Computational assessment of the retinal vascular tortuosity integrating domain-related information

[Abstract] The retinal vascular tortuosity presents a valuable potential as a clinical biomarker of many relevant vascular and systemic diseases. Commonly, the existent approaches face the tortuosity quantification by means of fully mathematical representations of the vessel segments. However, the specialists, based on their diagnostic experience, commonly analyze additional domain-related information that is not represented in these mathematical metrics of reference. In this work, we propose a novel computational tortuosity metric that outperforms the mathematical metrics of reference also incorporating anatomical properties of the fundus image such as the distinction between arteries and veins, the distance to the optic disc, the distance to the fovea, and the vessel caliber. The evaluation of its prognostic performance shows that the integration of the anatomical factors provides an accurate tortuosity assessment that is more adjusted to the specialists’ perception.Instituto de Salud Carlos II; DTS18/00136Ministerio de Ciencia, Innovación y Universidades; DPI2015-69948-RMinisterio de Ciencia, Innovación y Universidades; RTI2018-095894-B-I00Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2016-04

Artery/Vein Vessel Tree Identification in Near-Infrared Reflectance Retinographies

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10278-019-00235-x[Abstract]: An accurate identification of the retinal arteries and veins is a relevant issue in the development of automatic computer-aided diagnosis systems that facilitate the analysis of different relevant diseases that affect the vascular system as diabetes or hypertension, among others. The proposed method offers a complete analysis of the retinal vascular tree structure by its identification and posterior classification into arteries and veins using optical coherence tomography (OCT) scans. These scans include the near-infrared reflectance retinography images, the ones we used in this work, in combination with the corresponding histological sections. The method, firstly, segments the vessel tree and identifies its characteristic points. Then, Global Intensity-Based Features (GIBS) are used to measure the differences in the intensity profiles between arteries and veins. A k-means clustering classifier employs these features to evaluate the potential of artery/vein identification of the proposed method. Finally, a post-processing stage is applied to correct misclassifications using context information and maximize the performance of the classification process. The methodology was validated using an OCT image dataset retrieved from 46 different patients, where 2,392 vessel segments and 97,294 vessel points were manually labeled by an expert clinician. The method achieved satisfactory results, reaching a best accuracy of 93.35% in the identification of arteries and veins, being the first proposal that faces this issue in this image modality.This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research project and by the Ministerio de Economía y Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received financial support from the European Union (European Regional Development Fund—ERDF); the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016–2019, Ref. ED431G/01; and Grupos de Referencia Competitiva, Ref. ED431C 2016-047.Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2016-04

Digital ocular fundus imaging: a review

Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs.Fundação para a Ciência e TecnologiaFEDErPrograma COMPET

The Retinal Microvasculature in Secondary Progressive Multiple Sclerosis

In light of new data regarding pathology of multiple sclerosis (MS), more research is needed into the vascular aspects of the disease. Demyelination caused by inflammation is historically thought of as the main cause of disability in the disease. Recent studies, however, have suggested that MS is in fact a spectrum of overlapping phenotypes consisting of inflammation, oxidative damage and hypoperfusion. The microvasculature plays an important role in all of these pathogenic processes and its dysfunction may therefore be of crucial importance to the development and progression of the disease. This thesis focuses on investigating the microvasculature of the retina as a surrogate for the brain by assessing the vascular structure, blood flow dynamics and oxygen transfer of the retinal blood vessels in secondary progressive multiple sclerosis (SPMS). Studying the retinal microvasculature using a multimodal imaging approach has allowed us to develop a more detailed understanding of blood flow in MS and to identify new imaging markers for trials into neuroprotective drugs in MS. The work done in this thesis demonstrated; i) a higher rate of retinal microvascular abnormalities in MS which progresses with disease severity, ii) evidence of retinal vascular remodelling in SPMS and iii) changes in blood velocity and flow in the retina in SPMS. These observations pave the way for future investigations into the mechanisms of vascular alterations and vascular dysfunction in MS, and provide a set of imaging markers to further explore other cerebrovascular diseases through the retina