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Personalisation: patient-specific parameter estimation

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Personalisation: patient-specific parameter estimation

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  1. Personalised Electromechanical Model of theHeart for the Prediction of the Acute Effects ofCardiac Resynchronisation TherapyM. Sermesant1,3, F. Billet1, R. Chabiniok2, T. Mansi1,P. Chinchapatnam4, P. Moireau2, J.-M. Peyrat1, K. Rhode3, M. Ginks3,P. Lambiase6, S. Arridge4, H. Delingette1, M. Sorine7,C.A. Rinaldi5, D. Chapelle2, R. Razavi3, and N. Ayache11 INRIA, Asclepios project, 2004 route des Lucioles, Sophia Antipolis, France2 INRIA, Macs project, Le Chesnay, France3 King's College London, Division of Imaging Sciences, London, UK4 University College London, Centre for Medical Image Computing, London, UK5 Department of Cardiology, St Thomas' Hospital, London, UK6 The Heart Hospital, University College London Hospitals, London, UK7 INRIA, Sysiphe project, Le Chesnay, France

  2. Personalisation: patient-specific parameter estimation Diagnosis Therapy planning Personalisation anatomy electro-physiology perfusion & metabolism solid mechanics blood flow Clinical applications Cardiac data Cardiac modeling Personalised and predictive medicine

  3. Cardiac Resynchronisation Therapy • CRT has revolutionised the treatment of heart failure. However up to one third of patients receiving this CRT do not derive clinical improvement. The reasons for this are multifactorial, including: • heterogeneity of the heart failure population • inadequacy of techniques for patient selection • suboptimal positioning of the left ventricular lead • failure to optimise the device settings in order to enhance the hemodynamic response to treatment.

  4. Personalised Models for Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  5. Clinical Data: XMR Suite • Clinical case presented: • Sixty year old woman with NYHA class III symptoms • Dilated cardiomyopathy + non-viable areas consistent with previous infarction • no flow-limiting disease • LV Ejection fraction 30% on maximal tolerated medication • Left bundle branch block (LBBB) XMR = hybrid X-ray/MR imaging Common sliding patient table Path to MR-guided intervention

  6. XMR System at King’s College London M1 Scanner Space 6 4 T 3D Image Space X-ray Table Space 5 7 1 2 M2 3 X-ray C-arm space M3 8 R*P 2D Image Space • Registration: no inherent ability • Overall registration transform: composed of a series of stages • Calibration + tracking during intervention • Overlay of MRI-derived left ventricular (LV) surface model (red) onto live X-ray fluoroscopy image (grey scale). This real-time overlay was used to guide the placement of catheters prior to the start of pacing. • The catheters are: (1) St. Jude ESI balloon; (2) LV roving; (3) coronary sinus sheath; (4) coronary venous/epicardial; (5) pressure; (6) high right atrium; (7) His; and (8) right ventricle. K. Rhode, M. Sermesant, D. Brogan, S. Hegde, J. Hipwell, P. Lambiase, E. Rosenthal, C. Bucknall, S. Qureshi, J. Gill, R. Razavi, D. Hill. A system for real-time XMR guided cardiovascular intervention. IEEE Transactions on Medical Imaging, 24(11): 1428-40, 2005.

  7. Clinical MR images 3D+t Cine 3D Late Enhancement

  8. XMR Fusion of Clinical Data: ms Endocardial Mapping MRI Scars K. Rhode, M. Sermesant, D. Brogan, S. Hegde, J. Hipwell, P. Lambiase, E. Rosenthal, C. Bucknall, S. Qureshi, J. Gill, R. Razavi, D. Hill. A system for real-time XMR guided cardiovascular intervention. IEEE Transactions on Medical Imaging, 24(11): 1428-40, 2005.

  9. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  10. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  11. Personalised Anatomy Segmentation done with Scars Interactive Surface Generator Labelled Myocardial Volumetric Mesh

  12. Personalised Anatomy dtMRI Statistical Analysis Mean Structure J.M. Peyrat, M. Sermesant, X. Pennec, H. Delingette, C. Xu, E. McVeigh, N. A. A Computational Framework for the Statistical Analysis of Cardiac Diffusion Tensors: Application to a Small Database of Canine Hearts. IEEE Transactions on Medical Imaging, 26(11):1500-1514, November 2007

  13. Personalised Anatomy Statistical atlas of cardiac fibre architecture registered to patient anatomy

  14. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  15. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  16. For CRT, the main electrophysiology feature is the activation time, the model is chosen accordingly Eikonal-Diffusion Model T: Depolarisation time c0, k, D: speed parameters Cardiac Cell Models Three Main classes • Biophysical Ionic Models Noble, Luo-Rudy, Beeler-Reuter, Fenton-Karma,... • Phenomenological Models Fitzhugh-Nagumo, Aliev-Panfilov,... • Eikonal Models Keener, Colli-Franzone, ..

  17. Fast Electrophysiology Models • Fast-Marching Method: solves very efficiently Eikonal equation: • Anisotropic Propagation • new algorithm even for high anisotropy • Add curvature effect to correct equation second term • fixed-point algorithm • Implementation on unstructured grids • tetrahedral meshes Introduce repolarisation with an additional time scheme and discrete state representation of cell behaviour • resting / depolarised / refractory / resting • Extension of the fast-marching method E. Konukoglu, M. Sermesant, O. Clatz, J.-M. Peyrat, H. Delingette, N. Ayache. A Recursive Anisotropic Fast Marching Approach to Reaction Diffusion Equation: Application to Tumor Growth Modeling. IPMI2007. M. Sermesant, E. Konukoglu, H. Delingette, Y. Coudière, P. Chinchapatnam, K. Rhode, R. Razavi, N. Ayache: An Anisotropic Multi-front Fast Marching Method for Real-Time Simulation of Cardiac Electrophysiology. FIMH 2007: 160-169

  18. Electrophysiology Personalisation • Endocardial surface data to adjust myocardium volume conductivity • Onset location not in the data: LBBB • Minimise combined criterion: • on endocardial times to adjust sub-endocardial conductivity, with recursive domain decomposition • on QRS duration to adjust mid-wall and sub-epicardial global ventricular conductivities P. Chinchapatnam, K. Rhode, M. Ginks, C.A. Rinaldi, P. Lambiase, R. Razavi, S. Arridge, M. Sermesant. Model-based Imaging of Cardiac Apparent Conductivity and Local Conduction Velocity for Diagnosis and Planning of Therapy. IEEE Transactions on Medical Imaging, 27(11):1631-1642, 2008.

  19. Baseline Electrophysiology Personalisation Measured Endocardial Isochrones Endocardial Isochrones Error Adjusted Volumetric Isochrones (QRS error = 12 ms)

  20. Personalised Electrophysiology Final Parameter Map

  21. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  22. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  23. 3D Electromechanical Model Contraction forces Controlled by u Law of dynamics: Boundary forces Blood pressure forces acceleration velocity position mass damping stiffness boundary pressures State Vector θ = model parameters u=electric control (related to action potential) How to adjust the Electromechanical Model motion to the patient motion?

  24. Pro-Active Deformable Model Internal Force External Force

  25. Personalised Kinematics Colour encodes the contraction force intensity F. Billet, M. Sermesant, H. Delingette, and N. Ayache. Cardiac Motion Recovery by Coupling an Electromechanical Model and Cine-MRI Data: First Steps. In Proc. of the Workshop on Computational Biomechanics for Medicine III. (Workshop MICCAI-2008), September 2008.

  26. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  27. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  28. Modelling Cardiac Electromechanics Active nonlinear viscoelastic anisotropic and incompressible material • Bestel-Clément-Sorineconstitutive law ESseries element Epparallel element Eccontractile element  Manual adjustment of mechanical parameters Bestel J, Clément F, Sorine M. A biomechanical model of muscle contraction. In Medical Image Computing and Computer-Assisted Intervention (MICCAI 2001), volume 2208 of LNCS, Springer. J. Sainte-Marie, D. Chapelle, R. Cimrman and M. Sorine. Modeling and estimation of the cardiac electromechanical activity. Computers & Structures, 84:1743-1759, 2006

  29. Personalised Mechanics Measured (solid red) and simulated (dashed blue) pressure curves in sinus rhythm. Measured (solid red) and simulated (dashed blue) dP/dt curves in sinus rhythm. Personalised electromechanical model reproduces pressure characteristics  (dP/dt)max

  30. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  31. Application to Cardiac Resynchronisation Therapy Anatomical MRI Endocardial Mapping Cine MRI Pressure Catheter Data: Personalised Anatomy Personalised Electrophysiology Personalised Kinematics Personalised Mechanics Method: • Geometry • Fibres • Conductivity • Isochrones • Contours • Motion • Contractility • Stress Output: Predict pressure changes for different pacing conditions: in-silico optimisation of pacemaker leads locations and settings Result:

  32. P1TRIV Electrophysiology Personalisation Coronary sinus catheter LBBB Coronary sinus catheter RV catheter RV catheter Endocardial catheter Endocardial catheter Measured Baseline Endocardial Isochrones Measured Pacing Endocardial Isochrones Adjusted Volumetric Isochrones

  33. Prediction of the Acute Effects of Pacing Pacing dP/dt Baseline dP/dt

  34. Prediction of the Acute Effects of Pacing Personalisation Predictions

  35. Perspectives • Validate on a small cohort of patients • Automatic segmentation of the myocardium in MRI • in vivo DTI for patient-specific fibre architecture • Integrate functional blocks in electrophysiology model • Validation of kinematic prediction with 3D echo • Automatic adjustment of mechanical parameters • Remodelling for chronic effects of CRT • Optimisation of pacing leads position and delays

  36. On Cardiac Modelling «The notion of a single and ultimate (cardiac) model is as useful as the idea of a universal mechanical tool for all possible repairs and servicing requirements in daily life. The ideal model will be as simple as possible and as complex as necessary for the particular question raised. » Garny, Noble, Kohl, Dimensionality in cardiac modelling, Progress in Biophysics and Molecular Biology, Volume 87, Issue1 January 2005, Pages 47-66 Biophysics of Excitable Tissues

  37. http://tinyurl.com/ci2bm09 Early bird before 1st August

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