Available online at ScienceDirect. Procedia Engineering 126 (2015 )

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1 Available online at ScienceDirect Procedia Engineering 126 (2015 ) th International Conference on Fluid Mechanics, ICFM7 FSI modeling approach to develop right ventricle pulmonary valve replacement surgical procedures with a contracting actuator and improve ventricle ejection fraction Chun Yang a,b, Dalin Tang a,c,*, Nikolay Vasilyev d, Rahul Rathod e, Tal Geva e, Pedro J. del Nido d a Mathematical Sciences Department, Worcester Polytechnic Institute, Worcester, MA USA b Network Technology Research Institute, China United Network Communications Co., Ltd., Beijing, China c Southeast University, Nanjing, China d Department of Cardiac Surgery, Children s Hospital Boston, Dept of Surgery, Harvard Medical School, Boston, MA USA e Department of Cardiology, Children's Hospital Boston, Department of Pediatrics, Harvard Medical School, Boston, MA USA Abstract Image-based computational modeling has been used more and more for cardiovascular disease management and surgical planning in recent years. Computational modeling could perform virtual surgery with different surgical options avoiding risks associated with actual surgical experimentation on patients. For patients with repaired tetralogy of Fallot (TOF) needing right ventricle (RV) pulmonary valve replacement (PVR), the current surgical approach, which includes pulmonary valve replacement/ insertion, has yielded mixed results. In this paper, we propose a new surgical option placing a contracting actuator in the right ventricle to improve RV function measured by ejection fraction (EF). An interdisciplinary approach is proposed to combine cardiac magnetic resonance (CMR) imaging, modeling, and mechanical engineering techniques to construct the mechanical actuator, build the ventricle models, perform virtual surgery, demonstrate feasibility of the new surgical procedure with actuator insertion, and identify optimal mechanical conditions under which optimal surgical outcome could be achieved The Authors. Published by by Elsevier Ltd. Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of The Chinese Society of Theoretical and Applied Mechanics (CSTAM). Peer-review under responsibility of The Chinese Society of Theoretical and Applied Mechanics (CSTAM) Keywords: right ventricle model; tetralogy of Fallot; fluid-structure interactions; pulmonary valve replacement; heart model * Corresponding author. Tel.: ; fax: address: dtang@wpi.edu The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of The Chinese Society of Theoretical and Applied Mechanics (CSTAM) doi: /j.proeng

2 442 Chun Yang et al. / Procedia Engineering 126 ( 2015 ) Introduction Image-based computational modeling has been used more and more for cardiovascular disease management and surgical planning in recent years. The modeling approach could perform virtual surgery with different surgical options avoiding risks associated with actual surgical experimentation on patients. We have introduced fluidstructure interaction (FSI) models for patients with repaired tetralogy of Fallot (TOF) for right ventricle (RV) pulmonary valve replacement (PVR) surgical procedures optimization. Those patients account for the majority of cases with late onset right ventricle (RV) failure. The current surgical approach, which includes pulmonary valve replacement/insertion, has yielded mixed results [1,2]. In this paper, we propose a new surgical option placing a contracting actuator in the right ventricle to improve RV function measured by ejection fraction (EF) which is define as: RV EF = (EDRV-Vol ESRV-Vol) / EDRV-Vol, (1) where EDRV-Vol is end diastolic RV volume and EDRV-Vol is end systolic RV volume. Details are given below. 2. Method An interdisciplinary approach is proposed to combine cardiac magnetic resonance (CMR) imaging, modeling, and mechanical engineering techniques to construct the mechanical actuator, build the ventricle models, perform virtual surgery, demonstrate feasibility of the new surgical procedure with actuator insertion, and identify optimal mechanical conditions under which optimal surgical outcome could be achieved Cardiac magnetic resonance data Cardiac magnetic resonance (CMR) imaging was acquired from a patient with ToF for model construction at Harvard Medical School with informed consent obtained (Fig. 1). The RV and LV were imaged using ECG-gated, breath-hold steady state free precession cine MR in the ventricular short axis. The valve and patch positions were determined with cine MR imaging, flow data, and delayed enhancement CMR to delineate location and extent of scar/patch. Band location was determined by Dr. del Nido based on his surgical experience and ventricle anatomic limitations. Three-dimensional RV/LV geometry and computational mesh were constructed following the procedures published earlier [3-5]. Figure 1 shows pre-operative CMR images from a patient with repaired TOF and severe RV dilatation, segmented contour plots, the 3D re-construction RV/LV geometry with the actuator band and the patient-specific model with fiber orientations.echo image data were acquired from ten people, five patients with myocardial infarction (Group 1) and five healthy volunteers as control (Group 2). Standard echocardiograms were obtained using an ultrasound machine (E9, GE Mechanical Systems, Milwaukee, Wisconsin) with a 3V probe and data were segmented for model construction. Fig.1 and Fig. 2 show the echo images and re-constructed 3D LV geometries from the two group patients. The location of infarction was defined as a decrease in or cessation of myocardial contractility, which was determined by two experienced observers through visualization of all LV wall segments, combining with the electrocardiogram and results of coronary angiography Biaxial testing of myocardium tissue properties Tissue mechanical properties are essential to computational ventricle models. However, human heart tissue material properties are not readily available from the literature. Based on the methods of Sacks and Choung [6] for canine hearts and informed by our previous biaxial testing [7] and the methods of Humphrey and colleagues [8,9], we generated the first complete multiaxial mechanical data set for ventricular tissues using a cadaveric human heart sample (Fig 2). A detailed description of the custom planar biaxial testing device and method has been previously described [6,7]. The stress-strain data were recorded for computational modeling use.

3 Chun Yang et al. / Procedia Engineering 126 ( 2015 ) Fig. 1. CMR-based model construction process. (a) CMR images of a patient, selected slices; (b) segmented contours; (c) conventional patch; (d) reconstructed 3D geometry with a band; (e) model showing fiber orientation. Fig. 2. Biaxial mechanical testing and initial results. (a) The biaxial testing apparatus in Dr. Billiar s lab; (b) a human right ventricle tissue sample; (c) tissue sample mounted for biaxial test; (d) anisotropic data from a human right ventricle sample FSI model For the FSI model, blood flow in the right ventricle was assumed to be laminar, Newtonian, viscous and incompressible. The Navier-Stokes equations with arbitrary Lagrangian-Eulerian (ALE) formulation were used as the governing equations. The RV and left ventricle (LV) materials were assumed to be hyperelastic, anisotropic, nearly-incompressible and homogeneous. Patch and band materials were assumed to be hyperelastic, isotropic, nearly-incompressible and homogeneous. The nonlinear Mooney-Rivlin model was used to describe the nonlinear anisotropic and isotropic material properties. Parameter values in the material model were chosen to fit CMRmeasured RV volume data (See Fig. 3). The details of the FSI RV/LV/Patch/Band model can be found from Ref.[4,5].

4 444 Chun Yang et al. / Procedia Engineering 126 ( 2015 ) Fig. 3. Material Stress-Stretch curves, pressure conditions used in the paper and computational RV volume curve matching CMR-measured data. 3. Results The full RV/LV/Patch/Band models were solved by ADINA (ADINA R&D, Watertown, MA, USA) using unstructured finite elements and the Newton-Raphson iteration method [4,5]. RV ejection fraction was calculated to seek the optimal surgical design for potential RV EF improvement. Stress/strain distributions and flow shear stress conditions on the band were calculated which will provide important information for band design and tissue regeneration (Fig. 4). Our modeling results indicated that the band insertion, combined with active band contraction and tissue regeneration techniques that restore RV myocardium, has the potential to improve right ventricle ejection fraction. Contractions from the actuator could help the RV to improve EF by 2-5%. This compares favorably with recently published drug trials to treat heart failure where an improvement in LVEF of 3-4% resulted in a significant improvement in functional capacity. Detailed results will be presented at the conference. (a) Filling 1 (b) Filling 2 (c) Ejection 1. (d) Ejection 2, Peak, cm/s cm/s cm/s cm/s Fig. 4. Fig. 4. RV velocity plots from 4 time steps in a cardiac cycle showing flow behaviors. Different vortices were present at different time points. The actuator caused flow disturbances. 4. Discussion and conclusion It should be noted that the proposed surgical procedure requires long-term efforts from multi-disciplines to get close to and be implemented in clinical practice. The computational simulations (virtual surgery) provided a proof of concept for further investigations using in vitro experiments, animal models and final patient studies. Computational models are non-invasive and may be used to supplement/replace empirical and often risky clinical

5 Chun Yang et al. / Procedia Engineering 126 ( 2015 ) experimentation, or even guide the design of new clinical trials to examine the efficiency and suitability of various reconstructive procedures in diseased hearts. Tissue engineering and regeneration techniques also need to be developed to generate the contracting bands and viable myocardium. Acknowledgements This research was supported in part by NIH-1R01-HL (del Nido, Tang, Geva), NIH HL63095 (PI: del Nido) and NIH-NHLBI 5P50HL (PI: Geva; Co-Investigator: del Nido). Chun Yang's research is supported in part by the National Sciences Foundation of China References [1] P. J. del Nido. Surgical management of right ventricular dysfunction late after repair of Tetralogy of Fallot: right ventricular remodeling surgery, Semin Thorac Cardiovasc Surg Pediatr Card Surg Annu. 2006; [2] T. Geva, K. Gauvreau, A. J. Powell, F. Cecchin, J. Rhodes, J. Geva, P. J. del Nido, Randomized Trial of Pulmonary Valve Replacement With and Without Right Ventricular Remodeling Surgery, Circulation Sep 14;122(11 Suppl):S [3] D. Tang, C. Yang, T. Geva, P. J. del Nido, Image-Based Patient-Specific Ventricle Models with Fluid-Structure Interaction for Cardiac Function Assessment and Surgical Design Optimization, Progress in Pediatric Cardiology, (2010), 30, pp [4] Tang D, Yang C, Geva T, Gaudette G, del Nido PJ., Multi-Physics MRI-Based Two-Layer Fluid-Structure Interaction Anisotropic Models of Human Right and Left Ventricles with Different Patch Materials: Cardiac Function Assessment and Mechanical Stress Analysis, Computers & Structures, 89, , PMC [5] D. Tang, C. Yang, T. Geva, P. J. del Nido, Patient-Specific MRI-Based 3D FSI RV/LV/Patch Models for Pulmo-nary Valve Replacement Surgery and Patch Optimization, ASME Journal of Biomechanical Engineering, (2008), 130(4) [6] M. S. Sacks, C. J. Chuong, Biaxial mechanical properties of passive right ventricular free wall myocardium, J Biomech Eng, 1993; 115: [7] K. L. Billiar, M. S. Sacks. Biaxial mechanical properties of the natural and glutaraldehyde treated aortic valve cusp--part I: Experimental results. J Biomech Eng. 2000;122(1): [8] J. D. Humphrey, R. K. Strumpf, F. C. Yin. Biaxial mechanical behavior of excised ventricular epicardium. Am J Physiol Jul;259(1 Pt 2):H [9] V. P. Novak, F. C. Yin, J. D. Humphrey. Regional mechanical properties of passive myocardium. J Biomech Apr;27(4):