Modeling fiber anisotropy in multiscale musculoskeletal soft tissues

Transcription

1 Modeling fiber anisotropy in multiscale musculoskeletal soft tissues Hon Fai Choi, Switzerland 1

2 Introduction Static evaluation: geometry, volumes, Anatomical modeling [HMH14] Hiphealth.ca [HMH14] Handsfield GG, Meyer CH, Hart JM, Abel MF, Blemker SS. Relationships of 35 lower limb muscles to height and body mass quantified using MRI,

3 Introduction Anatomical modeling Static evaluation: geometry, volumes, Tissue structure modeling Mechanical response: elasticity, anisotropy,. Physical simulations Dynamic evaluation: deformation, articulation, 3

4 Introduction Fiber architecture important determinant for function: Muscles: force and moment generating capacity Force Connective tissue: tensile strength weight bearing joint stability Menisci Displacement F r l r( t) ( t) Moment: F x r thesteadmanclinic.com Ligaments Tendons activemotionphysio.ca 4

5 Motivation Medical images provide geometry for anatomical models: How to incorporate internal fiber structure?? 5

6 Motivation Measurement anatomical fiber arrangements Difficult in 3D Cadaver dissection Expensive, invasive usually not 3D Sparse measurements Translation to subjectspecific models? [WES09] DT-MRI Noisy data Fiber tracing not robust Only works for muscles Ultrasound Mostly planar measurements limited scan depth [HCK11] [BLD07] [KBK10] [WES09] SR Ward, CM Eng, LH Smallwood and RL Lieber. Are current measurements of lower extremity muscles architecture accurate?, Clin Orthop Relat Res 467: , 2009 [HCK11] RD Herbert, J Clarke, LK Kwah et al. In vivo passive mechanical behaviour of muscle fascicles and tendons in human gastrocnemius muscle-tendon units, J Physiolology 589: , 2011 [BLD07] Budzik JF, Le Thuc V, Demondion X et al. In vivo MR tractography of thigh muscles using diffusion imaging: initial results, Eur Radiol 17: , 2007 [KBK10] E Kermarrec, JF Budzik, C Khalil et al. In vivo diffusion tensor imaging and tractography of human thigh muscles in healthy subjects, AJR Am J Roentgenol 195: W352-6,

7 Motivation Medical images provide geometry for anatomical models: How to incorporate internal fiber structure? Computational approaches to generate plausible representations 7

8 Related work Variety of computational methods proposed [HCL10] Muscles: Action lines template warping [MSP09] Ligaments/menisci: centerline + diffusion gradient Hexahedral mesh [ERD13] [BLD05] [MSP09] X Maurice, A Sandholm, N Pronost et al. A subject-specific software solution for the modeling and visualization of muscles deformations. Vis Comput 25: , [BLD05] SS Blemker and SL Delp. Three-dimensional representation of complex muscle architectures and geometries. Ann Biomed Eng 33: , HCL10]: T Heimann, F Chung, H Lamecker and H Delingette. Subject-specific ligament models: towards a real-time simulation of the knee joint. In MICCAI 2009 Workshop Proceedings Computational Biomechanics for Medicine, pp , [ERD13]: A Erdemir. Open Knee: A pathway to community driven modeling and simulation in joint biomechanics. In proceedings of the ASME/FDA 1 st Annual Frontiers in Medical Devices,

9 Related work Multitude of methods not practical for medical applications [BLD05] [MSP09] [ERD13] [HCL10] [MSP09] X Maurice, A Sandholm, N Pronost et al. A subject-specific software solution for the modeling and visualization of muscles deformations. Vis Comput 25: , [BLD05] SS Blemker and SL Delp. Three-dimensional representation of complex muscle architectures and geometries. Ann Biomed Eng 33: , [ERD13]: A Erdemir. Open Knee: A pathway to community driven modeling and simulation in joint biomechanics. In proceedings of the ASME/FDA 1 st Annual Frontiers in Medical Devices, [HCL10]: T Heimann, F Chung, H Lamecker and H Delingette. Subject-specific ligament models: towards a real-time simulation of the knee joint. In MICCAI 2009 Workshop Proceedings Computational Biomechanics for Medicine, pp ,

10 Research question Multitude of methods not practical for medical applications Common approach possible? Fiber architecture is similar across tissues: Ordering in bundles running between attachments Muscles Ligament, tendon ( (en.wikipedia.org) meniscus (ubcmedicalart.wordpress.com) 10

11 Laplacian Method Generation fiber orientations based on physical properties: [CHB13] Laplace v 0 equation v 0 0 Anatomical model Identify Attachments Mesh construction Solve Laplace field [CHB13] HF Choi and SS Blemker. Skeletal muscle fascicle arrangements can be reconstructed using a Laplacian vector field simulation. PLoS One 8: e77576,

12 Laplacian Method Finite Element (FE) solver Vector field Stress and strain FE simulations of deformation Laplace equation = 0 Flux field Not robust Finite Volume (FV) solver [KRS12] vˆ i f i t nv Robust i xi vˆ i trajectory tracing [KRS12] Klausen RA, Rasmussen AF, Stephansen AF. Velocity interpolation and streamline tracing on irregular geometries. Comput Geosci 16:

13 Application in muscles = 0 [CHB13] [CHB13] HF Choi and SS Blemker. Skeletal muscle fascicle arrangements can be reconstructed using a Laplacian vector field simulation. PLoS One 8: e77576,

14 Application in muscles Extended approach: muscles with internal tendon tibialis anterior 0 Awkward surface geometry Difficult to mesh rectus femoris f Modify equation to indicate tendon with source term Difficult meshing avoided 14

15 Application in connective tissues Apply in different directions: 0 0 Meniscus: Multiple fibers Lateral Collateral Ligament Anterior Cruciate Ligament Lateral meniscus Simulations of knee displacement experiments with fibers isotropic 15

16 Application in connective tissues Comparison with OpenKnee model: [ERD13] OpenKnee Laplacian f1 2 f acos f 1 f 2 [ERD13]: A Erdemir. Open Knee: A pathway to community driven modeling and simulation in joint biomechanics. In proceedings of the ASME/FDA 1 st Annual Frontiers in Medical Devices,

17 Conclusions A Laplacian based approach provides a feasible collective methodological basis for multiscale tissues Advantages: Equation based = reproducible Templates, parameter tuning avoided Fast linear solvers available Independent of mesh topology Multiple attachments Limitations: Dependency on boundary conditions Further validations needed when experimental data are more available 17

18 Conclusions Impact on computer assisted intervention applications: Simulations of mechanical behavior soft tissue Incorporating fiber anisotropy needed for accurate simulation F isotropic [DEA04] A collective method for fiber modeling provides a practical strategy for implementation with broad range of usability. Important applications: Longitudinal fibers Predictive deformation modeling for surgical planning Simulations for surgical training in arthroscopy (still isotropic tissues in simulators) kneeandshoulderclinic. com [DEA04]: H Delingette and N Ayache. Soft tissue modeling for surgery simulation. In Handbook of Numerical Analysis 12 Computational methods for the human body, pp ,

19 Thank you for your attention Acknowledgements: Prof. Dr. Nadia Magnenat Thalmann (Supervisor, MSH project coordinator) All members of MIRALab, University of Geneva Institute for Media Innovation, Nanyang Technological University project European FP7 Marie Curie Actions, Initial Training Networks ITN multiscalehuman.miralab.ch 19 IMI - NTU research seminar Singapore,