Hierarchical Microimaging of Bone Structure and Function

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1 Hierarchical Microimaging of Bone Structure and Function Prof. Ralph Müller, PhD Institute for Biomechanics, ETH Zürich, Zürich, Switzerland 1 Motivation and aims Engineering endpoints have become an important factor for success in the research of living tissue Recent scientific advances require advanced 3D quantification for in vitro and in vivo functionality testing including in silico simulation techniques Present new strategies for imaging and quantification of living tissues and their structure function relationships Demonstrate importance of functional in vitro and in vivo imaging in the understanding of bone as our model system 2 1

2 Ideal imaging approach should be hierarchical organ level 500 µm structure level 50 µm tissue level 5 µm cell level 0.5 µm should be volumetric should be multi-contrast hard tissue soft tissue should be noninvasive 3 HR-CT MICRO-CT NANO-CT HIERARCHICAL IMAGING 1000 µm 100 µm 50 µm 10 µm 1 µm 100 nm 10 nm 4 2

3 Human lumbar spine Young normal Osteoporotic 5 BIOMECHANICAL IMAGING OF BONE FUNCTION 6 3

4 Motivation Constitutive laws of bone strength and bone failure behavior are limited in their general applicability due to large inhomogeneity in bone Biomechanical testing is gold standard direct mechanical testing provides detailed information on overall bone properties but fails in revealing local failure properties Incorporation of biomechanical imaging methods allows better insight into bone competence on various hierarchies of structural organization 7 8 4

5 9 10 5

6 11 Human Vertebral Bone 12 6

7 Thurner et al, Bone, Thurner et al, Bone,

8 Cortical bone imaging C3lit B6lit 2 mm 0.5 mm Mouse femur Canular void spaces within mid-diaphysis Schneider et al, JBMR, Cortical bone imaging Canals and osteocytes Mouse femur within anterior mid-diaphysis Schneider et al, JBMR, 2007 Mid-diaphysis of C3lit mouse 16 8

9 In collaboration with I. Kramer and M. Kneissel SOST KO have increased number of osteocytes WT MOUSE SOST KO 17 In collaboration with I. Kramer and M. Kneissel SOST KO have increased number of osteocytes WT MOUSE SOST KO 18 9

10 Analysis of osteocyte lacunae distribution Canals with Lacunae Canals with Lacunae Red Green z x higher lacuna density lower lacuna density z 100µm y Mader et al, J Biomech, FIB/SEM: 3D reconstruction of LCN Canaliculi Cn.V: canalicular volume Ct.TV: total cortical volume Cn.Sp: canalicular spacing Cn.SMI: canalicular structure model index + Lacunae Index Mean SD SD Total Cn.V/Ct.TV cortical [%] volume: 16.1x9.5x μm- 3 Cn.Th [nm] 95 - Nominal resolution: 19x19x30 nm 3 Cn.Sp [mm] Cn.SMI [1] Number of slices: 390 <Cn.Dm> [nm] <Cn.Le> [mm]

11 Ptychographic CT: 3D reconstruction of the LCN 7 mm Lacunae Bone tomogram Diameter of 50 mm Canaliculi Human donor (Male, 38) Volume: 58 x 58 x 32 mm 3 Voxel size: 44 x 44 x 44 nm 21 GENETICS - OF MEN AND MICE 22 11

12 Enters the Mouse Inbred strains of mice Provide large number of identical twins for linkage studies Genetically distinct Controlled environment Unique phenotype assessments Mouse genome can be manipulated to assess functional relationships High homology between mouse and human genome 23 Mouse Model B6-lit/lit C3.B6-lit/lit 0.5 mm 0.5 mm 2 mm 2 mm Schneider et al, JBMR,

13 F u [N] Three point bending 25 Bone strength is strain and gender specific *** * 0 B6-lit/lit C3.B6-lit/lit Female Male Schneider et al,

14 F u [N] <Ca.V> F [10 3 µm 3 ] u [N] 250 μm C3lit femur posterior cortex B6lit femur posterior cortex 27 Mechanostructure relationship *** * *** * B6-lit/lit C3.B6-lit/lit B6-lit/lit C3.B6-lit/lit Female Male Female Male Schneider et al, JBMR,

15 Predicted bone strength Bone strength Bone macrostructure and bone strength R 2 adj = 0.51 R 2 adj = 0.90 Macrostructure (> 100 µm) 10 0 C3.B6-lit/+ B6-lit/+ Bone size / bone mass Bone strength prediction based on macrostructure 29 Bone macrostructure and bone strength R 2 adj = 0.89 R 2 adj = 0.95 Macrostructure (> 100 µm) 10 0 C3.B6-lit/+ B6-lit/+ Measured bone strength Prediction improved by up to 75% Ultrastructure (1 10 µm) => Bone Ultrastructural strength prediction phenotypes based improve on macro- bone strength & ultrastructure prediction 30 15

16 WHAT HAPPENS ON ULTRASCALE? 31 Crack initiation and propagation Meier et al, J Biomech

17 Voide et al, Bone, 2009 C3lit femur posterior cortex 33 Microcrack initiation and propagation 3.0% 3.3% 3.6% 3.9% strain 34 17

18 Microcrack initiation and propagation B6 C3H 35 Microcrack path through lacunae C3H Voide et al, Bone,

19 Measurement of local strains strain mapping using deformable image correlation local strains reach about 15% at 4% applied strain propagation of microcracks occurs at 4-6% von Mises equivalent effective strain Christen et al, ESB D displacement and strain field Christen et al, J. Mech. Behav. Biomed. Mater.,

20 3D tensile, compressive and shear strains Christen et al, J. Mech. Behav. Biomed. Mater., Conclusions hierarchical imaging from macro to nano allows identification of ultrastructural bone features such as canals, cell lacunae and microcracks biomechanical imaging of cortical bone is valuable in studying bone failure mechanisms hierarchical investigations of bone function will lead to better understanding of osteoporotic fractures and hopefully their prevention method can also help to estimate local strains in bone for microcrack initiation and propagation 40 20

21 IN VIVO MICRO-CT FOR TIME- LAPSED IMAGING OF BONE 41 Motivation and specific aims bone strength is explained by bone mass and density, bone remodelling, bone structure and material properties today s imaging techniques can provide more micro and ultrastructural information for bone than standard bone densitometry problem: no information on in vivo bone remodeling specific aims: can we quantify and monitor bone remodeling in vivo? can we improve our strength predictions by including measures of in vivo bone remodelling? 42 21

22 In vivo monitoring of bone response to OVX female C57Bl/6 mice, 15 weeks old bilateral ovariectomy (OVX) or SHAM operation micro-ct on week 0, 2, 4, 6, 8, 10, 12 in caudal vertebra Isoflurane anesthesia vivact 40, Scanco Medical 10.5 µm voxel size image acquisition time 20 min 43 Register Align Extract Bone long structural cortical on axis previous shell parameters time point BS BV %BV MV Ct.Th Imax Full Week bone 0 Follow Cortical up time bone points 44 22

23 Extract Bone structural trabecular parameters bone BS BV BV/TV Tb.Th Tb.Sp Tb.N Full bone Trabecular bone 45 Methods Superimposing Scroll Bone dynamic through trabecular parameters images bone Bone Mineralizing formation apposition surface rate (BFR) (MAR) (MS) Bone Eroded Mineral resorption surface rate (BRR) (MRR) (ES) Week 0 Formed bone Resorbed Week 4 bone 46 23

24 Monitoring OVX induced changes Lambers et al, In vivo dynamic morphometry 48 24

25 In vivo monitoring using dynamic morphometry 49 Changes in dynamic parameters OVX SHAM BFR/BRR formation resorption constant 250 µm 250 µm Lambers et al,

26 BV/TV [%] COMBINED MECHANICAL AND PHARMACEUTICAL TREATMENT 51 Mouse model of bone adaptation (C57BL/6) Cyclic mechanical loading of the 6 th caudal vertebra (CV6, tail) 3000 cycles, 10 Hz, 8 N, 3x/week for 4 weeks [Webster et al., 2008] Weekly in vivo micro-ct measurements [Lambers et al, Bone, 2011] trabecular BV/TV CV5 CV6 CV7 Experiment week 52 26

27 Extract formation and resorption sites Register w1 (week 1) onto w0 Volumes in w0 only = resorbed Volumes in w1 only = formed formed resorbed Schulte et al, Bone, 2011 w0 w1 w2 w3 w4 53 Results trabecular thickening over time Week 0 Week

28 Mechanical environment Finite-element-modeling of week 26 E-modulus 14.8 GPa, ν = 0.3 Strain Energy Density (SED) defined as the mechanical signal. Arbenz et al, Int J Num Meth Eng, 2008 week

29 Visual comparison SED High formed resorbed Micro-CT Experiment FE Model (overlay week 0-4) (week 0) Low 57 Visual comparison SED High formed resorbed Micro-CT Experiment FE Model (overlay week 0-4) (week 0) Low 58 29

30 BV/TV (%) Visual comparison Formation SED High formed resorbed Resorption Micro-CT Experiment FE Model (overlay week 0-4) (week 0) Low 59 Bone volume fraction (BV/TV) VEH PTH BIS Age (weeks) 38 % 4 % 22 % 60 30

31 MAR (µm/d) MS (%) MRR (µm/d) ES (%) MAR (µm/d) MS (%) MRR (µm/d) ES (%) Dynamic bone morphometry Bisphosphonates * Control BIS * p < 0.05 Parathyroid hormone * * * Control PTH 61 Mechanoregulation in VEH SED formed > * * SED quiescent > SED resorbed Bone forms new bone where needed and resorbs it where not needed mechanically. formation sites quiescent resorption sites sites * p <

32 Mechanoregulation in BIS SED formed > * * SED quiescent > SED resorbed Similar as in VEH, adaptation is targeted to mechanical strains. formation sites quiescent resorption sites sites * p < Mechanoregulation in PTH SED formed > SED quiescent = * n.s. SED resorbed PTH produces targeted formation patterns similar to VEH leads to an increase in nontargeted bone resorption. formation sites quiescent resorption sites sites * p <

33 Conclusions time-lapsed in vivo imaging allows monitoring of microstructural properties in live animals strength assessment in live animals determination of dynamic bone remodelling parameters such as bone formation rate and bone resorption rate mechanical loading is an anabolic treatment regimen and often synergistic with other pharmaceutical interventions BIS increases bone mass by decreasing resorption depth while PTH increases bone mass by increasing mineralizing surfaces with deeper but less resorption cavities BIS does not interfere with mechanoregulation but does not add synergistic gains in bone mass PTH interferes with mechanoregulation by increasing nontargeted resorption but is highly synergistic