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. 2023 Aug 14;23(16):7350–7357. doi: 10.1021/acs.nanolett.3c01712

New Mechanical Markers for Tracking the Progression of Myocardial Infarction

Zhuo Chang †, Jing Zhang ‡, Yilun Liu †, Huajian Gao §,∥,*, Guang-Kui Xu †,*
PMCID: PMC10450805  PMID: 37580044

Abstract

graphic file with name nl3c01712_0006.jpg

The mechanical properties of soft tissues can often be strongly correlated with the progression of various diseases, such as myocardial infarction (MI). However, the dynamic mechanical properties of cardiac tissues during MI progression remain poorly understood. Herein, we investigate the rheological responses of cardiac tissues at different stages of MI (i.e., early-stage, mid-stage, and late-stage) with atomic force microscopy-based microrheology. Surprisingly, we discover that all cardiac tissues exhibit a universal two-stage power-law rheological behavior at different time scales. The experimentally found power-law exponents can capture an inconspicuous initial rheological change, making them particularly suitable as markers for early-stage MI diagnosis. We further develop a self-similar hierarchical model to characterize the progressive mechanical changes from subcellular to tissue scales. The theoretically calculated mechanical indexes are found to markedly vary among different stages of MI. These new mechanical markers are applicable for tracking the subtle changes of cardiac tissues during MI progression.

Keywords: Biomechanics, Viscoelasticity, Power-law rheology, Hierarchical structures, Dynamical mechanical properties

Soft tissues, whose mechanical properties have been correlated with diseases such as osteoarthritis,1 fibrosis,2 and cancer,3,4 are known to exhibit sophisticated nonlinear and viscoelastic behaviors that can be attributed to their multiscale architectures.5,6 Pathological changes in these tissues, such as those in cardiac tissues after myocardial infarction (MI), are believed to originate at the molecular scale and progress toward higher levels of architectures (i.e., cell and tissue levels), ultimately leading to impaired tissue mechanics and functions.1,6 Even though electrocardiogram and specific biomarkers have been used to diagnose MI,7 it is still difficult to quantitatively monitor its progression. An open question is whether changes in the mechanical properties of cardiac tissues during MI can serve as robust markers for accurate disease staging. Prior studies have attempted to correlate the static mechanical properties (i.e., elastic stiffness) of cardiac tissues in mouse models with their disease status after MI. For instance, Berry et al.8 discovered pronounced stiffening and greater mechanical anisotropy in infarcted cardiac tissues at the mid-stage of MI (2 weeks after MI). Later studies revealed that the left ventricular scar tissue exhibited varying degrees of stiffening at the late-stage of MI (6 weeks after MI), as a result of elevated collagen concentration, changes in the fiber network, and cross-linking of the extracellular matrix (ECM) components.9,10 It is noteworthy that simple tissue stiffness cannot detect the initial MI-related mechanical changes in infarcted cardiac tissues.10,11

Due to the viscoelastic nature of soft tissues, a few attempts have been tried to investigate the dynamical behavior of infarcted cardiac tissue,12,13 revealing the changes at the mid- and late-stages of MI (2 or more weeks after MI). For example, atomic force microscopy (AFM) has been used to characterize the altered viscoelastic properties of cardiac tissue ECM after 4 weeks of MI14 and track mechanical changes in cardiovascular diseases.15 To date, however, it is still a big challenge to effectively detect the early stage of MI and quantitatively monitor the progression of MI, where the pathology-driven dynamical changes in the mechanical properties of cardiac tissues are largely unknown.

To decipher the mystery of MI-driven alterations in myocardium dynamics, we utilized AFM-based microrheology to examine the dynamic creep responses of cardiac tissues at different stages of MI. Unexpectedly, we discovered a universal two-stage power-law rheological behavior in all cardiac tissues at different time-scales, regardless of their disease status, which is rarely observed in biological systems. More importantly, we found that these two power-law exponents are surprisingly associated with the initial dynamic changes in the early stage of MI. Subsequently, we developed a self-similar hierarchical theoretical model to further extract the indexes that characterize mechanical properties of infracted myocardium from the cytoplasm and cell to tissue levels. The theoretically obtained mechanical parameters are found to vary markedly among different stages of MI. These newly defined mechanical markers (i.e., experimentally found power-law exponents and theoretically calculated elastic stiffnesses at different hierarchies) offer a robust approach for quantitatively evaluating the progression of MI and hold great promise for tracking viscoelastic behaviors in other biological tissues during development, disease, and cancer.

The progression of myocardial infarction (MI) is classified as early-stage (from control to week 1), mid-stage (from week 1 to week 2), and late-stage (from week 2 to week 4), and all samples are compared to the control group (Figure 1). Figure 1c,f shows that with MI progression, the fibrous scar becomes dominant over the interstitium near the border of the necrotic area. For the week 4 group, the tissue integrity is substantially decreased and the left ventricular wall (LVW) is thinned, both of which indicate extreme remodeling of the myocardial scar (Figure 1d,f). In addition, the ratio of the fibrotic area to total cardiac tissue area increases considerably with the progression of MI (Figure 1b). Despite substantial structural changes in the LVW during the first 2 weeks, the ratio of the thicknesses of the ventricular walls (left:right) is invariable at 3:1 for all groups (p > 0.05), consistent with a previous report.16 Furthermore, we notice that the ratio of the cross-sectional area of the left ventricular cavity (LVC) to that of total cardiac tissue gradually increases from week 1 to week 2 and then doubles by week 4 (Figure 1b), resulting in abnormal cardiac functions.

Figure 1.

Figure 1

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Development of myocardial infarction (MI) model and histological features of MI at different stages. (a) Schematic of permanent ligation of the left anterior descending coronary artery (LAD) induced MI in a mouse model. (b) Bar charts of the fibrotic area, left ventricular cavity (LVC) area, and the left-to-right ventricular wall thickness ratio at different stages. Transverse sections of the mouse heart from control, week 1, week 2, and week 4 MI groups are stained with (c) Haematoxylin and eosin, (d) the enlarged photos of the purple square box in (c), and (e) the Masson’s trichrome, and (f) the enlarged photos of the yellow square box in (e). Left ventricular wall (LVW) and right ventricular cavity (RVC) are labeled, and the tissue necrosis at the left ventricular wall are marked with arrows, scale bar = 1000 μm for normal images, and scale bar = 100 μm for enlarged images.

Using the AFM-based microrheology approach,17 we investigated the dynamic creep responses of cardiac tissues at different stages of MI (Figure 2a,b). We define the time-dependent creep compliance J(t) as the ratio of tissue strain ε(t) to applied mechanical stress σ(t). With an increased indentation depth during force clamping, we obtained J(t) as a function of time and plotted it in a log–log scale (Figure 2c). Surprisingly, the dynamic mechanical responses of all cardiac tissues exhibit a conspicuous broad distribution of time-scales that result in a distinctive tissue status-independent two-stage power-law rheology. Specifically, a first linear region is observed at the short time scale (time range: 10–2 to 10–1 s), followed by a transition to a second linear region at the long time scale (time range: 1–10 s) in the creep compliance–time curves. These two regions can be accurately captured by power-law function J(t) ∼ tα with two exponents, αshort and αlong in different time scales. Table S1 summarizes the values of the two power-law exponents for each group. It is clearly seen that with MI progression, cardiac tissues become stiffer, as indicated by a decrease in two scaling exponents in both short- and long-time scales for all groups. In addition, we notice that the values of αlong are consistently smaller than those of αshort for each group, implying a ubiquitous tissue stiffening over time. Understanding the dynamic mechanical properties of cardiac tissues is crucial for monitoring the progression of MI, uncovering its underlying mechanisms, and supporting the development of biomaterial strategies for treating MI. Although some studies have been dedicated to addressing the static elastic stiffness of normal and infarcted cardiac tissues, the intrinsic viscoelastic behaviors of soft myocardium have received limited attention. This hinders the accurate assessment and staging of MI and the development of effective treatments, such as an epicardial patch.18 In recent years, a single power-law rheology has been extensively observed in a variety of living cells,17,19−22 whereas the double power-law rheology has only been observed in a few biological systems, such as the nucleus23 and individual cells.24,25 This experimentally observed power-law rheology enables us to delineate subtle viscoelastic transformations in infarcted tissues during MI progression. The two power-law exponents are believed to characterize the rheological behavior of intracellular and extracellular fluids as well as the global change in tissue architecture.

Figure 2.

Figure 2

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Two-stage power-law viscoelastic responses of cardiac tissues with different stages of MI. (a) Schematic of AFM-based creep compliance indentation measurement for characterizing the dynamic mechanical behavior of cardiac tissues. (b) Overview of dynamic responses of cardiac tissue during force clamping for a single creep compliance indentation measurement. (c) A universal two-stage power-law fitting of the representative compliance over time on the log–log scale for four groups. Two separate power-law exponents (i.e., αshort and αlong) correspond to time scales between 0.01–0.1 and 1–10 s, respectively. Data for (d) αshort and (e) αlong of each group and statistical analysis was performed using Kruskal–Wallis ANOVA test, followed by the two-stage step-up method of Benjamini, Krieger, and Yekutieli; *p < 0.05, **p < 0.01, and ****p < 0.0001. Black stars mark the bimodal distribution profiles.

To explore the subtle dynamic mechanical changes in cardiac tissues after MI, we further study αshort and αlong across different groups (Figure 2d,e and Table S1). At the short-time scale, the αshort values of all groups range from 0.6 to 0.9. We find that following MI, the αshort for all infarcted tissues decreased significantly compared to the control group (p < 0.0001), indicating a severe change of the tissue status from fluid-like to solid-like due to MI. Thus, αshort is potentially suitable for evaluating the early stage of MI, whose mechanical changes may result from initial alterations in the resistance of both intracellular26−28 and extracellular fluid phases29 under transient stress.30

Next, we discover that all tissue compliances at the long-time scale fit a second power law, and the exponents fall within the range of 0.15–0.3, suggesting a solid-like transformation of all tissues as time progresses. At this long-time scale, we observe a prominent reduction (∼25%) in αlong in all infarcted cardiac tissues compared to the control (p < 0.05; Figure 2d,e and Table S1). This decreased αlong signifies a stiffening of the infarcted tissues, which can be attributed to the loss of soft myocardial cells and the rapid deposition of relatively stiff ECM components (e.g., collagen). Our histological analysis also shows that stiff collagen becomes the predominant phase in infarcted tissues during MI, giving it a solid-like quality (i.e., smaller αlong; Figure 1f). Together, both power-law exponents could serve as effective diagnostic mechanical markers for the early stage MI.

The intricate hierarchical architecture of cardiac tissues, encompassing intracellular cytoplasm and cytoskeleton, as well as the ECM, presents a formidable obstacle in gaining a comprehensive understanding of its multiscale dynamics. We have previously proposed a hierarchical mechanical model to study the complex viscoelastic behavior of single cells based on their structural characteristics.31,32 Here, given the multiscale structure of cardiac tissues (Figure 3a), we consider the crowded cytoplasm medium as a large number of springs with an elastic stiffness E1 immersed in a viscous liquid with viscosity η. This fundamental building unit is treated as the first-level of hierarchy (J1). The emanative cytoskeletal fibers are strung together and are discretized into a series of springs with effective elastic stiffness E2 embedded in the cytoplasm, which serves as the second-level hierarchy (J2), with the first-level hierarchy as a building block (Figure 3a). Similarly, the tissues, as an intricate three-dimensional network with various types of resident cells, can be regarded as a large number of cells in series connected by springs (the transverse expansion of the tissue) with effective elastic stiffness E3, which forms the third-level hierarchy (J3), with the second-level hierarchy as a building block. The dynamic creep responses of all cardiac tissues can be well captured by our proposed self-similar hierarchical model (Figure 3b). In addition, our self-similar hierarchical theoretical model has also demonstrated the applicability in characterizing the longer time-scale dynamic mechanics of cardiac tissues at different stages of MI, as shown in Figure S1.

Figure 3.

Figure 3

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Self-similar hierarchical theoretical model for the dynamic mechanical responses of different cardiac tissues and newly proposed mechanical indexes for tracking MI progression. (a) Self-similar hierarchical model for capturing cardiac tissue dynamics from the cytoplasm level (blue), to the cellular level (purple), to the tissue level (gray). (b) Representative dynamic mechanical responses of all groups fitted very well by our theory. Violin plots with included box plots of viscoelastic properties of three hierarchies for (c) cytoplastic elastic stiffness (E1) and (d) viscosity (η), (e) cellular fiber stiffness (E2) and (f) the transverse stiffness of complete tissues (E3) with schematic diagram for each mechanical index. Bimodal distribution profiles are marked by stars.

Next, we utilized this model to obtain four new mechanical indexes and investigate their changes in all cardiac tissues during the progression of MI. The average values and distribution profiles of these parameters are summarized in Figure 3c–f and Table S3. First, it can be seen that the changes of E1 and η are not evident during different stages of MI, except that the average E1 at the midstage of MI increases by ∼50% compared to the early stage of MI (p < 0.001). In addition, the distribution of E1 at the midstage of MI is bimodal, whereas the distributions for the other groups are unimodal. All theoretically calculated values of E1 are in good agreement with previous experimental reports.28 As illustrated in Table S2, the average η increases by 23% during the mid-stage of MI (p < 0.05). All theoretically calculated values of η are also consistent with previous measurements.28,33 These changes in cytoplasmic viscoelastic properties are more likely to be associated with the subcellular remodeling and injury in the infarct area at the mid-stage of MI.34 During the progression of MI, there are a diverse range of microRNAs35 and proteins that are involved. For instance, transforming growth factor-β,36 tissue inhibitors of metalloproteinase37 and matrix metalloproteinase38 have been identified as upregulated proteins in cells within infarcted areas. The overexpression of these biomolecules contributes to the increased cytoplasmic stiffness (E1) and viscosity (η), which are consistent with the theoretical predictions of our model. To gain insight into the mechanical changes occurring at the molecular scale during the development of MI, we can further extend the self-similar hierarchical model. Specifically, considering the structural details of the cytoplasm, the interstitial fluid inside the cytoplasm (containing water, ions and small proteins) can be regarded as the first level hierarchy, the large proteins present in the cytoplasm as the second level hierarchy, and the interactions between these large proteins as the third level hierarchy.

We then study the changes in E2 during MI progression and find that E2 experiences little alteration during the early stage of MI (Figure 3e and Table S2), indicating that the initial changes in MI mainly occur at the subcellular scale instead of the cellular or higher level. We then find a 2-fold increase in E2 during the midstage of MI (the average E2 values are ∼700 Pa for week 1 and ∼1300 Pa for week 2) and a further remarkable stiffening in the late-stage of MI. Moreover, in the late-stage of MI, the heterogeneity of E2 increases more than double compared to the control group (the CV values are ∼45% for control and ∼100% for week 4). Our results also reveal an evident transformation of the distribution profile from unimodal at week 1 to bimodal at week 2 in the mid-stage of MI (Figure 3e), which is potentially associated with abnormal expression of cytoskeleton proteins and cross-linking.39−41 Thus, these changes in E2 represent the disease-modifying effects of MI on cytoskeletal mechanics and can be used as a new mechanical marker for differentiating samples from the early-, mid-, and late-stage of MI.

Finally, we examine the mechanical stiffness at the cardiac tissue level (E3) after MI (Figure 3f and Table S2). We find that the cardiac tissue experiences severe and continuous stiffening after the early stage of MI. To be specific, there is a 5-fold increase in E3 during the mid-stage of MI (the average E3 values are ∼3 kPa for week 1 and ∼15 kPa for week 2), and the infarcted tissue shows additional stiffening at the late-stage of MI (∼25 kPa for week 4). In addition, we find that after MI, the tissue mechanical variability increases by nearly a factor of 2 (control: ∼56% vs week 4: ∼90%). These changes may be attributed to excessive collagen deposition, loss of myocardial cells and structural integrity of cardiac tissues during MI progression.41,42 This is also supported by our histological findings, including a severe loss of myocardial cells (Figure 1d) and an excessive accumulation of collagen (Figure 1f). Our findings demonstrate that E3, characterizing the tissue scale mechanics, acts as a robust mechanical marker for assessing the mid- and late-stages of MI. It is worth mentioning that according to our theoretical model, the total stiffness of the tissue can be calculated as Etheory = E1 + E2 + E3, which is well validated by measuring the static elastic moduli (Etotal) at the same regions where we assess the dynamic creep responses (Figure S2 and Table S3).

Using receiver operating characteristic (ROC) analysis, we further investigated the ability of these newly defined mechanical markers to distinguish different stages of MI (Figures 4 and S3). The diagnostic performance of each mechanical marker is quantified through the areas under the ROC curve (AUC) and the analysis results are summarized in Table S4. Specifically, the delicate initial mechanical alterations in the early stage of MI can be tracked and distinguished from healthy samples (control vs week 1) using αshort and αlong (AUC > 0.7, Figure 4a,d). After that, E2, E3, and the Etotal reveal excellent discriminating performance (AUC > 0.6) in the mid-stage (week 1 vs week 2) and late-stage (week 2 vs week 4) of MI (Figure 4b–d).

Figure 4.

Figure 4

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Receiver operating characteristic (ROC) analysis of all mechanical markers for discriminating different stages of MI. The ROC curves of αshort (black), αlong (red), E1 (green), E2 (blue), E3 (purple), Etotal (dark red), and η (pink) for distinguishing (a) control and week 1 groups, (b) week 1 and week 2 groups, and (c) week 2 and week 4 groups. The dashed diagonal lines represent the threshold of effectiveness with 0.5 area under the ROC curve (AUC). (d) Ribbon chart of all the area under the ROC curve (AUC) values for assessing the discriminating effectiveness of new mechanical markers for different stages of MI.

These results could have emerged from the sequential order of MI-related changes in cardiac tissues, starting from the cytoplasmic to cellular levels and up to the tissue level (Figure 5). Pathological changes, ranging from subcellular, cellular to tissue levels, and their accompanying mechanical alterations, have also been reported in many diseases, such as aging cartilage and osteoarthritis degradation.1 Currently, it remains challenging to understand the relationship between pathological changes and mechanical alterations at each hierarchical level.6 Herein, the proposed mechanical markers show exceptional diagnostic potential for quantitative assessment of the progression of MI, as well as hold great promise for studying other relevant cardiovascular diseases.

Figure 5.

Figure 5

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New mechanical markers for characterizing intricate remodeling events from subcellular to cellular to tissue levels during different stages of MI. The sequential order of pathological changes from the cytoplasm level, to the cell level, then to the tissue level, leading to continuous multiscale dynamical alterations of cardiac tissues, can be characterized by the new mechanical markers. The top three effective mechanical markers are selected for distinguishing different stages of MI, as shown in Figure 4d.

In summary, by combining AFM-microrheology measurements with a self-similar hierarchical theoretical method, we present a series of hierarchical mechanical markers to quantitatively assess the progression of MI. Unexpectedly, we revealed that all cardiac tissues display a universal two-stage power-law rheology at different time scales, independent of their disease status. Both αshort and αlong can serve as markers for the early diagnosis of MI. Furthermore, we developed a hierarchical theoretical framework, which effectively integrates all of our experimental data, to quantitatively assess the progression of MI. This framework characterizes the multiscale viscoelastic properties of soft tissues at the cytoplasmic, cellular, and tissue levels through four mechanical indexes (i.e., E1, E2, E3, and η). Unlike the conventional biomaterials design that primarily focuses on static elastic stiffness, our approach offers remarkable feasibility in characterizing the natural viscoelastic behavior of soft cardiac tissues. This provides comprehensive and valuable mechanical information that can be utilized in the design of biomedical materials, such as the viscoelastic adhesive patch for MI.18 The sequential order of MI-related changes in cardiac tissues can be precisely distinguished and characterized by different mechanical markers that can be obtained from rheological experiments at once. Thus, these newly defined mechanical parameters can serve as a series of robust markers for tracking the progression of MI. In a future study, we are committed to expanding our approaches into the dynamic mechanics of a wide range of soft tissues. By exploring these tissues under various pathological and physiological conditions, we aim to gain a comprehensive understanding of their altered tissue statuses. This extensive exploration will not only contribute to advancing our knowledge of the dynamic mechanics of soft tissues, but also hold the strong potential to unveil novel insights into the progression of diseases and the development of effective treatment strategies.

Acknowledgments

Financial support from the National Natural Science Foundation of China (Grant Nos. 12122210, 12072252, and 12102326), the Fundamental Research Funds for the Central Universities of China, the research start-up grant (002479-00001) from Nanyang Technological University, and the Agency for Science, Technology and Research (A*STAR) is acknowledged.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.nanolett.3c01712.

  • Materials, methods section detailing myocardial infarction mouse model development, histological staining, tissue preparation, AFM-based creep compliance and static micron-indentation, statistical analysis, static elastic modulus analysis of complete cardiac tissues, diagnostic performance of mechanical markers; figures showing a comparison of theoretically and experimentally determined elastic moduli of complete cardiac tissues, ROC analysis of all mechanical markers; tables showing mean values and coefficients of variation of all mechanical markers, Youden’s indexes, optimal cutoff values, sensitivity and specificity values of high discriminatory power mechanical markers for discriminating different groups; references (PDF)

Author Contributions

G.K.X. and H.G. designed the research. J.Z. and Y.L.L. established the mouse model for MI and carried out the histological analysis. Z.C. conducted the mechanical tests on all cardiac tissues. Z.C. and G.K.X. established the hierarchical theoretical model. Z.C., J.Z., H.G., and G.K.X. conducted all the data analysis. All authors contributed to the writing and editing of the manuscript.

The authors declare no competing financial interest.

Supplementary Material

nl3c01712_si_001.pdf (391.3KB, pdf)

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