Automatic Identification and Intuitive Map Representation of the Epiretinal Membrane Presence in 3D OCT Volumes

[Abstract] Optical Coherence Tomography (OCT) is a medical image modality providing high-resolution cross-sectional visualizations of the retinal tissues without any invasive procedure, commonly used in the analysis of retinal diseases such as diabetic retinopathy or retinal detachment. Early identification of the epiretinal membrane (ERM) facilitates ERM surgical removal operations. Moreover, presence of the ERM is linked to other retinal pathologies, such as macular edemas, being among the main causes of vision loss. In this work, we propose an automatic method for the characterization and visualization of the ERM’s presence using 3D OCT volumes. A set of 452 features is refined using the Spatial Uniform ReliefF (SURF) selection strategy to identify the most relevant ones. Afterwards, a set of representative classifiers is trained, selecting the most proficient model, generating a 2D reconstruction of the ERM’s presence. Finally, a post-processing stage using a set of morphological operators is performed to improve the quality of the generated maps. To verify the proposed methodology, we used 20 3D OCT volumes, both with and without the ERM’s presence, totalling 2428 OCT images manually labeled by a specialist. The most optimal classifier in the training stage achieved a mean accuracy of 91.9%. Regarding the post-processing stage, mean specificity values of 91.9% and 99.0% were obtained from volumes with and without the ERM’s presence, respectively.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 projects and by the Ministerio de Ciencia, Innovación y Universidades, Government of Spain through the DPI2015-69948-R and RTI2018-095894-B-I00 research projects. Moreover, this work has received financial support from the European Union (European Regional Development Fund—ERDF) and the Xunta de Galicia, Grupos de Referencia Competitiva, Ref. ED431C 2016-047.Xunta de Galicia; ED431C 2016-04

Distinctive Mechanisms and Patterns of Exudative Versus Tractional Intraretinal Cystoid Spaces as Seen With Multimodal Imaging.

PurposeTo determine clear-cut distinctions between tractional and exudative intraretinal cystoid spaces subtypes.DesignRetrospective, multicenter, observational case series.MethodsA cohort of patients diagnosed with intraretinal cystoid spaces and imaged with optical coherence tomography (OCT), fluorescein angiography (FA), blue fundus autofluorescence (BFAF), en face OCT, and OCT angiography (OCT-A) was included in the study. All images were qualitatively and quantitatively evaluated.ResultsIn this study were included 72 eyes of 69 patients. Exudative intraretinal cystoid spaces (36/72 eyes, 50%) displayed a "petaloid" morphology as seen with en face OCT, FA, and BFAF. Tractional intraretinal cystoid spaces (24/72 eyes, 33.3%), displayed a radial "spoke-wheel" en face OCT pattern. There was no leakage with FA and BFAF did not reveal specific patterns. Eyes with full-thickness macular hole (FTMH, 12/72 eyes, 16.7%) displayed a "sunflower" en face OCT appearance. FTMH showed OCT, OCT-A, and BFAF features of both exudative and tractional cystoid spaces, but without any FA leakage. Inner nuclear layer (INL) thickness was significantly lower in tractional cystoid spaces (P < .001). There were a greater number of INL cystoid spaces in both the exudative and FTMH subgroups (P = .001). The surface area of INL cystoid spaces was significantly lower in the tractional subgroup (P < .001). There was a significant reduction of the microvascular density in eyes with exudative vs tractional (P = .002) and FTMH (P < .001) subgroups.ConclusionsExudative and tractional intraretinal cystoid spaces displayed characteristic multimodal imaging features and they may represent 2 different pathologic conditions with equally different clinical implications

Diabetic Macular Edema Characterization and Visualization Using Optical Coherence Tomography Images

[Abstract] Diabetic Retinopathy and Diabetic Macular Edema (DME) represent one of the main causes of blindness in developed countries. They are characterized by fluid deposits in the retinal layers, causing a progressive vision loss over the time. The clinical literature defines three DME types according to the texture and disposition of the fluid accumulations: Cystoid Macular Edema (CME), Diffuse Retinal Thickening (DRT) and Serous Retinal Detachment (SRD). Detecting each one is essential as, depending on their presence, the expert will decide on the adequate treatment of the pathology. In this work, we propose a robust detection and visualization methodology based on the analysis of independent image regions. We study a complete and heterogeneous library of 375 texture and intensity features in a dataset of 356 labeled images from two of the most used capture devices in the clinical domain: a CIRRUSTM HD-OCT 500 Carl Zeiss Meditec and 179 OCT images from a modular HRA + OCT SPECTRALIS® from Heidelberg Engineering, Inc. We extracted 33,810 samples for each type of DME for the feature analysis and incremental training of four different classifier paradigms. This way, we achieved an 84.04% average accuracy for CME, 78.44% average accuracy for DRT and 95.40% average accuracy for SRD. These models are used to generate an intuitive visualization of the fluid regions. We use an image sampling and voting strategy, resulting in a system capable of detecting and characterizing the three types of DME presenting them in an intuitive and repeatable way.Xunta de Galicia; ED431G 2019/01This research was funded by Instituto de Salud Carlos III, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia, Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project, Ayudas para la formación de profesorado universitario (FPU), grant ref. FPU18/02271; CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, receives financial support from Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia, through the ERDF (80%) and Secretaría Xeral de Universidades (20%)

Optical coherence tomography: evaluation and clinical application

The ability to examine the appearance of the retina is of paramount importance for the diagnosis and monitoring of ophthalmic disease and for the evaluation of treatment outcomes. Direct cross-sectional imaging of retinal structure could be useful for early diagnosis and more sensitive monitoring of a variety of retinal conditions such as macular oedema and glaucoma. The view of the fundus given by ophthalmoscopy provides very limited depth information and clinicians will often have to resort to additional techniques such as flourescein angiography or visual field testing for information on structural abnormalities within the retina. Other currently available imaging techniques do not provide sufficient depth resolution to produce useful cross-sectional images of retinal structure. Optical coherence tomography (OCT) is a new imaging technique which is capable of producing cross-sectional images of the retina with a resolution that surpasses that of conventional imaging techniques. This new technique has axial resolution of around 1 O.tm and can resolve individual retinal layers, thus providing information on retinal structure. In principle, OCT is very similar to ultrasound however it makes use of a light source rather than an acoustic one. The technique is non-contact and non-invasive and is generally well tolerated by patients. This thesis describes the evaluation of this new imaging technique with regards to its potential within routine clinical practice. A number of investigations were performed to fuffil this evaluation. Tests were carried out to experimentally measure the system's resolution and the accuracy and precision of measurements made from the OCT scans. A number of factors that could affect the quality of the scans were identified and their effects were minimised wherever possible. The software provided with the system was rigorously tested and potential sources of error were identified. Various studies were undertaken to quantify the repeatability and reproducibility of measurements made from scans and normative values were established. These results were used to assess the ability of the technique to detect and quantify several retinal disorders. The potential of the technique for corneal imaging was investigated - a scanning protocol was established and customised software for processing cornea! scans was developed. The relationship between OCT bands and retinal morphology was investigated by correlating scans from canine retina with corresponding light microscopy images and by observing the position of retinal abnormalities on scans from patients with a variety of conditions that affected different parts of the retina. Finally the clinical potential of OCT was investigated by carrying out various studies on a number of retinal conditions. Further clinical studies which combine anatomical information from OCT with functional information from electrophysiology are currently underway. Current developments are aimed at improving the imaging processing features and user interface so as to provide a more robust, user-friendly system for routine clinical use