Rev. Neurosci. 2015; 26(1): 75–93

Yaroslav Kolinko*, Kristyna Krakorova, Jan Cendelin, Zbynek Tonar and Milena Kralickova

Microcirculation of the brain: morphological assessment in degenerative diseases and restoration processes

Abstract: Brain microcirculation plays an important role

in the pathogenesis of various brain diseases. Several spe-

cific features of the circulation in the brain and its func-

tions deserve special attention. The brain is extremely

sensitive to hypoxia, and brain edema is more dangerous

than edema in other tissues. Brain vessels are part of the

blood-brain barrier, which prevents the penetration of

some of the substances in the blood into the brain tissue.

Herein, we review the processes of angiogenesis and the

changes that occur in the brain microcirculation in the

most prevalent neurodegenerative diseases. There are no

uniform vascular changes in the neurodegenerative dis-

eases. In some cases, the vascular changes are second-

ary consequences of the pathological process, but they

could also be involved in the pathogenesis of the primary

disease and contribute to the degeneration of neurons,

based on their quantitative characteristics. Additionally,

we described the stereological methods that are most

commonly used for generating qualitative and quantita-

tive data to assess changes in the microvascular bed of

the brain.

Keywords: angiogenesis; brain; capillary changes; neuro-

degenerative disease; quantitative histology; stereology.

DOI 10.1515/revneuro-2014-0049

Received July 16, 2014; accepted September 25, 2014; previously

published online October 22, 2014

Introduction

It is well known that the brain is particularly susceptible

to even short periods of oxygen deficiency, the occurrence

of which plays an important role in the pathogenesis of

cerebrovascular and neurodegenerative diseases (NDDs),

including Alzheimer disease (AD) (de la Torre and Stefano,

2000; Nemoto and Betterman, 2007; Lipinski and Pretorius,

2013). The brain structures consist of a complex of various

small units that closely interact with one another. The key

elements required for this specialized system are the brain

microvascular endothelial cells (ECs), the basement mem-

brane, and various types of cells, including neurons and

glial cells that are located close to the capillaries. The blood

vessels, with the participation of the blood-brain barrier

(BBB), shield the brain from toxic substances in the blood,

supply brain tissues with nutrients, and allow harmful

compounds to diffuse from the brain back into the blood-

stream (Persidsky et al., 2006). Consequently, neurovascu-

lar abnormalities play a pivotal role in the pathology of the

nervous system (Farkas and Luiten, 2001; Pantoni, 2010;

Zhang et al., 2011). Changes in the brain vessels can affect

the state and functionality of neuronal tissue via several

mechanisms. Obliterating the vessel lumen restricts the

blood perfusion of the tissue. Decreases in the density of

vessels lead to an increase in the distance between the cap-

illaries and the brain cells, thus increasing the trajectory for

the diffusion of oxygen, nutrients, catabolites, and other

substances (Hunziker et al., 1979; Lim et al., 2013). Hemor-

rhage leads to the destruction of the brain tissue. BBB disor-

ders allow harmful molecules to penetrate the brain tissue.

In addition, blood vessels are involved in the pathogenesis

of brain edema, which leads to an increase in the tissue

pressure and, thus, a decrease in the perfusion pressure and

also prolongs the diffusion trajectory. Finally, blood vessels

play a role in inflammation, and the endothelium is a source

of various biologically active substances.

*Corresponding author: Yaroslav Kolinko, Faculty of Medicine

in Pilsen, Department of Histology and Embryology, Charles

University in Prague, Karlovarská 48, 301 66 Pilsen, Czech Republic,

e-mail: kolinko.yaroslav@gmail.com; and Biomedical Centre,

Faculty of Medicine in Pilsen, Charles University in Prague, Husova

3, 306 05 Pilsen, Czech Republic

Kristyna Krakorova: Faculty of Medicine in Pilsen, Department of

Pathophysiology, Charles University in Prague, Lidická 1, 301 66

Pilsen, Czech Republic

Jan Cendelin: Faculty of Medicine in Pilsen, Department of

Pathophysiology, Charles University in Prague, Lidická 1, 301 66

Pilsen, Czech Republic; and Biomedical Centre, Faculty of Medicine

in Pilsen, Charles University in Prague, Husova 3, 306 05 Pilsen,

Czech Republic

Zbynek Tonar and Milena Kralickova: Faculty of Medicine in Pilsen,

Department of Histology and Embryology, Charles University

in Prague, Karlovarská 48, 301 66 Pilsen, Czech Republic; and

Biomedical Centre, Faculty of Medicine in Pilsen, Charles University

in Prague, Husova 3, 306 05 Pilsen, Czech Republic

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76      Y. Kolinko et al.: Microcirculation during degenerative processes

The mechanisms underlying angiogenesis are not only

active during growth and development but are also neces-

sary for some physiological and pathological processes

that occur during adulthood; for example, these mecha-

nisms are operational during the menstrual cycle (Fraser

and Lunn, 2000; Hazzard and Stouffer, 2000; Reynolds

et al., 2002; Demir et al., 2010), in wound healing, asthma,

atherosclerosis, retinopathies (Cavallaro et  al., 2014),

arthritis, hypertension, preeclampsia (Cerdeira and

Karumanchi, 2012), and particularly in neurodegeneration

(Brown et  al., 2007) and tumor development (Carmeliet

and Jain, 2000; Yancopoulos et al., 2000; Wurdinger and

Tannous, 2009; Claesson-Welsh and Welsh, 2013). Inhib-

iting angiogenesis is a very important approach for the

treatment of numerous diseases, particularly neoplasias,

because tumor growth requires adequate vascularization

(Collinson et al., 2012; Plate et al., 2012; Wang et al., 2012;

Johannessen et al., 2013; Martínez-Jabaloyas et al., 2013).

Among the CNS diseases that occur during middle

and advanced age, the most prevalent belong to a group

of NDDs (Mayeux, 2003; Palop et al., 2006), which are pro-

gressive diseases that are characterized by loss of more or

less specific neuronal populations, giving rise to particu-

lar clinical pictures (Matej and Rusina, 2012). The vascu-

lar changes that are observed in a number of NDDs are a

secondary reaction to changes in the neural tissue due to

defects in the signaling between vessels and neurons. The

changes that occur in the microvasculature subsequently

affect the neurodegenerative process (Buée et al., 1994).

Tracking the features of microvessels in different dis-

eases is difficult. Abnormalities in the cerebrovasculature,

such as number, length, or volume density of vessels,

have been reported in some studies (Miyazaki et al., 2011;

Guan et  al., 2013); however, some of these studies may

be unreliable, and the results cannot be compared with

the data that other researchers obtained because some

of the studies were not based on unbiased stereological

methods. Thus, in this review, we intended to combine the

recent information about brain microvessels, angiogene-

sis, and the blood vessel changes that occur in the most

common NDDs, focusing on their quantitative character-

istics. The most commonly used stereological methods for

both qualitative and quantitative analysis of the microcir-

culation are described, and we provide ideas for the devel-

opment of new morphological techniques.

Brain microvessels

The construction of the brain microvasculature across

mammalian species is remarkably similar and occupies

approximately 3% of the brain volume (Nicholson, 2001).

The arteries and arterioles supplying the brain penetrate

into the cerebral parenchyma and form a network of

somatic capillaries. The capillaries may intermittently

increase or decrease the size of their lumen, but capil-

laries are somehow constitutively perfused with blood

(Göbel et al., 1990; Hudetz, 1997). Generally, capillaries in

the brain may be as small as 7–10 µm in average diameter,

and the average intercapillary distance is approximately

40 µm (Duvernoy et al., 1983; Jucker et al., 1990; Nichol-

son, 2001). This means that each neuron is within 20 µm

of a capillary. The capillary density in the gray matter is

2–4  times higher than the average density of capillaries

in the brain (Borowsky and Collins, 1989; Heinzer et al.,

2008), which corresponds to a higher level of neural activ-

ity in the gray matter than in the white matter (Zhu et al.,

2012). Although the average numerical density of microves-

sels in the human brain cortex is 3160.0 ± 638.4 units/mm3

and the length density is 570.9 ± 71.8 mm/mm3, the subcor-

tical gray matter has a numerical density of 3782.0 ± 1602.0

units/mm3 and a length density of 652.5 ± 162.0 mm/mm3.

In the white matter, the numerical density (627.7 ± 318.5

units/mm3) as well as the length density (152.7 ± 42.0 mm/

mm3) are remarkably lower (Tonar et al., 2011). These find-

ings suggest that any potential pathological changes in

the brain microvasculature have to be considered in white

and gray matter separately.

The entry of blood components, such as plasma, red

blood cells, and leukocytes, outside the bloodstream into

the brain is limited by the BBB. Traditionally, the BBB is

defined as the layer of ECs that form the vessel walls. It is a

highly dynamic system in which cells transduce chemical

and mechanical signals in complex microenvironments

(Andrew et al., 2013; Wong et al., 2013). In such processes,

the smooth muscle cells, pericytes, astrocytes, and extra-

cellular matrix are also involved. All these elements are

organized into the different layers of the vessel wall.

Experimental evidence from various animal models

suggests that there may be significant biochemical dif-

ferences in the composition of the BBB. For example, the

expression level of transporters and pumps varies across

species, suggesting that they contribute to the uniqueness

of the human BBB (Hammarlund-Udenaes et  al., 2008).

Elucidating these differences is key for of experimental

studies of NDDs.

The ECs in the BBB function as a checkpoint for

different chemical and mechanical forces in the local

micro-neuro-environment and depend on the cell mor-

phology, protein and gene expression, proliferation,

transport, etc. (Dejana, 2004; Aird, 2007). The EC-cell

junctions have a key role in maintaining the integrity of

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Y. Kolinko et al.: Microcirculation during degenerative processes      77

the microvasculature and in regulating paracellular trans-

port. This is ensured through the formation of adherens

and tight junctions (Bazzoni and Dejana, 2004; Dejana,

2004; Aird, 2007). More than 20 proteins in the claudin

family, such as α-catenin, β-catenin, vinculin, and others,

are essential for the formation of tight junctions (Bazzoni

and Dejana, 2004; Dejana, 2004). Of great importance for

the correct functioning of these cells are pressures associ-

ated with directional blood flow (Caplan et al., 1974; Sata

and Ohashi, 2005; Aird, 2007) that are applied to the small

capillaries. Accordingly, ECs can wrap around to form

tight junctions with themselves, as well as their neigh-

bors (Nag, 2003). Shear stresses can also upregulate the

expression of genes associated with junctional proteins

and transporters (Cucullo et al., 2011).

Astrocytes in the brain are usually star-shaped with

many processes emanating from the cell body, with an

overall diameter of approximately 140 µm (Oberheim

et al., 2009). They interact with microvessels through the

end-feet of their cellular protrusions, which wrap around

the capillary (Abbott et al., 2006). Moreover, one astrocyte

may contact multiple capillaries (Oberheim et al., 2009).

The form of astrocyte contact plays an important role in

matching oxygen and glucose transport to neural activity

through the regulation of local blood flow (Zonta et  al.,

2003; Iadecola, 2004; Takano et  al., 2006; Iadecola and

Nedergaard, 2007).

Pericytes in the brain wrap around capillaries and

microvessels (Krueger and Bechmann, 2010; Bonkowski

et  al., 2011; Winkler et  al., 2011) and communicate with

ECs, astrocytes, and neurons to initiate multiple signal-

ing pathways (Bonkowski et al., 2011). The pericytes are

contractile cells with actin fibers and contribute to the

regulation of blood flow by controlling capillary diam-

eter (Peppiatt et al., 2006; Hamilton et al., 2010; Dalkara

et al., 2011). A thin layer of basement membrane, which is

composed of fibronectin, laminin (Aumailley et al., 2005),

and type IV collagen (Tilling et al., 2002; Hartmann et al.,

2007), separates pericytes from both ECs and the sur-

rounding astrocytes. The ratio of ECs to pericytes is typi-

cally approximately 1:3 (Shepro and Morel, 1993).

The extracellular space provides the main pathway for

transport between cells. Intercellular transport is usually

much faster than transport across the BBB, and hence,

it is particularly important for the local penetration of a

solute, such as tissue proteins and electrolytes. The extra-

cellular space is filled with hyaluronan-based extracellu-

lar matrix and a fluid phase, and its volume fraction can

reach up to 30% (for review, see Sykova and Nicholson,

2008). The fluid phase is a medium for transporting mole-

cules, such as essential molecules and neurotransmitters,

that are involved between microvessels and cells in the

brain (Andrew et al., 2013). The extracellular matrix in the

brain is composed of four main components: hyaluronic

acid, tenascin, lecticans, and hyaluronan and proteogly-

can link proteins (Zimmermann and Dours-Zimmermann,

2008). Widespread proteins such as collagen type I and

fibronectin are absent in the brain extracellular matrix

(Sanes, 1989).

Another barrier that is worth mentioning is the blood-

cerebrospinal fluid (CSF) barrier. This barrier is formed

in the plexus choroideus between the neuroependymal

cells that line the ventricular wall (which floats in the

CSF space) and the blood vessels that it vascularizes.

These structures produce approximately 150  ml of CSF

per day so as to renew the content of the ventricles and

the subarachnoid space approximately three to four times

per day (Marques et  al., 2013). Tight junctions bind the

neuroependymal cells to one another. These cells have

numerous villosities on its apical side, and they rest on

a basal lamina that is formed by connective tissue that is

highly vascularized by fenestrated capillaries. Although

the passage of molecules and cells through the blood-

CSF barrier is possible, they do not reach the paracellular

transport system due to the tight junctions between epi-

thelial cells (Segal, 2001; Saunders et  al., 2013). Exami-

nations of the blood-CSF barrier over the last decade

resulted in its reported participation in various aspects

of brain homeostasis. This suggests that it plays a much

greater role than was previously believed (Emerich et al.,

2005; Johanson et al., 2011; Falcao et al., 2012; Baruch and

Schwartz, 2013).

Although the regulation of brain capillaries by the

autonomic nervous system has not yet been described

(Peppiatt et  al., 2006; Fisher, 2009; Krueger and

Bechmann, 2010), biochemical and biomechanical inputs

from the vascular system, numerous paracrine signal-

ing pathways between microvascular ECs and astrocytes,

and pericytes are responsible for maintenance of the BBB

(Aird, 2007; Abbott et al., 2010).

Physiological aspects of

angiogenesis in the brain

Mechanisms of angiogenesis

The vascular system develops through two distinct pro-

cesses: vasculogenesis and angiogenesis (Reynolds et al.,

2000). Vasculogenesis is the de novo formation of blood

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78      Y. Kolinko et al.: Microcirculation during degenerative processes

vessels from angioblasts during embryonic development.

Angiogenesis is the process of neovascularization from

preexisting vessels (Zygmunt et  al., 2003), which can

occur via by two pathways – sprouting and intussuscep-

tion (nonsprouting angiogenesis). The primitive vascular

network is formed in three major steps, as follows: (a) the

proliferation and differentiation of hemangioblasts and

angioblasts, (b) the formation of primordial vessels, and

(c) the progressive expansion of the blood vessels through

angiogenesis (Risau, 1997; Zygmunt et al., 2003).

The angiogenic process is initiated by stimulation

by proangiogenic factors, including vascular endothelial

growth factor (VEGF) and placental growth factor or fibro-

blast growth factor (FGF), and the selection of endothelial

“tip cells”. Tip cells play a major role in the degradation

of the basement lamina, pericyte detachment, the detach-

ment of the perivascular feet of astrocytes from the glial

limiting membrane, and the loosening of EC junctions. The

selection of tip cells is controlled by Notch family receptors

and Delta-like ligand 4, which are activated by the inter-

action of VEGF and ECs (Liu et al., 2003; Tahergorabi and

Khazaei, 2012). This process is followed by chemotactic

migration and the proliferation of the ECs, the formation

of a lumen, and the functional maturation of the endothe-

lium (Risau, 1997). These processes are also mediated by

the interaction of VEGF-A and VEGF receptor 2 (Green-

way et  al., 2006). The channels the nascent ECs become

covered by pericytes and smooth-muscle cells, which

provide strength and allow the regulation of vessel perfu-

sion, in a process called arteriogenesis (Carmeliet, 2005).

Finally, the maturation of new blood vessels is achieved by

the annealing of pericytes and smooth-muscle cells, in a

process termed arteriogenesis (Heinke et al., 2012).

Regulation of angiogenesis

Angiogenesis is a complex process that regulates changes

in the ratio between proangiogenic and antiangiogenic

factors. Hypoxia is the primary factor that induces angio-

genesis (Taylor and Sivakumar, 2005; Zhong et al., 2008;

Arden and Sivaprasad, 2012; Konisti et al., 2012; Lin et al.,

2013). Other important inducing factors are VEGF, FGF,

and angiopoietins. The key activators and inhibitors of

angiogenesis are shown in Table 1.

Changes in the microvascular density in the

brain during life

Of all the organs, the brain has the most intensive meta-

bolic activity. The young adult brain retains the ability to

form vessels under hypoxic conditions, but this capacity is

lost in mature and aged brains (Shao et al., 2010; Sonnotag

et al., 1997; Harb et al., 2013). During early embryogenesis,

vessels in the pia mater invade the brain and converge cen-

tripetally toward the ventricles. The vessels that surround

the brain ventricles rise as second-order branches from

deeply penetrating vessels (Greenberg and Jin, 2005). The

second process is the centrifugal extension of the vessels

toward the pia mater (Greenberg and Jin, 2005).

Several investigators have studied the effect of aging

on the density of brain vessels (Table 2). Their findings are

conflicting because the vascular density has been reported

to decrease, increase, and remain unchanged (Riddle

et al., 2003). These conflicting data can be explained by

a phenomenon called a referent trap (Brændgaard and

Gundersen, 1986).

Table 1 Key activators (+) and inhibitors (-) of angiogenesis.

Name   Effect  Function   References

VEGF family   +   Stimulation of vasculogenesis/

angiogenesis

  Carmeliet and Jain, 2000,

2011

FGF   +   Stimulation of angiogenesis   Konisti et al., 2012

Angiopoietins   +   Maturation and stabilization of

the developing vessels

  Zacchigna et al., 2008

Transforming growth factor β   +   Stimulation of extracellular

matrix production

  Wang et al., 2013

Hepatocyte growth factor   +   Stimulation of angiogenesis/

arteriogenesis

  Tsunemi et al., 2013

Ephrins   +   Maturation of vessels   Adams et al., 1999

Platelet-derived growth factor  +   Effect on smooth-muscle cells   Moreno et al., 2013

Angiostatin   -   Inhibition of EC migration   Distler et al., 2003

Endostatin   -   Inhibition of EC migration   MacDonald et al., 2001

Vasostatin   -   Inhibition of endothelial growth  Pike et al., 1998

Thrombospondin   -   Stimulation of EC apoptosis   Jiménez et al., 2000

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Y. Kolinko et al.: Microcirculation during degenerative processes      79

In addition, various aging-related ultrastructural

changes in the wall of the vessels have been described,

including a decrease in the smooth-muscle and elastin

contents and an increase in the thickness of the base-

ment lamina (Keuker et  al., 2000; Peters and Sethares,

2012). Furthermore, the pericytes of the aging brain are

characterized by the increased size of their mitochondria

(Hicks et al., 1983) but not by changes in the extent of the

coverage of ECs by the pericytes or in the number of mito-

chondria in the ECs (Farkas and Luiten, 2001; Peters and

Sethares, 2012).

Pathological changes of

microvessels

In general, all vascular pathological changes can be clas-

sified via two principal mechanisms. First, the narrowing

(e.g., an increase or decrease in the surface area of plas-

molemma cell membranes or the formation of micropi-

nocytotic bubbles) or obstruction (e.g., via thrombosis or

embolism) of vessel lumens leads to ischemia of particular

parts of the brain. Second, the weakening of vessel walls,

Table 2 The effect of aging on brain vessel density in various brain regions.

Species   Part of CNS   Method   Changes of vessels during life   References

Human   Paraventricular nucleus  Fixed brain tissue   Decrease in vascular density   Wang et al., 2013

  Supraoptic nuclei     No changes  

Rat   Cerebral cortex   Immunohistochemistry with

quantitative image analysis

  Decrease in capillary length

and reduced intercapillary

distance

  Tsunemi et al., 2013

Human   Hippocampus   Thick celloidin sections   Decrease in vascular density   Abernethy et al., 1993

Human   Brain white matter   Computerized image

processing

  Decrease in vascular density   Moreno et al., 2013

Rat   Brain   Alkaline phosphatase

staining

  Decrease in capillary length

and volume

  Distler et al., 2003

Human   Cerebral cortex   Immunohistochemistry   Decrease in vascular density   MacDonald et al., 2001

Human   Cerebral periventricular

white matter

  Quantitative light and

electron microscopy analysis

  No changes   Pike et al., 1998

Rat   Olfactory bulb   Quantitative light and

electron microscopic

analysis

  Decrease in capillary density   Jiménez et al., 2000

Human   Cerebral cortex   Stereology   Increased capillary diameter,

volume, and total length per

unit cortex volume

  Wang et al., 2013

Rat   Hippocampus   Optical-electronic image

analysis technique

  Decrease in capillary number

and length

  Tsunemi et al., 2013

  Cerebral cortex     Reduction in capillary number

and length

 

Rhesus monkey  Hippocampus   Electron microscopy image

analysis

  Increase in the thickness of

basement membrane

  Adams et al., 1999

Human   Putamen   Stereology   Increase in the capillary

volume

  Moreno et al., 2013

  Cerebral cortex     Slight increase in the capillary

length

 

Rat   White matter   Immunohistochemistry and

stereological techniques

  Decrease in total length, total

volume, and total surface area

of the capillaries

  Distler et al., 2003

Rat   Cerebral cortex   Computer-aided image

analysis

  Decrease in vascular density   MacDonald et al., 2001

Human   Frontal lobe, occipital

lobe, striatum, and

hippocampus

  Immunohistochemistry

and computer-aided image

analysis

  Increase in tortuosity,

looping, bundling, stringing,

and effacement of endothelia

  Pike et al., 1998

Rat   Cerebral cortex   Vessel-filling technique and

a quantimet 720 shape-

analyzing computer

  Decrease in vessel number

and brain blood volume

  Jiménez et al., 2000

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80      Y. Kolinko et al.: Microcirculation during degenerative processes

their dilation, or their rupture (e.g., microclasmatosis,

abruption of ECs, exposure and easing of basal lamina)

leads to brain edema and an output of blood elements

outside the bloodstream (Robbins et al., 2010). Vessels of

any type can be affected; however, the most responsive

are small vessels (Iglesias-Gamarra et al., 2007).

In the case of damage to brain tissue, the activity of

several different lipases is stimulated, resulting in the

hydrolysis of many membrane lipids. Initially, this may

be caused by an augmented Ca2+ influx (Klein et al., 2000;

Amenta et  al., 1995). Within a short period of time fol-

lowing brain damage, there is an increase in neutrophil

infiltration, astrocytosis, edema, and both proinflamma-

tory (interleukin-1β, interleukin-6, tumor necrosis factor

alpha) and anti-inflammatory (interleukin-10 and trans-

forming growth factor beta) cytokine release (Stella and

Piomelli, 2001; Garcia-Ovejero et al., 2009).

Loss of pericytes and ECs is associated with the BBB

breakdown and is accompanied by extravascular deposi-

tions of IgG and fibrin (Sengillo et al., 2013). Indeed, peri-

cyte loss leads to BBB damage by two parallel pathways:

a reduction in brain microcirculation (causing chronic

perfusion stress and hypoxia), and the accumulation of

serum proteins and several neurotoxic and vasculotoxic

macromolecules in the brain, which ultimately leads to

secondary neuronal degenerative changes (Bell et  al.,

2010; Farkas et al., 2006).

Chronic systemic inflammation causes neuronal

damage and death (Li et al., 2013b). Systemic proinflamma-

tory mediators influence the integrity of the BBB, thereby

leading to an increase in its permeability (Muccioli and

Stella, 2008; Li et al., 2014; Trickler et al., 2014). BBB break-

down, including changes to the neuronal milieu, is due to

disruption of tight junctions. This alters the blood-to-brain

transport of molecules and results in aberrant angiogenesis,

vessel regression, brain hypoperfusion, and an inflamma-

tory response (Zlokovic, 2008). In this way, there are many

conditions that can initiate the “vicious circle” of the disease

process. This results in the progressive synaptic and neu-

ronal dysfunction and loss that is characteristic of NDDs.

However, this is time dependent and progresses slowly.

Circulatory-system changes in

neurodegenerative disorders

Alzheimer disease

AD is the most common NDD and the most frequent type

of dementia. The emergence of the neurodegenerative

process in AD is associated with activated microglia as

well as elevated levels of proinflammatory cytokines (Streit

et al., 2004). It is also accompanied by the accumulation

of amyloid-β (Aβ) in the brain parenchyma (Karran et al.,

2011). The supposed toxic effects of Aβ, while not the cause

of the illness, can lead to a significant reduction in the

number of neurons, the density of which decreases with

age by 37–48% in the CA1 field, 24% in the subiculum, and

14% in the hilus (Geinisman et al., 1996; West et al., 2004;

Bouras et al., 2006). The loss of neurons and synapses and

the presence of neurofibrillary tangles and senile plaques

are also accompanied by vascular pathology. An increased

frequency of twisted, kinked, and string-like vessels has

also been reported, which represent a reorganization of the

vascular extracellular matrix (Buchweitz-Milton and Weiss

1987; Gama Sosa et  al., 2010). A reduction in the length

and number of vessels without any change in their density

in mice models (Lee et  al., 2005) could simply reflect an

adaptive response of the capillary network to the neuronal

depression-related decrease in energetic demands in older

individuals (Bouras et al., 2006; Fleisher et al., 2009). There

have also been reports of various degrees of vascular wall

degeneration, with the loss of basal lumens and distorted,

swollen nuclei found in ECs, which promote the formation

of micro-hematomas of up to 100 µm in diameter (Price

et al., 2001; Gama Sosa et al., 2010; Winkler et al., 2013).

Such small hemorrhages are accompanied by an accumula-

tion of Aβ depositions in the tunica media, smooth muscle

cells, and adventitia (Charidimou et  al., 2012; Brown and

Thore 2011). Clinically, pathological changes in vessels in

the AD are manifested as cerebral amyloid angiitis (Chung

et al., 2011) or more frequently as cerebral amyloid angiopa-

thy (Charidimou et  al., 2012; Illsley and Ramadan, 2014),

which are responsible for 5–10% of spontaneous intracer-

ebral hemorrhage (Vinters, 1987).

Sengillo et  al. (2013) demonstrated a significant

decrease in the number of pericytes and mural vascu-

lar cells in the human cortex and hippocampus by 60%

and 33%, respectively. Changes in the structure of the

vascular wall were correlated with an increased produc-

tion of extracellular matrix-related proteins. Exploring

the considerable changes in the capillaries in AD led to

data that demonstrated that endoplasmic-reticulum

stress plays a significant role in the Aβ-induced decrease

in cerebral vascular densities, the presence of apoptotic

cerebral vascular cells, and the loss of cerebral vascular

cells, which further increase Aβ production (Wang et al.,

2004; Miao et al., 2005; Fonseca et al., 2013). The vascular

changes in AD were described as degenerative, with the

loss of the ability to perform vascular remodeling and/or

angiogenesis (Desai et al., 2009; Kannurpatti et al., 2010).

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Y. Kolinko et al.: Microcirculation during degenerative processes      81

Nevertheless, the underlying mechanisms of microvascu-

lar dysfunction have not been fully elucidated.

Parkinson disease

The second most prevalent NDD in the aging human is

Parkinson disease (PD) (de Lau and Breteler, 2006). This

progressive neuroinflammatory disease is characterized by

slow movements, rigidity, postural instability, and a resting

tremor resulting from the marked loss of dopamine (Fahn,

2003). The illness occurs mainly in men, primarily those

with a history of smoking (Schwartz et al., 2012). The neu-

ronal degeneration in PD affects the substantia nigra, basal

ganglia nuclei, and cerebral cortex, leading to dopamine

depletion in the nigro-striatal pathway (Poewe, 2009).

Guan et al. examined the condition of vessels in the

brains of PD patients, reporting a significant reduction in

the number of capillaries as well as a shorter length and

an increased diameter. There was also obvious damage to

the capillary network, as demonstrated by a reduction in

branching. The vascular pathology includes the formation

of endothelial “clusters” and a damaged capillary network,

possibly due to vessel fragmentation. Vessel degeneration

was observed in multiple brain regions, particularly in the

substantia nigra, cerebral cortex, and brain stem nuclei,

but not in the caudate nucleus (Guan et al., 2013). Similar

changes were also shown in animal models (Sarkar et al.,

2014). Such data suggest that vascular degeneration may

be an important additional factor that contributes to the

progression of PD and may even contribute to the initial

pathology that leads to neuronal degeneration. This

hypothesis is also supported by reports of significantly

increased levels of molecular markers, including mono-

cyte chemoattractant protein-1, VEGF, and endothelin-1.

This indicates that endothelial damage in PD patients

(Makarov et  al., 2013) can occur without changes to the

levels of monocarboxylates (MCT1 and MCT2) and glucose

in the study of animal models (Puchades et al., 2013).

Evaluating the brain using immunostaining for

integrin αvβ3, a marker for angiogenesis and activated

microglia, showed an increased number of microglia and

microglial activation in the substantia nigra, suggesting

the presence of newly created vessels that most likely had

not developed the restrictive properties of the BBB (Desai

Bradaric et al., 2012).

Lewy body disease

The histological hallmark of the degenerating neurons

present in Lewy body disease (LBD) is cytoplasmic

inclusions containing α-synuclein and other aggregated

proteins (Kalaitzakis et al., 2008; Lin et al., 2009). LBD is

thought to represent preclinical PD because Lewy bodies

were identified in these patients during autopsy but they

lacked the clinical symptoms of PD (DelleDonne et  al.,

2008). Epidemiological studies have shown a striking

inverse relationship between LBD and clinically mani-

fested vascular pathologies (e.g., a history of stroke)

(Ghebremedhin et al., 2010). Nevertheless, distinct vascu-

lar abnormalities have been detected histologically in LBD

patients. A small globular accumulation of TDP-43 protein

in close proximity to small, but not large, blood vessels

has been demonstrated by immunoelectron microscopy

(Lin et al., 2009). The tendency of these processes to be

associated with capillaries and their enclosure by the

vascular basal lamina and the formation of new basal

lamina that appeared to compress and pinch off the end-

feet of astrocytes may indicate microvasculopathy associ-

ated with loss of the integrity of the BBB. Changes in the

number of microglia and vessels during in the course of

the disease and increased angiogenesis were also docu-

mented in LBD, suggesting that these changes should

appear during the preclinical period of PD (Desai Bradaric

et al., 2012). However, the counts were obtained using 2D

sections without considering the tissue volume; therefore,

an analysis of the tissue volume will be necessary to pre-

cisely interpret the data.

Corticobasal degeneration and progressive

supranuclear palsy

Both corticobasal degeneration (CBD) and progressive

supranuclear palsy (PSP) are classified as Parkinson plus

syndromes. CBD is a progressive degenerative disease that

affects both the cortical and subcortical systems, begin-

ning at the age of approximately 60  years (Armstrong

et  al., 2013). One of the primary pathological processes

in CBD appears to be the degeneration of the cerebellar

dentate nucleus (Su et  al., 2000). The other cerebellar

nuclei have not yet been examined. A cytopathological

feature of CBD is immunoreactivity to phosphorylated

tau in neurons and glia. The morphological picture of

the disease includes pre-tangles, neurofibrillary tangles,

astrocytic plaques, tufted astrocytes, coiled bodies, and

argyrophilic threads (Katsuse et al., 2003).

PSP is featured by supranuclear ophthalmoplegia,

which affects primarily vertical gaze, pseudobulbar palsy,

dysarthria, dystonic rigidity of the neck and upper trunk,

and other less constant cerebellar and pyramidal symp-

toms. Formerly, this disease was considered to be arterio-

sclerotic parkinsonism (Critchley, 1929), but this idea was

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82      Y. Kolinko et al.: Microcirculation during degenerative processes

later abandoned. Commonly, PSP is a more rapidly pro-

gressing form of PD, with atypical clinical features (Steele

et al., 1964). This rapid progression is also related to the

more intensive angiogenesis and the higher number of

vessels in the affected areas (Desai Bradaric et al., 2012).

In postmortem studies of CBD and PSP patients,

astrocytic plaques and tuft-shaped astrocytes were fre-

quently found. A close proximity of the astrocytic plaques

to the nearest blood vessel was also observed, showing a

reduced diameter (Shibuya et al., 2011). This phenomenon

was explained by the distal accumulation of phosphoryl-

ated tau that was associated with blood vessels (Shibuya

et  al., 2011). These results suggest a similarity in patho-

genic mechanisms of vascular injury in these diseases.

Huntington disease

Huntington disease (HD) manifests in middle-aged people

(35–50 years). HD is an autosomal-dominant inherited

disease and is caused by an expansion of the CAG trinu-

cleotide repeat in exon 1 of the Huntingtin (Htt) gene,

resulting in the expansion of a polyglutamine tract in

the protein (Montoya et al., 2006; Novak et al., 2012). MR

imaging has identified marked gaps in the cerebral blood

flow in HD. In particular, reduced perfusion was found in

areas of the brain cortex that are closely associated with

higher neural activity (Chen et al., 2012). In contrast, the

immunohistological studies in humans and mice models

revealed significantly increased vessel density in the

cortical and striatal regions; the BBB likely was intact

and functional (Franciosi et  al., 2012; Lin et  al., 2013).

Chronic deposition of peripheral lipopolysaccharides,

which is typical for presymptomatic HD, had no effect on

the density or length of vessels but had significant effects

on vessel integrity (Franciosi et  al., 2012). The observed

narrowing of the vessel lumens was explained as due to

the increased thickness of basal lamina, which reflected

increased smooth-muscle cell proliferation and a decrease

in the activity of proteases involved in extracellular-matrix

turnover, resulting in an accumulation of vessel wall com-

ponents such as collagen IV (Franciosi et al., 2012). This

process has been shown to directly affect the expression

and activity of endothelial nitric oxide synthase (Deckel

et al., 1998; Duran-Vilaregut et al., 2011). However, there

are no reports on the effects of the mutant Huntingtin

protein on the endothelium. In contrast, the vessel density

in the cerebellum was similar in HD patients and healthy

patients (Maat-Schieman et al., 1999).

Treating HD by transplanting solid fetal striatal tissue

has been tested (Cisbani et  al., 2013). The striatal grafts

displayed significantly reduced numbers of large blood

vessels and astrocytes, which may have contributed to

the poor graft survival. It should also be noted that the

blood supply is proportional to the dimension of the graft

and the methods used to dissect the fetal tissue (Freeman

et al., 2011). Therefore, solid grafts, which contain donor-

derived vascularization, may be more immunogenic than

suspended-cell transplants (Freeman et al., 2011).

Amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) involves the slowly

progressive dysfunction and degeneration of the motor

neurons in the brainstem nuclei, corticospinal tract,

and ventral roots of the spinal cord and generally occurs

after the age of 40 years (Evans et al., 2013; Garbuzova-

Davis et  al., 2007). It has a familial and sporadic etiol-

ogy, wherein mutations in one of more than 12 genes are

thought to cause ALS (Greenway et  al., 2006; Su et  al.,

2014). At the subcellular level, the mitochondrial cristae

in the ECs and neuropil are disorganized and degenera-

tive. Here, the astrocytes lose the ability to pump water

from the neural tissue, thereby promoting edema in the

brainstem and spinal cord (Garbuzova-Davis et al., 2007;

Evans et  al., 2013). Swollen astrocyte foot processes,

endothelial degeneration, and extracellular edema

around the astrocytes and motoneurons contribute to

the disruption of the BBB (Garbuzova-Davis et al., 2007).

Perivascular deposits of erythrocyte-derived hemoglobin

and hemosiderin (typically 10–50 µm in diameter) and

extravasal plasma proteins have been found in ALS

patients (Winkler et al., 2013). Because hemoglobin has

a toxic effect on neural cells (Regan and Guo, 1998),

the rupturing of the microvessels plays a role in the

pathogenic neuronal degeneration. Furthermore, the

vascular rupturing coincides with reductions in capil-

lary pericyte population, which play a key role in the

BBB (Garbuzova-Davis et al., 2011; Winkler et al., 2013).

Vasoactive neuropeptides (which have critical roles

as neurotransmitters and vasodilators and regulators

of perfusion and hypoxia) and immune and nocicep-

tion modulators are produced in the pericytes (Staines

et  al., 2009). Therefore, the loss of the pericytes likely

also promotes the manifestation of the disease. There is

also evidence for decreased capillary length, number,

diameter, and perfusion in SOD1 mice (Zygmunt et  al.,

2003; Miyazaki et al., 2011); unfortunately, these studies

were not based on systematic uniform random sampling

(SURS) and therefore were prone to a biased selection of

microscopic imaging fields.

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Y. Kolinko et al.: Microcirculation during degenerative processes      83

Niemann-Pick disease

Postmortem electron-microscopic neuropathological

examination of Niemann-Pick disease (NPD) patients

revealed neurofibrillary tangles in many parts of the

brain. A4/β protein, which is the primary cause of the

disease, was not detected in the form of plaques or in the

walls of blood vessels (Love et  al., 1995). However, lipid

abnormalities in phenotypes A and B (McGovern et  al.,

2004), which may be associated with early atherosclerotic

heart disease, were reported. However, in phenotype C,

there was a significant reduction in cholesterol absorption

and the plasma cholesterol levels, which causes nearly

complete protection from the development of atheroscle-

rosis (Davis et al., 2007). Despite the existence of animal

models for NPD, pathological changes of the brain micro-

vasculature have not yet been studied.

The main pathological changes to brain microcircula-

tion in individual NDDs are briefly summarized in Table 3.

Methods of investigating

the microcirculation

The material presented above clearly indicates that the

microcirculatory bed affects the activity of neurodegen-

erative processes and that the neurodegenerative pro-

cesses affect the microvasculature. The shortcomings

and methodological bias, namely, the lack of systematic

unbiased sampling, in some studies that do not allow the

fullest appreciation and the ability to compare their find-

ings with those of other research teams have been already

mentioned. Therefore, high-quality studies of the vascu-

lar bed of the brain, based on specific vascular imaging

techniques, adequate and representative sampling, and

exact data quantification are extremely important for the-

oretical and practical medicine.

Vascular visualization techniques

Currently, immunohistochemical methods are used to

visualize the microvessel wall. Different researchers have

their own approaches for visualizing the vascular bed

using antibodies. For example, most vascular smooth-

muscle cells and pericytes are positive for α-smooth

muscle actin, desmin, calponin, or caldesmon but are

negative for angiopoietin-2 (Hughes and Chan-Ling, 2004;

Li et al., 2013a). Labeling microvascular ECs can also be

used as an approach for investigating brain vessels. In

contemporary studies, cluster-of-differentiation (CD)

molecules are widely used for specifically detecting

microvessels. One of them is CD31, a platelet EC adhesion

molecule (Newman and Albelda, 1992). Another marker of

vascular-associated tissue is CD34, a member of a family of

single-pass transmembrane sialomucin proteins (Krause

et al., 1996). Detecting the glycocalyx of ECs by labeling

using lectins is an alternative for visualizing blood vessels

(Holthofer et al., 1982). Good characterization of the pro-

cesses of angiogenesis and vascular remodeling was

obtained using Lycopersicon esculentum lectin (Mazzetti

et  al., 2004) and Ulex europaeus I agglutinin (Holthofer

et al., 1982). In particular, rabbit polyclonal anti-collagen

IV antibody (Qiu et al., 2011; Huang et al., 2013) and rabbit

polyclonal antilaminin antibody (Kochová et  al., 2011;

Tonar et al., 2011) have been shown to be convenient tools

for the serological examination of brain blood vessels.

To obtain quantitative data using confocal laser

microscopy, a plasma marker such as FITC-dextran

can be used (Anwar et  al., 1992; Kurozumi et  al., 2007)

or india ink/gelatin can be used as a space-occupying

Table 3 Main changes to brain microcirculation in individual NDDs.

NDDs  Changes in

microvessel lumens

  Changes in

microvessel wall

 

 

Quantitative changes in microvessels   Changes in

angiogenesis

  Known mechanism of

microvessel changesAnimal   Human

AD   +   +   +   +   -   ±

PD   +   +   ?   +   +   +

LBD   ?   +   ?   ±   ?   +

CBD   +   +   ?   ±   ?   ?

PSP   +   +   ?   +   +   ?

HD   +   +   +   +   +   +

ALS   ?   +   ±   ?   ?   +

NPD   +   +   ?   ?   ?   ?

+, vessel change present; -, vessel change not present; ± , contradictory findings;?, no data available.

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84      Y. Kolinko et al.: Microcirculation during degenerative processes

high-contrast material (Cassot et  al., 2006; Lokmic and

Mitchell, 2011). These approaches are based on visualiz-

ing the lumens of the vessels.

The tissue-sampling approach

Whereas biological objects in tissues are three-dimen-

sional (3D) structures, the information related to the

third dimension is reduced when they are visualized in

histological sections (Nyengaard and Gundersen, 2006;

Eržen et  al., 2011). Nevertheless, there are various tools

for obtaining statistically relevant data, among which is

a fractionator (West et al., 1991; Burke et al., 2009; Boyce

et  al., 2010), a disector (Sterio, 1984; Gundersen, 1986;

West, 1999), an isector (Nyengaard and Gundersen, 1992),

a cycloid (Baddeley et  al., 1986; Calhoun and Mouton,

2001), an orientator (Mattfeldt et al., 1990; Huang et al.,

2013), and spherical sampling probes (Mouton et  al.,

2002). Using them in combination is also possible.

The most widely used and simplest approach is the

combination of the fractionator and disector methods.

This method is based on multistep sampling of the tissue

using known and predetermined sampling-step sizes at

each phase. In the final sample, the structural quantity is

estimated (West et  al., 1991; Nyengaard and Gundersen,

2006). The first step of this technique is performing a

SURS. The reference space is sliced at regular uniform

intervals. For investigation, every n-th slice is used, where

n is sampling step (Figure 1A). Then, in the second phase,

each sampled section in the location of the first probe and

randomly selects in the x-y plane at a constant interval

(Boyce et  al., 2010; Mouton, 2011). Generally, a micro-

scopic imaging field is used for this purpose (Figure 1B).

Stereological analysis is applied using simple elements,

as follows: in each microscopic field that was prepared

minimally, a pair of visualized sectional planes is sepa-

rated by a known distance along the z axis (Figure 1D–F)

and an unbiased two-dimensional counting frame of a

known area is placed on each of these sectional planes

(Nyengaard and Gundersen, 2006).

This principle can be used in physical and optical

planes and generally involves paired serial 2- to 10-µm-

thick physical or focal sections. These constitute the

counting and look-up sections, with the section thickness

corresponding to the disector height (Glaser et al., 2007;

Boyce et al., 2010).

Typically, only 100–200 ultrastructural elements

must be counted in one object to obtain a precision that

is appropriate for experimental studies (West et al., 1991;

Gundersen et al., 1999).

Quantitative description of the

microvasculature

Unbiased stereology involves a collection of design-based

methods that have been accepted as state-of-the-art for

quantifying blood-network objects in tissue sections to

generate reliable structural data that describe biologi-

cal features. The options for these evaluations of their

parameters include a definition of regional volume and

determining the number of vessels, the lengths of the cap-

illaries, and tortuosity of the vessels within the reference

space (Mouton, 2011). Different interactive computer soft-

ware subroutines can be used to take these measurements

using the images on the monitor. The current stereological

methods are assumption-free, i.e., there are no assump-

tions made about the shape, size, orientation, or distribu-

tion of the structures to be quantified.

The quantitative data are obtained using the sampled

(reference) space and then the whole-object data are cal-

culated using the proportions determined using the ratio

of the sampled volume to the total-object volume. The

volume of the object can be determined by calculating

its fraction of the known volume. In turn, the fraction of

volume is estimated from the area of fraction multiplied

by the height. The sectional area is determined using the

point grid method. The essence of the method consists of

calculating the points overlying an object of interest and

then multiplying them by the area associated with each

point (Gundersen and Jensen, 1987; Løkkegaard et  al.,

2001).

One of the simplest ways to quantify vessels is deter-

mining the microvessel density. The tissue sections for

high-power analysis are selected using multilevel sam-

pling rules at the light microscopic level, and the blood

vessels per cross-sectional area are counted (Figure 1C).

A countable vessel is defined as a vessel lumen or any

EC or EC cluster separate from the adjacent microvessels

(Weidner, 2008; Lokmic and Mitchell, 2011). The sim-

plicity and rapid data production (2–3  min per section)

of this method contributed to its wide dissemination in

clinical practice (Fox and Harris, 2004). However, the

data obtained using this method can have a trending

nature and are not entirely objective (Schouten et  al.,

2014) because measurements are taken in the plane, and

depending on the placement features, a vessel may be

counted several times.

The number of structures as well as connectivity of

structures is determined by counting “specific points”

using the disector volume probe in accordance with the

Cavalieri principle, which may be performed on sections

with an arbitrary orientation (Nyengaard and Gundersen,

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Y. Kolinko et al.: Microcirculation during degenerative processes      85

2006). To estimate the number of capillaries, it is neces-

sary to have an unambiguous definition of a single capil-

lary. In accordance with the theories of capillary growth

and their general topology (Ausprunk and Folkman, 1977;

Patan et  al., 1992), the capillary network is considered

to be a node-segment network. A node is a place where

Figure 1 Sampling histological sections and quantification of microvessels.

(A) A mouse cerebellum that was sliced at regular uniform intervals for systematic random sampling of the tissue sections. (B) A sagittal

section through the mouse cerebellum. The systematic random sampling of microscopic imaging fields using predetermined and constant

xy steps is demonstrated. The area of the sampling fraction is equal to the frame area a(frame) divided by the area associated with each

sample step a(x, y step). (C) A microscopic imaging field of the cerebellum cortex with an unbiased counting frame. The vessels that are to

be counted are marked by a green dot and those excluded from the count are marked by a red dot. (D)–(F) One of the microscopic image

fields of the molecular layers of the cerebellum cortex that was prepared as a stack of three 5-µm-thick optical sections in the z axis, which

represents a disector volume probe. The nodes marked green are to be included in the count, and the valence of the nodes (n) is indicated

near the corresponding dots. The sections were immunohistochemically labeled with laminin antibodies that were visualized using horse-

radish peroxidase/diaminobenzidine (dark brown) and were counterstained using hematoxylin. Scale bar: 500 µm (B), 20 µm (C–F).

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86      Y. Kolinko et al.: Microcirculation during degenerative processes

a blood vessel branches. The capillary is consequently

defined as a loop created between two nodes of the vas-

cular network. To calculate the number of loops, it is

necessary to determine the connectivity of the capillary

network. The number of loops in the reference space is

indirectly calculated from the number and valence of the

nodes using the following equation:

2* 1,

2ref n

nN P

−= + ∑

where Nref

is the number of capillaries per reference

volume and Pn is the number of nodes of valence n. The

valence of a node depends on the number of vessel seg-

ments that join at the node. The unit is included because it

is not dependent on the presence of nodes in the reference

volume because even every small pieces of tissue contain

at least one capillary (Løkkegaard et al., 2001). The total

number of vessels is calculated by multiplying the inverse

sampling fraction by the number of capillaries in the final

sample.

Another relevant method used in many stereological

studies is analysis of the capillary length (Løkkegaard

et al., 2001; Mayhew, 2005; Eržen et al., 2011; Qiu et al.,

2011; Kubínová et al., 2013; and others). Depending on

the imaging technique utilized, the following methods

of determining the capillary length density can be used:

the interactive “tracer” method for length measure-

ment that is based on a manual delineation in 3D of the

axes of the capillary (Kochová et al., 2011; Tonar et al.,

2011: Kubínová et  al., 2013), and determination of the

expected (or average) number of intersections between

linear features of interest in SURS planes (Smith and

Guttman, 1953).

The method most widely used in stereological practice

is determining the length of vessels in probability of their

intersection by equidistant slices. The basic requirement

for using this method is preparing the tissue according to

the isector or orientator techniques (Mattfeldt et al., 1990;

Nyengaard and Gundersen, 1992). Under these conditions,

the length density will be equal to double the number of

vessel profiles per unit area of the section (Smith and

Guttman, 1953; Mayhew, 2005; Eržen et al., 2011; Mühlfeld

et al., 2013; and others).

The length density has been used to estimate the total

length of the capillaries in different subdivisions by multi-

plying its value by the investigational volume (West et al.,

1991; Løkkegaard et al., 2001).

The tortuosity (C) of the circulatory system can

be measured as a ratio; for example, simple tortuos-

ity between branching points can be calculated by

determining the vessel length between branches (AL)

and then selecting the shortest distance between these

branches (ML) (Hart et al., 1997). This method is optimal

for short vessels that have the classic arc shape. Another

method of computing the tortuosity of an entire vessel is

to weigh the tortuosity of each constituent segment by the

fraction of the arc length that the segment contributes to

the vessel (Hart et al., 1997). The equation for determin-

ing the tortuosity of the capillary network is shown below

(Enomoto and Okura, 2013; Kalitzeos et al., 2013):

2

s

s

s

AL*

ML,

ML

D

C

=∑

where ALs and ML

s are the length of segment and the

shortest distance between the extreme points, respec-

tively, and Ds is the height of segment’s arches defined by

a vector that perpendicularly connects the tangent to the

arc and the MLs. This method is suitable for long vessels

and capillaries that have two or more bends.

After the tissue processing is complete, the mean

amount of shrinkage of the tissue can reach approxi-

mately 65% (Burke et al., 2009), depending on the fixa-

tion method, the method used to dehydrate the tissue

block, and the temperature used for the paraffin embed-

ding. The failure to convert density estimates to the

total volume of the organ can often lead to erroneous

conclusions collectively known as the “reference trap”

(Brændgaard and Gundersen, 1986). These dangers can

be avoided by simply defining the quantity of all of the

vessels in the absolute volume of each organ under study

(Mayhew et al., 2003).

Conclusions

Our review showed that each individual NDD is charac-

terized by particular morphological features of changes in

the bloodstream. Most of these changes are secondary but

create a vicious cycle of pathogenesis.

Unfortunately, the heterogeneity of the methods used

in the published studies prevents us from clearly and

quantitatively describing the microvascular changes. The

problem is that the authors often used bias-prone and not

optimal approaches to obtain quantitative data or that the

method of data acquisition or processing has been insuffi-

ciently described. These factors and the variability of used

methods lead to contradictory results in studies of the

same disease. Thus, many aspects of the microvasculature

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Y. Kolinko et al.: Microcirculation during degenerative processes      87

changes in NDDs need to be reevaluated using the princi-

ples of unbiased stereology.

Despite the abundance of studies of the microvascu-

lature changes, an enormous amount of information is

still missing. For instance, there is a lack of studies of the

microvasculature in spinocerebellar ataxias that repre-

sent a broad heterogeneous group of diseases, and vari-

ability in the microvasculature changes, if any, could be

one of the components underlying their heterogeneity.

Furthermore, quantitative analysis of the perfusion of

various brain regions in mental illnesses, chronic alcohol

consumption, and multiple sclerosis would be of interest.

We believe that in-depth studies of the changes in

the blood supply of the brain that occur in NDDs will

improve therapeutic efficacy. Knowledge of the role of

microvasculature abnormalities in the pathogenesis of

NDDs is crucial for clinical applications. If the pathology

of the vessels plays an active role in the progression of the

disease instead of being only a secondary and subsidiary

phenomenon, it might be reasonable to target it therapeu-

tically. The experimental induction of microvasculature

changes, followed by the observation of the subsequent

changes in the brain tissue in animal models, would facili-

tate understanding the relationship between vessel injury

and the response of the brain tissue. Experimental treat-

ments to prevent or revert the changes in the microvascu-

lature are the next step in the translation of the research

to the clinic. Particular attention should be paid to the

BBB and its functionality because its failure has a strong

impact on the brain tissue.

The efficacy of the blood supply could also be impor-

tant for the performance of the endogenous regenerative

mechanisms of brain tissue and for brain plasticity. Brain

regeneration is insufficient to provide significant func-

tional improvement after brain injury. Brain plasticity,

however, can improve deteriorated functionality. Further-

more, therapy based on stimulating brain regeneration or

on substituting stem cells is under intensive investigation

and holds promise for the future. The fate of grafted cells

as well as endogenous neurogenesis is strongly depend-

ent on the neurogenic capacity of the nervous tissue

(Rossi and Cattaneo, 2002), which may be influenced by

perfusion of the tissue. Therefore, the state of the micro-

vasculature could also be important for the efficacy of

regeneration-based therapy, e.g., neurotransplantation

and trophic-factor delivery.

Acknowledgments: This review was supported by project

ED2.1.00/03.0076 from the European Regional Develop-

ment Fund and the Charles University Research Fund

(project number P36).

Competing interests: The authors declare that they have

no competing interests.

Author contributions: The first two authors performed

the literature search and wrote the manuscript. The last

three authors contributed equally to the generating ideas,

general editing, and commenting on the text. The final

manuscript preparation was conducted by the first author.

All authors read and approved the final manuscript.

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