mri-based computational modeling of fibrotic substrate in ... · matt halim junior farzana...
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MRI-Based Computational Modeling of Fibrotic Substrate in
Cryptogenic Stroke (ESUS)PATRICK BOYLE • UNIVERSITY OF WASHINGTON
Western AFib Symposium • February 29, 2020
•Conventional wisdom:•Fibrosis exacerbates AFib•AFib increases stroke risk
•Alternative hypothesis:•Fibrosis directly increases stroke risk, regardless of whether patient has AFib
•ESUS patients have extensive atrial fibrosis but no arrhythmia
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Atrial Fibrosis, AFib, and Stroke
AMA Ed Hub: Stroke Prevention in Atrial Fibrillation
•10 ESUS patients had LGE-MRI post-stroke
•Full workup including 30+ days monitoring prior to recruitment
•Comparison to controls from UW database
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Pilot Study at UW (Nazem Akoum)
K Tandon, [...] N Akoum (2019) Neurology 93(4):e381-7
•No difference in LA fibrosis burden between ESUS and AFib groups
•Both were significantly more fibrotic than Ctrl
•LA fibrosis by quartile was the only variable associated with ESUS
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Atrial Fibrosis in ESUS Patients
Unexpected!
Data from LGE-MRI
K Tandon, [...] N Akoum (2019) Neurology 93(4):e381-7
•Which ESUS patients will have recurrent stroke?
•Not feasible with current computational tools (yet)
•Which ESUS patients will have incident AFib?
•If ESUS patients have so much fibrosis, why don’t they have AFib?
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
How can modeling & simulation help?
•Possibility #1: something is fundamentally different about fibrotic substrate
•e.g., spatial pattern•Possibility #2: fibrotic substrate is the same but there is a lack of triggers
•Simulations can help clarify this ambiguity!
State-of-the-Art in Atrial EP Modeling
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Late Gadolineum Enhancement (LGE)-MRI
S Zahid*, H Cochet*, PM Boyle*, [...] NA Trayanova (2016) Cardiovasc Res
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
EP model parameterizationNon-fibrotic myocardium: human atrial model w/ changes for “chronic” AFib
Fibrotic myocardium: altered EP due to fibrotic remodeling (impaired excitability and conduction) mediated by TGF-β1
S Zahid*, H Cochet*, PM Boyle*, [...] NA Trayanova (2016) Cardiovasc Res
Evolution of Vm(t) Map of activation times
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Computational “substrate stress test”
Phase singularities of reentrant driver
For this individual, this region within the fibrotic substrate
has the necessary properties to initiate & sustain persistent
reentrant driver activity
S Zahid*, H Cochet*, PM Boyle*, [...] NA Trayanova (2016) Cardiovasc Res
Each patient has a subset of regions within the fibrotic substrate that are significantly more likely to harbor AF-sustaining reentrant drivers
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Key insight from our mechanistic studies
Example: n = 4 pro-RD regions
1
2
3
4
S Zahid*, H Cochet*, PM Boyle*, [...] NA Trayanova (2016) Cardiovasc Res
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Substrate stress test for ESUS
AFib LGE-MRI scans (n = 45)UW only (pre-ablation, first timers)
ESUS LGE-MRI scans (n = 45)UW + Klinikum Coburg
•Fully automated workflow for reconstructing bi-layer models of the left atrium
•Feasible to go from segmented images to results in ~3-4 hours
•In ESUS patients with fibrotic atria, does the substrate stress test show reentrant drivers?
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Simplified atrial modeling frameworkModel from ESUS LGE-MRI
ESUS (n = 45) AFib (n = 45)
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS [email protected]
ESUS (n = 45) AFib (n = 45)
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
In some models (both ESUS + AFib) rapid atrial pacing induced reentry
ESUS (n = 45) AFib (n = 45)
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
In others, pacing never engaged the substrate (n = 15 sites per model)
ESUS (n = 45)
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Ree
ntry
No
Ree
ntry
AFib (n = 45)
22/45 ESUS models were inducible (48.9%)29/45 AFib models were inducible (64.4%)
Within inducible models, was fibrosis different?
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Reentry inducibility and atrial fibrosis
Inducible despitelow fibrosis
Non-inducible despite high fibrosis
Atr
ial f
ibro
sis
(%)
n = 29 n = 22
n = 16 n = 23
# reentry-inducing pacing sites # distinct reentrant drivers
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Arrhythmia dynamics: ESUS vs. AFib
[email protected] Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Mechanistic Implications•Possibility #1: something is fundamentally different about fibrotic substrate
•Possibility #2: fibrotic substrate is the same but there is a lack of triggers
NOT SUPPORTED
SUPPORTED
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Atrial Fibrosis in ESUS PatientsKey Takeaways from Computational Modeling & Simulation
Fibrotic substrate in ESUS has same capacity to
sustain reentry as in AFib“Absence of triggers”
hypothesis is supportedArrhythmogenic substrate was more prevalent in AFib
Visit our poster at [email protected]
Western-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients
Atrial Fibrosis in ESUS PatientsKey Takeaways from Computational Modeling & Simulation
Fibrotic substrate in ESUS has same capacity to
sustain reentry as in AFib“Absence of triggers”
hypothesis is supportedArrhythmogenic substrate was more prevalent in AFib
Visit our poster at [email protected]
Savannah BifulcoBioE PhD Student
The Cardiac Systems Simulation (CardSS) Lab
Zih-Hua(Amber) Chen
MS student
SavannahBifulco
PhD student
KirstenKwanJunior
PatrickBoyle
PI
GriffinScott
Sophomore
KellyZhang
Sophomore
AlexOchs
PhD student
MattHalimJunior
FarzanaMohamedali
Senior
• Funding: AHA SDG16-30440006 (Boyle), NIH U01-HL141074 (Trayanova)• Collaborators: Nazem Akoum, Arun Sridhar (UW Cardiology), Juan Carlos del Alamo
(UW Mech E), Chuck Murry (UW BioE/Pathology), Natalia Trayanova (JHU BME), Edward Vigmond (Bordeaux), Steven Niederer (King’s College London)
• Coburg ESUS MRI team: Christian Mahnkopf, Peter Kuhnlein, Marcel MitlacherWestern-AF: Computational Modeling of Fibrotic Substrate in ESUS Patients https://cardsslab.org/
ChelseaGibbs
PhD student
Cartoonist!