A patient with sustained monomorphic ventricular tachycardia developed a second tachycardia of incessant character with alternating RR-interval and alternating QRS-complexes after treatment with amiodarone. A retrograde His bundle deflection was recorded during the latter arrhythmia, that was induced as well with atrial as with ventricular stimulation. The "alternating" tachycardia could be explained by alternating bundle branch reentry and alternating conduction in the myocardium. This view is supported by the finding of an alternating mid-diastolic potential. This case report introduces a new electrocardiographic entity in the spectrum of wide QRS-tachycardias

Clement, Denis

François, Bart

Jordaens, Luc

English

Ghent University Academic Bibliography

Multiphysics modeling in support of ultrasonicimage development: integration of fluid-structureinteraction simulations and Field IIapplied to the carotid arteryAbigail SwillensGianluca De SantisPatrick SegersIBiTech-bioMMedaGhent University, Ghent, BelgiumEmail: abigail.swillens@ugent.beLasse LovstakkenDepartment of Circulation and Medical ImagingNTNU, Trondheim, NorwaySt. Olavs University Hospital, Trondheim, NorwayJoris DegrooteJan VierendeelsDepartment of flow, heatand combustion mechanicsGhent University, Ghent, BelgiumAbstract—Previously, we proposed a multiphysics model cou-pling computational fluid dynamics (CFD) and Field II, allowingassessment of the performance of current and new blood flowestimators (e.g. color flow imaging=CFI, PW Doppler, speckletracking, vector Doppler) in the carotid artery against groundtruth information retrieved from CFD. Important limitationshowever were the rigid walls and the absence of the arterialwall and surrounding tissue in the simulations. The aim of thisstudy was to improve and expand the model to a more realisticsetup of a distensible carotid artery embedded in surroundingtissue. For this purpose, we integrated fluid-structure interaction(FSI) simulations with an ultrasound simulator (Field II), whichallows comparison of the ultrasound (US) images with the inputdata from FSI. Field II represents tissue as random pointson which ultrasound waves reflect and whose position can beupdated based on the flow field and vessel wall deformationfrom FSI. We simulated the RF-signal of a patient-specific carotidbifurcation, including the blood pool as well as the vessel walland surrounding tissue. Realism of the multiphysics model wasdemonstrated with duplex images.I. INTRODUCTIONUltrasound imaging of the carotid artery is a common proce-dure when screening for cardiovascular disease, as the vessel isparticularly prone to atherosclerosis and easily accessible withultrasound probes. However, to reveal abnormalities in carotidflow and wall deformation with increased sensitivity andspecificity, improved imaging modalities are desired. Since in-vitro and in-vivo testing of new imaging algorithms are oftentoo simplified or lack ground truth information, ultrasonicimage simulation based on fully known and realistic vascularbehavior can be expected to support image development.In this context, we developed a multiphysical simulationenvironment which integrates advanced numerical methods tocalculate complex flow patterns and mechanical deformationson the one hand with an ultrasonic simulator on the otherhand. For the ultrasonic image modeling, we relied on theField II-software [1], [2], which can simulate with greatscanning flexibility images of arbitrary tissue (i.e. both bloodand arterial wall), by representing tissue as an ensemble ofpoint scatterers on which the ultrasound waves reflect. In a firstphase, we coupled computational fluid dynamics (CFD) withField II, allowing simulation of radiofrequency (RF)-data fromrealistic and complex flow fields, by moving the scatterersaccording to the spatially and temporally interpolated velocityfields obtained from CFD. We demonstrated the realism of thesimulation environment with color flow imaging and pulsedwave Doppler examples in the carotid artery [3] and byvalidating the simulation strategy on an in-vitro flow phantomof the carotid bifurcation [4]. Fundamental limitations of thisapproach were the absence of the vessel wall signal and therigid vessel walls.In a next phase, we integrated fluid-structure interaction(FSI) simulations with the ultrasound simulator [5], whichallowed to simultaneously assess the complex flow field andvessel wall deformation by coupling the numerical solutionof a dedicated flow solver and structural solver. Hence, anFSI-Field II integration offers the possibility to simultaneouslysimulate the RF-signal of the blood pool and the moving vesselwall. This, however, requires a much more complex couplingmethodology (derivation of the scatterer displacement) com-pared to the CFD-Field II coupling, due to the temporallyvarying fluid volume and the complex layered vessel wall, asexplained in [5]. We demonstrated this FSI-Field II couplingin a 3D straight tube, representative of the common carotidartery [5].In this work, we further advance the realism of the syn-thetic vascular imaging set-up with the simulation of the 3Dblood flow and arterial mechanics of a patient-specific carotidbifurcation model. The model includes the tissue surroundingthe vascular wall, which is a stabilizing factor for the fluid-structure interaction simulation but also results in a morerealistic ultrasonic visualization of the arterial territory. Theextensive methodology behind the FSI-Field II coupling willbe briefly discussed, before demonstrating the realism of ourFig. 1. Setup of the FSI-simulationsmultiphysics modeling with simulated duplex images.II. METHODSA. FSI-simulations1) Numerical approach: A partitioned FSI-approach wasfollowed, i.e. the equations for the flow and structural domainwere solved separately with a dedicated flow (Fluent 12.0.16,Ansys, Canonsburg, PA, USA) and structural solver (Abaqus6.7, Simulia,Inc., Providence, RI, USA). The solutions forthe fluid and structural domain were coupled using in-housecode (Tango) with Dirichlet-Neumann partitioning (the flowproblem is solved for a given displacement of the fluid-structure interface, and the structural problem is solved fora given stress distribution on the wet side of the structure). Aconverged solution for both the fluid and structural equations(and coupling conditions) was found by performing couplingiterations between both solvers, until equilibrium between thefluid and structure was reached. To enhance convergence of thecoupling iterations, an Interface Quasi-Newton (IQN) methodwas used [6]. Note that the fluid and structural domain haveinherently different grid formulations, which was solved byusing an Arbitrary Lagrangian Eulerian (ALE) method forthe fluid domain. For more information on the IQN and ALEmethod, we refer to [5].2) (Meshing the) carotid geometry: The 3D geometry wasreconstructed from CT-scans of a stenosed carotid bifurcationof an 83-year old volunteer. An in-house open-source softwarepackage (Pyformex, pyformex.org) was used to construct acomputational grid for the vascular domain. This allowed tocreate a layered mesh of the vascular wall (to some extentmimicking the intima-media-adventitia layers), consisting of31680 first order hexahedral elements and refined near thelumen. Pyformex was subsequently used to mesh the vascularlumen with hexahedrons, resulting in 87522 elements and amatching grid at the fluid-structure interface, again refined nearthe vascular wall.The structural domain was further expanded to also includethe tissue surrounding the vascular wall. The carotid artery wasembedded in a cylinder with a radius of 2 cm. A tetrahedralelement type was chosen for the tissue volume (62 717 ele-ments). To ensure continuity of the hexahedral and tetrahedralmeshes at the wall-tissue interface, the quadrilaterals at theouter surface of the vascular wall were split into triangles tomatch with the tetrahedrons of the tissue domain.3) FSI-setup: Fluid domain: At the in- and outlets ofthe carotid geometry, we imposed physiologically realisticboundary conditions. We measured a velocity profile withpulsed wave Doppler (12L linear array vascular probe, GEMedical Systems, Milwaukee, WI, USA) in the commoncarotid of a healthy volunteer, which was further applied as amass flow inlet condition. Outflow percentages were imposedat the outlets (35% at the external and 65% at the internalcarotid). A non-invasively measured pressure (varying in time,with a pulse pressure of 40 mmHg) was further imposed. Assuch, when transferring the interface stress to the structuralsolver, a realistic pressure value was imposed on the wet sideof the structure. Blood was modeled as a Newtonian liquidwith a viscosity of 3.5 mPa · s and a density of 1050 kg/m3.Solid domain: Assuming that the mechanical properties ofthe vessel wall material can be linearized around the operatingpressure, we modeled the vessel wall as a linear elasticmaterial with Young’s modulus of 250 kPa, density of 1200kg/m3 and Poisson modulus of 0.49 (nearly incompressible).The properties of the surrounding tissue were chosen to obtaina realistic distension degree for the chosen vessel elasticity:a Young’s modulus of 10 kPa and Poisson modulus of 0.3.Longitudinal movement of the in- and outlets was prevented.We refer to fig.1 for a complete overview of the simulationsetup. The cardiac cycle of 1s was divided into timesteps of5 ms.B. Ultrasound-simulations1) Field II: The Field II software [1], [2] was used tosimulate the RF-signals from the fluid and structural domain.The RF-signals can be simulated by modeling tissue as adistribution of (random) point scatterers, whose position canbe updated for each simulated ultrasound beam. By movingthe scatterers according to flow fields and wall deformationsobtained from FSI, imaging algorithms can be studied incomplex conditions [3], [5].Fluid phantom: In [5], we described a method to gen-erate scatterers during Field II simulations based on CFD-calculations with rigid walls. 3D spatial interpolation wasperformed to transform the CFD velocity vectors to therandom scatterer cloud, and temporal interpolation of theCFD velocities was required due to the large disparity in theultrasound and CFD timescales (63 µs versus 5 ms for thesimulated color flow imaging application). For distensible fluidgeometries, straightforward linear temporal interpolation of thevelocity fields is however not possible. This is illustrated in fig.2, if one considers the position of the red point at time pointTFSI,1 of the FSI-calculation and the same absolute positionof this point at the next FSI timestep TFSI,2. In case of adecreasing fluid volume, this point ends up outside the fluidvolume at TFSI,2 (white point in fig.2) . In case of increasingABAQUS displacementsVelocity in m/sFLUENT velocities Fluid phantom = Wall phantom = Tissue phantom =Tissue scatterers generated for complete cylinder; scatterers in blood & wall removedIncreasing volumeDecreasing volumeScatterers color-coded according to grid displacement1. Mapping scatterer position2. Extracting velocity vector1. Mapping scatterer position2. Extracting velocity vectorTFSI,1 TFSI,2X  = specular reflectionO = rayleigh scatteringO = deleted scattererSame absolute positionFig. 2. Strategy behind integrating fluid-structure interaction simulations and Field IIfluid volume, the point ends up further from the vessel wallat TFSI,2 compared to TFSI,1 (yellow point in fig.2). Hence,temporal interpolation between the same absolute positionsat different FSI-timesteps is incorrect. Complex mathematicalmethods exist to derive velocity fields for changing fluiddomains at timesteps intermediate to the chosen FSI-timesteps.This, however, would be an impractical approach due to highcomputational times. We refer to [5] for further details on howthe scatterers can be propagated using FSI simulation resultsaccounting for the temporally varying fluid volume and theapplied ALE grid formulation.Wall phantom: To account for local changes in material(acoustic) properties, random point scatterers were generatedfor each element of the wall mesh. Further, as can be seen inecho images, the vessel wall also causes specular reflectionsdue to transitions between different tissue types. These cannotbe simulated but only mimicked in Field II, by placingscatterers in a structured fashion at the borders of the vesselwall (i.e. tissue/vessel wall and vessel wall/blood). For moredetails on the coupling methodology for the wall, we againrefer to [5].Tissue phantom: To reduce computational times, scattererswere not generated for each mesh element of the tissue (as forthe wall phantom), but for the complete cylinder surroundingthe carotid artery, comprising the fluid, wall and tissue domain.Afterwards, scatterers created inside the arterial wall and fluidvolume were removed.2) Imaging setup: A linear array transducer was modeledand imaging parameters can be found in table 1.Duplex scanning: A duplex scan is the superposition ofa color flow image (CFI) on a B-mode image. However,the image acquisition requirements of CFI and B-mode areinherently different due to dissimilar spatial and temporalresolution requirements, and therefore compromises have tobe made. A 5 MHz centre frequency was chosen for bothimage acquisitions, but the beam density was doubled for theB-mode imaging and the pulse length was increased for CFIfrom 1.5 to 4 pulse periods. To achieve these differing imag-ing properties, an interleaved scanning scheme was applied,switching between color flow and B-mode acquisitions. Thisresulted in a frame rate of 12 fps. The color flow velocitieswere estimated with the autocorrelation method for phase-shiftestimation. The phantom was angled 70 degrees towards theultrasound scanline to reduce flow transversal to the beam. Toimprove the CFI frame rate, we applied a beam interleavedTABLE IULTRASOUND SET-UP PARAMETERS FOR DUPLEX SCANNING AND WALLTRACKINGCFI/B-modecenter frequency 5 MHznumber of elements 192element pitch 0.25 mmelement height 6 mmtransmit focus Az 2 cmdynamic receive focusing yesexpanding aperture yesexcitation sinusoidalpulseperiods 4PRFmax 16 kHzPRF 4 kHz/16 kHzpacketsize 10/1cm/sFig. 3. Duplex images from multiphysics simulations:systolic acceleration,deceleration and diastoleacquisition scheme, typically used when the Doppler PRF (asdetermined by the imaged velocity range) is chosen lower thanthe maximal possible PRFmax (as determined by the imagingdepth). We chose a setup with a PRF of 4 kHz, a PRFmaxof 16 kHz, resulting in an interleave groupsize of 4 beams.III. RESULTSA. Duplex scanningDuplex images are shown during systolic acceleration anddeceleration, and diastole in fig. 3. Complex flow patterns arepresent throughout the cardiac cycle, and specular reflectionsare apparent when perpendicularly insonifying the blood ves-sel. This is particularly visible for the disappearing specularreflections in the external carotid artery as can be seen in theB-mode part of the image on fig.3.IV. DISCUSSION AND CONCLUSIONWe successfully expanded our multiphysics simulation toolto the 3D deforming carotid artery, accounting for (the RF-signal from) the surrounding tissue and hence increasing therealism of the simulations. However, we should note thatalthough our multiphysics simulations offer the opportunityto compare ultrasonic measurements with a ground truth,limitations exist both at the level of the FSI-simulations aswell as the ultrasound model. While we applied an advancedFSI-code, resulting in a strongly coupled solution for the flowand structure, the imposed boundary conditions (both for thestructure and fluid) and the assumed material model can beimproved. Also the ultrasonic simulator shows limitations, asit is restricted to linear wave propagation and does not allowmodeling complex wave phenomena typically encountered inmedical scanning (e.g. reverberations and aberrations). Further,Field II does not take into account the true scatterer nature ofthe tissue (e.g. red blood cells are represented by points insteadof discs, showing no inertia, no interaction and no frequencydependent scattering).REFERENCES[1] J. A. Jensen, “Field: A program for simulating ultrasound systems,”Medical and Biological Engineering and Computing, vol. 34, pp. 351–352, 1996.[2] J. A. Jensen and N. B. Svendsen, “Calculation of pressure fieldsfrom arbitrarily shaped, apodized, and excited ultrasound transducers,”IEEE transactions on Ultrasonics, Ferroelectrics, and Frequency control,vol. 39, no. 2, pp. 262–267, 1992.[3] A. Swillens, L. Lovstakken, J. Kips, H. Torp, and P. Segers, “Ultrasoundsimulation of complex flow velocity fields based on computationalfluid dynamics,” IEEE Transactions on Ultrasonics, Ferroelectrics andFrequency Control, vol. 56, no. 3, pp. 546–556, 2009.[4] A. Swillens, T. De Schryver, L. Lovstakken, H. Torp, and P. Segers,“Assessment of numerical simulation strategies for ultrasonic color bloodflow imaging, based on a computer and experimental model of the carotidartery,” Annals of Biomedical Engineering, vol. 37, no. 11, pp. 2188–2199, 2009.[5] A. Swillens, J. Degroote, J. Vierendeels, L. Lovstakken, and P. Segers,“A simulation environment for validating ultrasonic blood flow and vesselwall imaging based on fluid-structure interaction simulations: ultrasonicassessment of arterial distension and wall shear rate.,” Medical Physics,vol. 37, no. 8, pp. 4318–4330, 2010.[6] J. Degroote, K. J. Bathe, and J.Vierendeels, “Performance of a newpartitioned procedure versus a monolithic procedure in fluid-structureinteraction,” Computers & Structures, vol. 87, p. 793801, 2009.

Tachycardie avec complexes ventriculaires larges et alternance des complexes QRS et des intervalles RR

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Tachycardie avec complexes ventriculaires larges et alternance des complexes QRS et des intervalles RR

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