Fluid flow shear stress is postulated to be a mechano stimulator of osteocytes. As direct measurement is not an option, confocal image derived models of osteocytes are a valuable tool for conducting computational fluid dynamics analysis to evaluate fluid flow sheer stresses on the osteocyte dendritic membranes. Some of the work done in our lab corresponds to the recent developments in the field where actual osteocyte lacunae morphology, including the tortuosity and density of dendrites, are used along with the bone and lacunar-canalicular network in order to numerically determine the fluid flow shear stress and locations in the osteocyte dendritic structure where the stress is high.
Current technologies include various computational modelings, such as final element analysis, computational fluid dynamics, fluid structure interaction, image-based modeling, including X-Ray or confocal microscope for accurate 3D models and by mechanical testing systems to validate the models by measuring bone responses such as strains under control loading conditions. Our findings indicate that loss of dendrites due to aging or bone disease is a factor in bones becoming less responsive to physical activity. We predicted that osteocytes detect mechanical loads through high fluid flow shear stress regions which are dendrites.
And fluid flow shear stress is correlated to like lacunar morphology, especially surface area. With the establishment of this protocol, we are now working on an NIH project to study the fluid flow shear stress in the osteocyte dendrites of mice bones of two different ages and sexes. This study will help determine how aging and sex differences affect the mechano transduction in bone due to loading.
To begin, fix the femur collected from the mouse in cold 4%paraformaldehyde in phosphate-buffered saline for 24 hours at four degrees Celsius with gentle rocking. The next day, rinse the bone and phosphate-buffered saline and embed it quickly in a fast polymerizing acrylic. Cut thick 300-micrometer transverse slices above the third trochanter.
Using sandpaper, polish the bone sections to a final thickness of 90 to 100 micrometers. Then rinse the polished sections in 70%95%and 100%ethanol for five minutes each. Stain the sections in 1%fit C in 100%ethanol for four hours in the dark with moderate shaking.
Next, wash the sections thoroughly in 100%ethanol. And air dry them overnight before placing them into a drop of mounting media on a glass slide. Mount a cover slip on the specimen.
On a confocal microscope, Set a 488-nanometer laser for excitation and an emission collection window of 496 to 596 nanometers. First, capture a low power image of the entire bone section using the 5x objective. Then capture images of the three regions of interest using the 20x objective.
Use a 100x 1.44 numerical aperture oil objective with a digital zoom of 1.7 and a step size of 0.126 micrometers to collect detailed Z stacks of 400 Z planes at 1024 by 1024 pixels and 0.089 micrometer pixel resolution. For computer modeling of mouse osteocytes, open the ImageJ software after importing collected Z stack images of the mouse femur in TIFF format, adjust the threshold in the section menu to change pixel intensity limits for inclusion in a mask. Using the crop mask operation, crop one lacuna with its canaliculi as the region of interest.
Encase the lacuna in an imaginary bigger cube with side lengths of 21, 14 and 19 micrometers. Perform a region grow operation to select the connected pixel regions to generate a uniform lacunar-canalicular network or LCN. Next, using the calculated part operation, convert the lacunar-canalicular mask into an object.
Reduce the LCN volume using the smoothing operation to build the osteocyte and dendritic membranes. Then export the objects. Combine two surfaces of the LCN and osteocyte dendritic membranes into one surface.
Now, use the remesh operation to create a volumetric model of the lacunar canalicular space. Export the model as an STL file and adjust the object scale to micrometers. In a three-dimensional image-based processing software, choose the volumetric model of the mouse lacunar-canalicular space as the base model to build distinct osteocyte models.
Select a lower threshold to reduce the light intensity of the image and obtain a lacuna with fewer canaliculi. Next, develop osteocyte models with different lacunar-canalicular space thicknesses or dendrite canalicular diameters. Build larger or smaller osteocyte models using wrapping or smoothing operations respectively.
To create a fluid flow in the simulation software, import the developed confocal image-based geometries into the CFX software. Set the unit dimensions to nanometers. Next, click on subtract to achieve a single body of lacunar canicular space.
Right-click on the generated facet and convert it from facets to a solid domain without merging faces. Click on mesh and select linear tetrahedral elements with an element size of 0.06 micrometers. Refine the mesh with a mesh convergence study.
Now, select the surface and choose the canaliculi on the top side of the imaginary cube as fluid inlets. Using box, choose the canaliculi on the other five faces as fluid outlets. Then export the mesh.
After creating another fluid flow, import the fluent mesh into the setup section of CFX. Using the insert boundary option, define two boundary conditions of inlets and outlets for the faces. Exert a fluid inlet pressure of 300 and zero pascals on the inlets and outlets respectively.
Treat the remaining surfaces as walls with a no-slip condition. From the material library, treat the interstitial laminar fluid as water. Set the heat transfer, combustion, and thermal radiation sections to none.
Select turbulence as the fluid characteristic in the LCN. Next, run the software using double precision and direct start as the submission type. Insert a new contour in the results section of the CFD software.
Create a fluid flow shear stress or FFSS contour by choosing the wall shear on the osteocyte dendritic membranes as the variable at the domain. Next, insert a velocity streamlines contour inside the lacunar-canalicular domain starting from the inlets. The average FFSS on osteocyte and dendritic membranes in the young osteocyte model was 0.42 Pascal, which was significantly higher than 0.13 Pascal in the aged osteocyte model.
FFSS increased in osteocytes with larger lacunar canalicular space as seen in model seven and model eight where model eight displayed the highest FFSS. The lowest FFSS values of 0.19 Pascal and 0.13 Pascal were observed in model two and model four respectively with the lowest canalicular density. No significant change in FFSS was observed with increased dendrite diameter as seen in models five and six.
