This protocol enables the local assessments of both collagen architecture and mechanical failure characteristics of fibrous plaque tissue. Since both structural and mechanical assessments were performed on the same tissue sample, this technique allows for unraveling the functional link between the structural and mechanical assessments of the tissue. The knowledge obtained with this protocol on fibrous plaque tissue structure and failure characteristics is key to prevent and predict clinical fatal events triggered by atherosclerotic plaque rupture.
To begin, cut the plaque open along the longitudinal axis of the artery using surgical scissors and tweezers. Cut out rectangular test samples from the plaque specimens, ensuring that the samples are as large as possible while avoiding tissue regions containing tears or calcifications. Next, take a plaque test sample and fix both its ends to the silicone by pinning needles in the tissue.
Insert the needles in the region of the sample that will be in the clamps of the tensile testing device during the mechanical testing. Put on safety glasses. Use a side cutter to shorten the needles so they stick out less than a few millimeters above the sample surface to prevent them from damaging the microscope objective.
Fill the Petri dish with PBS until the sample is submerged. Next, turn on the microscope system, turn the multiphoton key, and open the operating software of the microscope. Put the Petri dish containing the test sample underneath the objective and lower the microscope objective.
Turn on the live scan mode. Move the objective to a corner of the sample using the knobs on the smart panel and click the mark position symbol in the Tile Scan panel. If performed correctly, a grid with all selected tiles for imaging will appear in orange.
Next, click Start in the bottom right corner of the screen to create a tile scan of the entire sample surface to obtain an overview of the sample geometry. After the tile scan, observe the X and Y coordinates of the upper left corner of the upper left tile in the Tile Scan panel shown automatically. Note these coordinates in a spreadsheet.
In the Tile Scan panel, observe the number of tiles in the X and Y directions in the box called ScanField. Note the size of the tile scan in the spreadsheet. Calculate the coordinates of the other tiles by adding or subtracting the size of the tile.
From the tile scan, select the tiles to be imaged with a second harmonic generation, or SHG imaging. For the selection, avoid tiles in the clamps and leave one tile between each selected tile in both the longitudinal and the circumferential direction. Next, identify the location of the tiles to be imaged by using the calculated coordinates in this spreadsheet.
Fill in the coordinates in the designated boxes and click Enter so the objective moves to the right tile. Turn on the live scan mode. Increase the multiphoton, or MP, laser power by using the slider in the upper panel and the beam path settings to get the highest possible laser power without significant bleaching.
Then, adjust the detector gain to obtain bright images without saturated pixels by using the knob on the smart panel or by clicking on the name of the detector and the beam path settings and additional channels. Typical values for the detector gain are between 500 and 800 volts. Use the Z-position knob on the smart panel to adjust the focus plane.
Then, move to the top of the sample and set the positions of the top of the Z-stack by clicking on the arrowhead in the Z-stack panel under the Acquisition tab from the third panel. Then, focus on the sample until the SHG signal is no longer detected. Again, click on the arrowhead in the Z-stack panel to set this position.
When finished, turn off the live scan mode. Under the Acquisition tab in the second panel, keep the scan speed at 400 hertz, set the line average to two, and the resolution to 512 by 512 pixels per image by using the dropdown lists. Toggle on the Bidirectional X scanning button.
Click on z-step size in the Z-stack panel and fill a z-step size of three microns in the box. Click Start in the bottom right corner of the screen to create a Z-stack. When finished, save the coordinates of the tile in the file name or give each tile its number.
After imaging, the sample is exposed to mechanical testing. To generate a spackle pattern, hold the airbrush filled with tissue dye approximately 30 centimeters away from the test sample and spray it on the lumenal surface. Next, for uniaxial tensile testing, place the sample in the tensile tester's clamps with the sample's circumferential direction aligned with the tensile stretching direction and the lumenal side of the sample facing upward.
Ensure the initial gauge length is set so that the strip's width-to-length ratio is less than one. Tighten the screws of the grips by applying a torque of 20 centinewton meters using a torque screwdriver. Add PBS into the heating bath until the sample is submerged.
Tear the load cell and start recording the global force and displacement measurements from the load cell and the actuator of the tensile tester. Straighten the sample by applying a pre-stretch of 0.05 newton to get rid of the slack in the sample. Perform 10 cycles of pre-conditioning, up to 10%strain, based on the gauge length measurement by the actuator after the application of pre-stretch.
Start the uniaxial tensile testing until complete failure of the sample while recording a video of the sample deformation with the high-speed camera. After failure, stop recording the global force and displacement measurements. Open the Z-stacks obtained during multiphoton microscopy, or MPM, with SHG in Image J and create maximum intensity projections, or MIPs, of each Z-stack.
Analyze each MIP with the open source MATLAB-based fiber orientation analysis tool to measure the orientation angle of the individual collagen fibers present in the tiles. Use another MATLAB-based tool, FibLab, to fit a Gaussian distribution to the angle distribution histogram. From the Gaussian distribution plot, extract the structural parameters such as the predominant fiber angle, which is the mode of the distribution, the standard deviation of the fiber angle distribution, and the anisotropic fraction.
Perform visual inspection on the camera images to identify the frame in which rupture initiation occurs. Visually identify the rupture location. Perform the digital image correlation, DIC, analysis with MATLAB-based software ncorr using the camera images recorded during the tensile test.
Select the last frame before the final stretching until failure as the reference image. For the current images, select ll images from the start of the final stretching until the last frame before the frame in which rupture initiation occurred. Select the sample surface as the region-of-interest, or ROI.
Exclude the areas that are near the clamps. Perform DIC by setting the parameter's subset radius to 30 pixels, subset spacing to three pixels, iteration cutoff to 50, norm of the difference vector cutoff to 10 to the power of five, strain radius to five, and autopropagation step to five. From the DIC analysis with ncorr, obtain the Green-LaGrange or Eulerian strain distributions of the ROI.
Use these strain distributions to calculate the average Green-LaGrange strain of the entire plaque sample surface at the last frame before rupture. Calculate the Green-LaGrange strain at the rupture location. Using the natural landmarks in the test sample, make an overlay of the reference image and the tile scan to identify the rupture location on the tile scan.
Identify the MPM-SHG tile where the rupture happened. If the rupture is not in a tile scanned with the MPM-SHG, identify the tile closest to the rupture location. Obtain the structural parameters found at the tile where the rupture occurred.
A fresh and intact plaque sample with little to no tears and macrocalcifications is shown here. Plaque samples may be retrieved from areas which do not include these tears and calcifications. SHG imaging and image post-processing provide MIPs from each imaged tile.
Further post-processing by fiber detection yields fiber orientation histograms from which collagen structural parameters can be extracted. In addition, color maps showing the local structural collagen parameters across the entire plaque sample are obtained for visual analysis. From these test samples, a large intrasample variation in the structural collagen parameters was observed.
The rupture initiation and propagation in a plaque tissue sample during the tensile test are demonstrated here. Digital image correlation analysis provides local tissue deformation maps, such as the Green-LaGrange strain maps. From these strain maps, a large intrasample variation in the local strains was observed.
Once the rupture location is identified on the camera recordings, it can be mapped back to the reference camera image and the microscopy tile scan. This provides the MPM-SHG tile where the rupture happened and the structural parameters found at this tile. Obtaining fibrous tissue samples that are free of calcifications and are of a large enough size workable for mechanical testing may be a challenging task for heavily-calcified plaques.
Once a mechanical or structural feature is identified as predictor of fibrous plaque tissue failure, an in vivo imaging system measuring this feature will allow predicting of plaque rupture risk in patients.
