A systematic review of the literature was conducted by observing PRISMA guidelines (Page et al., 2021a). This study is registered under the Open Science Framework or OSF (Registration Citation https://osf.io/8h7tb).

A search for articles was carried out in the databases of PubMed, Web of Science, and BASE (Bielefeld Academic Search Engine). The initial survey of the literature consisted of the following search terms:

(mechanic* OR material* OR biomechanic* OR biomaterial*) AND (propert*) AND

(tensil* OR uniaxial* OR quasistatic* OR anisotrop*) AND

(human* OR male* OR female* OR tissue* OR soft-tissue* OR cadaver* OR cadaveric OR postmortem* OR post-mortem* OR autopsy OR autopsie* OR biopsy OR biopsie* OR necropsy OR necropsie* OR dissection* OR dissect* OR donor* OR donation* OR donat* OR prosection* OR prosect* OR intraoperative* OR intra-operative* OR operation* OR operat* OR surger*)

A committee consisting of the co-authors was formed to further refine the search strategy. Two of the co-authors independently screened and identified the articles of interest based on search terms and selection criteria (see OSF, Registration Citation https://osf.io/8h7tb). Any disagreements were solved by consensus, or an independent third-party reviewer was consulted, if necessary.

Titles and abstracts were screened, and duplicates were removed using Endnote20 (Clarivate, United Kingdom) and Zotero software (Roy Rosenzweig Center for History and New Media, George Mason University, Fairfax, VA, United States). If the title or abstract did not provide sufficient information for screening, the full text of the manuscript was examined. All studies that met the selection criteria were included for full analysis and review.

Studies were included if the following inclusion criteria were met:

i. Articles investigated human soft-tissue samples only.

For the inclusion criteria i), studies that involved a test sample that contained more than one (single) type of tissue (e.g., ligament along with its attachment to bone, tendon together with its muscle) were excluded. Records without abstracts, review articles, conference or meeting proceedings, and editorials were also excluded.

The following information was extracted, if available, from the included studies: first author’s last name; year of publication; type of human soft tissue tested; sample shape; sample dimensions of width (midsection), thickness (midsection), CSA (midsection), gauge length, and AR; and clamping modifications. For the AR of gauge length to width at the midsection of the sample, the width was considered the lesser of the two values, unless otherwise reported. Gauge length was recorded as the distance between the clamps for non-tapered samples (rectangle or strips) and the parallel length in the gauge section of tapered samples (dog bone or dumbbell). The geometries of both sample shapes are displayed in Figure 1.

The same information was also retrieved, if available, from ISO standards for anisotropic and/or hyperelastic engineering materials of polymers, composites, leather, and wood. The ISO standards were obtained from the Perinorm database (Beuth, Berlin, Germany).

Data retrieved on the sample geometries from the included studies were compared against ISO standards. Gaussian distribution was assessed, and a comparison between groups was performed using a Mann-Whitney U test. A p-value of 0.05 or less was considered statistically significant. All statistical analyses were carried out in PRISM 9.2.0 (GraphPad Software, San Diego, CA, United States).

Finite Element (FE) simulations of a soft-tissue sample undergoing uniaxial tensile loading were performed using FEBio 3.5.1 and FEBio Studio 1.6.1 (Musculoskeletal Research Laboratories, University of Utah, Salt Lake City, UT, United States, and Musculoskeletal Biomechanics Laboratory, Columbia University, New York, NW, United States) (Maas et al., 2012). The Holzapfel-Gasser-Ogden (HGO) model was used (Gasser et al., 2006), which was chosen to allow for incorporation of parameters pertaining to collagen fiber orientation (i.e., the in-plane fiber orientation angle γ and the fiber dispersion κ ) and of experimentally corroborated material parameters of the extracellular matrix (c, k₁, and k₂) (Niestrawska et al., 2016; Niestrawska et al., 2019). As a first attempt, we considered a sample of little or no dispersion. As such, γ was set to 1° and κ <0.05, with γ indicating two fiber families, each angled one degree away from the specimens’ long axis in the XY-plane and each corresponding to highly aligned fibers, resulting in strong anisotropy. FE simulations were also performed with γ set to 50° and κ <0.05, as previously described (Gasser et al., 2006; Fereidoonnezhad et al., 2020). Next, we sought to investigate whether a small change in the material parameters could influenced the choice of sample shape and sample geometry during tensile loading. As such, material parameters of c (i.e., stiffness of the ground matrix, in kPa) and k₁ (i.e., stiffness of fibers, in kPa) were set to constant values; and k₂ (i.e., stiffening of loading curves due to collagen fibers, dimensionless) was increased.

Each sample was discretized by structured linear hexahedral elements. The element edge length was approximately 0.5 mm, which corresponds to eight elements in thickness. The element edge length was determined by additional numerical experiments on the effect of mesh size on the stress norm. The equilibrium equations were then solved using a three-field numerical scheme suitable for incompressible materials. The incompressibility constraint was enforced using augmented Lagrange multipliers. Tapered and non-tapered samples were modelled and analyzed through a range of aspect ratios (i.e., from 1:1 to 10:1). For both sample shapes, the gauge length was considered as the free length between the gripping jaws.

The simulation, which involves computing the first principle Cauchy stress, was divided into two steps. First, in order to account for clamping at both ends of the sample, the FE simulations were performed with a prescribed reduction of thickness by 1 mm in the clamping areas, which resulted in a thickness of 3 mm or 75% of the initial thickness value of 4 mm. The second step involved increasing strain along the loading direction, which was achieved by moving one of the clamping areas such that the gauge length of the sample was increased by 20%. The clamping and strain conditions were selected based on previous studies (Wale et al., 2021). The implemented boundary conditions are shown in Figure 2. The dimensions of the sample shapes followed ISO standards (Standardization, I.O.f., 2012; Standardization, I.O.f., 2014; Standardization, I.O.f., 2016; Standardization, I.O.f., 2018; Standardization, I.O.f., 2020; Standardization, I.O.f., 2021a; Standardization, I.O.f., 2021b). The resulting distribution of the first principle Cauchy stress was computed and displayed as a color map on the surface. Through a cross-section in the middle of the gauge section, the ratio between the highest and lowest first principle stress was calculated and also displayed as a color map. The ratio between the highest and lowest first principle Cauchy stress allows for a comparison between samples of different sample geometries. FE simulations described above were also performed for both sample shapes on a compressible material by releasing the incompressibility constraints. Also, for a compressible material, FE simulations were also performed with a prescribed reduction of thickness by 0.1 mm in the clamping areas, which resulted in a thickness of 3.9 mm or 97.5% of the initial thickness value of 4 mm. A summary of the material parameters utilized in all the FE simulations are provided in Supplementary Tables S1, S2.

Non-tapered (i.e., rectangular or strips) and tapered (i.e., dog bone or dumbbell) were the two most common sample shapes described, representing 56.0% (202 of 361) and 23.6% (85 of 361) of the included studies respectively (Supplementary Tables S3, S4). Seven studies or 1.9% reported both tapered and non-tapered shapes (Supplementary Table S5). A single edge notched tensile bar, a wedge shape, a square, and a tube shape were each reported once, and 16 studies reported a cylinder, for a total of 20 studies or 5.5% (Supplementary Table S6). The remaining 47 studies (13.0%) did not specify the sample shape (Supplementary Table S7).

From the seven ISO standards, three materials (i.e., polymer, leather, and wood) specified a tapered sample shape (Standardization, I.O.f., 2012; Standardization, I.O.f., 2014; Standardization, I.O.f., 2018; Standardization, I.O.f., 2020), three composite materials specified a non-tapered sample shape (Standardization, I.O.f., 2016; Standardization, I.O.f., 2018; Standardization, I.O.f., 2021a; Standardization, I.O.f., 2021b), and one material (i.e., polymer) included a description of both shapes (Standardization, I.O.f., 2018) (Supplementary Table S8).

Amongst the studies that reported a tapered sample shape, over two-thirds (67 of 92) of the articles provided the ARs and/or details of width and gauge length to calculate AR (Supplementary Tables S4, S5). However, for studies reporting the use of a non-tapered sample shape, these dimensions were seldom described, reported in only 87 of 210 articles (Supplementary Tables S3, S5). Thus, only 154 of 361 studies reported both sample shape and AR dimensions in the gauge section. Several of these studies also reported more than one AR. Overall, for a tapered sample shape, a total of 93 ARs were retrieved, ranging from 0.84 to 13.65; and for a non-tapered sample shape, a total of 125 ARs were retrieved, ranging from 0.20 to 11.86.

For the ISO standard materials, 12 ARs were retrieved amongst the 4 engineering materials using a tapered sample shape, and nine ARs were retrieved from the 4 materials using a non-tapered sample shape (Supplementary Table S8). Overall, the ARs ranged from 1.97 to 7.50 for a tapered sample shape and 3.00 to 10.00 for a non-tapered sample shape.

A comparison between the ARs from the included studies and the ISO standards revealed a significant difference in the mean for both tapered (4.57 versus 4.94, p = 0.0375) and non-tapered (2.94 versus 5.81, p = 0.0002) sample shapes (Figure 4). Of note, the other retrieved sample geometries were underreported and sporadic amongst the included studies (see Supplementary Tables S3–73); as such, no further considerations for comparison could be made.

Over two-fifths of the studies (156 of 361 or 43.2%) reported sample clamping modifications in their experimental setup (see Supplementary Tables S3–S5). The most common modifications were the use of sandpaper and glue, found in 68 and 58 studies respectively. Polymer inserts with pyramids to grip onto the tissues were reported in 10 studies; eight studies used cloth or gauze; seven used paper; seven used tape (adhesive or hook-and-loop); seven used cryoclamps; four studies partially plastinated the ends of their samples; six used rubber and/or roughened/toothed inserts in the clamping jaws; and six used sutures. There was no statistically significant correlation between the use of clamping modifications and sample shape or dimensions of AR.

In our preliminary pilot study, FE simulations performed for both tapered and non-tapered sample shapes under tensile loading within a range of the retrieved ARs are summarized in Figures 5, 6. A 3D overview of the first principle Cauchy stress in a sample is shown in Figure 5, and the stress distribution through a cross-section in the middle of the gauge section of a sample is shown in Figure 6. Tensile loading conditions were prescribed at a 20% strain increase in the gauge section in the undeformed state (i.e., the state of the sample without any further longitudinal displacement from tensile loading) and a 25% reduction of thickness in the clamping regions (Figure 5). Also, for both shapes, two sets of material parameters were explored that differed in one material parameter of k₂.

Two general observations were noted. First, the clamping area extends over a greater length at lower ARs for both sample shapes (Figure 5), which is more pronounced for a non-tapered sample shape (e.g., at an aspect ratio AR = 1:1 in Figure 5). Second, for both sample shapes, across the middle of the gauge section, the fold-difference between the highest and lowest stress follows an exponential decay with increasing ARs (Figure 6).

Upon closer examination at two slightly different sets of material parameters, differences were noted between sample shapes. For a given set of the same material parameters (Figures 6A, B), the fold-change in stress approaches 1 at increasing aspect ratios of AR>3:1 for both a tapered sample (Figure 6A) and non-tapered sample (Figure 6B). However, by increasing material parameter k₂ (Figures 6C, D), this fold difference approaches 1 at increasing aspect ratios of AR>5:1 for a tapered sample shape (Figure 6C) and AR>10:1 for a non-tapered sample shape (Figure 6D). Thus, with this increase in k₂, there is a greater fold-change in stress at smaller ARs for both sample shapes but is more pronounced for a non-tapered sample shape (e.g., at an aspect ratio of AR>2:1 in Figure 6B vs. Figure 6D).

Of note, the cross-sections in Figure 6 are representative outcomes of the FE simulations performed, which can result in generating a color map in discontinuity. In Figure 6A, although the color map is not continuous for AR>5:1, the actual difference between the largest and smallest first principle Cauchy stress values is near zero (as evidenced by a ratio of essentially 1).

For one set of the same material parameters ascribed in Figures 6A, B, we also explored in a limited study other parameters of compressibility with or without reduced clamping deformation (Figures 7A, B), and at an increase in fiber mean angle orientation of γ = 1° (Figures 7A, B) versus γ = 50° (Figures 7C, D). The same results of the FE simulations for an incompressible sample in Figures 6A, B are also included (in blue) in Figures 7A, B for ease of reference. For a sample of little or no fiber dispersion (i.e., κ <0.05), the fold difference approaches 1 at increasing aspect ratios of AR>3:1 for both a tapered (Figures 7A, C) and a non-tapered sample shape (Figures 7B, D)).

Soft tissues are described as incompressible and exhibit anisotropic and/or hyperelastic behavior (Fung, 1993). Since no standard testing protocols exist for human soft-tissue samples, sample geometries retrieved from the included studies were compared against ISO standards for tensile testing of anisotropic and/or hyperelastic engineering materials. There was a significant difference found between ARs from the included studies and ISO standards for both tapered and non-tapered shapes. At first glance, this difference could simply be amounted to the inherent differences in composition of human soft tissues versus engineering materials. However, a closer look and comparison between aspect ratios raises some interesting considerations. As aforementioned, tensile testing of anisotropic materials, in general, require a longer CDLs in comparison to isotropic materials (Arridge and Folkes, 1976; Horgan and Simmonds, 1994). Some of the included ISO standard engineering materials also exhibit isotropic properties. As such, in comparison to isotropic materials, tensile testing of human soft-tissue sample of a given sample shape should require a higher AR (Zwirner et al., 2020c). However, for both tapered and non-tapered sample shapes, the retrieved ARs were smaller for human soft-tissue samples in comparison to the ISO standard materials. This discrepancy might also be explained by extrinsic factors that could influence the mechanical properties of a soft-tissue sample, such the influence of water content (Lozano et al., 2019), chemical embalming (Steinke et al., 2012; Zwirner et al., 2019) and surface coating (Zwirner et al., 2020a). Along with differences in experimental setups, a minimal AR to facilitate a uniaxial stress-strain state in the gauge section would not be the same for all tissues. Therefore, the retrieved sample dimensions and mean ARs from the included studies should not be considered as absolute, but rather treated with caution.

The preliminary results from our pilot study using FE simulations shown herein provide a possible hypothesis on the stress distribution in the middle gauge section during uniaxial tensile loading in a sample of little or no fiber dispersion, for two different sample shapes at two sets of soft-tissue material parameters of c, k₁ and k₂ that differed only in k₂. For a tapered sample shape, the fold-difference in stress through a cross section in the middle gauge section was found to be negligible (i.e., a fold change towards 1) at aspect ratios of, e.g., AR>5:1 with either set of material parameters of c, k₁ and k₂. However, for a non-tapered sample shape, an increase in one of the material parameters of k₂ resulted in a larger aspect ratio of AR>10.1, in order to achieve a negligible fold-difference in stress. Thus, based on this preliminary pilot study on a sample of little or no fiber dispersion, for tapered and non-tapered sample shapes of samples with the same starting thickness and width in the clamping area (i.e., w = w₀ as defined in Figure 1), one hypothesis could be that a greater length in the clamping area could possibly be required for a non-tapered sample shape in order to achieve the same change in gauge length in the undeformed state. Also, a limited study into other parameters of compressibility, decreased clamping deformation, and/or increased fiber mean orientation angle γ might suggest the hypothesis that the fold-difference in stress through a cross section in the middle gauge section approaches 1 at aspect ratios of AR>5:1 (and perhaps even for AR>3:1).

As aforementioned, the rationale behind and the results obtained from our FEA pilot study should not be interpreted as definitive nor conclusive. In the FE simulations shown herein, only two sets of slightly different material parameters were selected for a sample of little or no fiber dispersion; as such, the results cannot be extrapolated to account for all different soft-tissue types of, e.g., cartilage, skin, dura matter and cardiovascular tissues. Also, clamping could impose a strong compression force not represented by the constitutive law which is only valid in the tensile state and at low dispersion. As such, experimentally, clamping modifications (e.g., sinusoidal-shaped or serrated jaws, sandpaper) are employed to increase the contact area of the clamp across the sample (Lake et al., 2023). Furthermore, incompressibility as a characteristic of soft tissues in computational biomechanics is not valid if the sample becomes dehydrated during an experiment. For a dried and dehydrated sample that is quasi-incompressible, a porous medium approach could be considered. However, measures are undertaken experimentally to keep samples moist and hydrated prior to and during testing, with accurate and efficient loading and alignment of the sample into the testing device (Scholze et al., 2020). As such, incompressibility has been assigned during computations. In our pilot study, the clamping parameters were designed such that compression in the clamping region is applied in the direction perpendicular to the tensile load and longitudinal orientation of fibers in the sample. Also, we did not prescribe any kinematic conditions at the outside edges of the sample that could result in physical unloading of the interior fibers from clamping forces. There are computational studies whereby the clamping region is not considered, and Dirichlet displacement boundary conditions could be used to bypass such a scenario. Although a rigorous computation study (or a design of such a study) is beyond the scope of this PRISMA systematic review, we note that any future computational study should also consider a range of material parameters (e.g., fiber and matrix stiffness) as to avoid unphysical behaviors (e.g., auxetic behavior) that can arise from hyperelastic anisotropic constitutive models of soft tissues (Fereidoonnezhad et al., 2020; Morin et al., 2021). Nevertheless, since computational study studies aim to realistically reproduce the experimental tests, accurate and thorough reporting of experimental testing parameters (e.g., sample geometry and clamping conditions) are relevant when determining the material properties of a soft tissue sample through mechanical testing.

For tensile testing of human soft-tissue samples, there are some factors to consider when choosing between a tapered versus a non-tapered sample shape. For our pilot study using FEA simulations, we considered a sample that exhibited hyperelastic behavior and of little or no fiber dispersion. In this scenario, for a gauge section of the same width and thickness, a tapered sample shape would require less overall length and a wider amount of starting material (to accommodate broader clamping ends) in comparison to a non-tapered sample shape. In general, with a non-tapered shape, individual testing samples can be derived in succession by stamping out adjacent strips, thereby maximizing use of the tissue sample. However, when testing until failure, clamping-induced stresses pose a problem in stress distribution, especially towards the clamped ends. For non-tapered samples, the stresses around the clamps often surpasses the stress in the midsection in magnitude and complexity (Horgan and Simmonds, 1994), which was also observed through the FE simulations at different ARs. Thus, if the AR and/or clamping area of a sample is inadequate during tensile loading, failure of the sample is more likely to occur within the unknown high-stress regions at the clamps. As aforementioned, the distance between clamps needs to accommodate a sufficient CDL so that the stresses from clamping can dissipate and allow for failure in the gauge section of a sample. In other words, for a given CDL, failure in the mid-section of a sample from tensile loading can be achieved by increasing the AR and thereby reducing the CSA in the gauge section. The forces required to pull the sample apart would act across a smaller CSA, and as such, the differences in stress in the gauge section would be greater than the stresses around the clamps, thereby promoting failure in the midsection. In essence, this reduction in the CSA by increasing the AR describes the intention of a tapered sample shape–a tapering of the sample in the gauge section reduces the CSA in the midsection with wider ends in the clamping area. Therefore, while a non-tapered sample may result in a more efficient use of tissue by minimizing tissue waste, tapered samples would favor greater stress homogeneity and propensity for failure in the gauge section under tensile loading. However, in this oversimplified view of a hyperelastic material, perhaps a tapered geometry could be advocated. In reality, deformation of soft tissues are time- and history-dependent, and the rate of deformation is related to the amount of the stress applied in a non-linear manner. As such, global (nominal) strains (i.e., change in length along the entire sample) and local strains (i.e., change in length in the gauge section) would differ more for a tapered geometry. If a relaxation phase follows the loading phase in a uniaxial test, likely the global (and not the local) strain will be kept constant. For a tapered sample, the result will be a non-zero strain rate in the different regions of the sample. Furthermore, the use of a tapered shape requires a local strain measurement and test control based on this local readout (e.g., through digital image correlation), which is absent in most cases. Taken together, the choice between a tapered and non-tapered sample is not straight-forward and a recommendation for one shape over the other is beyond the scope of this review.

The amount of starting material and the availability of human tissue samples are often limited, and as such, higher ARs may be difficult to achieve for a given CDL and sample shape. By enhancing friction at the interface between the clamps and the tissue, some issues associated with clamping (e.g., a more complex stress state at the clamped ends) can be attenuated. As such, the clamping force, as well as the area of clamped tissue, can be set a lower threshold whilst still maintaining a sufficient tensile load across the sample during tensile loading. Also, with a smaller area of clamped tissue, a greater amount of the sample would potentially be available to achieve a larger AR for a given sample shape. As such, the result would be greater homogeneity in the stress-strain state in the gauge section of the sample. The most common methods to enhance the friction include the use of sandpaper, cyanoacrylate glue, partial plastination, or additively manufactured serrated clamps. Most of these methods are inexpensive and easy to implement and therefore should be considered for tensile testing of human soft-tissue samples.

Taken together, we suggest a simple metric of reporting testing parameters when performing uniaxial tensile testing of human soft tissues (Table 1). In brief, three general categories of information are proposed: Tissue, Sample, and Experimental Setup.

For tissue specifics, these details would include the type of tissue (e.g., connective tissue, muscle), its anatomical location and name (e.g., leg, semitendinosus muscle), and other tissue characteristics (e.g., normal or unaffected versus pathologic); the source of the tissue (e.g., biopsied, operative, autopsied); the total number of tissue-donors; the age of tissue donors at time of retrieval (e.g., ages 55–74); the total number of each tissue-type retrieved from each tissue donor (e.g., two patellar tendons and two medial menisci of the knee retrieved from each of the 10 tissue donors, for a total of 20 patellar tendons and 20 medial menisci); and state of the tissue for testing (e.g., fresh or intact, frozen then freeze-thawed, preserved with method of fixation or chemical processing). If possible and under the appropriate ethical considerations, International Classification of Diseases or ICD codes (for the current ICD version, see https://icd.who.int/en) ascribed to the tissue donor could also be included.

For sample specifics, details would encompass the sample shape (e.g., tapered or dog bone) and method of achieving the shape (e.g., scalpel, scissors, die cutting); the total number of samples tested for each sample shape; and sample dimensions of overall length, width and thickness, gauge length, gauge width, and thickness at the middle of the gauge section; AR and CSA and in the gauge section; clamping area and if/any modifications to the clamped ends of the tissue (e.g., plastinated ends, sutures, cloth, paper, sandpaper) would also be noted.

For experimental setup, details would encompass information on the clamping method or type of clamps (e.g., self-tightening grips, pinching, webbing grips, rope and thread grips, hydraulic grips, wedged grips, pneumatic grips, manual vice grips; cryoclamps); clamp modifications (e.g., glue, sandpaper, rubber, serrated-pyramid); measurement methods (e.g., ruler, calipers, digital image correlation, laser); testing conditions (e.g., samples tested in air, in solution, under temperature control); and testing machine (e.g., original design or commercially available). Overall, such details would provide an important framework towards standard reporting of testing parameters used in tensile testing of human soft-tissue samples, thereby improving repeatability, reproducibility, and comparability of the results.

To conclude, it is worth noting that the findings from the systematic review presented herein, however intuitive or rudimentary they may (or may not) seem, could not have been accomplished without a rigorous and thorough survey of the literature, which was achieved by observing PRISMA guidelines. The advocacy for a set of criteria or standards in reporting for peer-reviewed publications is not novel (Munafo et al., 2017). Furthermore, journals such as Nature have their own mandatory reporting summary templates (https://www.nature.com/documents/nr-reporting-summary-flat.pdf). The above proposal on which testing parameters to report in future studies should not be view as absolute but should serve as a starting point towards standards and practice guidelines. In fact, such an endeavor necessarily requires further input from those who are engaged in experimental and/or computational studies in the mechanical testing of human soft tissues.