Conjunctival microvascular haemodynamics in sickle cell retinopathy

Valeshabad, Ali Kord; Wanek, Justin; Zelkha, Ruth; Lim, Jennifer I.; Camardo, Nicole; Gaynes, Bruce I.; Shahidi, Mahnaz

doi:10.1111/aos.12593

Cited by 30 publications

(29 citation statements)

References 43 publications

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“…Conjunctival microvascular and hemodynamic abnormalities including abnormal vessel diameter, vessel tortuosity, microaneurysms, and decreased blood velocity have been documented in SCD subjects 5, 6. Decreased conjunctival blood velocity has been associated with SCD complications such as stroke 16 and retinopathy 7. In this study, we reported conjunctival blood velocity in two SCD subjects with and without PH.…”

Section: Discussionmentioning

confidence: 69%

Conjunctival and pulmonary hemodynamic properties in sickle cell disease subjects with and without pulmonary hypertension

Valeshabad

Wanek

Molokie

et al. 2015

Clinical Case Reports

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Section: Discussionmentioning

confidence: 69%

Conjunctival and pulmonary hemodynamic properties in sickle cell disease subjects with and without pulmonary hypertension

Valeshabad

Wanek

Molokie

et al. 2015

Clinical Case Reports

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“…Alterations in the conjunctival microvascular hemodynamics can be readily quantified due to microcirculation accessibility for direct imaging (Cheung et al, 2002a; Cheung et al, 2009; Devaraj et al, 2007; Khansari et al, 2016b; Khansari et al, 2017; Kord Valeshabad et al, 2015; Koutsiaris et al, 2013; Smith et al, 2009). Furthermore, conjunctival microcirculation can provide insight into pathophysiology of conditions that can alter systemic circulation (Ohtani, 1996; Schaser et al, 2003; Tamosuitis et al, 2016; Yin et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…The primary conjunctival microvascular hemodynamic metrics are D and V which were shown to significantly change due to diabetes (Cheung et al, 2002a; Cheung et al, 2002b; Cheung et al, 2001; Kord Valeshabad et al, 2015). D variability was higher in more than half of DR than NC subjects, though the direction of change from the baseline to the follow-up visit was not consistent across subjects.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, commercial devices such as retinal functional imager (Jiang et al, 2013) and Heidelberg retinal flowmeter (Duench et al, 2007) have been modified to measure conjunctival hemodynamics. Application of these imaging modalities has shown conjunctival microvasculopathy and hemodynamic alterations due to systemic diseases such as Alzheimer's disease (Smith et al, 2009), hypertension (To et al, 2013), hypotension (Gaynes et al, 2012), diabetes (Khansari et al, 2017; Cheung et al, 2009; Cheung et al, 2001; Owen et al, 2008; To et al, 2011), and sickle cell disease (Cheung et al, 2002a; Kord Valeshabad et al, 2015; Paton, 1962; Wanek et al, 2013). Furthermore, a recent study showed a significant decrease in conjunctival blood flow, vessel density and non-perfused areas in brain dead subjects as compared to normal controls (Tamosuitis et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Inter-visit variability of conjunctival microvascular hemodynamic measurements in healthy and diabetic retinopathy subjects

Khansari

Tan

Karamian

et al. 2018

Microvascular Research

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Conjunctival microcirculation imaging provides a non-invasive means for detecting hemodynamic alterations due to systemic and ocular diseases. However, reliable longitudinal monitoring of hemodynamic changes due to disease progression requires establishment of measurement variability over time. The purpose of the current study was to determine inter-visit variability of conjunctival microvascular hemodynamic measurements in non-diabetic control (NC, N = 7) and diabetic retinopathy (DR, N = 10) subjects. Conjunctival microvascular imaging was performed during 2 visits, which were 17 ± 12 weeks apart. Images were analyzed to determine vessel diameter (D), axial blood velocity (V), blood flow (Q), wall shear rate (WSR) and wall shear stress (WSS). The inter-visit variability was determined based on mean inter-visit differences. In NC, inter-visit variability of D, V, Q, WSR and WSS were 0.2 ± 0.5 µm, −0.01 ± 0.16 mm/s, −8 ± 46 pl/s, −3 ± 46 s−1 and −0.01 ± 0.10 dyne/cm2, respectively. Inter-visit variability of D, V, Q, WSR and WSS were beyond the normal 95% confidence limits in 60%, 20%, 40%, 20% and 20% of DR subjects, respectively. The variability of hemodynamic measurements over time was established in non-diabetic subjects, suggestive of the potential of the method for detecting longitudinal changes due to progression of DR.

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“…On the other hand in extreme cases of sickle cell crisis, a dramatic near zero flow in cutaneous capillaries can occur [21,24] because of the extremely reduction of the deformability of the sickled erythrocytes [27] together with their adhesiveness [3].…”

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confidence: 99%

Role of blood viscosity in the microcirculation

Jung

Rampling

2017

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Blood fluidity is reported to influence capillary perfusion in healthy subjects and especially in patients with different diseases [6,10,29,31]. Up to now there is no simple way to quantify the influence of the different haemorheological parameters (haematocrit, plasma viscosity, erythrocyte aggregation, erythrocyte deformability) on the velocity of blood cells in human capillaries. In general, only a limited correlation can be shown [18]. One reason is the great variability of the diameter of human capillaries described in healthy subjects, with values between 3 and 15 m, and in patientsdepending on the disease -with values up to 50 m (e.g. giant capillaries in patients with scleroderma [33]). This is a very large range with respect to the role of the various haemorheological parameters of blood in microcirculation.The hypothesis of Barras, that plasma viscosity determines the perfusion of microvessels because the absolute capillary haematocrit is about 10-20%, so that blood viscosity in capillaries approaches plasma viscosity seems to be near the truth [4], as long as the capillary diameter is big in relation to the erythrocyte diameter. The work of Lipowsky would seem to confirm this [25]. In the case where the capillary diameter is smaller than the red blood cell diameter, the cells have to be deformed by shear forces before passing through a capillary. In this case the blood flow velocity should additionally depend on the erythrocyte deformability. This fact, which results from a fluid-dynamical point of view, however, is often not seen in patients using capillary microscopy in nailfold capillaries: neighbouring capillaries with different diameters and fed from the same arteriole show the same red blood cell velocity. Therefore we conclude that there is a regulatory mechanism in the capillary network possibly by the microvascular endothelium as described by different groups [8,15,26,34].In an animal model Driessen showed that rigidified erythrocytes slow down the capillary blood flow (up to stasis) only if the blood pressure was lowered below the normotensive state [9]. On the other hand in extreme cases of sickle cell crisis, a dramatic near zero flow in cutaneous capillaries can occur [21,24] because of the extremely reduction of the deformability of the sickled erythrocytes [27] together with their adhesiveness [3].The problem is more complicated in cases of a pathologically elevated erythrocyte aggregation. Under these conditions a massive sludging can be found -firstly described by M.H. Knisely´s group in conjunctival vessels -even in very small cutaneous capillaries [12]. Big erythrocyte aggregates pass very slowly through the capillary while immediately thereafter a single cell perfusion with significantly 1386-0291/16/$35.00

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Conjunctival microvascular haemodynamics in sickle cell retinopathy

Cited by 30 publications

References 43 publications

Conjunctival and pulmonary hemodynamic properties in sickle cell disease subjects with and without pulmonary hypertension

Conjunctival and pulmonary hemodynamic properties in sickle cell disease subjects with and without pulmonary hypertension

Inter-visit variability of conjunctival microvascular hemodynamic measurements in healthy and diabetic retinopathy subjects

Role of blood viscosity in the microcirculation

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