Scaffold Design To Prime Soft Tissue Regeneration and Replacement

Transcription

1 Scaffold Design To Prime Soft Tissue Regeneration and Replacement Antonio D Amore 1,2,3 and William R. Wagner 1 1 Department of Bioengineering, Swanson School of Engineering and The McGowan Institute for Regenerative Medicine,University of Pittsburgh 2 Dipartimento di Ingegneria Chimica, Gestionale,Informatica e Meccanica, University of Palermo 3 Fondazione RiMED, Italy

2 Altered tissue mechanics can lead to adverse tissue remodeling and regeneration

3 Ventricular wall thinning, stiffening in ischemic cardiomyopathy with increased wall stress Image: Jessup M, Brozena S. Heart Failure. N Engl J Med 348: 2007 (2003).

4 In tissue engineering, mechanical training is often necessary to develop correctly anisotropic, mechanically robust tissue Bioreactors for cyclic loading Actuating arm Stationary Pin Media bath 10 mm x 19 mm Bioreactor well Laboratory of Dr. Michael Sacks

5 Temporarily altering the mechanical environment of the tissue will alter remodeling, regeneration F F

6 How might the ventricular wall mechanical environment be altered with localized therapy? X

7 Elastomeric patch placement on 2 week old infarct (rat) examined at 8 weeks Infarct control PEUU patch patch S P 5mm 5mm Create myocardial infarction by ligating left anterior descending coronary artery 2 weeks post-infarct, implant PEUU scaffold to cover infarcted region of left ventricle Examine at 8 weeks 5mm 5mm

8 Fujimoto KL, et al. J Am Coll Cardiol 49:2292 (2007). Ventricular wall is significantly thicker and softer than controls Infarction alone Explant at 8 weeks H&E staining 500um PEUU patch

9 End-diastolic Area (cm 2 ) Fractional Area Change (%) Echocardiography EDA (end-diastolic LV cavity area) FAC (fractional area change) * 20 * Pre 4w 8w 10 Pre 4w 8w Infarction control Patch Mean ±SEM, Two-factor repeated ANOVA: *; p<0.05 between groups, ; p<0.05 vs. 0w within group Fujimoto K, et al. J Am Coll Cardiol. 49: 2292 (2007)

10 Mechanical support in the vascular system Could a mechanically protective elastic matrix be deposited around a saphenous vein for arterial bypass?

11 Spinning a temporary, conformal, elastic jacket on a vein to protect from sudden expansion at arterial pressure In collaboration with the laboratory of Dr. David Vorp El-Kurdi MS, et al. Biomaterials 29:3213 (2008).

12 Tuning wrap mechanical degradation PEUU/elastin/collagen El-Kurdi MS, et al. Biomaterials 29:3213 (2008).

13 Mechanical support for developing, engineered tissue Elastomeric scaffolds for the development of tissue engineered cardiovascular structures with matching mechanics (blood vessel & pulmonary valve)

14 An appropriately elastic scaffold, seeded with precursor cells, will match the compliance of the native artery and exhibit higher patency Collaboration with laboratory of Dr. David Vorp Soletti L, et al. Biomaterials 27:4863 (2006). Nieponice A, et al. Biomaterials 29:825 (2008). Soletti L, et al. Acta Biomater 5:2901 (2010). Nieponice, et al. Tissue Eng A 16:1215 (2010). He W, et al. Cardiovasc Eng Tech (2011).

15 Critical gap: Biodegradable materials with tunable properties to meet the hypothesized needs for soft tissue mechanical protection and tissue engineering

16 Structure Function Design Scales Nano (molecular) Micro Meso Macro

17 Molecular design: biodegradable thermoplastic elastomers Poly(ester urethane) urea (PEUU) O O HO(CH 2 ) 5 C C(CH 2 ) 5 OH + OCN(CH 2 ) 4 NCO Polycaprolactone diol (Mw=2000) 1,4-diisocyanatobutane 70 o C, Sn(OCt) 2 patch Prepolymer H 2 N(CH 2 ) 4 NH 2 Putrescine O O O O O O...HNRNHCNH(CH 2 ) 4 NHCO(CH 2 ) 5 C C(CH 2 ) 5 OCNH(CH 2 ) 4 NHCNHRNH...

18 Tuning degradation to be faster with polyether blocks Poly(ether ester urethane) urea

19 Creating enzymatically labile elastomers O O HO(CH 2 CH 2 O) n H + (MW=600 or 1000) O O HO O(CH 2 ) 5 C m O(CH 2 CH 2 O) n C(CH 2 ) 5 O m OH + OCN(CH 2 ) 4 NCO O O O O OCN(CH 2 ) 4 NHC O(CH 2 ) 5 C m O(CH 2 CH 2 O) n C(CH 2 ) 5 O m CNH(CH 2 ) 4 NCO + AAK elastase lability O O O O O O... KAANHCN(CH 2 ) 4 NHC O(CH 2 ) 5 C m O(CH 2 CH 2 O) n C(CH 2 ) 5 O m CNH(CH 2 ) 4 NCNHAAKNH...

20 Tuning degradation to be slower with a polycarbonate blocks Hong Y, et al. Biomaterials 31:4249 (2010)

21 Tuning mechanics with labile segment selection and length Diethylene glycol Diethylene glycol =PCL, PTMC or PVLCL Diethylene glycol BDI PUU Ma Z., et al. Biomacromolecules 12:3265 (2011) Putrescine

22 Stress (Mpa) Tuning mechanics with labile segment selection and length PUU-PTMC1500 PUU-PTMC2500 PUU-PCL2000 PUU-PVLCL2246 PUU-PTMC5400 PUU-PVLCL Ma Z., et al. Biomacromolecules 12:3265 (2011) Strain (%)

23 Structure Function Design Scales Nano (molecular) Micro Meso Macro

24 Introduction: overview on the modeling strategy Input: 1: Material sample 2: SEM Image Analysis Mechanical testing Artificial network model generation from experimental data FEM simulation From the micro-structure to the mechanical response at micro and macro levels Output: Mechanical response 1: Macro level 2: Micro level Output: Material fabrication parameters Optimal microarchitecture identification FEM simulation Artificial network model generation in the design space Input: clinical application, targeted macromeso mechanical response From the targeted mechanical behavior at micro and macro levels to the material micro-structure

25 Micro-control: electrohydrodynamic processing Isotropic A C Input: 1: Material sample 2: SEM VSMCs int 1 µm 1 µm B Anisotropic D Microspheres int 1 µm 10 µm fiber intersection density can be controlled by the rastering speed fiber main angle of orientation can be controlled by the mandrel speed

26 Methods: material fabrication A Isotropic C Input: 1: Material sample 2: SEM VSMCs int 1 µm 1 µm B Anisotropic D Microspheres int 1 µm 10 µm fiber intersection density can be controlled by the rastering speed fiber main angle of orientation can be controlled by the mandrel speed

27 Methods: image analysis and material characterization Input: 1: Material sample 2: SEM final result on color initial image final result on color initial image final result on color initial image final result on color initial image final result on color initial image final result on color initial image OI ϑ ϑ final result on color initial image [*] D Amore Stella, Wagner Sacks Characterization of the Complete Fiber Network Topology of Planar Fibrous Tissues and Scaffolds. Biomat 2010; 31:(20)

28 Methods: mechanical testing Mechanical testing A B [*] [*] Sacks. Biaxial Mechanical Evaluation of Planar Biological Materials. Journal of Elasticity 61: , 2000.

29 Methods: mechanical testing Mechanical testing A [*] λ NAR = 1 Nuclear Aspect Ratio from confocal microscopy NAR = 1.3 [*] Stella, Wagner et al et al. Tissue-to-cellular level deformation coupling in cell micro-integrated elastomeric scaffolds. Biomaterials Volume 29, Issue 22, August 2008, Pages

30 Methods: mechanical modeling, artificial fiber network generation Artificial network model generation from experimental data Anisotropic model Size=120 µm OI = 0.65 Diameter= 0.5 µm Int Den=0.28 [n/ µm 2 ] [*] D Amore et al. Micro Scale Based Mechanical Models for Electrospun Poly (Ester Urethane) Urea Scaffolds. Proceedings of the 7th European Solid Mechanics Conference (ESMC2009) September , Lisbon, Portugal.

31 Methods: mechanical modeling, finite element model FEM simulation Mesh Topology Fiber network cast into finite element form (from 20 x 20 µm 2 to150 x 150 µm 2 ). Element Fibers idealized as truss elements ( nodes, elements ) ABAQUS (t2d2h) Solver Static solution, Newton -Raphson method Large deformation enabled Boundary conditions Equi-biaxial stress conditions

32 Results: MESO LEVEL RESPONSE Output: Mechanical response 1: Macro level 2: Micro level SEM Confocal Model [*] ε Changes in isotropic ES-PEUU fiber microarchitecture under biaxial stretch. [*] J Stella, W R Wagner et al. Scale dependent kinematics of fibrous elastomeric scaffolds for tissue engineering. Journal of Biomedical Materials Research In press.

33 Results: MESO LEVEL RESPONSE Output: Mechanical response 1: Macro level 2: Micro level ( n=50 cells for each data point, model prediction solid line) Scaffold model under strip biaxial deformation. Red dots represent the experimental data, model prediction in black

34 Results: MICRO LEVEL RESPONSE Output: Mechanical response 1: Macro level 2: Micro level Single fiber initial shear modulus prediction [*] Kis A. et. al. Nanomechanics of Microtubules Phys. Rev. Lett. 89, (2002)

35 Stress [Pa] Stress [Pa] NAR n=20 for each data point Stress [Pa] 6 x 105 Results: 3 Levels quantitative prediction / validation MACRO MESO MICRO (1 cm organ level ) (50 µm cells level ) (1 µm fiber level ) SUMMARY x x Stretch NAR vs strain, method used in Stella 2008 Single fiber initial shear modulus Stretch Stretch strain [%] polygons and centroids Strain 42%

36 Results: Recapitulating organ level mechanical response SUMMARY Physiologically relevant mechanical anisotropy and cells integration [*] N. Amoroso, A. D Amore, Y. Hong, W. R Wagner and M. S. Sacks. Elastomeric Electrospun Polyurethane Scaffolds: The Interrelationship Between Fabrication Conditions, Fiber Topology, and Mechanical Properties. Advanced Materials; In press.

37 Results: Recapitulating cell level micro mechanical environment SUMMARY [ * ] Optimized Extra Cellular Matrix deposition [ * ] Stella, D Amore, Wagner Sacks manuscript in preparation

38 Summary: overview on the modeling strategy SUMMARY Models Macroscopic Structure - function Structure Fabrication Parameters Clinical application PEUU Leaflet Pulmonary artery PEUU Patch Cells Structure - function Cells - Extracellular matrix Left ventricle

39 Summary: overview on the modeling strategy SUMMARY Input: 1: Material sample 2: SEM Image Analysis Mechanical testing Artificial network model generation from experimental data From the micro-structure to the mechanical response at micro and macro levels FEM simulation Output: Mechanical response 1: Macro level 2: Micro level Output: Material fabrication parameters Optimal microarchitecture identification FEM simulation Artificial network model generation in the design space Input: clinical application, targeted macromeso mechanical response From the targeted mechanical behavior at micro and macro levels to the material micro-structure

40 Acknowledgements Cardiovascular Biomechanics Laboratory Dr Michael Sacks Dr John Stella Christopher Hobson Cardiovascular Engineering Laboratory Nicholas Amoroso, Dr Yi Hong Harvard Medical School, Children Hospital Dr A. Bayoumi, Dr J. E. Mayer

41 Acknowledgements Fondazione Ri.MED, Italy The McGowan Institute for Regenerative Medicine University of Palermo, Dipartimento di Ingegneria Chimica, Gestionale, Informatica e Meccanica National Institute of Health grant R01 HL Harvard Medical School