A stress fracture (SF) is a common sports injury defined as a partial or complete bone fracture resulting from repeated application of stress lower than that required to fracture the bone in a single loading (13). Consequences of SF for athletes include pain, lost training time, and medical expenses. Female athletes are at significantly greater risk for SF than male athletes (2), with the (posterior) distal tibia reported as the most common SF site (9,17,32).
There are numerous risk factors for SF in athletes including a lower dietary calcium and dairy product intake (20), smaller tibial cross-sectional area (12), and lower areal bone mineral density (aBMD) (5,23,29) compared with healthy non-stress fracture (NSF) subjects. However, the role of bone quality in SF etiology is not yet known. Bone microarchitecture and bone strength are important components of "bone quality" (16,36), and although the contribution of these aspects to fracture resistance is well accepted (36), in vivo assessment in humans has only recently become possible with the development of imaging modalities such as high-resolution magnetic resonance imaging (22) and high-resolution peripheral quantitative computed tomography (HR-pQCT) scanners (6). HR-pQCT provides measures of volumetric BMD and morphological outcomes such as trabecular number and cortical thickness. In addition to this standard analysis, three-dimensional HR-pQCT scans can be divided into subregions analyzed to investigate regional differences within the scanning site (38). A regional analysis may be important because SF typically occur in the posterior region of the distal tibia (9,17,32). Augmenting HR-pQCT density and morphological outcomes, the application of finite element analysis (FEA) to subject-specific HR-pQCT images provides the opportunity to estimate an individual's bone strength (25) and determine the load distribution between cortical and trabecular bone compartments (compartmental loading has been associated with wrist fracture) (7,26). Bone strength is influenced not only by bone mineral density and bone size but also by the organization of the trabecular microarchitecture-all three of these aspects can be characterized by HR-pQCT. To date, no study has used HR-pQCT and subject-specific FEA to investigate bone quality in individuals with SF.
An important consideration in SF studies is the influence of muscle forces because these may be related to lower leg bone quality (14,15,34). A protective role of muscles on the tibia during running is thought to be related to the shear component of muscle forces (18,35). These forces may counteract the joint reaction forces resulting in reduced net shear stresses in the tibia. Therefore, decreased lower leg muscle strength may increase the risk for SF resulting from running (18,35). Supporting this theory, less lean mass and a smaller calf girth, possibly indicating lower muscle strength, were found in female track-and-field athletes with SF (5). However, the role of muscle forces in the etiology of SF is complex, and to date, no study of female athletes in running-related sports has investigated the role of muscle forces in SF using direct measures of muscle function (4).
Considering the aforementioned knowledge gaps, further investigation into the etiology of SF is required to develop successful prevention and treatment strategies. Thus, the purpose of this study was to determine whether female athletes with lower limb SF have compromised bone quality of the distal tibia and reduced muscle strength compared with female athletes without a history of SF. We hypothesized that, because tibial SF occur most often in cortical bone, differences in bone quality between SF and NSF subjects would be most evident in the cortical bone compartment. Furthermore, as the posterior region of the tibia is most often affected (32), we hypothesized that differences in bone parameters influencing bone strength (i.e., trabecular thickness, cortical thickness) would be most prominent in the posterior distal tibia. Finally, because lower muscle strength is thought to induce higher shear stresses on the tibia during running (35), we hypothesized that athletes who suffer from SF will have significantly lower muscle strength than NSF subjects.
Female premenopausal athletes between the ages of 18 and 45 yr and with reported confirmation (e.g., by x-ray, bone scan, or magnetic resonance imaging) of a lower limb SF were recruited for this study (n = 19) and assessed within 1-47 wk (12.7 ± 13.7) of diagnosis. For each SF subject, a healthy NSF subject, who was matched according to age (±3 yr), sport, and average weekly training volume (±40%), was recruited. The training volume matching criteria was not strict for practical reasons (i.e., recruitment with a strict criteria was challenging) and because it was self-reported and subject to bias. (However, post hoc analysis was performed on the two groups to determine whether there were statistically significant differences in training volume.) A further criterion for NSF subjects was that they had never experienced an SF and were premenopausal. Women were excluded from the study if they were pregnant or long-term users of medications likely to influence bone metabolism (excluding oral contraceptives (OC)). The University of Calgary Conjoint Health Research Ethics Board approved this research study. Informed consent was obtained from all participants.
Height, weight, and tibia length of each subject were measured using standard methods. Standing height was measured to the nearest millimeter with a wall-mounted stadiometer (Seca model 222; Seca Hamburg, Germany). Weight was measured to the nearest 0.1 kg using an electronic scale (Seca model 876; Seca). Height and weight were used to calculate body mass index (BMI, kg·m−2). Tibia length was determined using an anthropometric tape to the nearest millimeter taking the distance between the distal end of the medial malleolus and the tibial plateau (edge at the joint line). All measures were taken in duplicate, and the mean was used for analysis.
All subjects were asked to complete two questionnaires: a Food Frequency Questionnaire and a Health and Training History Questionnaire. The Food Frequency Questionnaire (1) was used to determine average daily calcium intake (mg·d−1). The Health and Training History Questionnaire contained questions related to bone health including fracture history, OC use, age at menarche, regularity of menses since menarche, as well as questions assessing training volume for all sports and mileage for running. Subjects with SF answered questions about their SF such as date of first pain, date of bone scan/magnetic resonance imaging/x-ray used for diagnosis and information about the location of current and past SF.
Dual-energy x-ray absorptiometry.
aBMD (g·cm−2) and associated t scores of the lumbar spine (LS) and hip (including the femoral neck (FN) subregion) were obtained from dual-energy x-ray absorptiometry (DXA, Discovery A; Hologic, Inc., Bedford, MA) scans. In addition, total body lean mass (kg) and percent body fat were determined from a whole body scan. All scans were acquired and analyzed by one trained technician according to standard procedures.
The tibia of the dominant leg (i.e., preferred leg to kick a soccer ball) of all participants was scanned using HR-pQCT (XtremeCT; Scanco Medical, Brüttisellen, Switzerland). Two sites were scanned including the standard clinical site at the ultradistal tibia (26) and a more proximal scanning site at the distal tibia. The standard scanning site (ultradistal scanning site) was located 22.5 mm proximal from the plateau of the distal articulating surface of the tibia. The second, more proximal scanning site (distal scanning site) was located 37.5 mm proximal from this reference line. The ultradistal scanning site was acquired because it is the standard scanning site recommended by the manufacturer. The distal scanning site was included because athletes of running-related sports commonly sustain a SF at the distal two-thirds site (11). However, because of the limited bore length of the HR-pQCT, it was not possible to measure at the distal two-thirds site (∼110 mm from the reference line for an average tibial length of 36.6 cm); therefore, this scan represented a more distal location than the two-thirds site (Fig. 1). The ultradistal scanning site primarily was located in the epiphysis, and the distal scanning site was in the metaphysis (8). The scanning sites did not represent fracture locations of study participants; therefore, the fracture itself was not assessed.
The default human in vivo scanning protocol (60 kV (peak), 1000 μA, 100-ms integration time, 750 projections) was used to acquire all HR-pQCT scans (26). Each scan takes 3 min and results in an effective patient radiation dose of <3 μSv as measured in our laboratory. This protocol results in 110 slices of cross-sectional images (9.02 mm stack) with an isotropic voxel size of 82 μm. One trained technician, who also performed daily quality assurance procedures, acquired the scans. If significant motion artifacts were observed, the technician performed one rescan of the site.
A Laplace-Hamming filter (image noise reduction) and threshold, followed by automated segmentation of cortical and trabecular compartments (10), was applied to the HR-pQCT images. Density, microarchitectural, and morphological outcomes were determined using Scanco software (Image Processing Language, version V5.08b, Scanco Medical AG, Brüttisellen, Switzerland). Density measurements included total volumetric density (BMD, mg HA·cm−3), trabecular density (Tb.BMD, mg HA·cm−3), and cortical density (Ct.BMD, mg HA·cm−3). Microarchitectural measurements included trabecular number (Tb.N, 1 mm−1), trabecular thickness (Tb.Th, mm), trabecular separation (Tb.Sp, mm), and cortical thickness (Ct.Th, mm). In addition, cortical porosity (Ct.Po, %) was assessed using a customized segmentation algorithm (10,30). Additional morphological outcomes included total bone area (Tt.Ar, mm2) and cortical area (Ct.Ar, mm2). The in vivo short-term reproducibility of these standard HR-pQCT density and microarchitecture outcomes in our lab was <1% and <4.5%, respectively (27).
To investigate group differences at subregions within the distal tibia scanning sites, an automated regional analysis method was developed, which divided the scans into four quadrants to be analyzed separately (Fig. 2). The quadrants represented four anatomical regions including anterior, posterior, lateral, and medial sites of the tibia. The mask used to identify the quadrants was centered in the center of mass of the tibia (CMT) and aligned with the center of mass of the fibula (CMF) by rotating it to the line from the CMT to the CMF (Fig. 2). CMT and CMF were determined by calculating the moment of inertia of both bones in all scans (Image Processing Language, version V5.08b). These two landmarks for alignment were chosen owing to the lack of a clear fiducial landmark in the tibial morphology and to ensure consistency with the regional analysis study published by Sode et al. (38). Analysis of each quadrant was performed separately using the same methods described previously for the entire bone.
The HR-pQCT images were meshed automatically (FAIM, v4.0), where each image voxel was converted to hexahedron element in the model. Cortical and trabecular elements were assigned the same material properties (Etissue = 6829 MPa, ν = 0.3) to create a homogeneous, isotropic model. The elastic modulus used was determined by MacNeil and Boyd (25) in mechanical tests as part of a validation study. The boundary conditions represented a uniaxial compression test with the bottom nodes fixed and a displacement of 1% applied to the top nodes. The customized large-scale FE software used for analysis was developed in our laboratory (Bone Imaging Laboratory; FAIM v4.0, University of Calgary, Calgary, Canada). An automated segmentation algorithm described elsewhere (10) defined the cortical and trabecular compartments. The percentage of load carried by each compartment was determined using the FE software. The percent load carried by the cortical compartment (remaining load carried by trabecular compartment) was reported at the proximal slice of each scan. All models were run on a desktop workstation (MacPro, OS × v10.6; 2 × 2.8 GHz Quad-Core Intel Xeon, Apple, Cupertino, CA).
Muscle strength of the calf and ankle muscles involved in plantarflexion, eversion, and inversion of the foot and knee extension was estimated isometrically using a Biodex Isokinetic Dynamometer (Biodex, System 3, New York, NY). Each subject was seated on the Biodex chair, and the limb without SF was strapped to the Biodex measuring device to perform voluntary contractions. The maximum torque (N·m) recorded by the dynamometer was used as a measure of muscle strength. For plantarflexion, the footplate held the foot in a 90° angle to the shin (tibia horizontal) with a knee flexion of 20°-30°. A limb support against the upper leg minimized artificial peak torques produced by the subject pushing with their hips rather than solely using their lower leg muscles. Inversion and eversion tests were performed such that the subject's knee flexion was between 30° and 45° with a horizontal tibia fixed by a lower limb support. The knee angle was set to 60° for the knee extension test. All tests were conducted with a seatback tilt of 70°. Each test consisted of three trials with a maximum voluntary contraction of 5 s each, and a 60-s rest period between each trial. Verbal encouragement was used for all trials. The average of the 200 largest values was determined for each trial, and the maximum average value across the three trials was used for analysis. Regular calibration confirmation tests were performed to ensure comparability of test results taken on different days.
NSF subjects were matched to SF subjects according to age, sport, and training volume to ensure minimal variance in the groups. A pooled-group statistical approach was applied, and all bone outcomes were adjusted for body weight. All outcomes were tested for normal distribution using Shapiro-Wilk tests. If outcomes were not normally distributed, nonparametric tests were used (Mann-Whitney U tests) and adjustment for body weight was performed (i.e., Tt.Ar/body weight). t-Tests were used for parametric analyses. Analysis of HR-pQCT bone data included comparisons between groups for each skeletal site, as well as for the four quadrants. Results were considered statistically significant at P < 0.05. Trends were formally defined as a percent difference between the two group medians of more than 5% and P < 0.1. All statistical tests were run using SPSS (PASW Statistics 17.0; SPSS, Inc., Chicago, IL).
The study participants consisted of athletes in the following sports: running (n = 28), cross-country running (n = 2), triathlon (n = 4), soccer (n = 2), and ringette (n = 2). Athletes were either on varsity teams (n = 6) or trained recreationally (n = 23) at the club level (n = 6) or at the national level (n = 3). All but three athletes reported participation in competitions (e.g., 5 km, 10 km, half marathon, marathon, half ironman). The weekly mileage did not differ between SF and NSF groups (P = 0.657) and ranged from 10 to 125 km·wk−1 in the SF group (53.7 ± 32.7 km·wk−1) and 15 to 102 km·wk−1 (50.4 ± 24.1 km·wk−1) in the NSF group. Training volume also did not differ (P = 0.158), and ranged from 1 to 11 h·wk−1 (6.0 ± 2.8 h·wk−1) in the SF group and 1.3 to 21 h·wk−1 (average of 6.2 ± 4.2 h·wk−1) in the NSF group.
A physician medically confirmed all SF, and subjects were assessed between 1 and 47 wk (mean = 12.7 ± 13.7) of diagnosis. SF locations included the tibia (n = 12, 4 of which were bilateral), metatarsals (n = 5, 1 of which was bilateral), navicular bone (n = 1), and pubic ramus (n = 1). Previous SF were reported by 10 of the 19 subjects with SF (52.6%), often in different lower leg bones or in the contralateral limb to the limb with the present SF.
Descriptive measures (age, height, weight, BMI, tibia length) and pertinent questionnaire outcomes (total dietary calcium intake, menarche age, training start age) did not differ significantly between groups (Table 1). Although more individuals from the SF group (47%) than from the NSF group (37%) were on OCs, years of OC usage did not differ between groups (Table 1). Vitamin D supplements were taken by 53% of participants in the SF group and 47% of participants in the NSF group.
The DXA assessment of aBMD revealed a lower FN and total hip aBMD in the SF group compared with the NSF group (Table 2). At the LS, the SF group tended to have lower aBMD compared with NSF subjects, but this result was not statistically significant. Based on the T scores from LS results, six SF and four NSF subjects were classified as osteopenic (T score between −1.0 and −2.5). The remaining LS results, as well as all hip and FN results, were in the normal range (T score > −1.0). The DXA-assessed percentages of body fat and body lean mass were not statistically different between groups (P = 0.31 and P = 0.34, respectively).
HR-pQCT: ultradistal site.
Bone outcomes from HR-pQCT were not normally distributed; therefore, adjustments were performed by dividing by body weight. At the ultradistal scanning site, no scans were excluded because of motion artifacts. The volumetric density measures (BMD, Tb.BMD, and Ct.BMD) at this site differed less than 1% between groups. No statistically significant differences were observed in the regional analysis.
The trabecular outcomes of the standard and regional analyses were not significantly different between groups. However, there was a trend in the SF group to have thinner trabeculae compared with the NSF group in the lateral (Tb.Th 17.9% lower, P = 0.07) region.
The cortices of the groups did not differ significantly at the ultradistal scanning site as a whole; however, a smaller cortical area was observed in the posterior region (Ct.Ar 7.0% lower, P = 0.04).
HR-pQCT: distal site.
No scans were excluded because of motion artifacts. Density outcomes of the whole bone at the distal site were not significantly different between groups (Table 3), but the regional analysis revealed significantly lower trabecular BMD in the posterior region (Tb.BMD 19.8% lower, P = 0.02) (Table 3).
Trabecular microarchitectural outcomes (Table 3) did not differ significantly between groups when considering the whole bone. However, the regional analysis suggested trends toward lower trabecular thickness (Tb.Th 5.5% lower, P = 0.09) and trabecular number (Tb.N 17.9% lower, P = 0.08) in the posterior region of the SF group.
In the cortical compartment, analysis of the entire cortex revealed a trend toward lower cortical area (Ct.Ar 2.3% lower, P = 0.06) in the SF group, and regional analysis identified specifically that the posterior and lateral regions were significantly lower (Ct.Ar 1.2% to 5.2% lower, P < 0.03) (Table 3). Although cortical thickness was not different between groups (Ct.Th, P = 0.44), the significantly smaller tibial cross-sectional area (Tt.Ar 7.8% lower, P = 0.02) is consistent with the finding of reduced cortical area. Taken together, these results suggest the SF group has smaller tibia cross sections, with less cortical bone.
HR-pQCT: load distribution.
The FE-determined load sharing between the cortical and trabecular bone varied with the scanning site. At the ultradistal scanning site, load sharing was not significantly different between groups with the cortex carrying 69.1% in the SF group compared with 66.3% in the NSF group. At the distal scanning site, however, the load carried by the cortex was 4.1% greater in the SF group (P = 0.02) (Table 3). The estimated failure load trended lower in the SF group (8.6% lower, P = 0.09) suggesting the tibia were weaker in that group.
The muscle function results (plantarflexion, eversion, inversion, knee extension) are summarized in Table 4. Knee extension torque was significantly lower in the SF group compared with the NSF group (18.3% lower, P = 0.03).
This cross-sectional study presents a novel investigation of bone quality and muscle force in female athletes with SF using newly developed techniques such as three-dimensional HR-pQCT and associated FEA, as well as a customized regional analysis method to examine spatial variation by quadrants. The difference in bone quality measures was greatest at the distal scanning site, which is located closer to the distal one-third tibia site, a common site of tibial SF. In addition, the regional analysis isolated the posterior quadrant as having the largest significant differences between the SF and NSF groups. Notably, volumetric BMD measurements were not significantly different between groups, with the exception of trabecular bone in the posterior region. It was the overall bone size, and the relatively poor microarchitecture specifically in the posterior region that distinguished the SF from NSF controls. This was reflected by the lower bone strength and increased load carried by the cortex in the SF group, as estimated from FEA. In parallel to differences in bone quality, functional muscle testing indicated significantly lower knee extension muscle torque. Although a causal relationship cannot be determined with these cross-sectional data, our findings suggest that both bone quality and muscle strength are factors in SF. These results emphasize the need for a prospective study to further elucidate the importance of these muscle and bone characteristics in the etiology of SF.
Our initial hypothesis that bone quality of the cortex, as the most common site of tibial SF, would be compromised in athletes with SF was supported only in part. When analyzing the bone as a whole, cortical outcomes such as cortical thickness and cortical porosity were not different between groups. However, the regional analysis revealed trends of a thinner cortex and reduced cortical porosity and a significantly smaller cortical area in the posterior region in the SF group. The posterior region was also the site of lower trabecular BMD. Interestingly, when a post hoc analysis was performed on a subset of subjects specifically with tibial SF (n = 12), some of the trends previously identified were substantiated as reflected by significantly lower cortical area (−2.3%, P = 0.04) and cortical porosity (−14.7%, P = 0.03) in SF subjects (data not shown). On the whole, these data suggest that there are significant differences in both the trabecular and cortical bone between the SF and NSF groups and that the differences are mostly localized in the posterior region (as identified by the quadrant localization technique).
The proportion of load carried by the cortex was greatest at the most proximal slice of the distal scanning site and decreased in both SF and NSF groups at sites located more distally. This is consistent with the general pattern of distribution of trabecular bone within the tibia, as it was previously shown that the quantity of trabecular bone generally decreases from the ultradistal tibia (metaphyseal region) toward the midshaft (8). The gradient can be disrupted in certain disease states (e.g., in the estrogen deficient rat ), and although we are not suggesting that estrogen deficiency is responsible for the reduced trabecular bone we found in SF subjects, it is possible that a similar systemic difference in amount and distribution of trabecular bone occurs in individuals with SF compared with NSF subjects. The axial distribution of trabecular and cortical bone in the tibia may be an interesting factor to consider in future studies of SF. Our finding of altered trabecular bone is consistent with the findings of Prouteau et al. (33), who used fractal analysis to show a reduced quality of microarchitecture (surrogate measures for connectivity and porosity) in the calcaneus of women with SF.
The changes in the posterior region of the cortex are consistent with the most common site for SF (32). The significantly reduced cortical and trabecular bone quality in this region are notable, particularly because these changes have been evaluated by HR-pQCT at a site that certainly does not coincide with the axial location on the tibia of most SF. Using a two-dimensional DXA measurement, Beck et al. (2) estimated a generally smaller cortical thickness at the distal third of the tibia in female military recruits with SF compared with healthy recruits, and despite the differences in technology, this finding is consistent with our results. Together, these data support the concept that the posterior region in SF subjects may not be as well adapted to the peak stresses in the tibia during runningrelated activities.
Taking the trabecular and cortical bone microarchitecture and density, as well as bone size into account, the finite element method we used suggested a lower bone strength in the SF group, albeit not significant (P = 0.09). This result is consistent with the recent findings of Popp et al. (32), who found a smaller cortical area and, consequently, a lower estimated bone strength in the tibial midshaft of female runners with SF compared with healthy athletes. Using pQCT, Popp et al. were able to assess distal sites more closely associated with where most SF occur (9,17,32). The difference between scan site and the surrogate method for estimating bone strength used by Popp et al. may explain why our bone strength results were indicated by a strong trend, rather than a significant difference. Popp et al. (32) used the bone strength index and polar strength strain index as surrogates of bone strength, and both of these methods are based purely on geometric distribution of mineralized tissue in the single-slice pQCT scan (37,41). In contrast, the image-based FE method we applied incorporates three-dimensional trabecular and cortical microarchitecture in the 9-mm axial volume from HR-pQCT, and considering the spatial variability of the bone quality by quadrant, it is possible that differences in strength between SF and NSF groups were masked. Both our study and the study by Popp et al. consistently indicate that reduced bone strength is associated with SF in female athletes.
The BMD at the tibia was not significantly different between SF and NSF groups, and this is in contrast to the DXA results indicating lower aBMD at the spine and hip in the SF group. These apparently contradicting results are consistent with previous findings that showed both no differences in tibial BMD (3,12,21) between SF and NSF subjects, and yet low aBMD at one or more sites (e.g., hip, spine) has been identified as a risk factor for SF (5,23,29). A possible explanation is that the hip and spine are known to be composed of a significant trabecular bone component (28), and therefore, changes to the trabecular bone may dominate the aBMD measurements. At the distal tibia, there is a significant cortical component that may mask underlying differences in trabecular bone when averaged together, and this is further confounded when using densitometric methods that do not distinguish trabecular and cortical compartments. Using a quadrant-based analysis of three-dimensional image data, our results suggest a reduced trabecular bone quality in the posterior region. Regional differences are likely masked when averaged across the whole bone, and this likely explains why the whole-bone BMD was not significantly different between the SF and NSF groups. The posterior trabecular BMD deficit in SF subjects is consistent with the finding that athletes with SF tend to have systemically lower aBMD compared with their healthy peers (5,23,29). But, importantly, the lack of BMD difference between SF and NSF for the whole bone does not suggest a "normal" bone. We found important regional differences between SF and NSF that underpin the BMD measurements and may suggest the bone is not well adapted to regional loading differences.
We expected that lower leg muscle strength would be significantly lower in SF subjects compared with NSF subjects because muscle forces may have a role in reducing detrimental shear stresses in the tibia (35). However, our results only showed knee extension torque was significantly lower in the SF group. The role of muscle weakness in SF is unclear from previous studies. Some studies found no difference in quadriceps strength between military recruits with and without SF (40), whereas others showed a lower quadriceps strength (using a leg press test) in military recruits with SF compared with controls (19). Our findings are better aligned with the latter of these two studies; however, the use of military recruits rather than athletes may be a confounding factor due to the difference in a variety of factors such as training intensity, training approach, initial fitness, and footwear (12).
Lower knee extension strength was noted in SF subjects, and although some deconditioning since the injury may have occurred (albeit likely small), the role of muscle strength in SF is intriguing. A possible explanation for why reduced knee extension strength is associated with SF is that reduced quadriceps muscle strength in runners could necessitate a more extended knee joint position at heel strike, and therefore a "stiffer" running style. Increased knee stiffness would lead to higher compressive forces on the tibia and a reduced shear component that is, however, believed to decrease the risk for SF (18,35). This speculated mechanism relating muscle strength to SF warrants further investigation either by direct investigation into the role of quadriceps strength in bone loading, indirect interventional studies (i.e., muscle strengthening protocols), or via prospective studies to better elucidate the role of atypical running mechanics on the development of SF.
A fundamental limitation of our study is that it was a cross-sectional design, and thus our findings are limited to identifying differences between SF and NSF subjects. Prospective studies are needed to determine whether compromised bone quality and/or reduced muscle strength are predictive of lower limb SF, although these are challenging and expensive studies to perform and so far tend to be limited to military research. A second limitation is that although we focused the discussion on the muscle-bone relationship during running, not all of our SF subjects were pure runners, although they did participate in running-related sports (running, n = 14; cross-country running, n = 1; triathlon, n = 2; soccer, n = 1; and ringette, n = 1). It should be reiterated, however, that SF and NSF subjects were matched according to sport. A third limitation is that subjects were only scanned at distal tibia and not specifically at the subject-specific site of the medically confirmed SF (and likely far enough away from the actual SF site to avoid measuring effects of healing). At 63.2% (n = 12), most of the SF subjects in this study sustained tibial SF. Other SF locations included the metatarsals (n = 5, 26.3%), the navicular bone (n = 1, 5.3%), and the pubic ramus (n = 1, 5.3%). It is not known how closely bone quality at the distal tibia reflects bone quality at a remote SF site. Several subjects (n = 8, 42.1%) reported past SF in different bones (n = 5) or the contralateral side (n = 3), which supports the assumption that, if compromised bone quality is a risk factor for SF, it may be systemic. Indeed, others have shown good agreement between distal sites measured by HR-pQCT and other skeletal sites (24), further supporting this assumption. Lastly, another consideration is that functional muscle measurements, although made on the contralateral limb to the site of SF, may be influenced by muscle inhibition (39).
Clinical relevance and conclusions.
In summary, this study found a reduced bone quality as reflected by both trabecular and cortical parameters in the posterior tibial region of individuals with SF compared with NSF subjects. These findings are consistent with spatial position of the most common site of tibial SF, although our HR-pQCT measurements were from a more distal axial position on the tibia. Also, the regional alteration in bone quality was found despite no significant difference in whole-bone BMD. The lower bone quality in SF subjects was reflected by a shift in loading to the cortex, as determined by our FE analysis. Concurrent with the group differences in bone quality, knee extension strength (i.e., quadriceps) was lower in the SF group. Although no causal relationship can be determined, these findings suggest that both bone quality and muscular strength deficits should be addressed in research aimed at identifying risk factors for SF and possibly determining when an athlete can safely return to training. Studies directed toward optimal prevention and rehabilitation protocols to optimize and improve bone microarchitecture and muscle strength are needed.
The authors thank all the study participants for their time. The authors also thank Ms. Eva Szabo for HR-pQCT scanning and Ms. Karin Rasmussen for DXA scanning. The Canadian Institutes of Health Research and Alberta Innovates - Health Solutions provided funding for this study.
The authors report no conflict of interest.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Barr SI. Associations of social and demographic variables with calcium intakes of high school students. J Am Diet Assoc
. 1994;94(3):260-6, 269; quiz 267-8.
2. Beck TJ, Ruff CB, Shaffer RA, Betsinger K, Trone DW, Brodine SK. Stress fracture in military recruits: gender differences in muscle and bone susceptibility factors. Bone
3. Bennell K, Crossley K, Jayarajan J, et al. Ground reaction forces and bone parameters in females with tibial stress fracture. Med Sci Sports Exerc
4. Bennell K, Matheson G, Meeuwisse W, Brukner P. Risk factors for stress fractures. Sports Med
5. Bennell KL, Malcolm SA, Thomas SA, et al. Risk factors for stress fractures in track and field athletes: a twelve-month prospective study. Am J Sports Med
6. Boutroy S, Bouxsein ML, Munoz F, Delmas PD. In vivo
assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab
7. Boutroy S, Van Rietbergen B, Sornay-Rendu E, Munoz F, Bouxsein ML, Delmas PD. Finite element analysis based on in vivo
HR-pQCT images of the distal radius is associated with wrist fracture in postmenopausal women. J Bone Miner Res
8. Boyd SK. Site-specific variation of bone micro-architecture in the distal radius and tibia. J Clin Densitom
9. Brukner P, Bradshaw C, Khan KM, White S, Crossley K. Stress fractures: a review of 180 cases. Clin J Sport Med
10. Buie HR, Campbell GM, Klinck RJ, MacNeil JA, Boyd SK. Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo
micro-CT bone analysis. Bone
11. Coady CM, Micheli LJ. Stress fractures in the pediatric athlete. Clin Sports Med
12. Crossley K, Bennell KL, Wrigley T, Oakes BW. Ground reaction forces, bone characteristics, and tibial stress fracture in male runners. Med Sci Sports Exerc
13. Fredericson M, Jennings F, Beaulieu C, Matheson GO. Stress fractures in athletes. Top Magn Reson Imaging
14. Frost HM. Bone "mass" and the "mechanostat": a proposal. Anat Rec
15. Frost HM. Skeletal structural adaptations to mechanical usage (SATMU): 2. Redefining Wolff's law: the remodeling problem. Anat Rec
16. Fyhrie DP. Summary-measuring "bone quality." J Musculoskelet Neuronal Interact
17. Giladi M, Milgrom C, Simkin A, et al. Stress fractures and tibial bone width. A risk factor. J Bone Joint Surg Br
18. Haris Phuah A, Schache AG, Crossley KM, Wrigley TV, Creaby MW. Sagittal plane bending moments acting on the lower leg during running. Gait Posture
19. Hoffman JR, Chapnik L, Shamis A, Givon U, Davidson B. The effect of leg strength on the incidence of lower extremity overuse injuries during military training. Mil Med
20. Kelsey JL, Bachrach LK, Procter-Gray E, et al. Risk factors for stress fracture among young female cross-country runners. Med Sci Sports Exerc
21. Korpelainen R, Orava S, Karpakka J, Siira P, Hulkko A. Risk factors for recurrent stress fractures in athletes. Am J Sports Med
22. Krug R, Carballido-Gamio J, Burghardt AJ, et al. Assessment of trabecular bone structure comparing magnetic resonance imaging at 3 tesla with high-resolution peripheral quantitative computed tomography ex vivo
and in vivo
. Osteoporos Int
23. Lauder TD, Dixit S, Pezzin LE, Williams MV, Campbell CS, Davis GD. The relation between stress fractures and bone mineral density: evidence from active-duty Army women. Arch Phys Med Rehabil
24. Liu XS, Cohen A, Shane E, et al. Bone density, geometry, microstructure, and stiffness: relationships between peripheral and central skeletal sites assessed by DXA, HR-pQCT, and cQCT in premenopausal women. J Bone Miner Res
25. MacNeil J, Boyd S. Bone strength at the distal radius can be estimated from high-resolution peripheral quantitative computed tomography and the finite element method. Bone
26. MacNeil JA, Boyd SK. Load distribution and the predictive power of morphological indices in the distal radius and tibia by high resolution peripheral quantitative computed tomography. Bone
27. MacNeil JA, Boyd SK. Improved reproducibility of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys
28. Moore KL, Dalley AF. Clinically Oriented Anatomy
. 4th ed. Baltimore (MD): Lippincott Williams & Wilkins; 2007. p. 460.
29. Myburgh KH, Hutchins J, Fataar AB, Hough SF, Noakes TD. Low bone density is an etiologic factor for stress fractures in athletes. Ann Intern Med
30. Nishiyama KK, Macdonald HM, Buie HR, Hanley DA, Boyd SK. Postmenopausal women with osteopenia have higher cortical porosity and thinner cortices at the distal radius and tibia than women with normal aBMD: an in vivo
HR-pQCT study. J Bone Miner Res
31. Perilli E, Le V, Ma B, Salmon P, Reynolds K, Fazzalari NL. Detecting early bone changes using in vivo
micro-CT in ovariectomized, zoledronic acid-treated, and sham-operated rats. Osteoporos Int
32. Popp KL, Hughes JM, Smock AJ, et al. Bone geometry, strength, and muscle size in runners with a history of stress fracture. Med Sci Sports Exerc
33. Prouteau S, Ducher G, Nanyan P, Lemineur G, Benhamou L, Courteix D. Fractal analysis of bone texture: a screening tool for stress fracture risk? Eur J Clin Invest
34. Rittweger J, Beller G, Ehrig J, et al. Bone-muscle strength indices for the human lower leg. Bone
35. Sasimontonkul S, Bay BK, Pavol MJ. Bone contact forces on the distal tibia during the stance phase of running. J Biomech
36. Seeman E, Delmas PD. Bone quality-the material and structural basis of bone strength and fragility. N Engl J Med
37. Siu WS, Qin L, Leung KS. pQCT bone strength index may serve as a better predictor than bone mineral density for long bone breaking strength. J Bone Miner Metab
38. Sode M, Burghardt AJ, Kazakia GJ, Link TM, Majumdar S. Regional variations of gender-specific and age-related differences in trabecular bone structure of the distal radius and tibia. Bone
39. Suter E, Herzog W, De Souza K, Bray R. Inhibition of the quadriceps muscles in patients with anterior knee pain. J Appl Biomech
40. Valimaki VV, Alfthan H, Lehmuskallio E, et al. Risk factors for clinical stress fractures in male military recruits: a prospective cohort study. Bone
41. Wilhelm G, Felsenberg D, Bogusch G, Willnecker J, Thaten I, Gummert P. Biomechanical examinations for validation of the bone strength strain index SSI, calculated by peripheral quantitative computed tomography. In: Lyritis GP, editor. Musculoskeletal Interactions
. Athens (Greece): Hylonome Editions; 1999. pp. 105-10.