models of ischemic stroke e. grenier umpa, crns umr 5669 ecole normale supérieure de lyon in...
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Models of ischemic stroke
E. Grenier
UMPA, Crns Umr 5669
Ecole Normale Supérieure de Lyon
In collaboration with
JP Boissel, MA Dronne (pharmacology, Lyon I)
M. Hommel (Grenoble hospital)
S. Descombres, G. Chapuisat (ENS Lyon)
G. Bricca (pharmacology, Lyon I)
D. Bresch (mathematics, Grenoble)
T. Dumont (mathematics, Lyon I)
Contents
• Introduction: what is an ischemic stroke ?
• Ionic models
• Spreading depressions and related mathematical models
• Global models
Introduction : medical aspects
• One of the main cause of mortality in developped countries.
• No satisfactory therapeutic solutions !
• Good therapeutics for Rat.
• Difference between Rat / Human
• Try to make mathematical models to understand better the situation
• Lots of different phenomena: ionic motions, oedema, blood flow, anatomy, apoptosis and necrosis …
Clinical aspects
• Cerebral artery get blocked:– Various causes
– Temporary or definitive
– Partial or total
– Various localisations
• Clinical manifestations:- Loss of mobility (arms, legs, …)
- Loss of language (aphasia), cecity
- Evolution within a few hours
- Finished in 6 – 12 hours
Medical aspects
• Imagery:– Angiography (arteries map)
– Oedema (cell swelling: fraction of extracellular space)
– Blood flow (with large errors)
• Drugs:- None !
- Except thrombolysis (reopening of the blocked artery)
- Only valid in 10 % of the cases
- Risk: oedema
Stroke developpement
• Three zones:– Ischemic core: blood flow is very low, all the cells die (loss of
ionic balance, cell swelling and explosion by necrosis)
– Penumbra: cell viability is borderline. Part of them die of necosis, part of apoptosis.
– Rest of the brain
• Phenomena:- Ionic exchanges leading to oedema
- Necrosis and apoptosis (programmed cell death)
- Spreading depression: progressive waves (Rat)
- Risk: oedema
Scanner X – IRM
37 years old female: hemiplegia and aphasia. Scanner 4h30 after stroke
IRM diffusion + ARM
FLAIRFLAIR DWIDWI ARMARM
ROI sylvien profond
ROI sylvien superficiel
IRMBlood flow images
Recuperation of aphasia 4 days after stroke
FLAIRFLAIR DWIDWI ARMARM
J4
Penumbra = diffusion - perfusion
I. Models of ionic exchanges
• Main ions:– K+, Na+, Cl-, Ca2+, glutamate– Difference between intra and extracellular
concentrations:• K+: extra 4 mM/l, intra: 140 mM/l• Na+: extra 120 mM/l; intra: 12 mM/l• Ca2+: extra 1mM/l, intra: < 1 micromol / l
– Membrane potential is different from 0: about -50 mV to -60 mV
– Energy is needed to maintain these gradients of concentrations.
• Ionic motions:– Through voltage dependent channels, which
open and close, depending on the various stimuli: KDR, NaT, …
– Through exchangers– Through pumps:
• ATP dependent
• Ions move against their electrochemical gradient.
– Very complex system !– During stroke: pumps are not efficient > ions
follow their gradients > depolarization of the cell > cell swelling (oedema) ….
Grey and white matters
• Grey matter: neurons centers, glial cells
• White matter: glial cells, axons of neurons
Models of ionic
exchanges in
Grey matter
Neuron(soma)
Astrocyte
Extracellularspace
3Na+
2K+
Ca2+Cl-
pump Ca2+
pump Cl-
Cl-Ca2+
pump Ca2+
pump Cl-
Ca2+Ca2+ voltage-gated channel (CaHVA)
Na+Na+ voltage-gated
channel (NaP)
K+ K+ voltage-gated channel (KDR, BK)
Ca2+Ca2+ voltage-gated channel (CaHVA)
Na+
Na+ voltage-gatedchannel (NaP)
K+
3Na+
Ca2+
exchanger Na+/Ca2+
Ca2+
3Na+ exchanger Na+/Ca2+
K+
gluNa+glu
Na+
K+ glutamate transporter
Na+
2Cl-K+
contransporterNa+/K+/Cl-
Cl-HCO3
-exchanger Cl-/HCO3
-
Cl-exchanger Cl-/HCO3
-HCO3
-
K+
Na+receptor
AMPAK+
Ca2+
Na+
K+
Na+
receptor NMDA
receptor AMPA
K+ voltage-gated channel (KDR, BK, Kir)
glutamate transporter
pump Na+/K+
3Na+
2K+pump Na+/K+
glu glu
Cl- Cl-extra currents extra currents
ATP ATP
Grey matter
gap-junctions
Difficulties• Very large number of components
• Very large number of parameters ( ~ 100)
• Very large indetermination on the parameters:– Difficulty to measure them in vivo
– Difference in vivo / in vitro
– Difference from one species to another
– Difference from one type of cell to another
• Models of channels depend on the author
• Some parts of the models come from thermodynamics, some don’t
• Conductivities vary much !
Hopeless ?• Putting together various pieces of models from various
authors completly fail !
• Indetermination on the coefficients by a factor 4 or more !
• What can we expect from numerical simulations in these conditions ?
• In many published models, coefficients are laking: impossible to check the models !
Strategy: looking for parametersCollect the various equations
Collect the various domains for the parameters
Choose at random parameters
Check basic properties:
Equilibrium, stability, general behavior
Not Satisfied
Satisfied
Keep the parameters
Strategy: testing an hypothesisFormulate the hypothesis
Test all the parameters found in the precedent phase
All tests positive
Hypothesis is coherent with the model and the parameters
Some tests negative
Hypothesis is not consistant with the model, or the models needs further studies to refine the parameters
0.2 0.4 0.6 0.8 1temps
0.2
0.4
0.6
0.8
1
pATP
0.2 0.4 0.6 0.8 1temps
0.2
0.4
0.6
0.8
1
pATP
10 20 30 40 50 60t
-100
-80
-60
-40
-20
nVm
10 20 30 40 50 60t
-100
-80
-60
-40
-20
aVm
10 20 30 40 50 60t
0.6
0.7
0.8
0.9
rADCw
10 20 30 40 50 60t
-100
-80
-60
-40
-20
nVm
10 20 30 40 50 60t
-100
-80
-60
-40
-20
aVm
10 20 30 40 50 60t
0.75
0.8
0.85
0.9
0.95
rADCw
Strong attack Moderate stoke
dead core penumbra
Simulation of a stroke
Evolution of the ionic concentrations
Strong attack
10 20 30 40 50 60t
100105110115120125130135
Kn
10 20 30 40 50 60t
0.10.20.30.40.50.6
Can
10 20 30 40 50 60t
2025303540455055Nan
10 20 30 40 50 60t
20
25
30
35
Cln
10 20 30 40 50 60t1.75
22.252.52.75
33.253.5glun
10 20 30 40 50 60t
100105110115120125130135
Ka
10 20 30 40 50 60t
0.10.20.30.40.50.6
Caa
10 20 30 40 50 60t
2025303540455055Naa
10 20 30 40 50 60t
20
25
30
35
Cla
10 20 30 40 50 60t1.75
22.252.52.75
33.253.5glua
10 20 30 40 50 60t
20406080100120
Ke
10 20 30 40 50 60t
0.51
1.52
2.5
Cae
10 20 30 40 50 60t
20406080100120140Nae
10 20 30 40 50 60t
146147148149150Cle
10 20 30 40 50 60t
0.51
1.52
2.53
3.54glue
Coherent with experimental results
Study of the action of various neuroprotectors
• NaP channel blockers– Fosphénytoine (Pulsinelli, 1999)
• CaHVA channels blockers– Nimodipine (VENUS, Horn et al., 2001)– Flunarizine (FIST, Franke et al., 1996)
• NMDA receptors antagonists– Selfotel (Morris et al., 1999)– Aptiganel (Albers et al., 2001)
Good results on rats, but no results (even toxicity) for Man Clinical studies have been stopped
Simulation of the action of a NaP channel blocker
10 20 30 40 50 60t
-100
-80
-60
-40
-20
nVm
10 20 30 40 50 60t
-100
-80
-60
-40
-20
aVm
10 20 30 40 50 60t
0.8
0.85
0.9
0.95
rADCw
10 20 30 40 50 60t
-100
-80
-60
-40
-20
nVm
10 20 30 40 50 60t
-100
-80
-60
-40
-20
aVm
10 20 30 40 50 60t
0.75
0.8
0.85
0.9
0.95
rADCw
fig. 1 : potential and rADCW without neuroprotector
fig. 2 : values with a blocker introduced at t = 20 min
Positive effect (Man and animal) in a moderate stroke
Simulation of the action of a NaP channel blocker
Positive effet, for any residual ATP.
Values of rADCw with and without blcoker as a function of residual ATP production (Rat)
0.2 0.4 0.6 0.8 1pATP
0.5
0.6
0.7
0.8
0.9
1
rADCw
avec bloq NaP
sans bloqueur
Comparison human/animal
Values of rADCw (1h after stroke and addition of a NaP channel blocker at t = 20 min) as a function of residual ATP production.
Effect is more important in Rat that in human, whatever the residual ATP production is.
0.2 0.4 0.6 0.8 1pATP
0.5
0.6
0.7
0.8
0.9
1
rADCw
homme
animal
Simulation of the action of a KDR blocker
Values of rADCw with and without a NaP channel blocker, as a function of residual ATP production.
Negative effet of any KDR channel blocker.
0.2 0.4 0.6 0.8 1pATP
0.5
0.6
0.7
0.8
0.9
1
rADCw
avec bloq KDR
sans bloqueur
Effets of other pharmacological agents
blocker type Effect
KDR channel blocker -
BK channel blocker =
Kir channel blocker =
NaP channel blocker +
CaHVA channel blocker +
Na/Ca exchanger +
Glutamate transport +/-
Na/K/Cl transport +
NMDA receptor +
Results are coherent with experimental observations
Hints for new drugs
Drugs that may reduce ischemic damages in grey matter:
– blocker of the inversion of Na/Ca exchanger
– blocker of the inversion of the glutamate transport
– blocker of transporteur Na/K/Cl transport
Some of these agents are currently under test.
White matter
Neuron(axon)
Oligo-dendrocyte
Extracellularspace
3Na+
2K+
Ca2+Cl-
pump Ca2+
pump Cl-
Cl-Ca2+
pump Ca2+
pump Cl-
Ca2+Ca2+ voltage-gated channel (CaHVA)
Na+Na+ voltage-gated
channel (NaP)
K+ K+ voltage-gated channel (KDR, BK)
Ca2+Ca2+ voltage-gated channel (CaHVA)
Na+
Na+ voltage-gatedchannel (NaP)
K+
3Na+
Ca2+
exchanger Na+/Ca2+
Ca2+
3Na+ exchanger Na+/Ca2+
K+
gluNa+
gluNa+
K+ glutamate transporter
Na+
2Cl-K+
contransporterNa+/K+/Cl-
Cl-HCO3
-exchanger Cl-/HCO3
-Cl-
exchanger Cl-/HCO3
-HCO3
-
K+
Na+receptor
AMPA
K+ voltage-gated channel (KDR, BK, Kir)
glutamate transporter
pump Na+/K+
3Na+
2K+pump Na+/K+
glu glu
Cl- Cl-extra currents extra currents
White matter
ATP ATP
Ca2+
Comparison of a stroke in white and grey matters
Values of rADCw 1 hour after stroke as a function of residual production of ATP in grey and white matter
0.2 0.4 0.6 0.8 1pATP
0.5
0.6
0.7
0.8
0.9
1
rADCw
SB
SG
White matter is more resistant
II. Spreading depressions
• Ionic exchanges : reaction term
• Ions diffuse in extracellular space
• Ions diffuse through « gap junctions » (small holes in the membranes of cells).
Reaction diffusion equations in the center of the model
Are there travelling waves ? YES: spreading depressions
• observed in various species: rat, chicken, …
• observed during stroke in rats
• conjectured in man during migraine with aura
Spreading depression
In Rat cortex
• Injection of KCl in some part of the brain
• At injection point, depolarization of the cells
• Depolarization propagates 2 – 4 mm / min
• Recovery after depolarization
• Progressive wave: depolarization wave
• Two waves do not cross
Spreading depression
Occurs in • Migraine with aura
– Starts in visual areas– Stop at different locations, depending of the patients– Speed of a few mm / min
• Strokes in rat– Created at the border of the dying area– Propagate in the penumbra – Exhausts cells in the penumbra – Final size of the dead zone is proportionnal to the number of
spreading depressions which propagate.
• No evidence during stroke in human.
Spreading depression: simple model
Simple model through a bistable reaction diffusion equation
∂t u – ν∂Δ u = f(u)
with f bistable
f(u) = a u (1 – u) (u – u0)
u state variable:
• u = 0 in normal state
• u = 1 in completly depressed state
Parameters: ν (diffusion), a (strength of nonlinearity), u0
(0 < u0 < 1).
Spreading depression: classical questions
For such bistable reaction diffusion equations
∂t u – ν∂Δ u = f(u)
f(u) = a u (1 – u) (u – u0)
• Existence of progressive waves is well known:– In cylinders
– In cylinders, with transport terms ..;
• Behavior in domains with holes (Beresycki, …)
Spreading depression: grey substance
Here bistable f(u) only takes place in grey matter
∂t u – ν∂Δ u = f(u)
where: in grey matter
f(u) = a u (1 – u) (u – u0)
in white matter
f(u) = - b u
And the domain Ω is
The domain Ω
May the topography stop waves ?
• Propagation of progressive waves in a cylinder with variable radius
Ω = { (x,y) | || y || < R(x) }
with for instance
R(x) = R si x < 0
R(x) = R’ si x > 0
or
R(x) = R + R’ sin(x)
• Propagation in real geometries ?
May the topography stop waves ? Yes
Work with G. Chapuisat (to appear in C.P.D.E.).
Case R(x) = R for x < 0 and R’ for x > 0
Theorem: for some sets of coefficients, travelling waves coming from - ∞ are stopped near x = 0. They do not
go to + ∞ as time goes to + ∞
Proof relies on careful construction of supersolutions.
The domain Ω in ischemic stroke
The domain Ω for migraine with aura
Numerical computation: Rolando sulcus
Simulation for Rolando sulcus
Discussion
• Topography of grey matter may explain by itself that spreading depression do not propagate in the whole brain during migraine with aura– Shoud be verified on larger 2D cuts of brain
– Should be verified in 3D (difficult numerical challenge !)
– Should be verified on more complete ionic models (link with Ca channels)
• Topography of grey matter may explain why spreading depressions have never been observed during stroke– Should also come from experimental difficulties
– Observed in vitro on small cuts of grey substance (coherent)
• Big difference with Rat !
III. Global models of stroke
Very large models, combining
• Ionic models:– Simple bistable equations– Complete ionic model of the first section
• Oedema models• Blood flow• Death of cells (apoptosis / necrosis)
– Programmed cell death : a kind of cell suicide
• Energy management• Topography• Toxicity
Typical simulation
Dead zone Spreading depressions
Influence of diffusion / apoptosis / toxicity
Influence of diffusion / apoptosis / toxicity
Spreading depressions
• In Rat, spreading depressions are observed in vivo– Important in the progression of the dead core
– Important to try to block them
• In human, no spreading depressions are observed at large scales– Coherent with previous section
– Remains to be checked numerically on the whole model
– Explains failures of some therapeutics ?
• Existence of spreading depressions for very small strokes ?– Stroke in young men
– Trace of the propagations of spreading depressions ?
Perspectives
• To complete model– Include complete ionic model
– Add free radicals
– Realistic 2D geometries (in progress)
– Realistic 3D geometries (very challenging)
• To compare with clinical cases– Basis of clinical images already set up
• Numerical challenges– Very different time scales (from 1ms to 12h)
– Very complex topography (already in 2D, … 3D …)
– Very expensive !