Grading the Severity of Arteriolosclerosis from Retinal Arterio-venous Crossing Patterns

The status of retinal arteriovenous crossing is of great significance for clinical evaluation of arteriolosclerosis and systemic hypertension. As an ophthalmology diagnostic criteria, Scheie's classification has been used to grade the severity of arteriolosclerosis. In this paper, we propose a deep learning approach to support the diagnosis process, which, to the best of our knowledge, is one of the earliest attempts in medical imaging. The proposed pipeline is three-fold. First, we adopt segmentation and classification models to automatically obtain vessels in a retinal image with the corresponding artery/vein labels and find candidate arteriovenous crossing points. Second, we use a classification model to validate the true crossing point. At last, the grade of severity for the vessel crossings is classified. To better address the problem of label ambiguity and imbalanced label distribution, we propose a new model, named multi-diagnosis team network (MDTNet), in which the sub-models with different structures or different loss functions provide different decisions. MDTNet unifies these diverse theories to give the final decision with high accuracy. Our severity grading method was able to validate crossing points with precision and recall of 96.3% and 96.3%, respectively. Among correctly detected crossing points, the kappa value for the agreement between the grading by a retina specialist and the estimated score was 0.85, with an accuracy of 0.92. The numerical results demonstrate that our method can achieve a good performance in both arteriovenous crossing validation and severity grading tasks. By the proposed models, we could build a pipeline reproducing retina specialist's subjective grading without feature extractions. The code is available for reproducibility

Automated Systems for Calculating Arteriovenous Ratio in Retinographies : A Scoping Review

There is evidence of an association between hypertension and retinal arteriolar narrowing. Manual measurement of retinal vessels comes with additional variability, which can be eliminated using automated software. This scoping review aims to summarize research on automated retinal vessel analysis systems. Searches were performed on Medline, Scopus, and Cochrane to find studies examining automated systems for the diagnosis of retinal vascular alterations caused by hypertension using the following keywords: diagnosis; diagnostic screening programs; image processing, computer-assisted; artificial intelligence; electronic data processing; hypertensive retinopathy; hypertension; retinal vessels; arteriovenous ratio and retinal image analysis. The searches generated 433 articles. Of these, 25 articles published from 2010 to 2022 were included in the review. The retinographies analyzed were extracted from international databases and real scenarios. Automated systems to detect alterations in the retinal vasculature are being introduced into clinical practice for diagnosis in ophthalmology and other medical specialties due to the association of such changes with various diseases. These systems make the classification of hypertensive retinopathy and cardiovascular risk more reliable. They also make it possible for diagnosis to be performed in primary care, thus optimizing ophthalmological visits

AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline

Purpose: To externally validate a deep learning pipeline (AutoMorph) for automated analysis of retinal vascular morphology on fundus photographs. AutoMorph has been made publicly available, facilitating widespread research in ophthalmic and systemic diseases. Methods: AutoMorph consists of four functional modules: image preprocessing, image quality grading, anatomical segmentation (including binary vessel, artery/vein, and optic disc/cup segmentation), and vascular morphology feature measurement. Image quality grading and anatomical segmentation use the most recent deep learning techniques. We employ a model ensemble strategy to achieve robust results and analyze the prediction confidence to rectify false gradable cases in image quality grading. We externally validate the performance of each module on several independent publicly available datasets. Results: The EfficientNet-b4 architecture used in the image grading module achieves performance comparable to that of the state of the art for EyePACS-Q, with an F1-score of 0.86. The confidence analysis reduces the number of images incorrectly assessed as gradable by 76%. Binary vessel segmentation achieves an F1-score of 0.73 on AV-WIDE and 0.78 on DR HAGIS. Artery/vein scores are 0.66 on IOSTAR-AV, and disc segmentation achieves 0.94 in IDRID. Vascular morphology features measured from the AutoMorph segmentation map and expert annotation show good to excellent agreement. Conclusions: AutoMorph modules perform well even when external validation data show domain differences from training data (e.g., with different imaging devices). This fully automated pipeline can thus allow detailed, efficient, and comprehensive analysis of retinal vascular morphology on color fundus photographs. Translational Relevance: By making AutoMorph publicly available and open source, we hope to facilitate ophthalmic and systemic disease research, particularly in the emerging field of oculomics

Comparison of subjective and objective methods to determine the retinal arterio-venous ratio using fundus photography

Purpose: To assess the inter and intra observer variability of subjective grading of the retinal arterio-venous ratio (AVR) using a visual grading and to compare the subjectively derived grades to an objective method using a semi-automated computer program. Methods: Following intraocular pressure and blood pressure measurements all subjects underwent dilated fundus photography. 86 monochromatic retinal images with the optic nerve head centred (52 healthy volunteers) were obtained using a Zeiss FF450+ fundus camera. Arterio-venous ratios (AVR), central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) were calculated on three separate occasions by one single observer semi-automatically using the software VesselMap (ImedosSystems, Jena, Germany). Following the automated grading, three examiners graded the AVR visually on three separate occasions in order to assess their agreement. Results: Reproducibility of the semi-automatic parameters was excellent (ICCs: 0.97 (CRAE); 0.985 (CRVE) and 0.952 (AVR)). However, visual grading of AVR showed inter grader differences as well as discrepancies between subjectively derived and objectively calculated AVR (all p < 0.000001). Conclusion: Grader education and experience leads to inter-grader differences but more importantly, subjective grading is not capable to pick up subtle differences across healthy individuals and does not represent true AVR when compared with an objective assessment method. Technology advancements mean we no longer rely on opthalmoscopic evaluation but can capture and store fundus images with retinal cameras, enabling us to measure vessel calibre more accurately compared to visual estimation; hence it should be integrated in optometric practise for improved accuracy and reliability of clinical assessments of retinal vessel calibres

Fully Automatic Retinal Vascular Tortuosity Assessment Integrating Domain-Related Information

[Abstract] The fundus of the eye is the only part of the human body that allows a direct non-invasive observation of the circulatory system. Retinal vascular tortuosity presents a valuable potential for diagnostic and treatment purposes of relevant vascular and systemic diseases. This work presents a computational metric for the tortuosity characterization that combines mathematical representations of the vessel segments with anatomical properties of the fundus image such as the vessel caliber, the distance to the optic disc, the distance to the fovea and the distinction between arteries and veins. The evaluation of the prognostic performance shows that the incorporation of the domain-related information allows a reliable characterization of the retinal vascular tortuosity that provides a better representation of the expert perception.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 RTI2018-095894-B-I00 research projects; 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%)Xunta de Galicia; ED431G 2019/0

Correlation between Retinal Vessel Calibre and Neurodegeneration in Patients with Type 2 Diabetes Mellitus in the European Consortium for the Early Treatment of Diabetic Retinopathy (EUROCONDOR)

&lt;b&gt;&lt;i&gt;Purpose:&lt;/i&gt;&lt;/b&gt; To investigate the correlation between retinal vessel calibre and measurements of neurodegeneration in patients with type 2 diabetes (T2D) and no or early diabetic retinopathy (DR). &lt;b&gt;&lt;i&gt;Methods:&lt;/i&gt;&lt;/b&gt; Baseline data on 440 patients with T2D from the EUROCONDOR clinical trial were used. DR was graded according to the Early Treatment of Diabetic Retinopathy Study (ETDRS) scale, and patients with ETDRS levels 10-35 were included. Retinal vessel diameters were measured by semi-automatic software. Calibres were summarized into central retinal artery and vein equivalents (CRAE and CRVE). &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; Median age and diabetes duration were 64.0 and 10.3 years, respectively. ETDRS levels were 10 (42.3%), 20 (27.5%) and 35 (30.2%). The median CRAE and CRVE were 146.7 and 215.3 µm, respectively. CRAE did not differ according to ETRDS level (p = 0.12), but wider CRVE were found in patients with higher ETDRS levels (p = 0.04). In a multivariable linear regression model, CRAE was associated with macular ganglion cell layer thickness (coefficient 0.27 per micrometre, p &lt; 0.01), and CRVE was correlated with macular retinal thickness (coefficient -0.07 per micrometre, p = 0.04) and retinal nerve fibre layer thickness at the optic disc (coefficient 0.32 per micrometre, p &lt; 0.01). &lt;b&gt;&lt;i&gt;Conclusion:&lt;/i&gt;&lt;/b&gt; Retinal vessel calibre was independently associated with structural changes of the neuroretina in patients with no or early DR.</jats:p

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

Global tortuosity estimation of retinal vessel network in wide-field images taken from infants with retinopathy of prematurity

Determinare ed implementare un criterio automatico di tortuosità consistente con il giudizio dei clinici per ottenere una misura che possa fornire un ordinamento coerente con quelli degli espert

The retinal microcirculation in migraine: The Rotterdam Study

Background: To explore the role of microvascular pathology in migraine, we investigated the association between migraine and retinal microvascular damage. Methods: We included 3270 participants (age ≥ 45 years, 63% women) from the population-based Rotterdam Study (2006–2009). Participants with migraine were identified using a validated questionnaire based on ICHD-II criteria (n = 562). Retinopathy signs were graded on fundus photographs. Retinal arteriolar and venular caliber were measured by semi-automatic assessment of fundus photographs. Associations of migraine with retinopathy and retinal microvascular calibers were examined using logistic and linear regression models, respectively, adjusting for age, sex, and cardiovascular risk factors. Results: Migraine was not associated with the presence of retinopathy (odds ratio (OR): 1.09, 95% confidence interval (CI) 0.62; 1.92). In the fully adjusted model, adjusting for the companion vessel, persons with migraine did not differ in retina