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Modeling Left Atrial Flow, Energy, Blood Heating Distribution in Response to Catheter Ablation Therapy

Dillon-Murphy, Desmond (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
Marlevi, David (author)
Karolinska Institutet,KTH,Medicinsk avbildning
Ruijsink, Bram (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
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Qureshi, Ahmed (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
Chubb, Henry (author)
Stanford Univ, Dept Cardiothorac Surg, Palo Alto, CA 94304 USA.
Kerfoot, Eric (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
O'Neill, Mark (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
Nordsleffen, David (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
Aslanidi, Oleg (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
de Vecchi, Adelaide (author)
Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England.
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Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England Medicinsk avbildning (creator_code:org_t)
2018-12-14
2018
English.
In: Frontiers in Physiology. - : Frontiers Media S.A.. - 1664-042X. ; 9
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Introduction: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that commonly affects the left atrium (LA), causing it to quiver instead of contracting effectively. This behavior is triggered by abnormal electrical impulses at a specific site in the atrial wall. Catheter ablation (CA) treatment consists of isolating this driver site by burning the surrounding tissue to restore sinus rhythm (SR). However, evidence suggests that CA can concur to the formation of blood clots by promoting coagulation near the heat source and in regions with low flow velocity and blood stagnation. Methods: A patient-specific modeling workflow was created and applied to simulate thermal-fluid dynamics in two patients pre- and post-CA. Each model was personalized based on pre- and post-CA imaging datasets. The wall motion and anatomy were derived from SSFP Cine MRI data, while the trans-valvular flow was based on Doppler ultrasound data. The temperature distribution in the blood was modeled using a modified Pennes bioheat equation implemented in a finite-element based Navier-Stokes solver. Blood particles were also classified based on their residence time in the LA using a particle-tracking algorithm. Results: SR simulations showed multiple short-lived vortices with an average blood velocity of 0.2-0.22 m/s. In contrast, AF patients presented a slower vortex and stagnant flow in the LA appendage, with the average blood velocity reduced to 0.08-0.14 m/s. Restoration of SR also increased the blood kinetic energy and the viscous dissipation due to the presence of multiple vortices. Particle tracking showed a dramatic decrease in the percentage of blood remaining in the LA for longer than one cycle after CA (65.9 vs. 43.3% in patient A and 62.2 vs. 54.8% in patient B). Maximum temperatures of 76 degrees and 58 degrees C were observed when CA was performed near the appendage and in a pulmonary vein, respectively. Conclusion: This computational study presents novel models to elucidate relations between catheter temperature, patient-specific atrial anatomy and blood velocity, and predict how they change from SR to AF. The models can quantify blood flow in critical regions, including residence times and temperature distribution for different catheter positions, providing a basis for quantifying stroke risks.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Fysiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Physiology (hsv//eng)

Keyword

left atrium
computational fluid dynamics
atrial fibrillation
thermal modeling
catheter ablation

Publication and Content Type

ref (subject category)
art (subject category)

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