Retinal microvascular complexity comparing mono‐ and multifractal dimensions in relation to cardiometabolic risk factors in a Middle Eastern population

Abstract

Metrics that capture changes in the retinal microvascular structure are relevant in the context of cardiometabolic disease development. The microvascular topology is typically quantified using monofractals, although it obeys more complex multifractal rules. We study mono-and multifractals of the retinal microvasculature in relation to cardiometabolic factors. Methods: The cross-sectional retrospective study used data from 3000 Middle Eastern participants in the Qatar Biobank. A total of 2333 fundus images (78%) passed quality control and were used for further analysis. The monofractal (D f ) and five multifractal metrics were associated with cardiometabolic factors using multiple linear regression and were studied in clinically relevant subgroups. Results: D f and multifractals are lowered in function of age, and D f is lower in males compared to females. In models corrected for age and sex, D f is significantly associated with BMI, insulin, systolic blood pressure, glycated haemoglobin (HbA1c), albumin, LDL and total cholesterol concentrations. Multifractals are negatively associated with systolic and diastolic blood pressure, glucose and the WHO/ISH cardiovascular risk score. D f was higher, and multifractal curve asymmetry was lower in diabetic patients (HbA1c > 6.5%) compared to healthy individuals (HbA1c < 5.7%). Insulin resistance (insulin ≥ 23 mcU/mL) was associated with significantly lower D f values. Conclusion: One or more fractal metrics are in association with sex, age, BMI, systolic and diastolic blood pressure and biochemical blood measurements in a Middle Eastern population study. Follow-up studies aiming at investigating retinal microvascular changes in relation to cardiometabolic risk should analyse both monofractal and multifractal metrics for a more comprehensive microvascular picture.

TREND database: Retinal images of healthy young subjects visualized by a portable digital non-mydriatic fundus camera

“…As a proof of concept, our present study shows that all measured variables except lacunarity dimension were significantly lower in older group of participants confirming that complexity of microvascular network decreases with the age (Table 6 and Fig 4), which is in agreement with findings of other researchers [1,[20][21][22]. In these studies, age was associated with microvascular complexity measured by fractal dimension independent of other variables.…”

“…As a proof of the concept, a smaller set of 10 color digital fundus images from healthy older participants was also included. The 82 retinal images were used to show that differences in age, gender, body mass index (BMI), alcohol, and tobacco use among the participants translate to changes in retinal microvascular patterns, and that the observed changes are similar to those already described by others [1,[20][21][22].…”

“…The effect of age on retinal microvascular geometry by using fractal analysis parameters and blood vessel density parameters has been described in the past by other researchers [1,[20][21][22]. These studies showed that the microvascular complexity characterized by fractal dimension decreases with age.…”

Retinal vessel multifractals predict pial collateral status in patients with acute ischemic stroke

“…However, they showed variability in fractal outcomes in different studies which was attributed to differences in populations studied, the equipment used to capture retinal images and segmentation tools used to define and calculate the fractals [ 50 ]. We have recently shown that retinal vessel multifractals are associated with glucose, hypertension and the WHO/ISH cardiovascular risk score [ 31 ] and that retinal vessel analysis is uniquely associated with blood pressure, glycemic status and obesity [ 51 ]. The current data suggests that the differences in retinal vessel fractals in patients with acute ischemic stroke may be further related to the pial collateral status.…”

“…We calculated the generalized dimensions (D q ) for q = 0, 1, and 2, which are the capacity dimension (D 0 ), which captures how much the data fills the physical space and provides global information about the structure; the information dimension (D 1 ), which captures the data density and quantifies the degree of disorder in the distribution; and correlation dimension (D 2 ), which measures how scattered the data is with a higher value indicating more compact data. For a multifractal structure, the following applies: D 0 ≥D 1 ≥D 2 [ 30 , 31 ].…”