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Neovascularization Detection in Diabetic Retinopathy from Fluorescein Angiograms

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Neovascularization Detection in Diabetic Retinopathy from Fluorescein Angiograms Neovascularization Detection in Diabetic Retinopathy from Fluorescein Angiograms Benjamin Béouche-Hélias, David Helbert, Cynthia de Malézieu, Nicolas Leveziel, Christine Fernandez-Maloigne To cite this version: Benjamin Béouche-Hélias, David Helbert, Cynthia de Malézieu, Nicolas Leveziel, Christine Fernandez- Maloigne. Neovascularization Detection in Diabetic Retinopathy from Fluorescein Angiograms. Jour- nal of Medical Imaging, SPIE Digital Library, 2017, 4 (4), pp.044503. 10.1117/1.JMI.4.4.044503. hal-01625993 HAL Id: hal-01625993 https://hal.archives-ouvertes.fr/hal-01625993 Submitted on 3 Apr 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Neovascularization Detection in Diabetic retinopathies is one of the first cause of visual impairment worldwide, due to the increasing incidence Diabetic Retinopathy from of diabetes. Proliferative diabetic retinopathy (PDR) is Fluorescein Angiograms define by the outgrowth of preretinal vessels leading to retinal complication i.e. intravitreous hemorrhages and retinal detachments. Today the laser photocoagulation a b,* Benjamin Beouche-H´ elias´ , David Helbert , Cynthia is the standard of care treatment of proliferative diabetic a a de Malezieu´ , Nicolas Leveziel , Christine retinopathy, leading to a decrease of growth factors secre- b Fernandez-Maloigne tion in photoagulated areas of the retina. aDepartment of Ophthalmology, CHU Poitiers, 2 rue de la Miletrie,´ BP 577,86021 Poitiers cedex, France Vascular endothelial growth factor (VEGF) is responsi- bXLIM, CNRS U-7252 , University of Poitiers, 11 Bd Marie et Pierre ble of the growth of healthy vessels, but also of the NVs Curie, BP 30179 86962 Futuroscope Chasseneuil Cedex, France due to diabetes. Research is active on finding a specific type of anti-VEGF that could stop the growth of the NVs specifically. A clinical trial (ClinicalTrials.gov Identifier: Abstract. Even if a lot of work has been done on Optical Coherence NCT02151695), called ”Safety and Efficacy of Afliber- Tomography (OCT) and color images in order to detect and quantify diseases such as diabetic retinopathy, exudates or neovascularizations, cept in Proliferative Diabetic Retinopathy” is in progress none of them is able to evaluate the diffusion of the neovascularizations at the CHU of Poitiers, testing the effects of a specific in retinas. Our work has been to develop a tool able to quantify a neo- anti-VEGF : Aflibercept. This drug has been approved by vascularization and the fluorescein leakage during an angiography. The the European Medicines Agency (EMA) and the United proposed method has been developed following a clinical trial protocol, images are taken by a Spectralis (Heidelberg Engineering). Detections States Food and Drug Administration (FDA) for treat- are done using a supervised classification using specific features. Images ment of exudative age-related macular degeneration, an- and their detected neovascularizations are then spatially matched by an other retinal disease characterized by choroidal new ves- image registration.We compute the expansion speed of the liquid that sels. The aim of this pilot study is to evaluate the effi- we call diffusion index. This last one specifies the state of the disease and permits to indicate the activity of neovascularizations and allows a cacy and the safety of Aflibercept intravitreal injections follow-up of patients. The method proposed in this paper has been built compared to panretinal photocoagulation for proliferative to be robust, even with laser impacts, to compute a diffusion index. diabetic retinopathy. In ophthalmology, the majority of the works on the reti- Keywords: Diabetic retinopathy, neovascularization, classification, nal diseases is about the detection of the exudates,3–7 the anti-VEGF, diabetes. healthy vessels segmentation,8–10 the detection of the neu- *David Helbert, [email protected] ral disk11, 12 but none of them is about the detection of the proliferative diabetic retinopathy within angiograms. 1 Introduction Some works have also been done on the image regis- tration for retinal images. Can13 et al have proposed the The detection and follow-up of diabetic retinopathy, an in- registration of a pair of retinal images by using branching creasingly important cause of blindness, is a public health points and cross-over points in the vasculature. Zheng et issue. Indeed, loss of vision can be prevented by early de- al have developped in14 a registration algorithm by using tection of diabetic retinopathy and increased monitoring salient feature region description. Legg et al have illus- by regular examination. There are now many algorithms trated in15 the efficiency of mutual information for reg- for the automatic detection of common anomalies of the istration of fundus colour photographes and colour scan- retina (microaneurysms, haemorrhages, exudates, tasks, ning laser ophthalmoscope images. ...). However, very few researches have been done on the Few steps are needed to compute that diffusion index. detection of a major pathology, which is neovasculariza- It is a growth in time which means that we have to de- tion, corresponding to the growth of new blood vessels tect and quantify the pathology on both injection times due to a large lack of oxygen in the retinal capillaries. and compare their area. As it is nearly impossible to Our work has not been to substitute manual detections have exactly the same conditions during the acquisition of experts but to help them doing it by suggesting what (eye movements, focus of the camera, angle), we need areas of the retina could or not be considered as having an image registration to have an estimation of deforma- neovascularizations (NVs) and by providing quantitative tions and to correctly spatially correlate NVs. For the seg- and qualitative proliferative diabetic retinopathy such as mentation, we used a supervised classification by Random the area of NV, the location to the optical nerve, the ac- Forests16 using intensity, textural and contextual features, tivity of NV (diffusion index). The main goal has been to and a database of trained images from the clinical trials. provide a diffusion index of the injected fluorescent liq- These steps are shown in Fig.1. uid, which indicates the severity of the pathology, to fol- The paper is organized as follows. In section2 we low the patient over the years. present the microscope and the acquisition protocol. The 1 Fig 1: Example of a full detection by our method. image registration on both injection times is proposed in impacts are annoying because they are also very bright for section3. We then propose a novel neovascularization some parts. The blood still spread through some impacts, detection method in section4 and an automatic diffusion and can be big enough to be wrongly assimilated to a NV. index computation in section5. To qualify the PDR by the index leakage, different times of acquisition during fluorescein angiography were 2 Materials used. The protocol presented below is the clinical trial’s protocol which is composed of two image acquisitions: Our database is made of images taken by the c Spectralis Heidelberg Engineering microscope with an ultra- 1. fluorescein injection into the patient’s arm; widefield lens covering a 102o field of view. It deliv- ers undistorted images of a great part of the retina, mak- 2. acquisition of the early time injection (t0); ing the detection easier and monitor abnormal peripheral 3. acquisition of the late time injection (t ). changes. f The few minutes left between different acquisitions times allow visualization of the fluorescein laekage de- fined as a progressive increase of the NV area with blur- ring edges of the NV. No leakage is observed on normal retinal vessels. On Fig.3 we can see pictures of the same eye with acquisitions at t0 and tf , where we can see the fluorescein spreading first into arteries and then bleeds in neovascularizations. As images are taken by three minutes, some spatial dif- ferences occur and we need to spatially correlate both im- ages with an image registration which is presented in the next part. 15 diabetic patients were included in the analysis and ophthalmologists have identified 60 different NV from fluorescein angiographies on wide field imaging. 3 Image registration Fig 2: Image of an angiogram taken with the Heidelberg The image registration does not aim to be perfect but to al- Spectralis. Laser impacts are present all over the image, low spatial comparison between NV taken in both images some examples are highlighted in red. to compute quantitative data. The best registration model should be a local method, but for that reason just ex- Images are in gray levels, the areas that are bright are plained, a global method is widely enough for the compar- mainly 1/ those leaking during fluorescein angiography ison. Some of them are very popular and have been tested due to NV, 2/ normal retinal vessels or 3/ laser impacts. by many experts like Scale Invariant Feature Transform Some images we have taken from patients who have been (SIFT),17 Maximally Stable Extremal Regions (MSER)18 treated by laser photocoagulation, visible on Fig.2. These or Speeded Up Robust Features (SURF).19 We found that 2 ant to image scaling and rotation, and mostly invariant to change in illumination, they also need to be highly dis- tinctive by their description to be matched further. To match the extracted keypoints, we use the brute force method. For each keypoint we take the two nearest points in terms of Euclidean distance and we only keep those who the first nearest point is inferior to 0.8 times the second nearest neighbor (as proposed in17).
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