iii flow effects on thrombogenesis: insights from computational...
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Flow Physics & Computation Lab engineering.jhu.edu/fsag
III
Flow Effects on Thrombogenesis: Insights from Computational Models
Rajat Mittal & Jung Hee Seo
Mechanical Engineering
Thura Abd & Richard George Division of Cardiology
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Formation of Blood Clots in the Heart
• Clot (thrombus) formation flow statis
• Normal ventricles – Ejection fraction ~55% – Avoids flow statis (How???)
• Conditions associated with cardiac thrombus formation – Myocardial infarction (MI) – Heart failure – Arrhythmias – Cardiomyopathies – …
• Clinical significance
– Thomboembolic risk
2
LA
(Rehan et al. Cardiovascular Ultrasound, 2006 )
Platelets + Fibrin +…
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Post MI Thrombus Formation
• Patients recovering from MI are generally at higher risk of LVT formation – 720K MIs/yr in the US – Thrombus located in apical region
• Reduced ejection fraction (<40%) • Apical Akinesia/Dyskinesia • Ventricle remodeling • Hypercoagulable endothelium – Tissue factor pathway
3
LV
LVT
LV
AN
LA AO Apical Akinesia/Dyskinesia
+Apical Aneurysm
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LVT Risk Stratification & Therapy
• Risk criteria – Antero-apical STE-MI (250K/yr) – EF < 30%
• Implication
– Only 1/10 people who currently receive ‘triple’ therapy in US are actually at risk of LVT formation
– ½ patients receiving triple therapy are at high risk of bleeding.
• Better risk stratification metrics are needed.
• LVT risk determined by a complex coupling between flow dynamics and coagulation biochemistry.
4
• Antithrombotic Therapy – Anticoagulants – Anti platelet – Blood thinners Stroke Vol
End Dias. Vol EF=
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Stratification of LVT Risk?
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0Ej
ectio
n Fr
actio
n
CMP Group
NORMAL Group
LVT Group
Group N Description
LVT 25 Patients with diagnosed LVT
CMP 25 Severe cardiomyopathy; no LVT
NORMAL 25 Normal
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Approach
6
Computational Modeling
Patient Studies
Imaging
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Modeling Approach
Computational Hemodynamics
Biochemistry of
Coagulation
Patient Physiology
• EF, Stroke Volume • LV Geometry & Kinematics • Infarct Size & Location
• Tissue Factor Release • Thrombin Production • Platelet activation • Fibrin polymerization
• LV Flow Patterns • Flow Stasis • Transport of CC biomolecules
Understand how flow mediates coagulation in infarcted LVs
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Coagulation Cascade
8
• Extrinsic (Tissue-factor) Pathway • Damaged wall expose tissue
factor (TF) • TF-VIIa initiates reactions • Produce Thrombin • Thrombin activates other factors • Burst of Thrombin Production
TF
VIIa Active TF
IIa
IIa
IX
IXa
X Xa
VIII
VIIIa
IXa:VIIIa
V
Va
Xa:Va II
IIa
Prothrombin
Thrombin
Xa
Xa Damaged Wall
LV
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Role of Thrombin
9
Thrombin • activates platelets • converts fibrinogen to fibrin
(Angiolillo et al, European Heart J, 2009)
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TF Thrombin Coagulation Cacade (CC)
10
IX
IX : TF : VIIaIXaXX : TF : VIIaXaVIIIa : IXaX : VIIIa : IXaVVaVIIIVIIIa
(Thrombin)II (Pro-thrombin)Va : XaII :
IIa
Va :
TF : VIIa
XamIIa
18 Species
6 11
16
6 12
17
6 13
18
15
1
3
k k
k
k k
k
k k
k
k
k
k
IX IX : TF : VIIa IXa
X X : TF : VIIa Xa
X VIIIa : IXa X : VIIIa : IXa VIIIa : IXa Xa
IX Xa Xa IXaV Xa Xa Va
TF : VIIa TF : VIIa
TF : VIIa TF : VIIa
VIII Xa Xa VIIIaIIaV
→+ → +←
→+ → +←
→+ → +←
+ → +
+ → +
+ → +
+ 2
4
6 14
19
9
7
9
8
10
k
k
k k
k
k
k
k
k
k
VaVIII VIIIa
II Va : Xa II : Va : Xa Va : Xa mIIa
mIIa Va : Xa Va : Xa
VIII
IIa
a IXa
IIa IIa
II
VIIIa : IXa
Va Xa Va Xa
a
:
→ +
+ → +
→+ → +←
+ → +
→+ ←
→+ ←
Reactions (Biasetti et al, 2012)
2( )ii i i
i j
C U C D C Rt
R r
∂+ ⋅∇ − ∇ =
∂= ⋅S
(18 Eqs.)
D ≈ 1e-8 (m2/s) S: Stoichiometric Matrix rj: Reaction rate
Initial concentrations (mol/m3)
IX X
V VIII
VIIIa II
C 9e 5; C 1.7e 4C 2e 5; C 7e 7C 1e 11; C 1.4e 3
(Pro-thrombin)
= − = −= − = −= − = −
TF:VIIa,wallC : Prescribed on infarct
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Platelet Activation and Deposition
11
, , 1 ,2
,( () )m u m u P m u m uPT U PT D APTt
IIa PT∂= − ⋅∇ + ∇ −
∂
2, , ,
, max ,
,
,
1(
( )( ) (
( ) )
)adh a b m a coh b
m a m a P m a
m
m
a
u
k
PT U PT D P A IIa PT
h x PT PT PT k g PT PT
Tt∂
= − ⋅∇ + ∇ +
− − − ⋅∂
⋅
, max , ,( )( ) ( )adh a b m a coh bb m ak h x PT PT PT k g PTt
PP T T∂= − +
∂⋅
(Leiderman and Fogelson, 2011)
Inactivated, mobile
Activated, mobile
Bound
Activation by Thrombin
Activation by Thrombin
Adhesion to wall Cohesion to bound platelets
Adhesion to wall Cohesion DP≈1e-9 (m2/s)
1( )*
=+IIa
IIaIIa
CA IIa kC C
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Polymerization of Fibrinogen Fibrin
12
2( )f f f t fC U C C CDt
k∂= − ⋅∇ + ∇ −
∂
2 2( ) tm fm p mmC U C D C Ct
k C k∂= − ⋅∇ + +∇ +
∂
Fibrinogen
Fibrin (Monomer)
=+
cat IIat
m f
k CkK C
Conversion by Thrombin
1
3 3
2 3 -1 -1
3 3,0
84s7.2 10 mol/m
8.2 10 (mol/m ) s
9 10 mol/m
−
−
−
=
= ×
= ×
= ×
cat
m
p
f
kKk
C(Neeves et al. 2010, Biophysics J)
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Canonical Models- Comparative Study Design
13
Infarcted/Aneurysm
LV
AN
Normal
LV
AN
LV
LA
Large Aneurysm Small Aneurysm
Damaged wall due to the acute infarction
Case ESV (mL)
EDV (mL)
SV (mL)
EF (%) AN
A 105 167 62 37 L
B 105 146 41 28 L
C 70 111 41 37 S
D 70 97 27 28 S
E/A=1.2, HR=60 BPM
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Clinical Translation?
14
Damaged wall
0( )NW NW wd U H d ddt tτ τ∂ = + ⋅∇ = − ∂
• What flow metric can be used for the LVT risk prediction – Quantified correlation between flow metrics and coagulation – Could be obtained from echo PI or CMR
Residence Time (RT) -How long blood volume stays in ROI -Near damaged Wall Residence Time (NWRT) -Decreased flow strength leads to high NWRT
Marsden et al.
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Predicted Thrombogenic Risk
15
SV=62 mL, EF=37% SV=41 mL, EF=28% SV=41 mL, EF=37% SV=27 mL, EF=28%
Fibrin concentration (µmol/m3)
Risk: Low
Risk: High
Risk: Moderate
Risk: High
Peak:1e-5 Mean:3e-7
Peak:15 Mean:0.016
Peak:0.05 Mean:3e-4
Peak:0.5 Mean:0.012
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Average Surface Distributions
16
SV = 41 mL EF = 37 %
SV = 27 mL EF = 28 %
Thrombin (µmol/m3)
NWRT (sec)
Bounded Platelet (PTb/PTmax)
Hemodynamic Coagulation Small Aneurysm Cases
Distributions on the (damaged) aneurysm wall
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Patient-Specific Model from Multimodal Data Registration
Dynamic 4D CT scan
Segmented/Reconstructed Model
Mitral inflow Doppler Outflow tract Doppler
Patient: SV=84 mL, EF=47% Apical Aneurysm Apical Akinesia
time
Q[m
L/s
ec]
0 0.2 0.4 0.6 0.8 1
-200
0
200
Reconstructed LV Flow Profile
E-wave A-wave
Systole Nearly automated Procedure!
Infarct Indentification
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Chemo-Fluidic Interaction
Vortex Dynamics
Mixing and Washout
192x192x256 (9.4M) grid points
Time averaged flow and thrombin accumulation
Evolution of flow and thrombin
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Hemodynamics and Coagulation
19
Averaged flow and thrombin accumulation
LVT01 EDV=178 mL, EF=47%
LVT02 EDV=334 mL, EF=40%
LVT09 EDV=417 mL, EF=39%
Thrombin: 5e-4 µmol/m3 Thrombin: 1e-5 µmol/m3 Thrombin: 1e-6 µmol/m3
Inferior
Sept
al
Late
ral
Anterior
NWRT Bound PT Infarct NWRT Bound PT Infarct NWRT Bound PT Infarct
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NWRT as a Predictor for Thrombosis?
Case Correlation
SV=62 mL; EF=37% 0.61
SV=41 mL; EF=28%) 0.75
SV=41 mL; EF=37% 0.55
SV=27 mL; EF=28% 0.58
Correlation between NWRT and Bound PT
NWRT [sec]Th
rom
bin
[µm
ol/m
3 ]
0 0.5 1 1.5 2 2.5
0
0.1
0.2
0.3
0.4
0.5
CannonicalPatient-specific
Residence time of flow in the vicinity of the infarct is a key indicator of LVT risk. How to obtain a clinical measure of NWRT??
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Stratification of LVT Risk?
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
Ejec
tion
Frac
tion
CMP Group
NORMAL Group
LVT Group
Group N Description
LVT 25 Patients with diagnosed LVT
CMP 25 Severe cardiomyopathy; no LVT
NORMAL 25 Normal
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A New Metric for LVT Risk E-Wave Propagation Distance
Velocity = Time (VTI) Integral
E-Wave Propagation (EPI) = ( VTI / LLV ) Index
Group N Description
LVT 25 Patients with diagnosed LVT
CMP 25 Severe cardiomyopathy; no LVT
NORMAL 25 Normal EF, no cardiomyopathy
EPI = �< 1 → 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑖𝑖𝑤𝑤𝑖𝑖> 1 → 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑖𝑖𝑤𝑤𝑖𝑖
0.0
0.5
1.0
1.5
2.0
2.5
3.0
E-W
ave
Pene
trat
ion
Inde
x
CMP Group
NORMAL Group
LVT Group
LLV
Normal LVs High mixing and washout <1% of blood cells stay in ventricle for >5 cycles
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Cited Papers
• Seo, Jung Hee, Thura Abd, Richard T. George, and Rajat Mittal. “A Coupled Chemo-Fluidic Computational Model for Thrombogenesis in Infarcted Left Ventricles.” American Journal of Physiology-Heart and Circulatory Physiology (2016): ajpheart-00855. Published 25 March 2016 Vol. no. , DOI: 10.1152/ajpheart.00855.2015.
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