Funding from the Australian Research Council (FT180100338; IC190100020) is gratefully acknowledged.

The protocol was developed and tested with 12 femur specimens received from a body donation program. The specimens were obtained fresh and stored at &#8722;20 &#176;C at the Biomechanics and Implants Laboratory of Flinders University (Tonsley, South Australia, Australia). Bone moisture was maintained throughout the experiment. The donors were Caucasian women (66-80 years of age). Ethics clearance was obtained from the Social and Behavioural Research Ethics Committee (SBREC) of Flinders University (Project # 6380).
1. Planning a specimen-specific load step increment
<ol>
	<li>Scan the femur specimen using a clinical CT scanner targeting a slice thickness and an in-plane pixel size of approximately 0.5-0.7 mm. This step can be completed by an expert radiographer at any public imaging facility using standard pre-recorded imaging protocols for bone visualization.</li>
	<li>Together with the specimen, scan a CT densitometry calibration phantom with five known concentrations of dipotassium hydrogen phosphate (K2HPO4, equivalent density range approximately between 59 mg&#8729;cm&#8722;3 and 375 mg&#8729;cm&#8722;3).</li>
	<li>Segment the bone geometry from the clinical CT images15, mesh the segmented geometry of the bone, and map the isotropic material properties element by element to the calibrated bone density values by using the density-to-elastic modulus relationship reported by Schileo et al.8. Save the mesh for further analysis in the finite-element software. Complete each step by following the relevant guidelines provided with the segmentation and finite-element software.</li>
	<li>Import the mesh into the finite-element software. Fully constrain the 3-6 mm distal end of the model. Apply a nominal force of 1,000 N, adducted by 8&#176; from the femoral shaft axis in the coronal plane and passing through the center of the femoral head. This loading condition mimics a static one-leg stance task (orthoload.com).</li>
	<li>Solve the finite-element model using the built-in PCG solver (convergence tolerance: 1 x 10&#8722;7). 
	&#8203;NOTE: Here the finite element software ANSYS was used.
	<ol>
		<li>Generate an element table containing the first and third principal strain components at the element centroid by executing the following commands: 
		/POST1 
		ETABLE,, EPTO1,1 
		&#8203;ETABLE,, EPTO3,3</li>
		<li>Calculate the strain ratio between the first and third principal strain components in the model and the bone yield strain in tension (0.73% strain) and compression (1.04% strain)8 (Figure 1) by executing the following commands: 
		SMULT,RFT,EPTO1, ,1/0.0074,1, 
		SMULT, RFT,EPTO3, ,1/0.0104,1,</li>
	</ol>
	</li>
	<li>Scale the nominal force by the peak strain ratio in both tension and compression, and discard the biggest of the two in order to obtain an estimate of the fracture load. Determine the load increment as 1/4 of the calculated fracture load1.</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64947/64947fig01.jpg" /> 
Figure 1: The calculation of the fracture load. The finite-element strain map, the equations used to convert the nominal force into the fracture load (left), and the loading scheme displaying the femur (center right), the distal aluminum (top right) cup, and the polyethylene pressure socket (bottom right). <a href="https://www.jove.com/files/ftp_upload/64947/64947fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
2. Preparation of the femur specimen assembly (Figure 2)
<ol>
	<li>Remove the specimen from the freezer (&#8722;20 &#176;C).</li>
	<li>Thaw at room temperature (RT) for 24 h while keeping the specimen in a waterproof plastic bag wrapped in absorbent material soaked in a physiological solution to maintain the bone moisture.</li>
	<li>Cut the femoral diaphysis at 180 mm from the proximal femoral head.</li>
	<li>Center the femoral head on the vertical axis of the alignment rig by aligning the concave-shaped polyethylene pressure socket (Figure 2D) and the femur head.</li>
	<li>Align the plane containing the femoral neck and the diaphysis axis with the frontal plane&#160;(Figure 2).</li>
	<li>Rotate the diaphyseal axis to 8&#176; adduction so that the vertical axis represents the orientation of the hip reaction force during a static single-leg stance (Figure 2).</li>
	<li>Prepare the dental cement by following&#160;manufacturer&#39;s instructions.</li>
	<li>Pot the distal end of the specimen in an aluminum potting cup that is 55 mm deep, filling up the aluminium cup with dental cement. Allow no less than 30 min for the cement to complete curing.</li>
	<li>Store the specimen assembly at &#8722;20 &#176;C.</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64947/64947fig02.jpg" /> 
Figure 2: The alignment rig. A frontal (left) and lateral (right) photo of the alignment rig displaying (A) the frame, (B) the aluminum potting cup, (C) a synthetic femur model, and (D) the spherically shaped pressure socket. <a href="https://www.jove.com/files/ftp_upload/64947/64947fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Compression stage assembly
NOTE: The compression stage&#39;s external dimensions are 245 mm diameter, 576 mm height, and 14 kg weight, excluding the sample. The compression stage consists of two main parts: the compression chamber and the actuator, which are assembled as follows:
<ol>
	<li>Compression chamber
	<ol>
		<li>Mount the polyethylene pressure socket (104 mm diameter, 60 mm height) at the bottom of the aluminum cylinder (203 mm diameter, 3 mm wall thickness), which is closed by a welded aluminum plate at one end (bottom).</li>
	</ol>
	</li>
	<li>Actuator
	<ol>
		<li>Assemble the top structure using the disk, the three rods, the triangular plate, and the vertical rail (Figure 3).</li>
		<li>Mount the screw-jack mechanism (stroke: 150 mm, maximal load: 10,000 N, gear ratio: 27:1, displacement per revolution: 0.148 mm) on the triangular plate.</li>
		<li>Mount the angular adaptor onto the linear rail.</li>
		<li>Mount the low-friction x-y table onto the angular adaptor.</li>
		<li>Mount the six degrees of freedom load cell (maximal measurement error: 0.005%; maximal force: 10,000 N; maximal torque: 500 Nm) onto the low-friction table by aligning the x-z plane of the load cell to the frontal plane of the top structure.</li>
		<li>Connect the actuator screw to the angular adaptor.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64947/64947fig03.jpg" /> 
Figure 3: The custom-made radiotransparent compression stage assembly. A photo (left) and a model (right) of the compressive stage. (A) The compression chamber, which is a 3 mm thick aluminium cylinder closed at the bottom; (B) the actuator assembly with the top structure; (C) the screw-jack mechanism; (D) the low-friction x-y table; and (E) the six-axis load cell are displayed and indicated on the model. <a href="https://www.jove.com/files/ftp_upload/64947/64947fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
4. Setting up the experiment
<ol>
	<li>Thaw the specimen at RT for 24 h while keeping it in a waterproof plastic bag wrapped in absorbent material soaked in a physiological solution to maintain the bone moisture.</li>
	<li>Mount the aluminium cup specimen assembly to the load cell by aligning the frontal plane of the specimen assembly with that of the actuator.</li>
	<li>Assemble the top structure, including the specimen, into the compression chamber. Take care to align the femoral head with the spherical concavity on the polyethylene pressure socket. Ensure that the femoral head is engaged but slack within the spherical cavity of the pressure socket.</li>
	<li>Place the compressive stage on the rotation stage of the micro-CT scanner at Imaging and Medical Beamline (IMBL).</li>
	<li>Connect the load cell (error &#60; 0.005%; maximum force: 10,000 N; maximum torque: 500 Nm) to the strain amplifier.</li>
	<li>Connect, via USB, the strain amplifier to a laptop computer equipped with the application software provided with the load cell.</li>
	<li>Actuate the screw mechanism in the compression stage by moving the specimen downward toward the pressure socket while monitoring the reaction force measured by the load cell in the laptop. Stop the screw mechanism once a compression force equal to 100 N is achieved. Unload the specimen to 50 N pre-load.</li>
	<li>Select the single pco.edge sensor lens-coupled scintillator &#34;Ruby&#34; (http://archive.synchrotron.org.au/31-australian-synchrotron/imbl/811-preparation-for-imaging-experiments).</li>
	<li>Set the field of view to 76.31 mm x 64.39 mm, which for the 2,560 pixels x 2,160 pixels array size provides a pixel size of 29.81 &#956;m.</li>
	<li>Set the axis of the rotating stage to 8 mm (horizontally) from the axis of the field of view (off-set scanning mode) to extend the field of view to 145.71 mm x 64.39 mm at a pixel size of 29.81 &#956;m.</li>
	<li>Set the scanning parameters to a beam energy of 60 keV, a rotational increment of 0.1&#176;, two batches of 180&#176; rotation (off-set scanning), an exposure time of 50 &#956;s, and a frame-averaging of two per rotational position.</li>
	<li>Set the scan to acquire five consecutive, vertically stacked scans, with a 26 mm vertical shift each, so that the total height of the scanned volume is 132.2 mm for a total scanning time of 30 min.</li>
</ol>
5. Mechanical testing with concomitant microstructural imaging
<ol>
	<li>Perform micro-CT (pixel size: 0.03 mm) imaging twice in the reference condition (taken as a zero-strain condition).</li>
	<li>Apply the force increment by manually actuating the screw-jack mechanism at a constant rate of approximately 1&#160;s per round (0.1-0.2 mm/s).</li>
	<li>Perform micro-CT imaging.</li>
	<li>Repeat step 5.2 and step 5.3 up to causing the fracture of the specimen, as indicated by a sudden drop in the reaction force.</li>
	<li>Perform micro-CT imaging of the fractured specimen.</li>
	<li>Stitch the 1,800 projection images (2,560 pixels x 896 pixels in size, 76.8 mm x 26.88 mm, width x height, 32-bit floating point images). The process stitches two projection images (taken in horizontal off-set scanning mode), and the five vertically shifted images, hence&#160;producing&#160;a single projection image.
	<ol>
		<li>Reconstruct the volume of the cross-section images (4,407 images, each image 4,888 x 4,888 pixels in size), and save them as 32-bit, floating point files in .TIFF format (occupying 392 GB of disk space).</li>
		<li>Apply a 3 x 3 Gaussian filter to reduce noise. Convert the images into 8-bit (256 greylevel images, saved in bitmap format, occupying approximately 100 GB per volume). 
		&#8203;NOTE: In this work, the processing of the images was conducted using software available at the Australian Synchrotron under the guidance of the operator of the IMBL.</li>
	</ol>
	</li>
</ol>
6. Calculation of the displacement and strain field
<ol>
	<li>Subsample the cross-section images by four (120 &#956;m/pixel) to reduce the computation time.</li>
	<li>Rigidly co-register in space the images of the specimen under load to those of the specimen in the unloaded reference condition. Use the distal diaphysis as the target of the co-registration (Supplementary File 1 and Supplementary File 2).</li>
	<li>Create surface three-dimensional models (.STL files) for visualization after binarizing the micro-CT images11.</li>
	<li>Elastically register the image volume to the reference volume using a grid size equal to 50 pixels (SDER = 0.076% strain error, BoneDVC,&#160;https://bonedvc.insigneo.org/dvc/) to determine the displacements at the nodes of the grid.</li>
	<li>Convert the grid into a finite-element model. Apply the nodal displacement calculated by BoneDVC to the model. Solve the model to determine the strain tensor over the entire bone volume.</li>
	<li>Repeat the analysis in the region showing the highest strain levels using the full-resolution images.</li>
	<li>Map the DVC strain maps to the full-resolution images using cubic interpolation with the interp3 function (Matlab)2.</li>
	<li>Visualize the displacements, strain, and microstructural images for large-volume visualization and animation (Matlab)2.</li>
</ol>
7. Analysis
<ol>
	<li>Display the permanent deformation of the bone (damage) by overlaying the images obtained in the unloaded conditions and after the fracture2.</li>
	<li>Display the progressive microstructural deformation of the bone by overlaying the three-dimensional models in unloaded conditions, at increasing load levels, and post-fracture2.</li>
	<li>Display the strain of the bone at the fracture location2.</li>
	<li>Analyze the deformation energy, stiffness, and displacement using descriptive statistics and regression methods2.</li>
</ol>

<ol>
	<li>Martelli, S., Perilli, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time-elapsed+synchrotron-light+microstructural+imaging+of+femoral+neck+fracture.">Time-elapsed synchrotron-light microstructural imaging of femoral neck fracture.</a> Journal of the Mechanical Behavior of Biomedical Materials. 84, 265-272 (2018).</li><li>Martelli, S., Giorgi, M., Dall' Ara, E., Perilli, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Damage+tolerance+and+toughness+of+elderly+human+femora.">Damage tolerance and toughness of elderly human femora.</a> Acta Biomaterialia. 123, 167-177 (2021).</li><li>Perilli, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dependence+of+mechanical+compressive+strength+on+local+variations+in+microarchitecture+in+cancellous+bone+of+proximal+human+femur.">Dependence of mechanical compressive strength on local variations in microarchitecture in cancellous bone of proximal human femur.</a> Journal of Biomechanics. 41 (2), 438-446 (2008).</li><li>Thurner, P. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time-lapsed+investigation+of+three-dimensional+failure+and+damage+accumulation+in+trabecular+bone+using+synchrotron+light.">Time-lapsed investigation of three-dimensional failure and damage accumulation in trabecular bone using synchrotron light.</a> Bone. 39 (2), 289-299 (2006).</li><li>Jackman, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative,+3D+visualization+of+the+initiation+and+progression+of+vertebral+fractures+under+compression+and+anterior+flexion.">Quantitative, 3D visualization of the initiation and progression of vertebral fractures under compression and anterior flexion.</a> Journal of Bone and Mineral Research. 31 (4), 777-788 (2016).</li><li>Mayhew, P. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relation+between+age,+femoral+neck+cortical+stability,+and+hip+fracture+risk.">Relation between age, femoral neck cortical stability, and hip fracture risk.</a> Lancet. 366 (9480), 129-135 (2005).</li><li>Nazarian, A., Stauber, M., Zurakowski, D., Snyder, B. D., M&#252;ller, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+interaction+of+microstructure+and+volume+fraction+in+predicting+failure+in+cancellous+bone.">The interaction of microstructure and volume fraction in predicting failure in cancellous bone.</a> Bone. 39 (6), 1196-1202 (2006).</li><li>Schileo, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=To+what+extent+can+linear+finite+element+models+of+human+femora+predict+failure+under+stance+and+fall+loading+configurations.">To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations.</a> Journal of Biomechanics. 47 (14), 3531-3538 (2014).</li><li>Schileo, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+accurate+estimation+of+bone+density+improves+the+accuracy+of+subject-specific+finite+element+models.">An accurate estimation of bone density improves the accuracy of subject-specific finite element models.</a> Journal of Biomechanics. 41 (11), 2483-2491 (2008).</li><li>Dall'ara, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+nonlinear+QCT-based+finite+element+model+validation+study+for+the+human+femur+tested+in+two+configurations+in+vitro.">A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro.</a> Bone. 52 (1), 27-38 (2013).</li><li>Perilli, E., Parkinson, I. H., Reynolds, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro-CT+examination+of+human+bone:+from+biopsies+towards+the+entire+organ.">Micro-CT examination of human bone: from biopsies towards the entire organ.</a> Annali dell'Istituto Superiore di Sanit&#224;. 48 (1), 75-82 (2012).</li><li>Wearne, L. S., Rapagna, S., Taylor, M., Perilli, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro-CT+scan+optimisation+for+mechanical+loading+of+tibia+with+titanium+tibial+tray:+A+digital+volume+correlation+zero+strain+error+analysis.">Micro-CT scan optimisation for mechanical loading of tibia with titanium tibial tray: A digital volume correlation zero strain error analysis.</a> Journal of the Mechanical Behavior of Biomedical Materials. 134, 105336 (2022).</li><li>Bennett, K. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ex+vivo+assessment+of+surgically+repaired+tibial+plateau+fracture+displacement+under+axial+load+using+large-volume+micro-CT.">Ex vivo assessment of surgically repaired tibial plateau fracture displacement under axial load using large-volume micro-CT.</a> Journal of Biomechanics. 144, 111275 (2022).</li><li>Falcinelli, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+loading+conditions+analysis+can+improve+the+association+between+finite+element+bone+strength+estimates+and+proximal+femur+fractures:+A+preliminary+study+in+elderly+women.">Multiple loading conditions analysis can improve the association between finite element bone strength estimates and proximal femur fractures: A preliminary study in elderly women.</a> Bone. 67, 71-80 (2014).</li><li>Orthopedic Image Segmentation. Synopsys Available from: <a target="_blank" href="https://www.synopsys.com/simpleware/news-and-events/ortho-medical-image-segmentation.html">https://www.synopsys.com/simpleware/news-and-events/ortho-medical-image-segmentation.html</a> (2020)</li></ol>

All the authors declare no conflicts of interest.

The present protocol allows for studying the time-elapsed micromechanics of hip fractures in three dimensions ex vivo. A radiotransparent (aluminium) compressive stage&#160;capable of applying a progressive deformation to the proximal half of the human femur and measuring the reaction force has been custom-designed, manufactured, and tested. A large-volume micro-CT scanner is employed in this protocol to provide a temporal sequence of image volumes displaying the entire proximal femur with progressive loading at...

Fractures of the femoral neck are a major burden to the aging population. Micro-computed tomography (micro-CT) imaging and concomitant mechanical testing&#160;allow for observing the bone microstructure and studying its relationship to bone strength, its age-related changes, and displacements under load1,2. However, until recently, micro-CT studies of bone under load were limited to excised bone cores3, small animals4, and human spine units5. The present protocol can quantify the displacement of the microstructure of the entire proximal human femur under load and after a fracture.
Several studies have been conducted to investigate the failure of the human femur, and at times, these have reached contrasting conclusions. For example, the age-related thinning of the cortical and trabecular structures is thought to determine the age-related susceptibility to fracture by causing elastic instability of the bone6,7, which is in apparent contrast with the high coefficient of determination of cortical strain and femoral strength predictions assuming no elastic instability (R2 = 0.80-0.97)8,9. Nevertheless, such studies have systematically underestimated the femoral strength (by 21%-29%), thus bringing into question the brittle and quasi-brittle bone responses implemented in the models8,10. One possible explanation for these apparently contrasting findings may reside in a different fracture behavior of entire bones compared to isolated bone cores. Therefore, observing the deformation and fracture responses of the bone microstructure in entire proximal femurs may advance knowledge of hip fracture mechanics and related applications.
Current methods for imaging entire human bones with micrometric resolution are limited. The gantry and the detector size must provide a suitable working volume to host the human proximal femur (approximately 13 cm x 10 cm, width x length) and possibly a pixel size in the order of 0.02-0.03 mm to ensure that relevant micro-architectural features can be captured11. These specifications can currently be met by some synchrotron facilities1 and some commercially available large-volume micro-CT scanners12,13. The compressive stage has to be radio-transparent in order to minimize X-ray attenuation while generating a force sufficient for causing a fracture to the human femur (e.g., between 0.9 kN and 14.3 kN for elderly white women)14. This large fracture load variation complicates the planning of the number of load steps to fracture, the overall experiment time, and the corresponding amount of data produced. To address this problem, the fracture load and location can be estimated via finite-element modeling by using the bone density distribution of the specimen from clinical computed tomography (CT) images1,2. Finally, after the experiment, the large volume of data generated needs to be processed for studying the failure mechanisms and energy dissipation capacity in the entire human femur.
Here, we describe a protocol for obtaining a sequence of three-dimensional microstructural images of the entire proximal femur under progressively increasing deformation, which causes clinically relevant fractures of the femoral neck2. The protocol includes planning the stepwise increment&#160;of the specimen compression, loading via a custom radio-transparent compressive stage, imaging via a large-volume micro-CT scanner, and processing the images and the load profiles.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Absorbent tissue</td>
			<td>N/A</td>
			<td></td>
			<td>Maintain the bone moisture throughout the experiment</td>
		</tr>
		<tr>
			<td>Alignment rig</td>
			<td>Custom-made</td>
			<td></td>
			<td>Rig for positioning the specimen in the potting cup</td>
		</tr>
		<tr>
			<td>Aluminium potting cup</td>
			<td>Custom-made</td>
			<td></td>
			<td>Potting cup</td>
		</tr>
		<tr>
			<td>Bone saw</td>
			<td>N/A</td>
			<td></td>
			<td>Cut the specimen to size</td>
		</tr>
		<tr>
			<td>Calibration phantom QCT Pro</td>
			<td>Mindways Software, Inc., Austin, USA</td>
			<td>CT Calibration 13002</td>
			<td>Calibrate grey levels in the images into equivalent bone mineral (ash) density levels</td>
		</tr>
		<tr>
			<td>Clinical Computed-Tmography scanner</td>
			<td>General Electric Medical Systems Co., Wisconsin, USA</td>
			<td>Optima CT660</td>
			<td>Preliminary imaging for the prediction of the load step to fracture</td>
		</tr>
		<tr>
			<td>Compressive stage</td>
			<td>Custom-made</td>
			<td></td>
			<td>A 10 kg, radiotransparent compressive stage for applying and maintaining throught imaging a prescribed deformation to the specimen.</td>
		</tr>
		<tr>
			<td>Dental cement</td>
			<td>Soesterberg, The Netherlands</td>
			<td>Vertex RS</td>
			<td></td>
		</tr>
		<tr>
			<td>Femur specimen</td>
			<td>Science Care, Phoenix, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Finite-element analysis software</td>
			<td>ANSYS Inc., Canonsburg, USA</td>
			<td>ANSYS Mechanical APDL</td>
			<td>Finite-element software package</td>
		</tr>
		<tr>
			<td>Freezer</td>
			<td>N/A</td>
			<td></td>
			<td>Store specimens at -20 &#176;C</td>
		</tr>
		<tr>
			<td>Hard Drive</td>
			<td>Dell</td>
			<td></td>
			<td>Disk space: 500 GB per volume</td>
		</tr>
		<tr>
			<td>Image bnarization and segmentation software</td>
			<td>Skyscan-Bruker, Kontich, Belgium</td>
			<td>CT analyzer</td>
			<td>Image processing software</td>
		</tr>
		<tr>
			<td>Image elastic segmentation</td>
			<td>The University of Sheffield</td>
			<td>Bone DVC</td>
			<td>https://bonedvc.insigneo.org/dvc/</td>
		</tr>
		<tr>
			<td>Image processing and automation software</td>
			<td>The MathWork Inc.</td>
			<td>Matlab</td>
			<td>Image processing software</td>
		</tr>
		<tr>
			<td>Image registration software</td>
			<td>Skyscan-Bruker, Kontich, Belgium</td>
			<td>DataViewer</td>
			<td>Image processing software</td>
		</tr>
		<tr>
			<td>Image segmentation and FE modelling software</td>
			<td>Simpleware, Exeter, UK</td>
			<td>Scan IP</td>
			<td>Bone egmentation software</td>
		</tr>
		<tr>
			<td>Image stiching script</td>
			<td>Australian syncrotron, Clayton, VIC, AU</td>
			<td></td>
			<td>The script is available at IMBL</td>
		</tr>
		<tr>
			<td>Image visualization</td>
			<td>Kitware, Clifton Park, NY, USA</td>
			<td>Paraview</td>
			<td>Image visualization</td>
		</tr>
		<tr>
			<td>Image visualization</td>
			<td>Australian National University</td>
			<td>Dristhi</td>
			<td>Image visualization: doi:10.1117/12.935640</td>
		</tr>
		<tr>
			<td>Imaging and Medical beamline</td>
			<td>Australian syncrotron, Clayton, VIC, AU</td>
			<td></td>
			<td>Large object micro-CT beamline at the Australian Synchrotron</td>
		</tr>
		<tr>
			<td>Laptop</td>
			<td>Dell Inc., USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Low-friction x-y table</td>
			<td>THK Co., Tokyo, Japan</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>NI signal acquisition software</td>
			<td>National Instruments, Austin, TX</td>
			<td>NI-DAQmx</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate-buffered saline solution</td>
			<td>Custom-made</td>
			<td></td>
			<td>Maintain the bone moisture throughout the experiment</td>
		</tr>
		<tr>
			<td>Plastic bag</td>
			<td>N/A</td>
			<td></td>
			<td>Maintain the bone moisture throughout the experiment</td>
		</tr>
		<tr>
			<td>Rail</td>
			<td>SKF Inc., Lansdale, PA, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Screw-jack mechanism</td>
			<td>&#160;Benzlers, &#214;rebro, Sweden</td>
			<td>Serie BD (warm gear unit)</td>
			<td>stroke: 150 mm, maximal load: 10,000 N, gear ratio: 27:1, a displacement per revolution: 0.148 mm</td>
		</tr>
		<tr>
			<td>Single pco.edge sensor, lens coupled scintillator</td>
			<td>Australian syncrotron, Clayton, VIC, AU</td>
			<td></td>
			<td>Detector Ruby FOV: 141 x 119 mm; 2560 x 2160 px; 55 &#181;m/px; 50 fps</td>
		</tr>
		<tr>
			<td>Six axis load cell</td>
			<td>ME-Me&#223;systeme GmbH, Hennigsdorf, GE</td>
			<td>K6D6</td>
			<td>Maximal measurement error: 0.005%; maximal force: 10000 N; maximal torque: 500 Nm</td>
		</tr>
		<tr>
			<td>Strain amplifier</td>
			<td>ME-Me&#223;systeme GmbH, Hennigsdorf, GE</td>
			<td>GSV-1A8USB K6D/M16</td>
			<td></td>
		</tr>
	</tbody>
</table>

imaging of the microstructural failure mechanism in the human hip

Imaging the bone microstructure under progressively increasing loads allows for observing the microstructural failure behavior of bone. Here, we describe a protocol for obtaining a sequence of three-dimensional microstructural images of the entire proximal femur under progressively increasing deformation, causing clinically relevant fractures of the femoral neck. The protocol is demonstrated using four femora from female donors aged 66-80 years at the lower end of bone mineral density in the population (T-score range = &#8722;2.09 to &#8722;4.75). A radio-transparent compressive stage was designed for loading the specimens replicating a one-leg stance, while recording the applied load during&#160;micro-computed tomography (micro-CT) imaging. The field of view was 146 mm wide and 132 mm high, and the isotropic pixel size was 0.03 mm. The force increment was based on finite-element predictions of the fracture load. The compressive stage was used to apply the displacement to the specimen and enact the prescribed force increments. Sub-capital fractures due to opening and shear of the femoral neck occurred after four to five load increments. The micro-CT&#160;images and the reaction force measurements were processed to study the bone strain and energy absorption capacity. Instability of the cortex appeared at the early loading steps. The subchondral bone in the femoral head displayed large deformations reaching 16% before&#160;fracture, and a progressive increase in the support capacity up to&#160;fracture. The deformation energy linearly increased with the displacement up to&#160;fracture, while the stiffness decreased to near-zero values immediately before&#160;fracture. Three-fourths of the fracture energy was taken by the specimen during the final 25% force increment. In conclusion, the protocol developed revealed a remarkable energy absorption capacity, or damage tolerance, and a synergic interaction between the cortical and trabecular bone at an advanced donor age.

The images display the entire proximal femur, the pressure socket, the dental cement, the aluminum cup, and the wrapping tissue. The bone micro-architecture can be seen progressively deforming as the load increases before fracture and after fracture (Figure 4).
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/64947/64947fig04.jpg" /> 
Figure 4: The compressive stage con...

Watch this Scientific Journal Video about Imaging of the Microstructural Failure Mechanism in the Human Hip at JoVE.com

Imaging of the Microstructural Failure Mechanism in the Human Hip

The protocol enables the measurement of the deformation of the bone microstructure in the entire proximal human femur and its toughness by combining large-volume micro-CT scanning, a custom-made compressive stage, and advanced image processing tools.

Imaging the bone microstructure under progressively increasing loads allows for observing the microstructural failure behavior of bone. Here, we describe ...

imaging-of-the-microstructural-failure-mechanism-in-the-human-hip

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710 Views.  Queensland University of Technology. The protocol enables the measurement of the deformation of the bone microstructure in the entire proximal human femur and its toughness by combining large-volume micro-CT scanning, a custom-made compressive stage, and advanced image processing tools. 

Video: Imaging of the Microstructural Failure Mechanism in the Human Hip

Spatial Separation of Molecular Conformers and Clusters

Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold molecular beams. However, these beams often contain multiple conformers and clusters, even at low rotational temperatures. We present an experimental methodology that allows the spatial separation of these constituent parts of a molecular beam expansion. Using an electric deflector the beam is separated by its mass-to-dipole moment ratio, analogous to a bender or an electric sector mass spectrometer spatially dispersing charged molecules on the basis of their mass-to-charge ratio. This deflector exploits the Stark effect in an inhomogeneous electric field and allows the separation of individual species of polar neutral molecules and clusters. It furthermore allows the selection of the coldest part of a molecular beam, as low-energy rotational quantum states generally experience the largest deflection. Different structural isomers (conformers) of a species can be separated due to the different arrangement of functional groups, which leads to distinct dipole moments. These are exploited by the electrostatic deflector for the production of a conformationally pure sample from a molecular beam. Similarly, specific cluster stoichiometries can be selected, as the mass and dipole moment of a given cluster depends on the degree of solvation around the parent molecule. This allows experiments on specific cluster sizes and structures, enabling the systematic study of solvation of neutral molecules.

We present a technique that allows the spatial separation of different conformers or clusters present in a molecular beam. An electrostatic deflector is used to separate species by their mass-to-dipole moment ratio, leading to the production of gas-phase ensembles of a single conformer or cluster stoichiometry.

Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold ...

Fast Imaging Technique to Study Drop Impact Dynamics of Non-Newtonian Fluids

In the field of fluid mechanics, many dynamical processes not only occur over a very short time interval but also require high spatial resolution for detailed observation, scenarios that make it challenging to observe with conventional imaging systems. One of these is the drop impact of liquids, which usually happens within one tenth of millisecond. To tackle this challenge, a fast imaging technique is introduced that combines a high-speed camera (capable of up to one million frames per second) with a macro lens with long working distance to bring the spatial resolution of the image down to 10 &#181;m/pixel. The imaging technique enables precise measurement of relevant fluid dynamic quantities, such as the flow field, the spreading distance and the splashing speed, from analysis of the recorded video. To demonstrate the capabilities of this visualization system, the impact dynamics when droplets of non-Newtonian fluids impinge on a flat hard surface are characterized. Two situations are considered: for oxidized liquid metal droplets we focus on the spreading behavior, and for densely packed suspensions we determine the onset of splashing. More generally, the combination of high temporal and spatial imaging resolution introduced here offers advantages for studying fast dynamics across a wide range of microscale phenomena.

Drop impact of non-Newtonian fluids is a complex process since different physical parameters influence the dynamics over a very short time (less than one tenth of a millisecond). A fast imaging technique is introduced in order to characterize the impact behaviors of different non-Newtonian fluids.

In the field of fluid mechanics, many dynamical processes not only occur over a very short time interval but also require high spatial resolution for ...

Ambient Method for the Production of an Ionically Gated Carbon Nanotube Common Cathode in Tandem Organic Solar Cells

A method of fabricating organic photovoltaic (OPV) tandems that requires no vacuum processing is presented. These devices are comprised of two solution-processed polymeric cells connected in parallel by a transparent carbon nanotubes (CNT) interlayer. This structure includes improvements in fabrication techniques for tandem OPV devices. First the need for ambient-processed cathodes is considered. The CNT anode in the tandem device is tuned via ionic gating to become a common cathode. Ionic gating employs electric double layer charging to lower the work function of the CNT electrode. Secondly, the difficulty of sequentially stacking tandem layers by solution-processing is addressed. The devices are fabricated via solution and dry-lamination in ambient conditions with parallel processing steps. The method of fabricating the individual polymeric cells, the steps needed to laminate them together with a common CNT cathode, and then provide some representative results are described. These results demonstrate ionic gating of the CNT electrode to create a common cathode and addition of current and efficiency as a result of the lamination procedure.

A method of fabricating, in ambient conditions, organic photovoltaic tandem devices in a parallel configuration is presented. These devices feature an air-processed, semi-transparent, carbon nanotube common cathode.

A method of fabricating organic photovoltaic (OPV) tandems that requires no vacuum processing is presented. These devices are comprised of two ...

In Situ Time-dependent Dielectric Breakdown in the Transmission Electron Microscope: A Possibility to Understand the Failure Mechanism in Microelectronic Devices

The time-dependent dielectric breakdown (TDDB) in on-chip interconnect stacks is one of the most critical failure mechanisms for microelectronic devices. The aggressive scaling of feature sizes, both on devices and interconnects, leads to serious challenges to ensure the required product reliability. Standard reliability tests and post-mortem failure analysis provide only limited information about the physics of failure mechanisms and degradation kinetics. Therefore it is necessary to develop new experimental approaches and procedures to study the TDDB failure mechanisms and degradation kinetics in particular. In this paper, an in situ experimental methodology in the transmission electron microscope (TEM) is demonstrated to investigate the TDDB degradation and failure mechanisms in Cu/ULK interconnect stacks. High quality imaging and chemical analysis are used to study the kinetic process. The in situ electrical test is integrated into the TEM to provide an elevated electrical field to the dielectrics. Electron tomography is utilized to characterize the directed Cu diffusion in the insulating dielectrics. This experimental procedure opens a possibility to study the failure mechanism in interconnect stacks of microelectronic products, and it could also be extended to other structures in active devices.

In Situ Time-dependent Dielectric Breakdown in the Transmission Electron Microscope: A Possibility to Understand the Failure Mechanism in Microelectronic Devices

The time-dependent dielectric breakdown (TDDB) in on-chip interconnect stacks is one of the most critical failure mechanisms for microelectronic devices. This paper demonstrates the procedure of an in situ TDDB experiment in the transmission electron microscope, which opens a possibility to study the failure mechanism in microelectronic products.

The time-dependent dielectric breakdown (TDDB) in on-chip interconnect stacks is one of the most critical failure mechanisms for microelectronic devices. ...

Electron Channeling Contrast Imaging for Rapid III-V Heteroepitaxial Characterization

Misfit dislocations in heteroepitaxial layers of GaP grown on Si(001) substrates are characterized through use of electron channeling contrast imaging (ECCI) in a scanning electron microscope (SEM). ECCI allows for imaging of defects and crystallographic features under specific diffraction conditions, similar to that possible via plan-view transmission electron microscopy (PV-TEM). A particular advantage of the ECCI technique is that it requires little to no sample preparation, and indeed can use large area, as-produced samples, making it a considerably higher throughput characterization method than TEM. Similar to TEM, different diffraction conditions can be obtained with ECCI by tilting and rotating the sample in the SEM. This capability enables the selective imaging of specific defects, such as misfit dislocations at the GaP/Si interface, with high contrast levels, which are determined by the standard invisibility criteria. An example application of this technique is described wherein ECCI imaging is used to determine the critical thickness for dislocation nucleation for GaP-on-Si by imaging a range of samples with various GaP epilayer thicknesses. Examples of ECCI micrographs of additional defect types, including threading dislocations and a stacking fault, are provided as demonstration of its broad, TEM-like applicability. Ultimately, the combination of TEM-like capabilities &#8211; high spatial resolution and richness of microstructural data &#8211; with the convenience and speed of SEM, position ECCI as a powerful tool for the rapid characterization of crystalline materials.

The use of electron channeling contrast imaging in a scanning electron microscope to characterize defects in III-V/Si heteroexpitaxial thin films is described. This method yields similar results to plan-view transmission electron microscopy, but in significantly less time due to lack of required sample preparation.

Misfit dislocations in heteroepitaxial layers of GaP grown on Si(001) substrates are characterized through use of electron channeling contrast imaging ...

Quantification of Hydrogen Concentrations in Surface and Interface Layers and Bulk Materials through Depth Profiling with Nuclear Reaction Analysis

Nuclear reaction analysis (NRA) via the resonant 1H(15N,&#945;&#947;)12C reaction is a highly effective method of depth profiling that quantitatively and non-destructively reveals the hydrogen density distribution at surfaces, at interfaces, and in the volume of solid materials with high depth resolution. The technique applies a 15N ion beam of 6.385 MeV provided by an electrostatic accelerator and specifically detects the 1H isotope in depths up to about 2 &#956;m from the target surface. Surface H coverages are measured with a sensitivity in the order of ~1013 cm-2 (~1% of a typical atomic monolayer density) and H volume concentrations with a detection limit of ~1018 cm-3 (~100 at. ppm). The near-surface depth resolution is 2-5 nm for surface-normal 15N ion incidence onto the target and can be enhanced to values below 1 nm for very flat targets by adopting a surface-grazing incidence geometry. The method is versatile and readily applied to any high vacuum compatible homogeneous material with a smooth surface (no pores). Electrically conductive targets usually tolerate the ion beam irradiation with negligible degradation. Hydrogen quantitation and correct depth analysis require knowledge of the elementary composition (besides hydrogen) and mass density of the target material. Especially in combination with ultra-high vacuum methods for in-situ target preparation and characterization, 1H(15N,&#945;&#947;)12C NRA is ideally suited for hydrogen analysis at atomically controlled surfaces and nanostructured interfaces. We exemplarily demonstrate here the application of 15N NRA at the MALT Tandem accelerator facility of the University of Tokyo to (1) quantitatively measure the surface coverage and the bulk concentration of hydrogen in the near-surface region of a H2 exposed Pd(110) single crystal, and (2) to determine the depth location and layer density of hydrogen near the interfaces of thin SiO2 films on Si(100).

We illustrate the application of 1H(15N,&#945;&#947;)12C resonant nuclear reaction analysis (NRA) to quantitatively evaluate the density of hydrogen atoms on the surface, in the volume, and at an interfacial layer of solid materials. The near-surface hydrogen depth profiling of a Pd(110) single crystal and of SiO2/Si(100) stacks is described.

Nuclear reaction analysis (NRA) via the resonant 1H(15N,&#945;&#947;)12C reaction is a highly effective method of depth profiling that quantitatively and ...

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

For slender and lightweight structures, vibration serviceability is a matter of growing concern, often constituting the critical design requirement. With designs governed by the dynamic performance under human-induced loads, a strong demand exists for the verification and refinement of currently available load models. The present contribution uses a 3D inertial motion tracking technique for the characterization of the in-field pedestrian behavior. The technique is first tested in laboratory experiments with simultaneous registration of the corresponding ground reaction forces. The experiments include walking persons as well as rhythmical human activities such as jumping and bobbing. It is shown that the registered motion allows for the identification of the time variant pacing rate of the activity. Together with the weight of the person and the application of generalized force models available in literature, the identified time-variant pacing rate allows to characterize the human-induced loads. In addition, time synchronization among the wireless motion trackers allows identifying the synchronization rate among the participants. Subsequently, the technique is used on a real footbridge where both the motion of the persons and the induced structural vibrations are registered. It is shown how the characterized in-field pedestrian behavior can be applied to simulate the induced structural response. It is demonstrated that the in situ identified pacing rate and synchronization rate constitute an essential input for the simulation and verification of the human-induced loads. The main potential applications of the proposed methodology are the estimation of human-structure interaction phenomena and the development of suitable models for the correlation among pedestrians in real traffic conditions.

A protocol is presented for the characterization of the in-field pedestrian behavior and the simulation of the resulting structural response. Field-tests demonstrate that the in situ identified pacing rate and synchronization rate among the participants constitute an essential input for the simulation and verification of the human-induced loads.

For slender and lightweight structures, vibration serviceability is a matter of growing concern, often constituting the critical design requirement. With ...

In Vitro Culture of Epicardial Cells From Mouse Embryonic Heart

During embryogenesis, the epicardial contribution to coronary vasculature development has been very well established. Cells derived from the epicardium differentiate into smooth muscle cells, fibroblasts and endothelial cells that contribute to the formation of coronary vessels. Here we have established an in vitro culture method for embryonic epicardial cells. Using genetic labelling, we have demonstrated that the majority of the migrating cells in our explant culture are of epicardial origin. Epicardial explant cells also retain the expression of epicardial markers (Wt1 and Tbx18). Furthermore, we provide evidence that epicardial explant cells undergo epithelial to mesenchymal transition (EMT), migrate and differentiate into smooth muscle cells after Transforming growth factor beta 1 (TGF-&#946;1) treatment in a manner indistinguishable from that of epicardial cells in vivo. In conclusion, we provide a novel method for the culture of embryonic epicardial cells, which will help to explore the role of specific genes in epicardial cell biology.

In Vitro Culture of Epicardial Cells From Mouse Embryonic Heart

The epicardium is an essential source of multipotent cardiovascular progenitor cells and paracrine factors that are required for cardiovascular development and regeneration. We describe here a method to culture mouse embryonic epicardial cells.

During embryogenesis, the epicardial contribution to coronary vasculature development has been very well established. Cells derived from the epicardium ...

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the main trend in the advanced development of flow cytometry. Notably, adding high-resolution imaging capabilities allows for the complex morphological analysis of cellular/sub-cellular structures. This is not possible with standard flow cytometers. However, it is valuable for advancing our knowledge of cellular functions and can benefit life science research, clinical diagnostics, and environmental monitoring. Incorporating imaging capabilities into flow cytometry compromises the assay throughput, primarily due to the limitations on speed and sensitivity in the camera technologies. To overcome this speed or throughput challenge facing imaging flow cytometry while preserving the image quality, asymmetric-detection time-stretch optical microscopy (ATOM) has been demonstrated to enable high-contrast, single-cell imaging with sub-cellular resolution, at an imaging throughput as high as 100,000 cells/s. Based on the imaging concept of conventional time-stretch imaging, which relies on all-optical image encoding and retrieval through the use of ultrafast broadband laser pulses, ATOM further advances imaging performance by enhancing the image contrast of unlabeled/unstained cells. This is achieved by accessing the phase-gradient information of the cells, which is spectrally encoded into single-shot broadband pulses. Hence, ATOM is particularly advantageous in high-throughput measurements of single-cell morphology and texture &#8211; information indicative of cell types, states, and even functions. Ultimately, this could become a powerful imaging flow cytometry platform for the biophysical phenotyping of cells, complementing the current state-of-the-art biochemical-marker-based cellular assay. This work describes a protocol to establish the key modules of an ATOM system (from optical frontend to data processing and visualization backend), as well as the workflow of imaging flow cytometry based on ATOM, using human cells and micro-algae as the examples.

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

This protocol describes the implementation of an asymmetric-detection time-stretch optical microscopy system for single-cell imaging in ultrafast microfluidic flow and its applications in imaging flow cytometry.

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the ...

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics

Imaging Biomarker Explorer (IBEX) is an open-source tool for medical imaging radiomics work. The purpose of this paper is to describe how to use IBEX's graphical user interface (GUI) and to demonstrate how IBEX calculated features have been used in clinical studies. IBEX allows for the import of DICOM images with DICOM radiation therapy structure files or Pinnacle files. Once the images are imported, IBEX has tools within the Data Selection GUI to manipulate the viewing of the images, measure voxel values and distances, and create and edit contours. IBEX comes with 27 preprocessing and 132 feature choices to design feature sets. Each preprocessing and feature category has parameters that can be altered. The output from IBEX is a spreadsheet that contains: 1) each feature from the feature set calculated for each contour in a data set, 2) image information about each contour in a data set, and 3) a summary of the preprocessing and features used with their selected parameters. Features calculated from IBEX have been used in studies to test the variability of features under different imaging conditions and in survival models to improve current clinical models.

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics

We describe IBEX, an open-source tool designed for medical imaging radiomics studies, and how to use this tool. In addition, some published works that have used IBEX for uncertainty analysis and model building are showcased.

Imaging Biomarker Explorer (IBEX) is an open-source tool for medical imaging radiomics work. The purpose of this paper is to describe how to use IBEX's ...