Reliability of Using Retinal Vascular Fractal Dimension as a Biomarker in the Diabetic Retinopathy Detection

Abstract

The retinal fractal dimension (FD) is a measure of vasculature branching pattern complexity. FD has been considered as a potential biomarker for the detection of several diseases like diabetes and hypertension. However, conflicting findings were found in the reported literature regarding the association between this biomarker and diseases. In this paper, we examine the stability of the FD measurement with respect to (1) different vessel annotations obtained from human observers, (2) automatic segmentation methods, (3) various regions of interest, (4) accuracy of vessel segmentation methods, and (5) different imaging modalities. Our results demonstrate that the relative errors for the measurement of FD are significant and FD varies considerably according to the image quality, modality, and the technique used for measuring it. Automated and semiautomated methods for the measurement of FD are not stable enough, which makes FD a deceptive biomarker in quantitative clinical applications.

Systematic Review on Fractal Dimension of the Retinal Vasculature in Neurodegeneration and Stroke: Assessment of a Potential Biomarker

“…FDCt(ABC) was revealed as a better predictor of stroke compared with SFDt(ABC) and BCFDt(ABC), with overall lower median value for cases compared to controls Agreement between different software packages appears to be poor (McGrory et al, 2018). Huang et al showed an important effect of vessel annotations from human observers, automatic segmentation methods, various regions of interest, accuracy of vessel segmentation methods, and different imaging modalities on FD measurement, suggesting FD must be determined under very strict conditions to deliver a stable parameter (Huang et al, 2016). After image processing, automated FD calculation was performed.…”

A fully automated pipeline of extracting biomarkers to quantify vascular changes in retina-related diseases

“…In the framework of the RetintaCheck project 1 (Dashtbozorg et al 2016a), we have developed several retinal image analysis tools including automatic retinal vessel enhancement (Zhang et al 2016b;AbbasiSureshjani et al 2015), segmentation (Zhang et al 2015(Zhang et al , 2016a, OD/fovea detection (Dashtbozorg et al 2016b), artery/vein classification (Huang et al 2017a(Huang et al , 2018, calibre calculation (Huang et al 2017b), vessel curvature measurement (Bekkers et al 2015) and fractal analysis (Huang et al 2015(Huang et al , 2016 to obtain important vessel biomarkers like central retinal arterial equivalent (CRAE), central retinal venous equivalent (CRVE), the arterial-venous diameter ratio (AVR), vessel tortuosity and FD.…”

“…where NðrÞ represents some measurements applied on the complicated pattern of the object at a scale r, and F is the FD that implies how many new similar patterns are observed as the scale changes. For the calculation of the FD, we use the method proposed by Huang et al (2016). The FD is computed on the binary segmented images using three classic FD measurements that are widely used in the literature.…”

“…These three measurements are the box dimension (BD), information dimension (ID) and correlation dimension (CD), which measure different properties of the selfsimilar pattern of the retinal vessel structures, respectively. In this paper, we extensively estimate the FD of a vascular network by using the BD, ID, CD (Huang et al 2016), Renyi FD spectrum, Mandelbrot singularity spectrum and the lacunarity (Kinsner 2008). BD is the direct implementation of the Hausdorff dimension in mathematics.…”

Artery/vein classification using reflection features in retina fundus images

“…Many clinical studies on retinal vascular changes reveal that biomarkers like vessel tortuosity and vessel caliber are associated with the development of diabetic retinopathy, glaucoma, hypertension and other cardiovascular diseases [1][2][3]. In addition, previous works on retinal fractal dimension [4] and vascular tortuosity [5] implied that traditional retinal biomarkers might reveal more information for disease progression if they were measured separately on arteries and veins. Therefore, A/V classification is a necessary step for the measurement of retinal vascular biomarkers, such as central artery equivalent and central vein equivalent and artery-to-vein diameter ratio (AVR) [6,7].…”