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First published online July 20, 2006
Journal of Experimental Biology 209, 3025-3042 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.02304
The influence of collagen fiber orientation and other histocompositional characteristics on the mechanical properties of equine cortical bone
1 Utah Bone and Joint Center, 5323 S. Woodrow Street #202, Salt Lake City,
UT 84107, USA
2 Bone and Joint Research Laboratories, Deparment of Veteran's Affairs
Medical Center, Salt Lake City, UT, USA
3 Department of Orthopaedics, University of Colorado Health Sciences Center,
Aurora, CO, USA
4 Orthopaedic Research Laboratory, University of Utah, Salt Lake City, UT,
USA
* Author for correspondence at address 1 (e-mail: jskedros{at}utahboneandjoint.com)
Accepted 27 April 2006
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Summary |
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 TOP Summary IntroductionMaterials and methodsResultsDiscussionReferences |
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Key words: collagen fiber orientation, osteon, equine third metacarpal, cortical bone, bone mechanical properties
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Introduction |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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; Kalmey and Lovejoy,
2002; Mason et al.,
1995; Riggs et al.,
1993a; Skedros,
2001; Skedros et al.,
2004; Skedros and Kuo,
1999; Skedros et al.,
1996). Standard material tests (conducted typically in tension but
not in the context of the local habitual loading mode) in bones from various
species have shown that predominant CFO can significantly influence cortical
bone stiffness and strength, supporting the suggestion that regional
variations in this characteristic are generally mechanically important
(Ascenzi, 1988;
Batson et al., 2000;
Currey, 2002;
Evans and Vincentelli, 1969;
Evans and Vincentelli, 1974;
Martin and Boardman, 1993;
Martin and Ishida, 1989;
Reilly and Burstein, 1974;
Riggs et al.,
1993b).1
With few exceptions (e.g. Riggs et al.,
1993b), these past studies did not examine the relative influences
of predominant CFO, mineralization and other ultrastructural/microstructural
variables on regional mechanical properties specifically in the more
physiologic context of the presumed habitual loading mode, or
`strain-mode-specific' (S-M-S) loading (e.g. compression testing specimens
from cortical regions habitually loaded in compression, or tension testing
specimens from cortical regions habitually loaded in tension). Mechanical
testing in this context is important since: (1) in vivo surface
strain measurements have shown that many long bones receive a consistent
direction of bending, which in most long bones occurs during the time of peak
loading of stance phase in typical gait-related activities
(Biewener, 1993;
Biewener and Bertram, 1993;
Biewener et al., 1986;
Coleman et al., 2002;
Fritton and Rubin, 2001;
Indrekvam et al., 1991;
Lanyon and Baggott, 1976;
Lanyon et al., 1979;
Lieberman et al., 2003) and
(2) cortical bone is substantially stiffer and stronger, has different fatigue
behavior and likely has greater toughness and/or energy absorption in
compression than in tension or shear
(Boyce et al., 1998;
Burstein et al., 1976;
Carter and Hayes, 1977;
Jepsen et al., 2001;
Norman et al., 1996;
Pattin et al., 1996;
Reilly and Currey, 2000;
Turner et al., 2001). Because
long bones must accommodate regional strain-mode-related disparities in
mechanical requirements in order to ensure the beneficial aspects of strain
produced by loading (e.g. nutrient delivery)
(Martin, 2003), S-M-S
mechanical testing may demonstrate a rather different role for CFO and other
histocompositional characteristics than suggested by results of non-S-M-S
testing (which typically emphasize pre-yield behavior). This is also suggested
by studies showing that variations in collagen organization can significantly
influence post-yield behavior (e.g. energy absorption) and the microdamage
processes (e.g. microcrack formation, propagation and arrest) that correlate
with fatigue life (Burr, 2002;
Burstein et al., 1975;
Gibson et al., 2006;
Hiller et al., 2003;
Riggs et al., 1993b;
Shelton et al., 2000;
Wang et al., 2001;
Zioupos et al., 1999). From
this perspective we hypothesized that mechanical testing of bone in the more
physiologic context of S-M-S loading would show that, among several
histocompositional characteristics, CFO is more important in influencing
energy absorption and other aspects of post-yield behavior than was revealed
by studies conducted in non-S-M-S contexts. In view of previous
histocompositional studies of equine limb bones, expected CFO correlations in
S-M-S test specimens include relatively more longitudinal CFO in habitual
tension regions and relatively more oblique-to-transverse CFO in habitual
compression regions (Mason et al.,
1995; Skedros et al.,
1996).
Using the equine third metacarpal (MC3), we examined the biomechanical
significance of variations in CFO, mineralization and other microstructural
characteristics in the context of S-M-S vs non-S-M-S testing. In
general, we selected the equine MC3 because it has been the focus of studies
dealing with its mechanical properties and biomechanical and
pathophysiological (e.g. stress fractures) implications of its
histocompositional organization (Hiller et
al., 2003; Les et al.,
1997; Martin and Boardman,
1993; Martin et al.,
1997; Nunamaker,
2001; Reilly et al.,
1997; Skedros et al.,
2003a; Skedros et al.,
1996; Stover et al.,
1992). More specific reasons for selecting this bone included the
fact that independent investigators have described its habitual strain
distribution at mid-diaphysis using in vivo strain measurements
(Biewener et al., 1983a;
Biewener et al., 1983b;
Gross et al., 1992). In the
most recent of these studies (Gross et
al., 1992), a finite element mesh and three equidistantly placed
triple-rosette strain gauges were used to describe strain characteristics
across an entire mid-diaphyseal cross-section of a thoroughbred horse's MC3.
Their results showed that the neutral axis (where strains change from
compression to tension) passed through the dorsal cortex, resulting in a
narrow band of tension with the remainder of the cortex experiencing a wide
range of compression strains (Fig.
1). Additionally, toward the end of the stance phase of the
medium-speed gait examined, the neutral axis shifted significantly, placing
the dorsal-lateral region in net tension. This strain distribution was also
found in quarter horses when run at similar speeds (T. S. Gross and C. T.
Rubin, personal communication). Although our hypotheses were formed
prospectively in the context of this strain distribution, we also consider an
alternative distribution reported by Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b). In
this case a habitual tension-loaded region was not found; compression
dominated along the dorsal-palmar axis (i.e. where the two gauges were
placed), ranging from low compression in the dorsal aspect to high compression
in the palmar aspect. As described below, considering both of these habitual
strain distributions was important since the habitual loading histories of the
bones that we used were obtained from non-thoroughbred horses, from which we
could not determine details of their loading histories.
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Materials and methods |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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).
Mechanical test data from our previous study were also used in the present
study.
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) and used
previously (Skedros et al.,
2003a), these locations represent areas that experience in
vivo tensile strains, and a range of compression magnitudes [e.g.
dorsal-medial (low) to palmar-medial (high)]
(Fig. 1,
Fig. 2A). This strain
distribution was derived from in vivo strain data obtained from three
triple-rosette gauges at equidistant locations and a two-dimensional
finite-element mesh of a mid-diaphyseal MC3 of a 460 kg 5-year-old
thoroughbred horse that was studied during a medium-speed trot (3.6 m
s-1). This study showed that toward the end of stance phase, the
neutral axis shifted significantly, loading the lateral cortex in both tension
and compression at different times during stance. Observations in racing
horses imply that this shift might be greater at higher speeds, which places
more of the lateral cortex in net tension
(Nunamaker, 2001). In
contrast, an independent study reported in vivo data obtained from
two triple-rosette strain gauges at mid-diaphysis, with one located on the
dorsal and one on the palmar cortex, with no finite element analysis, of three
relatively smaller non-Thoroughbred horses (268, 281 and 291 kg) during gaits
ranging from walking (1.3 m s-1) to galloping (6.2 m
s-1) (Biewener et al.,
1983a; Biewener et al.,
1983b). These results showed the absence of net tension during the
stance phase along the dorsal-palmar axis. Rather, these regions experienced
net compression, and the magnitudes of the prevalent/predominant compression
strains increased across the cortex from low in the dorsal region to high in
the palmar region. The data from the present investigation are also considered
in the context of this alternative strain distribution.
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).
Although Riggs et al. used 8 mmx8 mmx8 mm cubes in compression
testing of equine radii, we used 5 mmx5 mmx5 mm cubes because of
narrower cortices in some of the MC3 locations
(Fig. 3B).
From contralateral bones, a 50 mm-thick segment was sectioned transversely
such that the midpoint was at 50% bone length. Rectangular slabs were milled
to the proportions of the dumbbell-shaped tension specimens used in earlier
work (Riggs et al., 1993b;
Evans et al., 1992)
(Fig. 3A). Two `tension'
(dorsal-lateral, D-L, cortex) and two `compression' (palmar-medial, P-M,
cortex) specimens were milled from each bone
(Fig. 2B). However, only one
tension specimen could be milled from the dorsal-lateral cortex of two bones
with narrow cortices; this reduced the total number of specimens from 40 to
38. During milling, orientation of the long axes remained parallel to the
longitudinal diaphyseal axis. Integrity of the specimens during the extraction
and milling process included cutting and milling slowly under saline
irrigation to minimize heating of the bone, saw blade and milling bit.
Specimens were also examined under a dissecting (epi-fluorescence) microscope
to ensure the absence of surface flaws.
Using an Instron Model 4303 (Canton, MA, USA) with a 25 kN load cell, cubic specimens were compressed to failure along the longitudinal diaphyseal axis unrestrained between parallel platens at a strain-controlled rate of 0.001 s-1. Strain measurements were obtained from the measured crosshead displacement and corrected for machine compliance.
Tension tests were performed using an MTS® 858 Bionix testing machine
(MTS® Systems Corporation, Eden Prairie, MN, USA) with a 20 kN load cell.
Tensile specimens were held by identical grips that spanned the transverse
breadth of the specimen ends. This allowed elongation along the anatomic
longitudinal axis of the bone. Strain measurements were obtained using an
MTS® 632.13F-20 extensometer attached to each specimen with rubber O-ring
fasteners. Specimens were loaded to failure at a strain-controlled rate of
0.01 s-1. The use of different strain rates in compression and
tension was done so that the compression and tension test data from our
previous study (Skedros et al.,
2003a) could be compared to data previously reported
(Riggs et al., 1993b) that
also used these different strain rates (verified by personal communication, C.
M. Riggs). Although these previous investigators did not provide a rationale
for the use of these different strain rates, they both fall in a physiologic
range. Additionally, Evans et al. have shown similar mechanical behaviors of
equine MC3 cortical bone tested in tension at 0.01 s-1 and 0.001
s-1 strain rates (Evans et al.,
1992).
Elastic modulus, yield stress and strain and ultimate stress and strain
were determined for each specimen in both tension and compression testing,
with the yield point defined at 0.2% strain offset (0.002 strain offset
criterion) (Fig. 4B). Although
this strain-offset yield criterion is arbitrary, it is commonly used to define
material yield (Tommasini et al.,
2005; Turner,
1989; Turner and Burr,
1993).
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) and ground and polished to a surface transverse to the
longitudinal diaphyseal axis. This surface was then imaged in the
backscattered electron (BSE) mode of a scanning electron microscope
(Mason et al., 1995).
Depending on the cross-sectional area available for analysis, one or two
high-resolution 50x BSE images (1.6x2.4 mm, Polaroid 52 film:
Polaroid Corp., Waltham, MA, USA) were taken of the ground/polished surfaces
of the fragments of each tested specimen. These images were used for standard
stereological point-counting techniques
(Parfitt, 1983;
Russ, 1986), including
analysis of: secondary osteon population density (On.N/T.Ar), fractional area
of secondary osteon bone (On.Ar/T.Ar), estimated mean area per osteon (On.Ar),
fractional area of porosity (porosity) and osteocyte lacuna population density
(Ot.Lc.N/B.Ar) (see List of Abbreviations)
(Skedros et al., 2000;
Skedros et al., 1996).
Secondary osteon counts included: (1) complete secondary osteons, (2)
partially formed osteons, in which the entire circumference of the preceding
resorption space was lined with new bone and (3) osteon fragments with a
complete central canal. Central canals were considered part of the osteons.
The On.N/T.Ar refers to the number of secondary osteons (On.N) per
mm2 of the total (T) image area (Ar), where T.Ar includes central
canals but excludes primary vascular canals and Volkmann's canals. The
On.Ar/T.Ar is the fraction of total bone area occupied by secondary osteon
bone and is expressed as a percentage: (secondary bone area/total bone
area)x100. Porosity is also expressed as a percentage and is defined as:
(total porosity area/total bone area)x100. Porosity includes all
vascular canals but excludes osteocyte lacunae and canaliculi. The On.Ar was
calculated by dividing the total area of complete secondary osteons in each
image by the total number of complete secondary osteons in each image. The
Ot.Lc.N/B.Ar refers to the number of osteocyte lacunae per mm2 of
bone (B.Ar), where B.Ar excludes all non-lacunar porosity (e.g. primary
vascular canals, Volkmann's canals and central canals of secondary osteons).
Osteocyte lacuna population density is not meant to estimate the concentration
of osteocytes since no differentiation could be made between living and dead
osteocytes.
Mineral content (% ash) was determined by ashing a portion representing
30% of each fractured specimen (Fig.
3C), and was calculated by dividing the mass of the ashed bone
(Mab) by the mass of the dried, defatted bone
(Mdb), and multiplying by 100
[(Mab/Mdb)x100]
(Skedros et al., 1996).
Two 1 mm-thick sections, obtained from each of the embedded specimens used
in the BSE-image microstructural analyses, were ultra-milled to 100±5
µm. In these sections, and depending on area of the specimen fragments
available for analysis, predominant CFO was determined in 1-3 62x images
using circularly polarized light, according to published methods
(Boyde and Riggs, 1990;
Skedros et al., 1996).
Regional differences in CFO were quantified in terms of corresponding
differences in the transmitted light intensity, where darker gray levels
(lower numerical values) represent relatively more longitudinal CFO and
brighter gray levels (higher numerical values) represent relatively more
oblique-to-transverse CFO. Transmitted light intensity is referred to as
weighted mean gray level (WMGL). The methods used to quantify regional CFO
differences in cortical bone as differences in gray levels
(Bromage et al., 2003;
Skedros et al., 1996) have
produced relative differences that are similar to the `longitudinal structure
index' described by Martin and co-workers
(Martin and Burr, 1989;
Martin et al., 1996a), and
recently used by Takano et al. (Takano et
al., 1999) and Kalmey and Lovejoy
(Kalmey and Lovejoy,
2002).
A one-way ANOVA design with Fisher's PLSD test was used to assess regional variations. Analyses of the histocompositional characteristics were conducted on: (1) all sampled regions, (2) sampled regions from locations habitually loaded in compression (S-M-S compression), and (3) sampled regions habitually loaded in tension (S-M-S tension). Pearson's correlation coefficients (r values) were determined for comparisons of mechanical test results and histocompositional values. Multivariate multiple regression analyses were used to determine the percentage of variance explained by each histocompositional variable for each mechanical property based on R2 values, allowing for the number of degrees of freedom. Although formal analysis of statistical interactions could not be determined due to limitations in degrees of freedom, the Pearson correlation coefficients that are reported were examined in order to identify and discuss how these might reflect interactions between factors.
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)
(SAS v.8, 2002. Cary, NC, USA). Compression-tested specimens from the lateral
cortex were excluded from regression analyses since this region might be
adapted for the tensile strains that it could receive at higher speeds. In
forward stepwise multiple regression analyses, all variables are independently
considered in the first regression analysis, or step, which results in a
ranking of the variables according to relative variance explained. During the
second step, the top variable (i.e. highest variance explained) from the first
regression is carried over, and all possible two-variable regressions
containing this top variable are computed. Again, the two-combination model
explaining the most variance is identified, thereby ranking the second most
explanatory variable. The third step involves all possible three-variable
models containing the first two explanatory variables. This process continues
until all variables have been added to the model. |
Results |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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)
(Fig. 1). The alternative
strain distribution of Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b) is
considered in the Discussion.
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During tensile testing, premature catastrophic failure (failure at low stress) and/or failure outside the region between the extensometer clips resulted in seven specimen exclusions from the dorsal-lateral region and two specimen exclusions from the palmar-medial cortex; this reduced the sample size from 19 to 12 in the dorsal-lateral cortex and from 19 to 17 in the palmar-medial cortex. No failures occurred at the gripped ends. Three compression specimens from the lateral cortex were also excluded for premature catastrophic failure (failure at low stress); this reduced the sample size from 10 to 7.
When considering all tests, elastic modulus values were on the order of 35% higher in tension testing than in compression testing regardless of their location in the bone (i.e. when considering all S-M-S and non-S-M-S data). Yield stress was lower in S-M-S tension testing (148.59 MPa, dorsal-lateral) than in S-M-S compression testing (167.03 MPa, mean of palmar-medial and dorsal-medial) (P>0.2 for dorsal-lateral in tension vs palmar-medial in compression; P<0.001 for dorsal-lateral in tension vs dorsal-medial in compression). Ultimate stress of the tension-tested dorsal-lateral cortex (161.20 MPa) was significantly lower than the compression-tested dorsal-medial cortex (191.54 MPa) (P<0.0001), and only slightly lower than the compression-tested palmar-medial cortex (170.28 MPa) (P>0.14).
Regardless of location in the bone, pre-yield (elastic) energy values were on the order of 60% lower in tension tests, and post-yield (plastic) energy values were on the order of 70% lower in compression tests. Values of pre-yield (elastic) energy and post-yield (plastic) energy show significant S-M-S differences between the tension-tested dorsal-lateral cortex, and the compression-tested palmar-medial and dorsal-medial cortices (P<0.0001 for pre-yield energy; P<0.01 for post-yield energy).
The results from the S-M-S testing of both the dorsal-lateral and palmar-medial cortices show that in a number of ways the bone material is unexpectedly `weaker' in S-M-S testing than non-S-M-S testing. For example, the dorsal-lateral cortex had lower pre-yield energy and yield and ultimate stresses in S-M-S tension testing when compared to non-S-M-S compression testing. Additionally, the palmar-medial cortex had lower post-yield and total energy, ultimate strain and elastic modulus in S-M-S compression testing when compared to non-S-M-S tension testing.
Histocompositional analyses
When considering data in a non-S-M-S perspective, there were generally no
significant On.N/T.Ar, On.Ar/T.Ar, On.Ar, Ot.Lc.N/B.Ar, or porosity
differences in either tension-tested or compression-tested specimens, and
mineral content (% ash) variations were minimal (<1.5%)
(Table 2). Predominant CFO
values were also similar in tension-tested specimens (P>0.5) even
though they are presumed to come from habitual `tension' or `compression'
regions (Table 2, rows A and
B). Among compression-tested specimens, there were also no significant
differences in predominant CFO between the dorsal-lateral `tension' and
dorsal-medial `compression' cortices (P>0.5), but each of these
locations had significantly more oblique-to-transverse collagen than the
lateral cortex (P<0.01). This difference, representing gray levels
ranging from 132 to 94, has been shown to be significant in affecting
stiffness and strength in material testing of cranial `tension' and caudal
`compression' cortices of equine radii
(Riggs et al., 1993b).
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Correlation matrices suggest that some variables (especially predominant CFO and On.N/T.Ar (and/or On.Ar/T.Ar)) can be interdependent (Table 3A-D). Two unexpected findings in the histocompositional data included: (1) the dorsal-lateral `tension' specimens tested in tension and compression had significantly different histocomposition in two out of seven characteristics (On.N/T.Ar, On.Ar/T.Ar; rows A and C in Table 2), and (2) the palmar-medial `compression' specimens tested in tension and compression had significantly different histocomposition in four out of seven characteristics (On.N/T.Ar, On.Ar/T.Ar, porosity, CFO; rows B and D in Table 2). Additionally, in each location these variations were present in 50% to 70% of the bone pairs.
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Regression analyses
Results of stepwise regression analyses show that in S-M-S compression
tests (Table 4A), CFO was the
most important histocompositional variable in explaining total energy, and
second-most important in pre-yield and post-yield energy absorption. In S-M-S
tension testing (Table 4B), CFO
was most important in explaining post-yield energy and total energy. Compared
to energy absorption data, CFO was less important in explaining elastic
modulus, and yield and ultimate stress in S-M-S tension and compression tests.
Porosity in S-M-S tension tests, and % ash and Ot.Lc.N/B.Ar in S-M-S
compression tests best explained variability in these three mechanical
parameters. For example, in S-M-S compression Ot.Lc.N/B.Ar was the first or
second most important explanatory variable in pre-yield energy, elastic
modulus, yield stress and ultimate stress. Porosity was the first or second
most important in explaining all six S-M-S tension tests. In contrast, % ash
was the first or second most important explanatory variable in four of the six
S-M-S compression tests.
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In S-M-S compression tests, only 34-70% of the total variance is explained by all seven variables in the measured mechanical parameters. In contrast, the same variables explained comparatively greater variance in S-M-S tension tests.
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Discussion |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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). They showed that CFO was consistently the best predictor of
tensile strength. Using bovine bone, Martin and Boardman demonstrated that
among CFO, porosity, mineralization and histologic type (plexiform, osteonal,
or mixed), CFO ranked highly as a predictor of bending properties
(Martin and Boardman, 1993).
Such studies support a conventional view that CFO primarily affects
strength- or stiffness-related material properties of
cortical bone (Ascenzi, 1988;
Evans and Vincentelli, 1974;
Reilly and Burstein, 1974;
Vincentelli and Evans, 1971).
However, as noted, these and other studies have sustained this view without
examining mechanical behavior in the context of S-M-S loading. Additionally,
these previous studies have typically examined non-equine bone, and the extent
to which inter-species comparisons can be made between mechanical properties
of bovine and equine limb-bone tissue is not well understood
(Martin et al., 1997).
Limitations of the present study may include our prospective preference,
and hence selection bias, for the habitual strain distribution derived from
the finite element analyses of Gross et al.
(Gross et al., 1992). However,
the alternative strain distribution of Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b) is
considered below. Examining cortical bone of animals from which in
vivo strains and finite element analysis were obtained would have
strengthened our comparisons. The importance of this limitation is reduced by
the observation that the strain distribution obtained by Gross et al.
(Gross et al., 1992) is highly
consistent in quarter horses and Thoroughbreds when run at similar speeds (T.
S. Gross and C. T. Rubin, personal communication). Additional limitations are
revealed by the results of the multiple regression analyses for S-M-S testing
showing that the histocompositional characteristics in tension tests explain a
much greater percentage of variance than in compression tests (e.g. in S-M-S
compression testing, Ot.Lc.N/B.Ar ranks first in pre-yield energy absorption,
but explains only 18% of variance). Predictive power in compression tests may
be improved by further increasing sample size and/or the area/volume of each
specimen analyzed, and by considering additional histocompositional
characteristics such as collagen cross-links, mineral crystal size and
orientation, population densities of specific secondary osteon `types' (e.g.
`hoop' osteons, which can influence fatigue resistance by modifying osteon
pullout), and microscopic mineralization heterogeneity (e.g. percentages of
compliant (younger) vs less compliant (older) osteons or interstitial
bone) (Bailey et al., 1999;
Boskey et al., 1999;
Burr, 2002;
Gibson et al., 2006;
Hiller et al., 2003;
Martin et al., 1996b;
Turner et al., 1995;
Yeni et al., 2001;
Zioupos and Currey,
1998).
Recent studies indicate that regional variations in some histocompositional
characteristics (e.g. variations in collagen content/structure), which can
substantially affect cortical bone toughness, are not necessarily linked with,
nor explain, a relatively small percentage of variance in the tissue's mineral
density, porosity, elastic modulus, yield strength and ultimate strength
(Currey et al., 1996;
McCalden et al., 1993;
Reilly et al., 1997;
Wang et al., 2001). From this
perspective, additional characteristics from the residual portions of our
tested specimens will be used in future studies that examine these
possibilities. This is not unexpected since many of the material
characteristics are interdependent (e.g. On.N/T.Ar, On.Ar and On.Ar/T.Ar are
all produced by the remodeling process). Important interactions were also
detected in our results, and are illustrated by the high correlations shown in
Tables 3A-D (especially between
CFO and On.N/T.Ar and CFO and On.Ar/T.Ar in S-M-S tests).
Strain-mode-specific tension testing in the dorsal-lateral `tension' region
showed unexpectedly more oblique-to-transverse CFO (i.e. the higher WMGLs
typically associated with compression) than the other regions similarly
tested. An explanation for this finding may be that the strain distribution of
Gross et al. (Gross et al.,
1992) does not apply for the majority of the bones from the
non-Thoroughbreds that we examined. Although some of our animals might have
experienced tension strains that were of magnitudes/durations that were
adequate for evoking the `expected' collagen adaptation in the dorsal/lateral
cortices (i.e. lower WMGL, representing more longitudinally oriented CFO)
(Carando et al., 1991;
Kalmey and Lovejoy, 2002;
Mason et al., 1995;
Riggs et al., 1993a;
Skedros et al., 2003a;
Skedros et al., 2004;
Skedros et al., 1996), it is
possible that the majority of our horses did not. In turn, the strain
distributions across the mid-diaphyseal MC3s of our non-Thoroughbreds may have
experienced net compression as described by Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b). This
would be expected to produce relatively higher WMGLs (i.e. relatively more
oblique-to-transverse CFO) as a consequence of the habitual compression. If
the strain distribution of Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b) is
actually more applicable to our sample of bones, then this helps to explain
why the dorsal-lateral cortex exhibited CFO more indicative of a compression
environment.
Paradoxes and inconsistencies:
Dissimilar histocomposition in similar locations
It is difficult to explain why the dorsal-lateral specimens tested in
tension and compression (Table
2, rows A and C) and the palmar-medial specimens tested in tension
and compression (Table 2 rows B
and D) did not have similar histologic characteristics. In other words,
specimens from essentially the same location in the MC3 should have similar
histologic organization. Dissimilar organization occurred in two out of seven
characteristics (On.N/T.Ar, On.Ar/T.Ar) for the dorsal-lateral cortex, and
four out of seven characteristics (On.N/T.Ar, On.Ar/T.Ar, porosity, CFO) for
the palmar-medial cortex. These `paradoxes' were not infrequent, occurring in
50% to 70% of the ten left-right bone pairs for each of the six cases noted.
The relatively small sampling volumes, especially for the dumbbell specimens
used for tension testing, might influence these data. It is possible that
inadequate sampling was further skewed by natural variation within the
locations examined, which could be influenced by the laterality of gait
(`handedness') that has been shown in galloping horses
(Deuel and Lawrence, 1987).
But the random selection of bones for compression vs tension testing
would be expected to minimize this possibility since roughly equal left and
right bones were used for each testing mode.
We suggest that it is more likely that these paradoxical and inconsistent
findings reflect the possibility that some of our bones had habitual strain
distributions similar to that described by Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b), and
others had habitual strain distributions similar to that described by Gross et
al. (Gross et al., 1992). It
is also possible that some may have had habitual loading conditions that were
intermediate with respect to these two loading regimes. Additionally, the
shifting neutral axis shown by Gross et al. represents significant torsion,
which can obscure `expected' strain-mode-related osteonal or CFO patterns in
limb bones that also receive bending. For example in bones that receive
habitual torsion superimposed on bending (e.g. turkey ulnae and sheep tibiae),
regional CFO variations and secondary osteon distributions that might be
expected between the `tension' and `compression' regions of these relatively
complexly loaded bones do not occur; shear stresses may have `priority' in
evoking adaptation when compared to these other strain modes
(Skedros, 2001;
Skedros and Hunt, 2004).
Hence, we have speculated that the relatively uniform oblique/transverse CFO
across mid-diaphyseal cross-sections of these bones is an adaptation
for prevalent/predominant shear (Skedros
and Hunt, 2004). If these interpretations are correct in whole or
in part, the paradoxical findings reported in the present study may similarly
represent relatively heterogeneous regional histologic organization that
correlates with relatively heterogeneous loading histories in the sample
studied. Indirect support for this possibility is further suggested by the
observation that equine radii from various breeds show highly consistent
regional histologic organization that correlates with habitual tension- and
compression-loaded (cranial/caudal) cortices
(Riggs et al., 1993a;
Riggs et al., 1993b;
Mason et al., 1995). In
contrast to the equine MC3, the spatially consistent structure/function
relationships in the equine radius are also correlated with this bone's
longitudinal curvature and oblong cross-sectional geometry, which are
synergistic in highly constraining bending in the cranial-caudal direction
(Bertram and Biewener, 1988;
Skedros et al., 1996).
Similar to our findings in equine MC3s, unexpected or paradoxical regional CFO
patterns in mid-diaphyses of human femora have been reported in a study where
it was hypothesized that habitual medial-lateral (compression) to
anterior-lateral (tension) bending in this region would be of sufficient
intensity/duration to evoke corresponding S-M-S CFO patterns
(Goldman et al., 2003).
Although the strain environment at the mid-diaphyseal femur has never been
measured experimentally, in vitro strain measurements on femora
loaded in simulated single-legged stance contradict this idea of a habitual
medial-lateral bending moment by showing increased inter-specimen variability
of the strain distribution and reduction in the magnitude of the bending
moment at this location (the medial-lateral bending moment is substantially
greater in the subtrochanteric area)
(Cristofolini et al., 1996;
Oh and Harris, 1978).
Consequently, the relatively complex loading environment (torsion/bending) of
the femoral mid-diaphysis might explain why `expected' tension/compression
lateral/medial CFO differences are typically absent
(Goldman et al., 2003;
Portigliatti Barbos et al.,
1984; Portigliatti Barbos et
al., 1987), but are present in the proximal diaphysis and
subtrochanteric regions (Skedros et al.,
1999) where a habitual medial-lateral (compression-tension)
bending moment has been shown in vivo during walking at peak loading
of stance phase (Aamodt et al.,
1997). Our explanation for these relatively heterogeneous
histologic findings in mid-diaphyseal human femora is similar to that given
for the present study; heterogeneous loading histories, especially if the
bones studied received varying amounts of torsion and bending, would
not be expected to produce clear regional patterns of histologic
organization.
Clearly these unexpected/paradoxical results in previous studies, and those
reported herein, suggest that the MC3s from the mixed breeds that we examined
do not represent the `clean' model that we had anticipated. Studies
investigating the etiology of these paradoxes are warranted, especially since
they may help to elucidate how activity-related differences in loading
conditions among the individuals examined - a possibility that is typically
not considered, even in rigorous studies (e.g.
Tommasini et al., 2005) -
might influence the pathogenesis of stress fractures in horses and humans
(Burr, 1987;
Milgrom, 2001;
Nunamaker, 2001). We speculate
that investigation of bones from the same breed of horses that also share
similar histories of physical activities will yield greater statistical power
for testing the hypothesis of S-M-S osteonal or CFO adaptation. The
possibility that the mixed breeds and probable various ambulatory activities
among our horses can explain their histologic paradoxes is supported by the
relatively uniform regional histologic organization of the Thoroughbred MC3s
that has been reported by Martin, Gibson and co-workers
[(Gibson et al., 2006) and
table 1 therein].
When considered in the context of the strain distribution of Gross et al.
(Gross et al., 1992)
(Fig. 1), our results from
S-M-S testing of both the dorsal-lateral and palmar-medial cortices also show
that in a number of ways the bone material is `weaker' in S-M-S testing than
non-S-M-S testing (e.g. dorsal-lateral: lower pre-yield energy and yield and
ultimate stresses in S-M-S tension testing; palmar-medial: lower post-yield
and total energy and ultimate strain and elastic modulus in S-M-S compression
testing). If the different cortices of the equine MC3 were `adapted' to their
habitual strain environments, then it would be reasonable to expect that the
values of the mechanical properties examined would be higher under S-M-S
testing. In view of these results, the hypothesis of S-M-S adaptation is not
strongly supported by our data. However, when considering the alternative
strain distribution of Biewener et al.
(Biewener et al., 1983a;
Biewener et al., 1983b), which
considers the dorsal region as being habitually loaded in net compression, the
mechanical properties are not unexpectedly deficient (e.g. in compression the
values in the dorsal-lateral cortex are relatively high for pre-yield energy,
yield stress and ultimate stress).
An alternative explanation for the emergence of what might have a greater
influence upon bone adaptation than tension or compression, includes the
possibility that these variations are correlated with the variable presence of
shear stresses, which might have greater priority than tension or compression
in evoking adaptation. This idea is supported by data showing that the
mechanical properties of bone material are generally superior in compression
and tension when compared to shear (Boyce
et al., 1998; Burstein et al.,
1976; Carter and Hayes,
1977; Jepsen et al.,
2001; Norman et al.,
1996; Pattin et al.,
1996; Reilly and Currey,
2000; Turner et al.,
2001). Spatial/temporal variations in shear strain magnitudes
across mid-diaphyseal equine MC3s, which are indicative of torsion, have been
reported (Biewener et al.,
1983b): (1) shear stress is greater in the dorsal than in the
palmar MC3 during walking, (2) shear stresses decrease during slow and fast
trotting and (3) shear stresses increase again dorsally during cantering.
Examining a `shear-resistance priority hypothesis' might be one avenue of
research that could help to clarify some of the paradoxes and inconsistencies
found in the present study [see McMahon et al.
(McMahon et al., 1995) where a
`tension-resistance priority hypothesis' is considered). Advanced mechanical
testing methods that more closely mirror physiologic loading conditions and
mimic natural damage accumulation should also prove useful for determining if
histocompositional variations between regions of the same bone represent
mechanical adaptation (Gibson et al.,
2006; Tommasini et al.,
2005).
Influences of Ot.Lc.N/B.Ar in S-M-S and non-S-M-S tests
Results of an analytical study (Yeni
et al., 2001) suggest that Ot.Lc.N/B.Ar can significantly
influence the apparent stiffness of the bone matrix (`matrix' refers to hard
tissue containing lacunae without microstructural pores such as central
canals); however, the differences were small within the physiologic
Ot.Lc.N/B.Ar range. Nevertheless, these data challenge conventional wisdom
that osteocyte lacunae are inconsequential in influencing the mechanical
behavior of cortical bone (Martin,
1984). Osteocyte lacunae may also become stress-concentrators for
microdamage formation (Currey,
1962; Kim et al.,
2004; McCreadie and Hollister,
1997; Reilly,
2000), especially with age or excessive exercise, and osteocytes
may be the mechanosensors of microdamage
(Lanyon, 1993;
Martin, 2003) influencing
their repair. Thus decreasing their concentrations may enhance a bone's
fatigue life, hinder stress and fragility fractures, and/or modify other
aspects of mechanical behavior (Dunstan et
al., 1993; Fyhrie and
Vashishth, 2000; Martin,
1984; Martin,
2002; Reilly,
2000; Vashishth et al.,
2000; Yeni et al.,
2001).
Results of the present study show that Ot.Lc.N/B.Ar can have important
influences on bone mechanical properties in S-M-S testing. For example, in
S-M-S compression tests, Ot.Lc.N/B.Ar was first or second most important in
explaining observed variation in stiffness (elastic modulus), yield and
ultimate stress, and pre-yield (elastic) energy absorption. Our studies of
S-M-S compression testing of the dorsal `compression' cortex of deer calcanei
show that Ot.Lc.N/B.Ar is similarly important: third most important in
explaining variance in all six of the same mechanical parameters that were
evaluated (Skedros et al.,
2003c). Also, in both deer calcanei and equine MC3s the
correlations of Ot.Lc.N/B.Ar with S-M-S compressive stiffness, and yield and
ultimate stress are negative, suggesting that osteocyte lacunae may have a
significant role as stress-concentrators in these ex vivo compression
tests. Additional investigations are necessary to determine the role that the
relative percentage of lacunae with and without viable osteocytes, and the
corresponding density of the cellular network may play in influencing bone
mechanical properties, especially in the context of influencing the
propagation, arrest and targeted repair of microdamage
(Da Costa Gómez et al.,
2005; Vashishth et al.,
2000). Fatigue testing and more rigorous `formal' fracture
toughness testing2 may
also reveal important, more physiologically relevant roles for Ot.Lc.N/B.Ar in
the mechanical behavior of cortical bone that are not evident in the present
study.
High elastic moduli in tension: adaptation or inherent material property?
Regardless of the habitual strain mode, elastic moduli in tension testing
were 35% higher than in compression, which are also consistent with
results of S-M-S and non-S-M-S testing of cranial `tension' and caudal
`compression' cortices of mature equine radii at mid-diaphysis
(Riggs et al., 1993b). Using
bone from various species, such increases in elastic moduli are positively
correlated with bending strength (Currey,
1999a). In turn, it is suggested that this relationship may help
resist failure in the equine MC3 should accidental/atypical loading conditions
occur (e.g. tension in a habitually compressed cortex)
(Batson et al., 2000;
Reilly et al., 1997). The
alterative scenario (compression in a habitually tensed cortex) might be
comparatively less deleterious since bone has higher yield in compression.
This is also supported by data from the radius of a Thoroughbred horse,
showing that there are different thresholds for microdamage formation in
tension vs compression: tension microcracks appeared at lower strains
than compression microcracks (Reilly and
Currey, 1999).
In bone from MC3 diaphyses of eight Thoroughbred horses subjected to 4
months of race training, elastic modulus and bending strength are well
correlated with impact strength or work (the area under the load-deformation
curve to failure, per unit of cross-sectional area of the specimen)
(Reilly et al., 1997). It was
concluded that although elastic modulus is a good indicator of bending
strength, it is not a good indicator of toughness (work). The possibility that
there is a `division of labor' for predominant CFO vs the other
histocompositional characteristics in this context is supported by our
results: predominant CFO is generally more influential in energy absorption
and post-yield behavior, while the other histocompositional characteristics
have a more dominant influence in elastic modulus, pre-yield behavior and
strength. The possibility that CFO and/or other aspects of collagen
content/structure are mechanically adaptive in this context is supported by
results of past investigations (Burstein
et al., 1975; Shelton et al.,
2000; Wang et al.,
2001; Zioupos et al.,
1999). For example, in human bone, Wang et al.
(Wang et al., 2001) showed
that the percentage of denatured collagen compared to the total collagen
content is significantly related to failure energy and fracture toughness
(work), supporting the idea that collagen in bone is a primary arrestor of
microcracks (Burr, 2002;
Sobelman et al., 2004).
Regardless of habitual strain mode, values of post-yield energy were
approximately 2-3 times higher in tension than in compression, while values of
pre-yield energy were approximately 50-100% higher in compression than in
tension. The higher elastic modulus we observed in tension-tested specimens
may therefore also serve to offset a corresponding lower yield and ultimate
stress. This could, in turn, lead to higher total energy absorption values for
tensile specimens by increasing pre-yield energy absorption. This disparity
may reflect an arrangement aimed at keeping habitual tensile and compressive
strains at the same proportion of their yield point
(Currey, 1984). In the equine
radius, it has been suggested that similar differences may reflect a
propensity to maintain uniform `regional' safety factors throughout the bone
(Riggs et al., 1993b), but
this interpretation has been challenged by data from our study of equine MC3s
when considered in the context of the strain distribution of Gross et al.
(Gross et al., 1992;
Skedros et al., 2003a).
Reconsidering this issue in the context of the strain distribution of Biewener
et al. (Biewener et al.,
1983a; Biewener et al.,
1983b) is warranted.
Additional possible reasons for the high modulus values in tension,
compared to compression, can be gleaned from considering the results of
tension and bending tests of cortical bone specimens from various species
reported by Currey in the perspective of bending of the whole bone
(Currey, 1999b). Currey showed
that because the stress at a particular strain is nearly proportional to
Young's elastic modulus, for a similar yield strain, a high Young's modulus
would be associated with a high yield stress and therefore a high bending
moment when the specimen yields. If, furthermore, tissue modifications that
enhance energy dissipation (e.g. by osteonal or interlamellar debonding) allow
more post-yield strain, then the bending moment increases further, increasing
the apparent bending strength. This is a context where S-M-S
histocompositional variations across a bone's cross-section might be
important. In turn, loading in bending results in a much smaller proportion of
the volume of the structure being raised to high stresses than would be the
case for pure tension loading of a machined specimen, and this reduces the
likelihood of a weak part of the specimen being loading to failure
(Currey, 1999b;
Taylor, 2000). Hence, the
high elastic modulus in tension locations shown in
Table 1 might enhance
performance in bending, and this might be a general characteristic of bone
material (i.e. regardless of habitual strain mode). In other words, high
tensile elastic modulus in this perspective might simply be a
consequence/constraint of the material properties of bone and not a product of
developmental adaptation. Similarly, the higher post-yield tension energy
absorption, and higher pre-yield compression energy absorption, regardless of
location in the bone, might also reflect an inherent material property of
bone.
CFO and secondary osteon population densities
Interactions, associations and adaptation
In S-M-S compression testing, predominant CFO was a relatively important
explanatory variable in total energy absorption, but relatively less important
in pre-yield and post-yield energy absorption. In contrast, in S-M-S tension
tests, predominant CFO was relatively important in post-yield and total energy
absorption, but also was less important in pre-yield energy absorption. These
differences, if adaptive, may reflect the complex interactions of modulus,
strength and energy absorption (Currey,
1999a; Zioupos et al.,
1999). It is possible that the S-M-S tensile modulus, which is not
greatly influenced by predominant CFO, may play a much stronger role in
tension pre-yield energy than the compression modulus does in compression
pre-yield energy. Clarifying the interactions between these variables may be
an avenue for future studies.
Les, Stover and co-workers (Les et al.,
2002; Stover et al.,
1995) reported indirect evidence of biomechanically significant
S-M-S material adaptation in the equine MC3; the dorsal cortex is
significantly less ductile and has greater fatigue life than the palmar
cortex. Stover et al. attributed these differences to regional variations in
osteonal pullout (Stover et al.,
1995), but did not examine possible regional CFO variations, which
may be the product of osteonal remodeling. This possibility is suggested by
the observations of highly transverse collagen in the most peripheral aspects
of osteons (i.e. `hoop' osteons) in the dorsal and dorsal-lateral cortex of
equine MC3s (Martin et al.,
1996b; Skedros et al.,
1996; Skedros et al.,
2006), which significantly enhance fatigue resistance by modifying
osteon pull-out strength, and can be beneficial by dissipating energy in
fatigue loading (Gibson et al.,
2006; Hiller et al.,
2003). In the present study, the possibility of the existence of a
biomechanically important CFO/remodeling association is supported by the
positive correlations between On.N/T.Ar and predominant CFO in regions tested
in S-M-S loading (r=0.614 in compression; r=0.607 in
tension) (Table 3A,B).
Region-predominant CFO and On.N/T.Ar have also been shown to be strongly
correlated in `tension' and `compression' cortices of other bones including
ovine, cervine and equine calcanei, and ovine and equine radii; the
`compression' cortex usually has increased On.N/T.Ar and more highly
oblique-to-transverse CFO (Mason et al.,
1995; Riggs et al.,
1993a; Skedros,
2001; Skedros et al.,
2004). Although comparisons of bone histocompositional
organization between species and between different locations within the same
animal or bone can be subject to the confounding influences of growth rates
and histologic/developmental constraints
(Chinsamy-Turan, 2005;
Currey, 2003;
McMahon et al., 1995;
Skedros and Hunt, 2004),
studies of various bones of various species that exhibit osteonal remodeling
generally show that regional histocompositional variations (e.g. CFO,
On.N/T.Ar, On.Ar/T.Ar, On.Ar) can modify local mechanical properties (e.g.
strength, fatigue and impact resistance, energy absorbed to failure, fracture
toughness) (Batson et al.,
2000; Carter and Hayes,
1976; Corondan and Haworth,
1986; Evans and Bang,
1967; Evans and Vincentelli,
1974; Hiller et al.,
2003; Moyle et al.,
1978; Reilly et al.,
1997; Saha and Hayes,
1977; Shelton et al.,
2000; Skedros et al.,
2003b; Yeni et al.,
1997). One challenge posed by these data is to determine if one or
more of these characteristics is strongly sensitive and specific for
interpreting a bone's loading history. A growing body of data supports
predominant CFO as pre-eminent in this regard in the context of a spectrum of
habitual loading complexity, from simple bending (e.g. artiodactyl calcanei)
to multiaxial or complex/torsional loading (e.g. equine MC3s, sheep tibiae and
turkey ulnae) (Skedros, 2001;
Skedros and Hunt, 2004;
Skedros et al., 2004;
Skedros et al., 1996).
Regional histocompositional adaptation, microdamage formation and stress fracture risk
The idea that regional adaptations would be expected in the equine MC3 is
supported by the high incidence of two major disorders involving the dorsal
MC3 cortex in race horses: `bucked shins' and stress fractures
(Norwood, 1978;
Stover et al., 1993). In
these maladies, it has been suggested that osteonal remodeling does not keep
pace with microdamage production in prevalent/predominant `tension'
vs `compression' regions
(Nunamaker, 2001;
Stover et al., 1993). In
horses that sustain habitual dorsal/palmar variations in net
tension/compression, respectively, corresponding variations in predominant CFO
and/or On.N/T.Ar may represent adaptations that differentially enhance energy
absorption, minimizing regional disparities in fatigue behavior. This may be
an important selective advantage of the regional variations in predominant CFO
and/or On.N/T.Ar that have been reported between the `tension' and
`compression' regions of other mammalian bones subject to habitual bending
(Carando et al., 1991;
Kalmey and Lovejoy, 2002;
Lanyon et al., 1979;
Mason et al., 1995;
Skedros, 2001;
Skedros et al., 1999).
However, the majority of stress fractures in the equine MC3 occur in the
dorsal-lateral cortex (Nunamaker,
2001). Such fractures are more common in Thoroughbreds, which
probably reflects their relatively fast racing speeds and lower
cross-sectional moments of area. Relationships between cross-sectional
geometry, cortical robusticity (e.g. ratio of cortical area to total
cross-sectional area), and tissue mechanical properties produced by variations
in histocomposition, may be important considerations in this context
(Tommasini et al., 2005) but
were not considered in the present study. Nevertheless, in all racing breeds
it is not entirely clear why microcracks tend to form more frequently in the
dorsal-lateral cortex. Nunamaker has suggested that the shift from prevalent
tension in the dorsal cortex during race training at lower speeds to
compression at higher racing speeds may provide an explanation
(Nunamaker, 2001). He suggests
that tension-related adaptations produced by modeling and remodeling
activities (specific remodeling-mediated adaptations were not stated) would
not be expected to accommodate compression strains produced at greater speeds:
`It seems obvious that bone that models and remodels for tensile forces on the
dorsal aspect of M3III [MC3] will be poorly adapted for the large compressive
strains that are seen during racing' [p. 213
(Nunamaker, 2001)]. In turn,
when the tension-adapted dorsal cortex receives more prevalent, high magnitude
compression strains microcrack formation is enhanced. This probability is
supported by Reilly and Currey, who showed that microdamage formed in
compression is highly detrimental to tensile mechanical properties
(Reilly and Currey, 2000). In
tension vs compression, microdamage not only occurs at different
thresholds (more readily forms in tension), but can exhibit different
morphologic characteristics (e.g. length, shape and orientation)
(Boyce et al., 1998;
George and Vashishth, 2005;
Joo et al., 2004;
Muir et al., 1999;
Reilly and Currey, 1999;
Reilly et al., 1997). In MC3s
from horses run at higher speeds, the probability that microdamage formation
might also occur at different strain thresholds in different regions might be
especially important for understanding the material organization of the
dorsal-lateral region since it experiences a greater range of strain by being
loaded in tension and compression when compared to the palmar-medial and
dorsal-medial cortices. Also, the prevalence of shear strains, which can be
more deleterious to mechanical properties than tensile strains, probably
increase in the vicinity of the dorsal-lateral cortex during racing, since the
neutral axis (where shear strains tend to be greatest,
Fig. 1B) traverses this region
at these speeds (Nunamaker,
2001). In view of these possibilities, an MC3 sufficiently exposed
to sub-racing speeds would be expected to become adapted primarily for tension
in the dorsal/lateral cortices. However, if higher speeds are more
consistently sustained, the MC3 may become primarily adapted for compression
and shear in this region. As we have suggested above, the fact that the
mechanical test results reported in the present study are not strongly
consistent with either of these interpretations may reflect the possibility
that not all of our bones experienced dorsal-palmar bending of sufficient
duration/intensity to evoke what we had considered would be `expected'
tension-compression S-M-S adaptations.
Conclusions
Despite a number of limitations and difficulties arising from this complex
study, several issues are clear. (1) Predominant CFO appears to be most
strongly correlated with post-yield energy absorption, especially in tension.
(2) These data generally support the hypothesis that differentially affecting
S-M-S energy absorption may be an important consequence of regional
histocompositional heterogeneity in the equine MC3. (3) Data inconsistent with
this hypothesis (e.g. lack of highly longitudinal collagen in the
dorsal-lateral `tension' region, paradoxical histologic organization in some
locations, and lack of significantly improved S-M-S properties in some
locations) might reflect the absence of a similar habitual strain distribution
in all bones. In contrast to a history of habitual
dorsal/lateral-to-palmar/medial bending, an alternative strain distribution
showing net compression along the dorsal-palmar axis might be more
characteristic of the habitual loading of some of the bones that were used in
the present study. In turn, some of the inconsistencies that were found might
also reflect the complex loading regime that the MC3 sustains when the animal
undergoes a variety of gaits and activities, which may be representative of
only a portion of our animals. Nevertheless, the paradoxical/inconsistent
histologic findings reported in this study are useful for drawing attention to
problems that can be encountered even when using models that are based on
rigorous measurements of seemingly simple strain environments. In turn,
ensuring detailed knowledge of the loading histories of the animals and bones
studied would enhance future studies that attempt to decipher the causal
mechanisms that mediate developmental structure-function relationships.
|
Acknowledgments |
|---|
|
Footnotes |
|---|
; Currey,
2002; Lanyon et al.,
1979; Martin et al.,
1998; Schaffler et al.,
1985; Woo et al.,
1981), or (2) the presence of regional differences in structural
and/or material organization that are strongly influenced by normal functional
stimuli occurring during normal development within or between bones (e.g.
Bertram and Swartz, 1991;
Currey, 2002;
Martin et al., 1998;
Riggs et al., 1993a;
Riggs et al., 1993b;
Skedros et al., 2004;
Skedros et al., 1996). In the
present investigation, `adaptations' are considered to be biomechanically
relevant regional variations in cortical bone material organization that are
produced by the modeling and remodeling processes during normal skeletal
development. In addition to being mediated by genetic and epigenetic
influences, which are heritable, these processes can be influenced by
nonheritable (`extra-genetic') stimuli, such as regional variations in
microdamage incidence. 
2 In this study we distinguish between `informal' and `formal' methods for
assessing energy absorption (also referred to as `toughness'; see definition
below). `Informal' methods, such as employed in the present study, measure
energy absorption as the area under the stress/strain curve obtained in
typical material tests. `Formal' tests of `work-of-fracture' or `toughness'
include measures of energy required to propagate a crack through specimens
that are specifically machined to control crack formation and the direction of
crack propagation (e.g. Brown et al.,
2000; Currey,
2002; Norman et al.,
1996; Turner et al.,
2001). Toughness refers to the amount of energy required to
fracture a specimen. The more the overall amount of energy consumed, the
`tougher' the material (Zioupos and
Currey, 1998). Because toughness, more rigorously defined,
reflects the ability to resist crack growth and withstand brittle fracture
from an applied single load, it is a function of applied stress, size of
material flaws, and specimen composition and geometric thickness. This
contrasts with energy absorption, a measure of work of fracture. An example in
terms of mineral content would be a highly mineralized material that absorbs a
large amount of energy to failure and typically brittle failure (very little
energy absorbed post-yield) vs a less mineralized, less stiff
material which, although it may or may not absorb a high amount of energy to
failure, undergoes a greater degree of post-yield strain, thereby exhibiting
fracture toughness.
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References |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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