ultra-Widefield Scanning Laser Ophthalmoscopy

The classification of blood vessels into arterioles and venules is a fundamental step in the automatic investigation of retinal biomarkers for systemic diseases. In this paper, we present a novel technique for vessel classification on ultra-wide-field-of-view images of the retinal fundus acquired with a scanning laser ophthalmoscope. To the best of our knowledge, this is the first time that a fully automated artery/vein classification technique for this type of retinal imaging with no manual intervention has been presented. The proposed method exploits hand-crafted features based on local vessel intensity and vascular morphology to formulate a graph representation from which a globally optimal separation between the arterial and venular networks is computed by graph cut approach. The technique was tested on three different data sets (one publicly available and two local) and achieved an average classification accuracy of 0.883 in the largest data set.

Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: A systematic review

Advanced machine learning methods might help to identify dementia risk from neuroimaging, but their accuracy to date is unclear.

Evaluation of coronary artery disease as a risk factor for reticular pseudodrusen

Purpose Reticular pseudodrusen (RPD) are a risk factor for late age-related macular degeneration (AMD). Associations between RPD and coronary artery disease (CAD) have been reported from small case–control studies. This study investigated the association of RPD within a predominantly CAD cohort. Methods A subgroup of subjects from a multicentre randomised controlled trial of CT coronary angiography (CTCA) underwent ultrawide field (UWF) retinal imaging CAD determined by CTCA and was categorised as normal, non-obstructive or obstructive. Specific AMD features in UWF images were graded. Standardised grids were used to record the spatial location of AMD features, including RPD. Multivariate confounder adjusted regression models assessed the association between RPD and CAD. Results The 534 participants were aged 27–75 years (mean 58±9 years; 425 (80%) ≥50 years) with a male preponderance (56%). Within the study sample, 178 (33%) had no CAD, 351 (66%) had CAD. RPD was detected in 30 participants (5.6%) and bilaterally in 23. Most participants with bilateral RPD had intermediate AMD 17 (74%). After adjustment for potential confounders (age, sex, drusen >125 µm, smoking status), multivariate analysis found no significant association between CAD and RPD (OR 1.31; 95% CI (0.57 to 3.01); p=0.52). A significant association was identified between RPD and intermediate AMD (OR 3.18; 95% CI (1.61 to 6.27); p=0.001). Conclusion We found no evidence to support an association between CAD and RPD. RPD was strongly associated with intermediate AMD features. Trial registration number NCT01149590, Post results.