1. Vasculature of the eye (Fig. 1)The arterial supply to the eye arises primarily from the ophthalmic artery (OA), which is the first branch of the internal carotid artery (ICA) and is approximately 0.5 mm in diameter. The OA branches into the central retinal artery (CRA) and one to five posterior ciliary trunks which divide into multiple branches forming separate groups of the main posterior ciliary arteries (PCA). The PCA branches into arteries supplying the outer retina, choroid, and retrobulbar tissues. The main PCAs further divide into several short posterior ciliary arteries (SPCA) before or after piercing the sclera. The CRA penetrates the optic nerve approximately 15 mm behind the eye globe, courses adjacent to the central retinal vein (CRV), passes through the lamina cribrosa (LC) and branches into four major arterioles supplying the inner retinal layers.

The venous drainage of the retina, choroid and optic nerve is mainly through the CRV and the ophthalmic veins (OV). The CRV and OV are major tributaries to the cavernous sinus, which ultimately drains into the internal jugular veins (IJV) at the base of the skull.

The vascular beds supplying the eye are typically divided into three groups: the retinal, choroidal, and retrobulbar vascular beds. The retinal vascular bed is supplied by the CRA, drained by the CRV, and nourishes the inner two-thirds of the retina. The choroidal vascular bed is supplied by the PCA, drained by the OV, and nourishes the deep outer retinal layer. The retrobulbar vascular bed is supplied by the PCA and branches of the CRA, drained by the CRV, and nourishes the superficial nerve fiber layer, the pre-laminar (or pro-laminar) region, the laminar region, and the retrolaminar region.

18. The role of blood flow in glaucomaScott Wentz1, Casey Seizys1, Giovanna Guidoboni2, Julia C. Arciero2, Katherine Hutchins1, Brent Siesky1, Alon Harris1

1Eugene and Marilyn Glick Eye Institute and Indiana University School of Medicine, Indianapolis, IN USA; 2Department of Mathematical Sciences, IUPUI, Indianapolis, IN, USA

Correspondence: Scott Wentz, Eugene and Marilyn Glick Eye Institute and Indiana University School of Medicine, Indianapolis, IN 46202, USA.E-mail: scowentz@iupui.edu Glaucoma Research and Clinical Advances: 2016 to 2018, pp. 243-260 Edited by P.A. Knepper and J.R. Samples © 2016 Kugler Publications, Amsterdam, The Netherlands

1.1. Mechanisms of blood flow regulationVascular beds exhibit an intrinsic ability to maintain blood flow (BF) despite changes in perfusion pressure. This ability is known as autoregulation and has been observed in numerous tissues in the body including the eye. The control of blood flow is achieved by appropriate changes in arteriolar smooth muscle tone that cause vessels to dilate or constrict in response to changes in factors such as intraocular pressure (IOP), blood pressure (BP), metabolic demands, pH levels, and neural stimuli. For example, according to the myogenic response mechanism, an increase in arterial pressure causes vessel constriction. An increase in wall shear stress causes vessel dilation, most likely mediated through the release of nitric oxide. Local and non-local changes in tissue metabolic status also trigger vaso-dilation, as in conditions of hypercapnic acidosis. Metabolic mechanisms include responses to factors such as nitric oxide and adenosine and conducted responses that communicate downstream tissue status to upstream resistance vessels via an electrical signal conducted along the vascular endothelium. In vessels with innervations that can affect vessel tone, stimulation of the sympathetic nervous system leads to altered smooth muscle tone. Failure of the above-men-tioned mechanisms to combine and maintain stable blood flow to the eye may result in ischemic damage of the ONH and/or retinal ganglion cells, which can then lead to retinal ganglion cell (RGC) death and structural changes of the optic nerve (ONH) head consistent with the pathophysiology of glaucoma.

Fig. 1. Anatomy of blood supply to the retina, choroid, and retrobulbar regions. Image taken from the Atlas of Ocular Blood Flow1

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1.2. Interactions of ocular blood flow with the extra-cellular matrixThe vasculature is a dynamic component of the circulatory system that has a variety of functions including the distribution and regulation of blood (and, subsequently, nutrient delivery and waste removal) as well as the delivery of immune cells to protect and defend against pathogens. Blood vessels rely on the extracellular matrix (ECM) to maintain their shape, to allow for diameter constriction or dilation, and to dampen mechanical forces and energy produced by both pulsatile flow and vasoconstriction.2 The ophthalmic artery supplies blood to the eye and contains several layers of smooth muscle in order to accommodate the wide blood pressure range created by pulsatile blood flow. Medium-to-small-sized arteries,

such as the OA, have an ECM composition that is dense in smooth muscle cells in order to regulate blood flow over a certain pressure range, whereas large-sized arteries have an ECM composition that is dense in elastic proteins in order to dampen mechanical forces induced by pulsatile flow produced during the cardiac cycle.3

1.3. Effects of pulsatility on ocular blood flowOne of the key functions of large arteries (e.g., the aorta) is to store and release energy during the cardiac cycle. Specifically, a network of elastic fibers allows these vessels to store energy during systole and release energy during diastole. During systole, blood is ejected from the heart into the vasculature. This results in an increase in pressure across the vessel wall (i.e.,

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transmural pressure). According to the Law of Laplace (P = T / r, where P is transmural pressure, T is wall tension, and r is vessel radius),5 as the transmural pressure increases, the ratio of wall tension to vessel radius must also increase. In its native and relatively relaxed state, the vascular ECM network is coiled, whereby uncoiling of the fibers leads to the storage of potential energy. The vascular ECM stores energy during systole in the form of wall tension by the uncoiling of the vascular elastic fiber network. Following systole, diastole begins during which the stored energy of the vascular ECM network exerts force on the blood volume that entered the vessels during systole.4 Since blood is negligibly compressible and back flow is precluded by the aortic valve, the ECM-produced force blood to flow to the medium-sized and small-sized arteries, arterioles, and capillaries.

In the normal, physiologic state, the retrobulbar vessels (e.g., the OA, CRA, and PCA), the choroidal vessels, and the retinal vessels are able to regulate blood flow through the range of pressures created by pulsatility.6 This is important since a relatively constant amount of blood needs to perfuse through a mass of tissue in order to prevent ischemic tissue damage. Without the ability to regulate blood flow, pulsatile blood flow would result in variable and erratic blood flow – thus reducing perfusion and compromising the ocular tissues. In disease states, such as primary open-angle glaucoma (POAG) and diabetes, poor blood flow regulation within the ocular vasculature has been observed to contribute to the damage of ocular tissues.7,8 Essentially, the capacity for the vasculature to compensate for constant blood flow throughout a wide range of pressures becomes reduced in these disease states.

Elevated pulsatility due to arterial aging can also lead to poor tissue perfusion. With age, both changes in the vascular ECM and atherosclerosis lead to hardening of large arteries. This hardening increases the magnitude of pulsatility, and, consequently, overwhelms the capacity of the resistance vessels to regulate BF. Older patients are, thus, at an increased risk of end-organ damage (e.g., damage to the eye).9

2. Blood flow and glaucomaPOAG is an optic neuropathy characterized by progressive RGC death, structural changes to the retina

and ONH, and irreversible visual field loss. Elevated IOP has been validated as an independent risk factor for POAG, and it is currently the only treatable risk factor. There are many other risk factors that are involved in glaucoma pathogenesis, as IOP is not the only risk factor that can increase a patient’s risk for POAG. This section mentions some of these risk factors and discusses how blood flow is a notable player in glaucoma pathogene-sis.

2.1. Glaucoma risk factorsAs previously mentioned, elevated IOP is the only treatable risk factor for POAG, even though there is overwhelming evidence that elevated IOP is not the only factor involved in the disease process. Other factors that have been shown to be associated with POAG development include cup-to-disc ratio,10,11 visual field patterns,10 disc hemorrhages,12,13 myopia,14,15

central corneal thickness (CCT),10,11,16 ocular perfusion pressure,17,18 intracranial pressure (ICP),19-21 trans-lam-ina cribrosa pressure gradient,19,22 diabetes,15 systemic blood pressure,15,18,23,24 ocular blood flow,17 vascular dysregulation,15,25-27 genetic factors,15,28-31 and age.10,11 Gender and ethnicity are known modifiers of the relative risk for POAG, although, how they contribute to an individual’s POAG risk has yet to be established.15

2.2. Blood flow as a risk factor for glaucoma

There is significant evidence that several risk factors, both independent of and in combination with IOP, contribute to the development of glaucoma. In particular, several associations between blood flow deficits and glaucoma symptoms have been observed, and, thus, it is necessary to understand the role of ocular blood flow as a risk factor for glaucoma.

● Retinal blood flow: Total retinal flow as measured by Doppler OCT was found to be significantly lower in POAG patients compared to healthy controls (38.08 ± 14.4 µl/min vs. 54.3 ± 5.9 µl/min, respectively, p = 0.048). These results were also highly correlated with severity of visual field loss (p = 0.003).32

● Ocular structure: Decreased retinal capillary perfusion was associated with increased optic cup depth.33

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● RNFL thickness and visual field: Blood flow deficits have been linked to visual function. Retrobulbar blood flow correlates positively with RNFL thickness34 and visual field mean defect after two years.35

2.3. Glaucoma medications that target ocular blood flowIn 2003, Costa et al. reviewed a number of studies that investigated the ocular hemodynamic effects of various anti-glaucoma medications.36 Since then, additional clinical studies have demonstrated the vasoactive properties of various anti-glaucoma medications in healthy and glaucoma patients. Many of these anti-glau-coma medications are formulated in topical drops and are currently used to treat glaucoma by lowering IOP. Here, we review several anti-glaucoma drug classes and provide evidence that many of the medications used to treat glaucoma via lowering IOP also affect ocular hemodynamics. Consequently, medications that improve OBF may protect against glaucoma in an IOP-independent manner.

Prostaglandin analogs (PGAs): Prostaglandin analogs including latanoprost, unoprostone, bimatoprost, and travoprost have been shown to lower IOP and, thus, are used to treat glaucoma. The exact means by which these medications lower IOP is not fully understood, but there is very convincing evidence that they enhance uveoscleral reabsorption of aqueous humor. It is not yet clear if these medications affect the trabecular meshwork or other ocular structures as well.37 Generally, these medications are well-tolerated due to a relatively benign side effect profile with the most common side effects being conjunctival hyperemia, pigmentation of the iris, periocular skin or eyelashes, hypertrichosis, and ocular surface irritation.38

Latanoprost is a very widely-used PGA used for anti-glaucoma therapy since it has the benefit of being one of the most well-tolerated agents along in addition to a desired efficacy in lowering IOP.39 A randomized, double-masked, placebo-controlled crossover study on healthy subjects showed that latanoprost has mostly neutral effects on the ocular circulation,40 but the study did not evaluate its effects on glaucoma patients. Other studies have supplied additional information on the effects of latanoprost on the ocular circulation in both POAG and OHT patients. For example, Koz et al.

showed that, at a six-months follow-up assessment, topical latanoprost significantly reduced the RI in the OA compared to the baseline values.41

Bimatoprost, one of the most efficacious PGA agents in terms of lowering IOP, gives mixed results when its effects on ocular hemodynamics are evaluated.39 Koz et al. showed that bimatoprost was hemodynamical-ly neutral, meaning BF values were not significantly changed in POAG or OHT patients after administering the medication.41 BF velocities in retrobulbar vessels were not altered in NTG patients taking bimatoprost,42 but the end-diastolic velocity in the CRA was signifi-cantly higher compared to baseline values in patients with newly-diagnosed POAG taking bimatoprost.41 More research will further clarify the effects of bimatoprost on OBF.

Travoprost is a widely-used anti-glaucoma medication that has been shown to reduce IOP, increase OPP (defined as OPP = 2/3*MAP-IOP), and reduce the RI of the CRA in patients with either POAG or OHT.41 In a study comparing the effects of travoprost and latanoprost on pulsatile ocular blood flow (pOBF) in POAG patients,43 both medications caused an increase in pOBF, but the effect of travoprost did not diminish over time. Also, the travoprost group showed an inverse correlation between IOP and pOBF.43 Studies in rabbits also demonstrated that PGAs increase ONH BF properties, even after only a single dose.44 Overall, the ability of travoprost to increase blood flow within the ONH and decrease IOP makes it an attractive option for treating glaucoma.

A placebo-controlled study investigated the effects of unoprostone on ONH blood volume, velocity, and flow in control patients and patients with NTG. The treated groups, both NTG patients and normal controls, showed changes in ocular hemodynamics, while the placebo groups did not. Specifically, the normal controls experienced a significantly higher mean blood flow velocity and flow at hours one and two after administration. Blood volume was not significantly increased in the normal controls. In NTG patients, all three of the investigated hemodynamic parameters (blood volume, velocity, and flow), were significantly higher than baseline values measured before admin-istering the medication. Of note, unoprostone admin-istration did not result in a significant decrease in IOP when comparing the control patients with NTG patients.45 This is likely due to the low baseline IOP

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values seen in both normal controls and NTG patients.

Beta-blockers (BBs): Systemic beta-blockers are used in medicine because they are antagonists of beta-ad-renergic receptors. Many tissues within the body have beta-adrenergic receptors, including the heart, lungs, brain, kidney, the ciliary apparatus within the eye, and many others.46-48 In the eye, BBs lower IOP by reducing cyclic AMP in the ciliary epithelium.49 Since BBs can affect multiple body sites, BBs used for glaucoma treatment (e.g., timolol, betaxolol, and levobunolol) are topical. This allows for local antagonism of the ciliary epithelium without blocking sites in other parts of the body.

Timolol is one of the most widely used anti-glau-coma BBs on the market. It is available in the United States as a sole agent or contained in a combination eye drop (e.g., Cosopt®). A study on healthy Japanese subjects showed that timolol was hemodynamical-ly neutral in the ONH circulation when used as a sole agent. However, when timolol was combined with dorzolamide, the combination product increased ONH BF.50 This suggests there may be a synergistic effect on ONH BF when the combination product is used. However, it is also possible that the size of the study (n = 15) was not sufficient to observe a statistical difference in BF when studying the medications in isolation.

Carbonic anhydrase inhibitors (CAIs): Carbonic anhydrase inhibitors are a relatively common treatment modality for glaucoma. The mechanism of action in lowering IOP for CAIs is the inhibition of carbonic anhydrase within the ciliary apparatus of the eye. Carbonic anhydrase normally produces both a bicarbonate ion and hydrogen ion within the ciliary epithelium. The production of these two ions leads to the transport of water into the posterior chamber of the eye, thus increasing the volume of aqueous humor. CAIs block this process, and, as a result, lower IOP by decreasing the volume of aqueous humor produced.51 Similar to the beta-adrenergic receptors, carbonic anhydrase is present elsewhere in the body. Conse-quently, topical CAIs instead of systemic CAIs are used to treat POAG in order to prevent systemic side effects (e.g., metabolic acidosis, paresthesias, dysgeusia with carbonated beverages).52 However, in the case of an acute angle-closure glaucoma attack, acetazolamide, a systemic CAI, is used, since the benefit of preserving

retinal ganglion cells outweighs the systemic side effects of the medication.53

Dorzolamide is a common topical CAI used to treat glaucoma. It is available in the United States as either a sole agent or a combination product with another drug class agent. When added to timolol, dorzolamide has been shown to increase BF within the superficial retinal vasculature for POAG and non-POAG patients and within the retrobulbar vessels for POAG.54,55

Brinzolamide is another commonly used CAI that has been shown to improve retinal blood flow in the peripapillary retina.56 A comparative study of brinzol-amide and dorzolamide suggests that brinzolamide may be more efficacious in increasing retinal BF than dorzolamide.55 However, brinzolamide does not seem to affect the retrobulbar circulation while dorzolamide does.55,57,58 This vessel selectivity exhibited by brinzol-amide could be used in cases requiring increased BF only to the retina.

Alpha2-adrenergic agonists: Brimonidine is a selective alpha2-adrenergic receptor agonist which has been shown to reduce IOP through both decreased aqueous humor production and increased uveoscleral outflow.59 It is still unclear if brimonidine increases OBF since some studies showed an increase in blood flow velocity and pOBF60,61 while other studies showed no change in BF in POAG and OHT patients.62-65 Despite this, there is significant evidence to assert that brimonidine acts to stabilize the ocular vessels by enhancing blood flow autoregulation in POAG and NTG patients.66,67

Like brimonidine, apraclonidine is an alpha2-adren-ergic receptor agonist. Apraclonidine has been shown to lower RI and PSV in the retrobulbar circulation of newly-diagnosed POAG patients,68 but did not affect peripapillary retinal blood flow or ONH BF.45 It has been proposed that topical application of apraclonidine may cause vasoconstriction, thereby decreasing the amount of aqueous humor.37

Cholinergic agonists: Cholinergic agonists reduce IOP by causing the ciliary muscle to contract, resulting in enhanced reabsorption of aqueous humor through the trabecular meshwork. Examples of cholinergic agonists include pilocarpine, echothiophate, and carbachol. Pilocarpine has been shown to increase pulsatile OBF in untreated ocular hypertension patients69 but had no direct effect on pulsatile OBF in POAG patients.70

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Like apraclonidine, the ability of pilocarpine to reduce aqueous humor production may be partly due to triggering vasoconstriction in the blood vessels supplying the iris and ciliary processes.71 The effects of echothiophate and carbachol on OBF have not been well-studied which illustrates a relative need for more research in this area. Ultimately, the side effect profile of cholinergic agonists (e.g., miosis leading to reduced vision due to increased light diffraction, myopia, brow ache) makes them a poor choice for glaucoma therapy.

Systemic medications: It is important to identify the effects of systemic medications on OBF since many glaucoma patients have comorbidities that necessitate treatment with systemic medications. Two examples include patients with hypertension require treatment with anti-hypertensive medications and patients with idiopathic intracranial hypertension, also known as pseudotumor cerebri, who are treated with medical therapy (i.e., acetazolamide).72 As mentioned previously, acetazolamide is used in glaucoma therapy for acute angle-closure glaucoma attacks meaning it is only used on a short-term basis for glaucoma. Knowing how the medication affects OBF would provide useful information.

Fortunately, a 2013 study investigated this and showed that acetazolamide leads to the dilation of retinal vessels, increased BF to the ONH, and decreased para-papillary retinal BF.73 Acetazolamide also has been shown to increase choroidal BF.74 Another systemic medication, bisoprolol, a systemic beta-blocker, shows evidence of unfavorably affecting OBF75 while propranolol does not.76 Another systemic beta-block-er, nebivolol, showed accelerated BF in the small retrobulbar vessels, possibly due to its nitric oxide-re-leasing properties.77 Lastly, nimodipine and nifedipine, systemic calcium-channel blockers, have been shown to affect OBF in a beneficial way.78,79

The list is much more extensive, but, for brevity, the key point is that a plethora of data is available that supports the notion that both topical and systemic anti-glaucoma medications affect OBF. Many of these medications affect OBF in a beneficial way by accelerat-ing BF velocities in the ONH, choroid, and retinal vessels. However, some affect OBF in a detrimental way by reducing OBF in certain vascular beds. The consequenc-es of increasing or decreasing OBF may be protection against or increased risk for glaucoma, respectively.

2.4. Effects of hypertension on blood flow in glauco-ma patientsAlthough decreases in perfusion pressure and blood pressure have been associated with glaucomatous damage, the association between arterial hyperten-sion and POAG remains unknown due to inconsis-tent study findings. The Blue Mountain Eye Study, for example, showed that hypertension was associated with an increased risk of POAG, whereas the Barbados Eye Study concluded that low systolic blood pressure is a significant risk factor for POAG.80,81

Several studies link low OPP with glaucoma, including the Baltimore Eye Survey, the Egna-Neu-markt Study, Proyecto VER, the Rotterdam Study, the Los Angeles Latino Eye Study, the Singapore Malay Eye Study, the South Indian Study, the Barbados Eye Study, and the Early Manifest Glaucoma Trial.18,80,82-87 Since OPP is defined as the difference between arterial blood pressure and IOP, high IOP and low blood pressure may also be risk factors for glaucoma. However, the association between blood pressure and glaucoma has been inconsistent.

The Thessaloniki Eye Studies investigated the rela-tionship between blood pressure and glaucomatous progression. A subgroup analysis of blood pressure status, which takes into account whether or not a subject uses antihypertensive medication, provided more conclusive data.88,89 Only subjects with low diastolic BP who were being treated with anti-hyper-tensive medications had an associated increase in cup area and cup-to-disc ratio. Another study showed that the use of calcium channel blockers was associated with POAG.90 Grunwald et al. noted that treatment of systemic hypertension may further decrease ocular blood flow in glaucoma patients with hypertension.91

There are two major hypotheses for the role of anti-hypertensive medication in the relationship between glaucoma and decreased systemic and ocular perfusion pressure. The first hypothesis is that impaired vascular regulation disrupts the natural ability of blood vessels to maintain BF to the eye, causing ischemia or reperfusion damage and ultimately glaucomatous progression.92 Studies have demonstrated optic nerve head autoreg-ulation with increasing IOP but altered hemodynamic responses in patients with hypertension.93-95 BF dysreg-ulation may be due to chronic microvascular damage caused by systemic hypertension, or possibly due to the antihypertensive medications themselves, as

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suggested by the results of the Thessaloniki Eye Studies.The second hypothesis is that subjects treated for

systemic hypertension experience larger reductions of nocturnal blood pressure, or ‘nocturnal overdipping’, which may increase chances of ischemia and reperfusion damage and thus tissue damage and glau-comatous progression.96 Several studies have investi-gated this theory and have provided supporting results, showing an association of glaucomatous progression with nocturnal overdipping and greater fluctuations in circadian blood pressure.96-99

3. Diabetes and blood flowSeveral studies have indicated that diabetic patients with glaucoma have a stronger vascular component to their glaucomatous progression than non-diabetic POAG patients. Specifically, diabetes is shown to affect structural and hemodynamics factors associated with ocular blood flow.

3.1. Impact of diabetes on ocular structural factorsIn POAG patients with diabetes, changes in inferior retinal blood flow was significantly correlated with changes in the ONH (e.g., rim volume, cup to disc area ratio, rim area, cup area, cup shape, linear c/d ratio) after four years.100,101 In addition, the change in retinal blood flow in these patients was significantly correlated with changes in macular thickness after four years. This suggests that POAG patients with diabetes may have a stronger vascular contribution to their glaucomatous structural damage.102 It is also important to note that changes in vascular resistance were strongly correlated with deterioration of the RNFL and macula in POAG patients with DM.103

3.2. Impact of diabetes on ocular hemodynamic factorsPOAG patients with diabetes may have more ocular vascular contributions to glaucomatous progression than non-diabetic patients. In POAG patients with diabetes, the resistive index was found to increase in the central retinal artery and temporal posterior ciliary arteries.104,105 These results suggest blood flow may be altered to the retina and ONH in POAG patients with diabetes.106

Preliminary studies also suggest that POAG patients with diabetes may have impaired vascular autoreg-

ulation compared to non-diabetic POAG patients. In POAG patients with diabetes, changes in SBP, MAP, SPP, OPP, and MPP correlated to changes in EDV and RI. It was found that changes in SCPH blood flow correlated to changes in systemic blood pressure and ocular perfusion pressures,107 suggesting alterations of autoregulation during BP and OPP fluctuations. Another study demonstrated that impaired retrobulbar vascular autoregulation may lead to passive blood flow dynamics from the retrobulbar blood supply to the retinal vessels.108

Furthermore, Egan et al. found that POAG patients with diabetes had decreased areas of capillary blood flow than non-diabetic patients, suggesting that diabetic patients with POAG experience more capillary dropout.109

In summary, these studies suggest that POAG patients who also have diabetes experience many additional changes in ocular vasculature as opposed to POAG patients without diabetes, and these changes may enhance glaucomatous progression.

3.3. Impact of diabetes on the extracellular matrixPathologic complications of diabetes that occur in the retina are typically due to hyperglycemia-induced changes of the microvasculature. Non-enzymat-ic glycation (NEG) and accumulation of extracellular matrix (ECM) proteins in the vasculature is the primary pathophysiologic mechanism by which these complica-tions arise. NEG of proteins can cause modification of protein function and gene expression.

Accumulation of ECM is caused by several factors. An increase in laminin and type-IV collagen production via altered oncogene expression causes thickening of capillary basement membranes, which affects cell migration, adhesion, and growth and may impair vascular metabolism.110-112 Glycation of these ECM proteins also alters the interaction between the cell and ECM. Hyperglycemia can activate the protein kinase C (PKC) pathway, which upregulates endothelins (ET), causing activation of Nuclear Factor-κβ (NF-κβ) and activating protein-1 (AP-1) to increase production of fibronectin.113

After glycation of certain proteins, advanced glycation end products (AGEs) can form through a series of chemical reactions. Elevated levels of AGEs have been found in diabetic retinal tissue and impart damage to the retinal vasculature by increasing inflammation,

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vascular permeability, oxidative damage, and cellular apoptosis and potentially inducing a pro-coagulatory state. By binding to their receptor (i.e., RAGE), AGEs can induce activation of cell signaling cascades, including Nuclear Factor-κβ (NF-κβ), that have many deleterious effects, such as increased formation of cytokines and free radicals; altered vasodilator response to nitric oxide (NO); altered gene expression of thrombomod-ulin, tissue factor (TF), and endothelin-1 (ET-1); and modified levels of growth factors such as vascular endothelial growth factor (VEGF) and basic fibroblastic growth factor (FGF).110,112,114 Current research is investi-gating a new target for the prevention and treatment of microvascular diabetic complications by blocking RAGE/AGE interaction.115

AGEs also induce cross-linking of collagen fibrils, causing corneal stiffening. This would suggest that diabetic patients would have an increased risk of glaucoma, due to low corneal hysteresis (CH), i.e., low viscous damping capacity of the cornea influenced by its viscoelastic properties.

Hager et al. evaluated changes in the ECM of the cornea in diabetic patients and found that CH was sig-nificantly higher in diabetic patients than in non-di-abetics. Although AGE-induced cross-linking does cause corneal stiffening, Hager et al. discussed the hypothesis that the increase in glycosaminoglycans from the glycation of corneal proteoglycans may play a major role in increasing corneal hysteresis, and, thus, protecting diabetics from glaucoma.116 Although many studies have reported that diabetes is a risk factor for glaucoma, several other studies reported that diabetes has a protective effect against the progression of glaucoma.117,118 Such studies thus show an inconclu-sive link between diabetes and the progression of glaucoma.117,118

ET-1 is an essential mediator for the activity of proteolytic enzymes that degrade ECM proteins called matrix metalloproteinases (MMP) and is a regulator of ECM protein production, specifically fibronectin (FN). ET-1 is elevated in diabetes, and the levels of fibronectin and the expression of MMP and matrix scaffold protein genes are altered in diabetic retinal disuse.119 Khan et al. used bosentan, an ET antagonist, to prevent FN expression in cells exposed to high levels of glucose, suggesting that ET may be a future target for therapy for diabetic complications.120 FN not only causes basement membrane thickening, but it also is

involved in cellular proliferation and VEGF expression, which plays a key role in neovascularization in prolifer-ative diabetic retinopathy.

3.4. Impact of diabetes on pulsatilityThe effects of diabetes on the ECM of the vasculature likely translate to changes in the pulsatility of the vasculature within the eye. As described in Section 3.2, the RIs in diabetic, POAG patients are signifi-cantly higher than in patients with only POAG. This is supported in other systems outside of the eye, as the resistive indices of diabetics (calculated as peak systolic velocity minus end diastolic velocity) measured within intra-renal arteries are significantly higher compared to RIs in healthy control subjects.121 Further, the pulsatility index (PI) and RI within renal arteries are both associated with the progression of chronic renal failure, indicating that pathologic perfusion through aberrant pulsatile blood flow is one of many sequelae that results from diabetes.122 Qualitatively, the RI may be used to infer pulsatility since the PI takes into account the mean velocity during the cardiac cycle while the RI does not.

Resistive Index = peak systolic velocity ‒ end diastolic velocity

Pulsatility Index = RI / mean velocity during cardiac cycle

If the same vessels are measured at similar locations within the body between groups, a statistical difference in RI values between groups would likely yield a statistical difference in PI values for the same system.

In conclusion, previous studies assessing pulsatile BF in the kidney support the idea that aberrant pulsatility within the eye is associated with the progression of glaucoma in the eye. This makes sense since diabetes is a systemic disease. There is also convincing evidence that the ECM changes incurred from diabetes is the keystone to the pathophysiology.

4. SummaryThe involvement of vascular factors in glaucomatous optic neuropathy was postulated as early as 1885 by Priestley Smith, who suggested involvement of both mechanical and vascular factors in glaucoma pathology. Over the past several decades, many pop-

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ulation-based studies have found low OPP to be an independent risk factor for glaucoma while numerous small clinical studies have identified decreased retinal, choroidal, and retrobulbar blood flow to be associated with glaucoma prevalence and incidence. While the relationship between OBF and glaucoma is relatively a well-established concept, the nature of that relation-ship is not well understood. The reduced ocular blood flow seen in OAG patients may be secondary to elevated IOP, RGC death, or of primary vascular origin. Some theorize that decreased blood flow causes ischemic insult to the optic disc and retina, which may play a role in the structural and functional damage that is charac-teristic of glaucoma. Others theorize that elevated IOP in glaucoma leads to tissue injury, thus obviating the need for blood flow to that region.

The more recent focus on the need for prospective longitudinal vascular-based studies has finally begun to produce initial pilot data showing decreased ocular blood flow to be predictive of and/or correlated with glaucomatous structural and functional progression. However, these studies are small in number, often measure only one vascular bed and require larger longitudinal samples confirm these pilot findings. The lack of a gold standard in measuring all relevant vascular beds in the eye for glaucoma risk assessment remains the largest barrier to advancement, as does limited availability of imaging expertise in traditional glaucoma management facilities. Future development of improved devices for the non-invasive vascular imaging for the eye is still paramount for the field to advance from its current status.

Finally, individual susceptibility and personalized risk evaluations hold the promise of improved patient care as glaucoma is non-uniform in its disease presen-tation. Persons with diabetes have been shown to be at elevated risk for vascular complications in glaucoma, as have persons of African descent. In general, age affects vascular compliance and autoregulation, as may gender, obesity, medications, and overall health. So an individual may be at a much higher risk for vascular impairment and subsequent glaucoma risk based upon their diabetic status, race and confounding health issues. Therefore the long-term focus for glaucoma management should be on identifying individualized risk assessment, using a model, which incorporates vascular functionality, diabetic status, race, gender, and other health factors.

4.1. The role of clinical blood flow studies in under-standing the pathophysiology of glaucomaIn the previous section, we outlined the need for larger, longitudinal studies to follow up on pilot work showing how vascular impairment is linked to glaucoma progression. The need for more standardized and easily accessible non-invasive blood flow evaluation methodology is key to increasing the existing body of evidence to a point of differentiation. Meanwhile individualized risk assessment factoring in multiple variables and overall health status may provide the key for elucidating why many individuals have glaucoma pathology while others with similar traditionally measured variables do not experience glaucomatous vision loss. Future studies that may greatly impact our understanding of glaucoma will likely have several key characteristics:

● Studies should be longitudinal, with large patient populations similar in size and scope to the previously established IOP trials;

● Due to the non-uniformity of glaucoma pathology, studies should account for age, sex, race, obesity, blood pressure, and medication use, all of which may greatly affect individualized outcomes;

● Diabetic status, which has begun to be found to have substantial influences on the ocular vasculature, will need to be accounted for, as will other vascular-impacting pathologies;

● Other confounding variables, such as intracranial pressure, may be highly influential in determining how IOP and vascular perfusion are linked;

● Mathematical and other dynamic modeling of fluid forces and regulatory mechanisms may be increasingly important for differentiating outcomes for individuals who present with different combinations of variables that a study population may not reveal regardless of size and scope.

Taken as a whole, there remains much work to be done to understand how OBF and metabolism are spe-cifically involved in the glaucomatous disease process. However, there is little doubt that a healthy vibrant ocular vascular system would not be protective of other influences while the presence of an impaired vascular system may increase susceptibility. Diabetic status, race,

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gender, age, medication use, obesity, and many other physiological and pathological factors are likely linked, as are other fluid forces such as intracranial pressure, blood pressure and IOP. What will be most impactful will be future studies that take as many individualized risk factors into account as possible to produce a risk profile specific to that individual. Groups of patients are by nature heterogeneous, and glaucoma is specifically a multifactorial optic neuropathy. Therefore the true advancement of glaucoma risk assessment may very well lie in the individualized modeling approach, or at least in advanced statistical applications which look beyond static, traditional one-for-one paradigms and take into account the complex, interwoven nature of known and theorized risk factors and also the dynamic nature of the human body.

4.2. Role of mathematical modeling in understand-ing relationships between blood flow and glaucomaThe evidence reviewed in the previous sections show that several important questions concerning the relation-ship between blood flow and glaucoma remain open. The following issues are among the most controversial open questions in glaucoma research: are alterations in ocular blood flow primary or secondary to glaucoma-tous damage? Is low OPP dependent or independent of the two separate risk factors of low MAP and high IOP? Does the answer to the previous question depend on the ranges of MAP and IOP?123,124 Indeed, multiple popula-tion-based studies have found significant associations between low OPP and glaucoma incidence, prevalence, and progression,82,85,86,125 providing the strongest evidence for vascular contributions in glaucoma. However, several factors can affect OPP, including fluc-tuations in MAP and IOP,126,127 alterations of cerebrospi-nal fluid pressure (CSFp),19,128 and impairment of blood flow regulation.25 The extent to which these different factors alter OPP has not yet been assessed. Addition-ally, the extent to which different ocular vascular bed, including retinal, choroidal, and ONH, are affected by low OPP has not yet been determined.123

Mathematical modeling can help disentangling the influence of individual factors on the behavior of a complex system thereby creating a virtual lab where various hypotheses can be tested and various scenarios can be simulated as to better interpret clinical and exper-imental findings. Due to the complexity of the anatomy and physiology of the human eye, the development of

mathematical models describing ocular blood flow, vascular autoregulation and their relationship with blood pressure and IOP can be extremely useful in aiding the interpretation of clinical data. However, the mathematical modeling of the human eye is an extremely challenging task. As a matter of fact, this is a fervent and active area of scientific investigation to which our group has significantly contributed. In order to effectively address the above-mentioned open questions in glaucoma research, mathematical models must combine descriptions of ocular biomechanics, hemodynamics and oxygen transport,129 as discussed below.

4.2.1. Ocular biomechanicsAlterations in the biomechanical response of the optic nerve head (ONH) to changes in IOP have been identified as a major factor in the pathogenesis of glaucoma. 130-133 Particular attention has been devoted to the math-ematical description of the IOP-induced mechanical stresses and strains arising within the lamina cribrosa, which is thought to be a primary site of axonal injury in glaucoma.134 Recent studies have utilized finite element models of the eye to investigate IOP-induced stresses and strains in the optic nerve head,135-139 as well as growth and remodeling mechanisms including adaptation of tissue anisotropy, tissue thickening/thinning, tissue elongation/shortening and tissue migration.140-144 Further development of these sophis-ticated finite element models may benefit from the recent advances in OCT imaging aimed at providing a more accurate characterization of the architectural microstructure within the lamina cribrosa.145

In these modeling approaches IOP and retrolam-inar tissue pressure (RLTp) are assumed to be given values set by the user. Interestingly, mathematical models has already been developed to investigate the mechanisms leading to IOP elevation, with particular focus on the relationship between ciliary blood flow and aqueous humor production146 and the biome-chanics of the Schlemm’s canal,147,148 even considering realistic three-dimensional ocular geometries.149 It would be extremely interesting to couple the models for the ONH response to IOP elevation with models actually investigating the mechanisms leading to IOP elevation, as to provide a more complete description of the IOP action on the ocular apparatus. The retrol-aminar tissue pressure (RLTp) is another very important

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factor influencing ONH biomechanics. RLTp has been shown to be strongly correlated to CSFp in dogs, for CSFp higher than four mmHg.150 Mathematical models describing CSFp dynamics have been developed in the context of cerebral and spinal circulation.151-153 The extension of such models to describe the complex rela-tionship between CSFp and RLTp in the ONH would be very beneficial to better understand the role played by CSFp alterations in glaucoma.

4.3.2. Ocular hemodynamicsThe modeling of retinal blood flow has attracted the attention of many investigators in the recent years.154-157 A few groups have pioneered the mathe-matical modeling of the complex relationship between ocular blood flow, blood flow autoregulation, IOP and RLTp and the use of such models for the interpretation of clinical data.158-163 For example, in [158] the electric analogy between blood flow in a vascular network and the flow of a current in a circuit is utilized to theoretical-ly investigate the mechanisms governing the hemody-namics in the retina and in the central retinal vessels. Arterioles can actively adjust their vascular resistance by dilating and constricting to attain blood flow regulation, whereas venules can passively compress due to the IOP action on their walls and eventually collapse (acting like Starling resistors). The model is used to investigate how IOP elevation (from 15 to 45 mmHg) influences total RBF for three different scenarios, namely high, normal and low blood pressure denoted by HBP, NBP, and LBP, respectively, characterized by systolic/diastolic blood pressures of 140/90 mmHg, 120/80 mmHg, and 100/70 mmHg, respectively. If IOP < 26 mmHg, the model predicts the presence of an autoregulation plateau for the HBP and NBP cases, but not for the LBP case. When IOP is elevated beyond 26 mmHg, the model does not predict any autoregulation plateau for any of the theoretical scenarios, suggesting the loss of autoreg-ulation capacity regardless of the blood pressure. The model allowed to identify the progressive collapse of retinal veins as the main mechanism responsible for the loss in autoregulation capacity following IOP elevation. These results are in agreement with the findings of the clinical experiment performed by Boltz et al.,164 who showed that inadequate autoregulation of ONH blood flow occurs at IOP values at 26 mmHg or greater where blood flow became independent of MAP. Contrastingly, blood flow was always dependent on IOP throughout

all data values for MAP. Our model predictions are in good agreement with these clinical data, and most importantly, they helped explaining why these trends are observed, namely the importance of the venous collapse (Starling resistor).

Mathematical modeling can also be used to investigate the relative role of blood pressure, IOP and CSFp on ocular hemodynamics. For example, in [163] the central retinal vessels are modeled as compliant tubes whose walls deform under the action of an external pressure that varies along the vessel length to include CSFp, IOP, and the effect of mechanical deformation of the lamina cribrosa (induced by the translaminar pressure difference TLpD = IOP ‒ CSFp). Retinal arterioles, capillaries and venules are modeled as a network of resistances as described in the study by Guidoboni et al.158 The total retinal blood flow (Q) and the blood velocity in the CRA and CRV (Va and Vv) are simulated and compared assuming that IOP and CSFp vary independently and assuming that IOP and CSFp may or may not be accompanied by changes in MAP. The model predicts that, for a certain TLpD, the level of IOP affects hemodynamics more than the level of CSFp. For example, for TLpD = 33 mmHg, when IOP = 40 mmHg and CSFp = 7 mmHg, Q is reduced of 38% from baseline, whereas for IOP = 15 mmHg and CSFp = 48 mmHg, Q is reduced of only 4% from baseline. The model also predicts that a decrease in CSFp from 13.64 to 11.48 mmHg due to MAP variations induces a decrease in Q, Va and Vv of 56.6%, 54.7%, and 56.7%, respective-ly. Thus, the model suggests that changes in IOP have a stronger hemodynamic implications than changes in CSFp, even though these changes lead to the same TLpD. This might be due to the fact that, unlike CSFp, IOP acts directly on the intraocular retinal vessels, thereby altering the vascular resistance of the microcir-culation. Our model suggests that the influence of CSFp on hemodynamics might be mediated by associated changes in arterial blood pressure.

In the study by Causin et al.,161 a mathematical model was proposed to investigate the mechanisms governing the perfusion of the ONH tissue and, particularly, the lamina cribrosa. More precisely, the lamina cribrosa is modeled as a poro-elastic material, where (1) blood vessels are viewed as pores in a solid matrix; (2) the vascular porosity (N) (ratio between blood volume and tissue total volume) changes with the local state of stress and strain; (3) tissue permeability (ability of the porous

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material to allow fluid passing through it) is assumed to be proportional to the square of N; and (4) the solid matrix is assumed to behave as a non-linear elastic material. Blood flow is driven by the difference between the arterial pressure in the SCPAs and the venous pressure in the CRV. The model is used to investigate the influence on the distributions of stress, blood volume fraction (or vascular porosity) and blood velocity within the lamina cribrosa due to the application of different levels of the intraocular pressure (IOP) and the enforcement of different mechanical constraints at the lamina’s boundary. The model simulations suggest that the degree of fixity of the boundary constraint strongly influences the lamina’s response to IOP elevation. Spe-cifically, when the boundary is mechanically clamped, IOP elevation leads to an increase in stress close to the lamina’s boundary, making it more susceptible to tissue damage. On the other hand, when rotations are allowed at the boundary, the most vulnerable region appears to be located at the lamina’s central axis, in proximity of the eye globe, where increased stress and reduced vascular porosity and blood velocity are predicted for increased levels of IOP. The extension of such a model to incorporate a more realistic description of the structural ONH biomechanics (see Section 4.3.1) would be very beneficial to better understand the mechanisms governing ONH perfusion in health and disease.

4.3.3. Ocular oxygenationSeveral authors have addressed the modeling of oxygen transport and delivery within the retina. In the study by Liu et al.,165 the Navier-Stokes equations for blood flow and the convection-diffusion equation for oxygen transfer were solved numerically to obtain detailed blood flow and oxygen distribution patterns in a realistic network of retinal arterioles. The image-based arterial geometry is combined with a structured tree model for the distal peripheral vessels. The intravascular oxygen tension profiles predicted by the computational model were in good agreement with in vivo measurements reported in the literature, demonstrating the potential of our model for prediction of oxygen distribution. In

the study by Causin et al.,166 the model was extended to simulate oxygen transport and diffusion in the whole retinal vascular network, from arteries to veins, and the oxygen delivery and consumption within the layers of the retinal tissue. The model predicted that the oxygen tension in the RGCs is particularly sensitive to changes in arterial blood pressure and metabolic consumption rate. In Arciero et al.,159 oxygen transport and delivery was also modeled along the whole retinal vascular network. Here, the level of oxygen saturation within the vessels was used to define a stimulus function dictating the vasoactive response of retinal arterioles to changes in blood pressure and/or IOP. The stimulus function also included other regulatory mechanisms, namely the myogenic response, the shear-stress response , and the response to the level of carbon dioxide. The combined effects of the responses to changes in oxygen and carbon dioxide levels were predicted to be critical for achieving retinal autoregulation. It would be extremely beneficial for glaucoma research to extend these modeling approaches to the description of oxygen transport, delivery and consumption within the ONH tissue as this would help to better understand the pathogenesis of axonal injury and RGC loss.

The reliability of the predictions of a mathemati-cal model strongly depends on the rationality of the assumptions on which the model is based, the precision of the parameter values involved in the model, and the accuracy with which the model solutions have been obtained.129 Thus, the development of a reliable math-ematical model is a truly interdisciplinary endeavor. It requires active collaboration and continuous interaction between groups of theoretical and applied investigators. Mathematical modeling is certainly not a stand-alone investigative tool; it complements and syn-ergistically combines with laboratory experiments and human or animal studies. Experimental and/or clinical data are critical for obtaining parameter values in the model. Moreover, the comparison between model predictions and experimental/clinical data might unveil new phenomena to be studied with future experiments.

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