We have developed a mechano-imaging pipeline to study the heterogeneous structural and mechanical atherosclerotic plaque properties. This pipeline enables correlation of the local predominant angle and dispersion of collagen fiber orientation, the rupture behavior, and the strain fingerprints of the fibrous plaque tissue.
The rupture of atherosclerotic plaques in coronary and carotid arteries is the primary cause of fatal cardiovascular events. However, the rupture mechanics of the heterogeneous, highly collagenous plaque tissue, and how this is related to the tissue’s fibrous structure, are not known yet. Existing pipelines to study plaque mechanics are limited to obtaining only gross mechanical characteristics of the plaque tissue, based on the assumption of structural homogeneity of the tissue. However, fibrous plaque tissue is structurally heterogeneous, arguably mainly due to local variation in the collagen fiber architecture.
The mechano-imaging pipeline described here has been developed to study the heterogeneous structural and mechanical plaque properties. In this pipeline, the tissue’s local collagen architecture is characterized using multiphoton microscopy (MPM) with second-harmonic generation (SHG), and the tissue’s failure behavior is characterized under uniaxial tensile testing conditions using digital image correlation (DIC) analysis. This experimental pipeline enables correlation of the local predominant angle and dispersion of collagen fiber orientation, the rupture behavior, and the strain fingerprints of the fibrous plaque tissue. The obtained knowledge is key to better understand, predict, and prevent atherosclerotic plaque rupture events.
Ischemic stroke, often triggered by atherosclerotic plaque rupture in carotid arteries, is one of the leading causes of mortality and morbidity worldwide1. However, the current surgical treatment planning strategies to prevent carotid atherosclerosis-related stroke do not include plaque rupture risk assessment2. This is mainly because the previously suggested risk biomarkers, such as plaque cap thickness3 and lipid core size4, have been shown to have suboptimal predictive value for future clinical events5,6. A better understanding of plaque mechanics and rupture mechanisms is necessary to optimize plaque rupture risk assessment and identify new risk markers of atherosclerotic plaques.
Plaque rupture is a local mechanical event where the highly fibrous plaque tissue fails to withstand the mechanical loading exerted on it by the blood pressure and loses its structural integrity7. Despite this, the mechanics of the plaque rupture event and its link to the underlying microstructure are poorly understood8. The few experimental studies that characterized plaque tissue failure features9,10,11,12,13 reported gross mechanical rupture properties (i.e., ultimate tensile failure strain and strength), derived with the assumption of structural homogeneity of the tissue. However, the fibrous plaque tissue is structurally heterogeneous, arguably mainly due to local variation in the collagen fiber architecture14. Moreover, the link between the plaque tissue mechanical failure characteristics and the collagen architecture was only investigated in a recent study by Johnston et al. The authors showed an interplaque difference in the predominant fiber orientation and reported higher ultimate stresses and lower ultimate strains for fibrous plaque cap samples with a predominantly circumferential fiber orientation15. However, the study was also limited to gross mechanical and structural properties.
To shed light on the essential information about the local collagen architecture and local mechanical properties of the fibrous plaque tissue, in the current study, we have developed a mechano-imaging pipeline. This ex vivo pipeline enables quantification of the local collagen fiber direction and dispersion, as well as local rupture strain. The pipeline involves MPM imaging with SHG to image collagen fibers in the plaque tissue, as well as DIC and uniaxial tensile testing to quantify the tissue's rupture characteristics.
Multiphoton microscopy-second-harmonic generation (MPM-SHG) has become a popular technique to study collagen in biological tissues16. The technique has many advantages compared to other collagen imaging techniques, such as histology17, diffusion tensor imaging (DTI)14, and small-angle light scattering (SALS)15. First, MPM-SHG imaging is non-destructive, which makes it ideal to combine with mechanical testing18. Second, the SHG signal is specific for collagen, and therefore no staining of the tissue is necessary. Due to the long excitation wavelengths (near-infrared), the penetration depth is greater than with other microscopy techniques16. The high resolution (µm-level) achieved with SHG imaging also allows visualization of individual fibers. This offers many possibilities, such as local quantification of the number of collagen fibers, collagen fiber orientation, and distribution19.
Digital image correlation (DIC) combined with mechanical testing is a widely used method to obtain local mechanical properties of biological tissues20. With DIC, the displacement of speckles applied on the tissue surface is tracked by comparing high-speed camera images acquired during mechanical testing20. This image postprocessing method is used to estimate the full-field surface strains of the specimen20 and can also be used to study the rupture behavior of the tissue21.
All methods described in this paper were approved by the Ethical Research Committee at the Erasmus Medical Center in Rotterdam; informed consent was obtained from patients before plaque specimen collection. A workflow chart of the protocol is given in Figure 1.
1. Tissue collection, micro-computed tomography (µCT) imaging, and test sample preparation
2. Multiphoton microscopy imaging
3. Mechanical testing
4. Data analysis
Tissue collection and test sample preparation
The tissue collection yields plaque fibrous tissue specimens that can be dissected into individual test samples for structural imaging and uniaxial tensile testing. Ideally, a collected fibrous tissue sample contains areas with little to no tears (Figure 5A) and macrocalcifications (Figure 5B). An excess of these tears and calcifications (Figure 5C) may lead to plaque samples that do not meet the previously mentioned sample dimension requirement of WL 1.
Multiphoton microscopy imaging
SHG imaging and image postprocessing provides MIPs from each imaged tile (Figure 6A,B). Further post-processing by fiber detection (Figure 6C) yields fiber orientation histograms (Figure 6D) from which collagen structural parameters can be extracted (Figure 6E). In addition, color maps showing the local structural collagen parameters across the entire plaque sample can be obtained for visual analysis (Figure 6F,G). For the representative test sample in Figure 6, a large intrasample variation in the structural collagen parameters is found (average ± SD of µp = -34° ± 32°; σp = 21° ± 4°; Pani = 0.49 ± 0.14, if the circumferential direction is defined as 0°). This intrasample variation emphasizes the importance of obtaining local structural parameters instead of assuming homogeneity.
Mechanical testing
Rupture behavior
The high-speed camera provides images of the deformation and rupture behavior of the plaque samples during mechanical testing (Figure 7). From these images, the location of rupture initiation and the rupture propagation path can be identified. The rupture identification results are suboptimal if bubbles or reflections are present in the camera images, or if the rupture propagates too fast to be captured by the chosen frame rate.
Local strain patterns
Digital image correlation analysis on the camera recordings acquired during the uniaxial tensile testing provides the local tissue deformation maps, such as the Green-Lagrange strain maps shown in Figure 8. These maps display the three strain components (εxx, εxy, and εyy) at the frame before rupture initiation. From these strain maps, the average strains in a region of interest and local strain at a spot, such as rupture location, can be extracted.
For the representative sample in Figure 8, the local strain data show a large intrasample variation. For the representative test sample in Figure 8, a large intrasample variation in the local strains is found (the ranges of the observed strains are as follows: εxx = -0.30-0.17; εxy = -0.13-0,20; εyy = 0-0.40). This emphasizes the importance of obtaining local data instead of gross, average values obtained with the assumption of tissue homogeneity.
Correlating mechanical and structural tissue information
The above-mentioned results allows association of the local deformation and rupture behavior of the tissue to the collagen architecture. Once the rupture location is identified on the camera recordings (Figure 9A), it can be mapped back to the reference camera image (Figure 9B) and to the microscopy tile scan (Figure 9C). This provides the MPM-SHG tile where the rupture happened and the structural parameters found at this tile (Figure 9D). The structural parameters found in the tile where rupture occurred in a representative sample, shown in Figure 9, are µp = 28°, σp = 19°, and Pani = 0.6. The same procedure can also be applied to the non-ruptured tissue locations. It is important to note that mapping the rupture location on the reference image from the rupture frame may be challenging in case of a poor speckle pattern and unclear natural landmarks. In addition, if the natural landmarks of the tissue are not clear enough, co-registration of the tile scan overlay and the high-speed camera images may be difficult.
Figure 1: Workflow chart of the presented experimental protocol. Please click here to view a larger version of this figure.
Figure 2: Selection of tiles for SHG imaging from the tile scan. (A) Test sample pinned in silicon. (B) Tile scan of the test sample obtained by brightfield microscopy. The tiles that are selected for SHG imaging are marked by blue squares. (C) Maximum intensity projection of the MPM with SHG. Scale bar = 140 µm (C). Abbreviations: SHG = second-harmonic generation; MPM = multiphoton microscopy. Please click here to view a larger version of this figure.
Figure 3: Plaque sample placed under the objective of the multiphoton microscope. The location of the plaque sample is secured by a phosphate-buffered saline-filled Petri dish. Please click here to view a larger version of this figure.
Figure 4: Custom-designed uniaxial tensile tester with its different components indicated. (A) Total overview of the system. Note that the sandpaper inserts in the clamps are visible as only the bottom clamps are attached. (B) Zoomed-in image of the clamps of the tensile tester with the test specimen ready for testing. Abbreviations: PVC = polyvinyl chloride; LED = light-emitting diode. Please click here to view a larger version of this figure.
Figure 5: Tissue collection and sample preparation results from representative samples. (A) Fresh and intact plaque sample, retrieved from consenting patients who underwent carotid endarterectomy surgery. (B) 3D reconstruction from a µCT scan. Calcified tissue is shown in light blue and non-calcified in red. An optimal sample without calcified tissue could be obtained from the area between the blue lines. (C) 3D reconstruction from the µCT scan showing a suboptimal plaque with an excess of calcified tissue. Scale bar = 3 mm. Abbreviation: µCT = micro-computed tomography. Please click here to view a larger version of this figure.
Figure 6: MPM-SHG results from a representative sample. (A) Tile scan overview; the selected tiles for imaging are shown in blue. (B) MIPs from various tiles. (C) Fiber detection by the FOA tool from a selected tile (#1). (D) Fiber orientation histogram from a selected tile. (E) Fiber orientation histogram + Gaussian fit, from which collagen structural parameters can be extracted from a selected tile. (F) Representation of the µp (orientation black line) and σp (background color) across the entire plaque sample. (G) Representation of the µp (orientation black line) and Pani (background color) across the entire plaque sample. Scale bars = 140 µm (B,C). Abbreviations: MPM-SHG = multiphoton microscopy-second-harmonic generation; MIPs = maximum intensity projections; FOA = fiber orientation analysis; µp = predominant fiber angle; Pani = anisotropic fraction; σp = standard deviation of the fiber angle distribution; Piso = isotropic fraction. Please click here to view a larger version of this figure.
Figure 7: Rupture initiation and propagation in a plaque tissue sample during the tensile test procedure.1) Prestretched state, intact tissue. 2) Rupture initiation-first frame in which rupture is observed. The rupture initiation location is marked with a red square. 3) and 4) Rupture propagation. 5) Complete rupture of the plaque sample. Scale bars = 1 mm. Please click here to view a larger version of this figure.
Figure 8: Green-Lagrange strain patterns of a representative sample (εxx, εxy, and εyy) at the frame before rupture, obtained with DIC analysis. Average and standard deviation over the entire plaque are given, together with the strain at the rupture location. Abbreviations: DIC = digital image correlation; εxx = longitudinal strain; εxy = shear; εyy = tensile strain. Please click here to view a larger version of this figure.
Figure 9: Overlay image of the rupture location (red square) on images. (A) High-speed camera image, where rupture is identified (rupture frame). (B) High-speed camera image, where only prestretch is applied (reference frame). (C) The tile scan image obtained via microscopy. (D) A color-coded map showing local collagen structural parameters at various tiles. The µp (orientation black line) and Pani (background color) across the entire plaque sample are presented. Abbreviations: µp = predominant fiber angle; Pani = anisotropic fraction. Please click here to view a larger version of this figure.
The current study focused on developing a mechano-imaging pipeline to study the correlation between the local collagen orientation and dispersion, local mechanical properties, and rupture behavior of fibrous atherosclerotic plaque tissue. The protocol described herein is innovative for several reasons. First, this is the first time that digital image correlation has been applied to measure the local deformation of fibrous plaque tissue under mechanical loading. Second, this protocol provides the necessary information to analyze the association between the local deformation pattern and the local collagen architecture of the fibrous plaque tissue. The importance of the local assessment is emphasized by both the strain data and the collagen data presented in the results section, which show the heterogeneous nature of the tissue. Therefore, the use of techniques that enable local assessment, such as the ones utilized in this protocol, is recommended for future studies of fibrous plaque properties.
Test sample preparation is among the critical steps of this protocol. Carotid plaques are mainly collagenous tissues; however, they may contain calcifications that are considered to affect the overall plaque mechanical behavior36,37. As the study focuses on the fibrous tissue component of the plaque, calcifications are avoided in the test samples by using µCT imaging38. If µCT is not available, other imaging techniques such as MRI or OCT39 can be considered for detecting the calcified regions in the plaque. Obtaining fibrous tissue test samples that are free of calcifications and are of a large enough size that is workable for mechanical testing may be a challenging task for plaques that are heavily calcified or contain dispersed calcifications. Another challenging task in the protocol is generating an optimal speckle pattern for digital image correlation. Optimal DIC requires a black/white ratio of 50:5028 and speckles the size of three to five pixels29 to ensure appropriate quality. Failure to meet these requirements may result in inaccurate local strain measurements. Finally, mapping the rupture location to the SHG images can be challenging if the natural landmarks of a tissue are not clear. For such samples, application of several fiducial markers to the tissue before imaging will be helpful.
The MPM-SHG technique used in the current protocol is superior to many other collagen imaging techniques, as it is a high-resolution and non-destructive technique with a relatively large penetration depth. Yet, the penetration depth (<400 µm) of MPM-SHG poses a limitation, as it does not allow imaging the entire thickness of the test samples, which ranged between 0.5 and 2 mm. In a recent study with diffusion tensor magnetic resonance imaging (DT-MRI), we have demonstrated that the predominant fiber orientation in the deeper parts of the plaque tissue can be different from the one in the more superficial, luminal parts of the tissue14. Therefore, further studies are warranted to investigate the local collagen architecture in the deeper parts of thick fibrous plaque tissue samples and its relation to the local tissue mechanics. For this purpose, polarized spatial frequency domain imaging (pSFDI) can be utilized. This recently developed optical imaging technique was reported to have the potential to measure fiber orientation as deep as 0.8 mm in mitral valve leaflets12. The pSFDI also offers a fast acquisition, which could also facilitate visualization of the entire sample area instead of only a selection of tiles, as is the case in the current protocol. Another limitation of the current protocol is that only surface deformation could be identified. In future studies, mirror-assisted multi-view DIC40 or digital volume correlation (DVC)41 can be included in this protocol to obtain additional information on the volumetric, subsurface strains.
The current experimental protocol can be further extended or modified in several ways to obtain additional information about plaque rupture mechanics and its relation to the underlying microstructure. First, the current protocol includes uniaxial tensile testing in the circumferential direction. This type of mechanical testing was chosen since the plaque predominantly experiences tensile stretch in the circumferential direction in vivo. For more comprehensive mechanical characterization, this protocol can be further extended to incorporate inflation testing, biaxial testing, or uniaxial tensile testing in the longitudinal direction. Second, the current protocol only focuses on obtaining local strains through DIC. However, a more complete view of the plaque mechanical behavior can be acquired by also including local stress analysis in the protocol, yet this requires characterization of local stiffness. Although currently challenging, this can be achieved by computational techniques such as the inverse finite element method42,43 and the virtual fields method44. Aside from experimental adaptation, some additional postprocessing steps can also be added to the current protocol. First, instead of only identifying the rupture location, the crack-propagation path can be identified via the obtained high-speed camera images. This propagation path can be correlated to local structural and mechanical parameters. Second, the rupture initiation location was visually identified in the described protocol. A previous study on non-biological tissues has used discontinuities in DIC strain measurements to detect rupture45. Applying such automated rupture detection on plaque tissues can possibly improve the accuracy of the rupture detection. Finally, a great advantage of MPM-SHG compared to other collagen imaging techniques is that it visualizes individual collagen fibers. Therefore, the data obtained via this protocol can also be used to investigate additional local collagen characteristics, such as the collagen content.
This protocol can be used to provide a better understanding of the local characteristics of fibrous plaque tissue, the component that mechanically fails in plaque rupture in vivo. This information is needed to establish new structural and functional imaging markers that predict plaque rupture in patients. These new markers are necessary, since the previously suggested risk biomarkers have been shown to have suboptimal predictive value for future clinical events5,6. In the future, OCT and ps-OCT can possibly identify and quantify fibrous tissue in the arterial system46,47,48. In addition, strain was regarded a surrogate marker for local plaque composition49. Thus, in vivo strain measurements49 could potentially aid in the identification of plaque stability in patients. However, one should be careful with directly translating the obtained results to in vivo plaque rupture. First, the fibrous plaque tissue experiences more complex loading in vivo than the unidirectional tensile loading used in this protocol. Second, atherosclerotic plaques are multicomponent structures; the in vivo stress and strain distributions in the fibrous plaque tissue can be affected by the presence and location of the other plaque components, such as calcifications37.
This mechano-imaging pipeline can also be utilized to study other collagenous tissues. Global mechanical testing and structural imaging of collagen are already widely used for biological tissues. However, local assessment of pre-failure and failure properties, as well as collagen architecture, is critical for accurate mechanical characterization of heterogeneous fibrous tissues. We anticipate that the structure of this new protocol will provide further insight into the interplay between the microstructure and mechanics of several biological tissues.
The authors have nothing to disclose.
This work was funded by an NWO-Vidi grant (18360).
10 mm extension ring | Thorlabs Inc. | CML10 | |
15 mL tube | VWR | 525-0150 | |
20x APO water immersion objective | Leica | 507701 | |
3D Slicer software | N/A | Version 4.11 | |
50 mL tubes | VWR | 525-0156 | |
Airbrush pistol AB 430- nozzle diameter 0.3 mm | Conrad | 4.01614E+12 | |
Blackout, Nylon Fabric with Polyurethane Coating | Thorlabs | ||
Black tissue dye | Polysciences inc | 24113-2 | |
Camera lens, focal length 50 mm | Thorlabs Inc. | MVL50M1 | |
Camera stand | VWR | 241-0093, 241-7311 | |
Chameleon Ultra multiphoton laser | Coherent | ||
Compressor + air hose | JUN-AIR, Conrad | B07GB9HC62, 4016138577198 | |
Excel | Microsoft | Version 2208 | |
Foam tape double-sided, 1.9 x 150 cm | Pattex | ||
Heating bath | N/A | Custom made | |
High-speed camera + imaging software | Pixelink-Navitar Inc. | PL-D725 | |
Human carotid atherosclerotic plaques (from carotid endarterectomy surgery) | N/A | ||
Image J | National Institute of Health | N/A | |
LAS-AF | Leica | Version 2.3 | Imaging software multiphoton microscope |
LEICA TCS SP5 II | Leica | Microscope used for SHG imaging | |
Lighting system | AMZ instruments | LED-60TB | Used to obtain clear images with the high-speed camera |
MATLAB | MathWorks | Version R2021A | |
MATLAB-based FibLab software | Eindhoven University of Technology | N/A | |
MATLAB-based FOA (Fibre Orientation Analysis) tool | Eindhoven University of Technology | N/A | |
MATLAB-based Ncorr software | Georgia Institute of Technology | Version 1.2 | |
Needles | Emerald | BDAM302986 | |
Petri dish (10 cm diameter) | VWR | BRND452000 | |
Parafilm | VWR | 291-1214 | |
Pasteur Pipettes | VWR | ELKA127-P511-000 | |
Quantum GX2 Micro computed tomography (μCT) scanner + X-ray filter of Cu 0.06 mm + Al 0.5 mm | PerkinElmer | CLS149276 | |
Ruler | Fine Science Tools | 1800030 | |
Sandpaper (P180) | Conrad | 4.00932E+12 | |
Side cutter | Conrad | 4.25084E+12 | |
Silicon elastomer base and curring agent (Sylgard 184) | VWR | 634165S | |
Tensile tester + software + clamps | N/A | Made in-house using a cylindrical linear actuator (EACM2E10AZAK, Oriental Motor Ltd.), and a 10 N load cell (LCMFD-10N, Omega Engineering Inc.) | |
Torque screwdriver | Garant, Hoffman group | 659906 |