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The purpose of the study was to evaluate trabecular bone score (TBS) technology for orthopedic application (TBSortho) as a predictor of a screw pull-out strength in a cadaveric model. This study finds that TBSortho correlates more strongly with the screw pull-out strength compared to cortical density, computed tomography (CT) Hounsfield units (HU), and dual-energy X-ray absorptiometry (DXA) bone mineral density (BMD).
Introduction
Patient bone quality impacts the mechanical strength of surgical fixation constructs. Preoperative assessments of bone quality and the potential for a screw pull-out are important for surgical planning as well as postoperative rehabilitation protocols. Previous work has correlated the screw pull-out strength with the screw insertional torque, cortical thickness, and CT HU. TBS is a gray-level textural metric that can be extracted from a two-dimensional DXA scan, improves fracture prediction, and may evaluate the mechanical competence of both the cortical and trabecular bones. The purpose of the study was to evaluate TBS technology for TBSortho as a predictor of the screw pull-out strength in a cadaveric model.
Methods
Twenty paired, fresh-frozen cadaver femurs stripped of soft tissue were obtained (5 M, 5 F specimens, age range of 56–96 years). Standard clinical femur CT were performed to obtain HU, cortical thickness, and cortical density. DXA was also performed using a novel analysis technique as distal femur DXA is not routinely acquired clinically. DXA data were used to generate TBSortho values in two distal femur regions of interest. All femurs then underwent a screw pull-out testing with five lateral distal femoral 5-mm locking screws (n = 100 screws total). The correlation coefficient from Spearman tests and R-squared of the fixed effects from the linear mixed effects models were calculated.
Results
TBSortho was found to correlate most strongly of CT and DXA measures with the screw pull-out strength, having marginal R2 and standardized beta of 0.75 and 0.87 in the proximal screw cluster and 0.67 and 0.83 in the distal screw cluster, respectively. TBSortho accounted for 75% variance in the pull-out strength. CT HU and DXA bone mineral density (BMD) did not have a statistically significant correlation with the screw pull-out strength.
Conclusion
This study finds that TBSortho correlates more strongly with the screw pull out strength in a cadaveric distal femur model compared to cortical density, CT HU, and DXA BMD. These preliminary results suggest that TBSortho may be a valuable tool to model mechanical integrity of bone preoperatively.
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Introduction
Each year in the United States, 53 million people have low bone mass or osteoporosis [1], resulting in approximately 2 million osteoporosis-related fractures annually [2]. The surgical management of fractures in patients with low bone mass or osteoporosis has higher complication rates due to mechanical failure with the need for subsequent revision surgery [3]. The most common surgical treatments for these patients involve stabilizing the fracture with plates and bone screws. The most common complication following these surgical treatments is screw loosening, often through pull out. Osteoporosis is a known risk factor for a screw pull-out in many orthopedic procedures such as sliding hip screw fixation of intertrochanteric femur fractures [4], locked plating of proximal humerus fractures [5], and thoracolumbar fusion [6, 7]. Thus, preoperative knowledge of bone quality and its relationship to a common failure mechanism of bone screws would help guide fixation strategies to mitigate the failure risk and could aid in determining postoperative weightbearing restrictions.
Medical imaging is a non-invasive means of examining bone and is commonly performed on orthopedic patients. Clinically available options include radiographs, computed tomography (CT), magnetic resonance imaging (MRI), and dual-energy X-ray absorptiometry (DXA). Radiographs do not provide quantitative data and require radiation exposure. CT is expensive and requires radiation exposure. MRI is also expensive and is better at profiling soft tissue structures than bone. DXA, by comparison, is an attractive option because it is low cost, widely available, and uses minimal radiation. However, DXA only calculates bone mineral density and does not assess strength or architecture of bone, which are key contributors to screw engagement [8]. Trabecular bone score (TBS) is a more recent technology that addresses this limitation using the two-dimensional DXA image to generate a gray-level textural metric that is highly correlated to bone michroarchitecture [9]. Clinically, this technology is applied to the lumbar spine; however, the TBS approach was adapted to the Texture Research Investigational Platform (TRIP) software (Medimaps, Geneva, Switzerland), which allows assessment of many skeletal sites imaged by various modalities [10]. The TRIP approach is currently referred to as TBSortho and generates a bone texture score for non-spine anatomy, making it a plausible tool to test skeletal structure and perhaps predict screw pull out.
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Bone mineral density (BMD) as determined by DXA [11] and quantitative CT [12] correlates to a screw pull-out strength. TBS, a measurement of bone texture, correlates with vertebral body stiffness [13]. The screw pull-out strength has been studied in relation to an insertional torque [14], BMD [15], and CT Hounsfield units (HU) [16]. The screw pull-out strength has not been studied with TBS and, since it is a measure of texture, TBS may correlate more strongly with mechanical properties of the bone. The vast majority of the screw pull-out research has been performed on cadaver spines and may not be generalizable to long bones; studies on the screw pull-out strength outside of the spine are needed. Additionally, none of the previously tested clinical circumstances has had a strong, reproducible correlation to the screw pull-out strength. We chose a distal femur model as this is a common site for screw loosening and implant failure, with an incidence as high as 7% [17]. Because implant failure is a substantial problem across all orthopedic subspecialties, the ability to preoperatively predict the integrity of implanted orthopedic devices would allow surgeons to change their operative strategy if a patient is at increased risk of a screw pull-out, implant loosening, or subsidence. A better clinical predictor of the pull-out strength is needed to realize this potential.
Accordingly, the purpose of this study was to evaluate the correlation of TBSortho and screw pull-out strength in the distal femur. We hypothesize that TBSortho will correlate more strongly with the screw pull-out than cortical density, CT HU, and DXA BMD.
Methods
Ten sets of paired, fresh-frozen femur bones (i.e., right and left femur from the same cadaver) stripped of soft tissue were obtained. The age of the cadavers ranged from 56 to 96 years. There was one male and one female from each decade of age (i.e., age in 50 s, age in 60 s). Specimens did not have a known history of conditions that would cause an altered bone status (e.g., osteoporosis, metabolic bone disease, skeletal malignancy, prior fracture, previous surgery). The femurs were stored in freezers at − 20 °F until testing was performed, at which point the femurs were allowed to thaw to room temperature.
Imaging
The specimens underwent standard clinical Discovery CT750 HD CT scans (General Electric, Madison, WI). Picture Archiving and Communication Systems (PACS) was used for measurements. Cortical width (the linear distance between the outer edges of the femoral cortex) and cortical index (the ratio of the sum of the medial and lateral cortical width divided by the entire width of the bone) were measured at two levels within the distal femur (Fig. 1). Measurements were performed three times by one author (JTB) and averaged. The locations (i.e., 2 and 4 cm proximal to the most distal point of the distal femoral condyles) were chosen to represent two locations of screw clusters in a standard distal femoral locking plate. HU were obtained on axial CT slices at the same two levels in the distal femur. An elliptical region of interest (ROI) was drawn as large as possible without including the cortical bone (Fig. 2).
Fig. 1
Representative measurements of cortical width and cortical index on a mid-coronal CT image of the distal femur. Measurements are made at 2 and 4 cm proximal to the most distal aspect of the bone
Elliptical region of interests to measure CT HU drawn on axial CT slice 4 cm (A) and 2 cm (B) proximal to the end of the femur. Coronal CT (C) shows the levels of the axial slices
DXA scans were performed with Lunar iDXA (General Electric, Madison, WI, USA). Due to the absence of a specific distal femur acquisition software, scans were acquired using the orthopedic knee acquisition feature. The femurs were suspended in air using a sheet of foam insulation, to minimize contribution of mass, above a plastic container holding 6 cm of water to simulate soft tissue (Fig. 3). The approach was selected after a series of experiments using various combinations and densities of water and acrylic to mimic lean and fat respectively for a soft tissue equivalent. This method provided the best technical acquisition and image quality.
Fig. 3
Cadaver femurs were suspended via custom radiolucent jig above 6 cm of water to simulate soft tissue during DXA acquisition
Custom regions of interest (ROIs), 2 cm in height were manually placed using index lines to measure the distance at defined locations along the distal femur (Fig. 4). The areas were again chosen to simulate the location of screw clusters. TBSortho was determined within these same ROIs using the TRIP software version 1.0.1.23.
Fig. 4
DXA (A) and TBSortho (B) analysis of the distal femur. DXA regions of interest (ROI) were determined by manually placing a 2-cm vertical index line at the most distal tip of the femoral condyle marking the placement for the lower edge of a 2-cm horizontal region of interest. A second 2-cm ROI was stacked proximal to the initial ROI. A Subsequently, the DXA scan images were converted to DICOMs, and uploaded into TRIP software to generate TBSortho values. TBSortho ROIs were manually drawn inside the 2 DXA custom ROIs to avoid inclusion of DXA edges with the measurement. An 8-point ROI was used to outline the bone with 3 points just inside the superior and inferior DXA ROI (at each edge and in the middle), as well as a point at the center of the medial and lateral edges (B)
The femurs were rigidly fixed to a custom stabilizing jig using two 5-mm external fixator pins and a toe clamp (Fig. 5A). Five screws were placed into the bone in a configuration that simulated the use of a lateral distal femoral locking plate that is commonly used to fix distal femur fractures (4.5-mm variable angle–curved condylar plate, Depuy Synthes, Raynham, MA, USA) (Fig. 5B).
Fig. 5
A Each cadaver femur was rigidly stabilized with transverse external fixator pins and a toe clamp. The MTS applied a constant rate of axial displacement along the axis of the bone screw, which was inserted into the lateral aspect of the distal femur, to determine screw pull-out strength. Red arrow points to screw head. B Screw configuration used for pull-out testing which simulated a lateral distal femoral locking plate. Screw 1 = anterior/distal, screw 2 = posterior/distal, screw 3 = proximal/anterior, screw 4 = proximal/posterior, screw 5 = proximal. C Anterior–posterior radiograph representing the typical position of a lateral distal femoral locking plate
The plate was placed 2 cm from the most distal surface of the lateral femoral condyle and 1 cm posterior to the anterior cortical bone, and screw positions were marked (Fig. 5B). The holes were drilled with a 4.3-mm bit and a 5.0-mm variable angle–locking screw was placed into the bone at a depth up to but not through the far cortex. A custom jig was created to hold the screw head (Fig. 5A). An axial displacement force was imposed at a constant rate of 5 mm/s (MTS Bionix system, MTS, Eden Prairie, MN, USA). The maximum force reached before failure during each trial was determined from the axial force–displacement data (MATLAB 2021b, The MathWorks, Inc., Natick, MA) (Fig. 6). Failure was defined as the peak force reached during the displacement-controlled test. The maximum pull-out force was normalized to the length of the screw within the bone.
Fig. 6
Representative plot of the axial force and screw displacement during the displacement-controlled screw pullout tests. The peak force (*) represents the point of screw failure
Means and standard deviations, unless otherwise indicated, were used to describe the cadavers, pull-out strengths, and imaging metrics. For statistical analyses, the proximal three screw holes were averaged (proximal) and the distal two screw holes were averaged (distal). These locations within the femur correlated to the proximal and distal ROIs on the DXA. Statistical analyses were completed using the R Statistical language (version 4.3.1; R Core Team, 2023). Linear mixed effect models with the random effects for the cadaver were utilized to assess the association between imaging measures and normalized pull-out strength. The random effects model for the cadaver was included to account for the fact that both the left and right limb of a given cadaver were included in this analysis. Marginal R-squared, standardized beta, and the significance of the fixed effects from the linear mixed effect models were reported. P-value significance was set at 0.05.
Results
All 20 femurs underwent successful acquisition of CT, DXA, and pull out of five screws (Table 1). The average cortical index 4 cm and 2 cm proximal to the end of the femur were 5.11% (± 1.76% std dev) and 2.49% (± 0.80%), respectively. The average CT HU 4 cm and 2 cm proximal to the distal end of the femur were 118.2 (± 84.7) and 182.2 (± 76.0), respectively. The average DXA BMD was 0.791 (± 0.176) g/cm2 in the proximal ROI (4 cm proximal to the distal end of the femur) and 1.031 (± 0.214) g/cm2 in the distal ROI (2 cm proximal to the distal end of the femur). The average TBSortho score was 1.273 (± 0.099) in the proximal ROI and 1.282 (± 0.071) g/cm2 in the distal ROI.
Table 1
Average CT, DXA, TBS, and pull-out values for all cadaver femurs
Average
Std Dev
Min
Max
Cortical index proximal
5.1
1.75
2.92
10.07
Cortical index distal
2.49
0.81
1.05
4.55
CT HU proximal
118.2
84.6
−73
233
CT HU distal
182.2
76
19
290
DXA BMD proximal (g/cm2)
0.791
0.176
0.46
1.133
DXA BMD distal (g/cm2)
1.031
0.214
0.587
1.362
TBS proximal
1.273
0.099
1.095
1.412
TBS distal
1.282
0.071
1.138
1.386
Prox. pull-out avg. (N)
703.8
472.5
137.9
1489.1
Prox. pull-out normalized to screw length
1092.3
812.9
156
2535.4
Dist. pull-out avg. (N)
494.5
277.9
97.9
1073
Dist. pull-out normalized to screw length
658.5
393.4
102
1425.5
CT computed tomography, DXA dual-energy X-ray, HU Hounsfield unit, TBS trabecular bone score
The screw pull-out strength varied from 61.3 to 2003.9 N. The most proximal screw had the highest average screw pull-out force of 783.2 (± 584.6) N, while the distal/posterior screw had the lowest average screw pull out force of 453.9 (± 283.4) N.
Using a linear mixed effects model with one predictor (imaging technique) and one random effect (cadaver), TBSortho was found to correlate most strongly with the screw pull-out strength, having marginal R2 and standardized beta of 0.75 and 0.87 in the proximal screw cluster and 0.67 and 0.83 in the distal screw cluster, respectively (Table 2).
Table 2
Results of linear mixed effects model with one predictor (imaging technique) and one random effect (cadaver)
Variable
Marginal R2
Standardized beta [95% CI]
p-value
Cortical index (proximal)
0.21
0.48 [− 0.1, 0.97]
0.06
Cortical index (distal)
0.16
0.41 [− 0.05, 0.87]
0.07
CT HU (proximal)
0.05
0.24 [− 0.32, 0.80]
0.39
CT HU (distal)
0.07
0.26 [− 0.24, 0.76]
0.29
DXA BMD (proximal)
0.01
− 0.09 [− 0.68, 0.50]
0.75
DXA BMD (distal)
0.03
0.19 [− 0.34, 0.72]
0.46
TBSortho (proximal)
0.75
0.87 [0.62, 1.12]
< 0.001
TBSortho (distal)
0.67
0.83 [0.55, 1.11]
< 0.001
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Cortical index, CT HU, and DXA BMD did not correlate with the screw pull-out strength (Table 2, Fig. 7). R-squared is the percent variance in the model explained by a given variable. Therefore, TBSortho accounted for 75% and 67% of the variance in the pull-out strength in the proximal and distal segments, respectively.
Fig. 7
Scatter plot comparison of pull-out strength to cortical index, CT HU, DXA BMD and trabecular bone score in the proximal and distal regions of interest
In this cadaver distal femur model, we found that TBSortho has the strongest correlation with the screw pull-out strength compared to the cortical index, BMD, and CT HU. This is the first study, to our knowledge, to assess TBS in relation to the screw pull-out strength, and the strength of this relationship suggests TBSortho is a promising technique to guide surgical planning to mitigate screw pull-out failures.
Previous studies have found that TBS correlates with vertebral stiffness [13]. No prior studies have assessed the utility of TBS in predicting the screw pull-out strength. Additional studies are needed to validate these findings of TBSortho correlating to the screw pull-out in the distal femur as well as in other areas of the skeleton. In previous clinical cohort studies, TBS was related to the fracture risk and discriminated patients with fragility fractures from those without fracture, independently of BMD [18, 19]. Therefore, TBS is proving to be a useful tool for assessing the fragility fracture risk in the general population as well as the mechanical failure risk in the surgical population.
BMD, bone geometry, and bone quality all contribute to bone strength. Bone quality, specifically, is determined by mineralization, microarchitecture, microdamage, bone turnover, and collagen structure. TBS does not measure anything directly; rather, it calculates a gray-scale mathematical relationship between pixels, which has been shown to be a better predictor of the fracture risk than BMD. Currently, TBS is only clinically available in the spine, but this study demonstrates the promise of using TBS in the appendicular skeleton to assess bone quality. While DXA and TBS would not likely be used in the setting of an acute fracture requiring urgent stabilization, these results could be used to support the preoperative evaluation of bones with DXA/TBS prior to major orthopedic operations such as spine fusions and major joint replacements.
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Multiple modes of mechanical failure exist for orthopedic implants, all of which may be impacted by properties of the implant and the host bone. These modes include screw breakage/failure, cantilever bending, toggle, and screw pull-out. The pull-out strength of screws in porous materials is governed by the following factors: the major diameter of the screw, the length of engagement of the thread, a thread shape factor which accounts for thread depth and pitch, and the shear strength of the material into which the screw is embedded [20]. Much investigation has been undertaken to model and predict the shear strength of the human bone.
The screw pull-out testing has been sparsely reported in the distal femur. One study reported a range of 100–1500 N with an average of approximately 500 N [21]. The authors used 4.5-mm cortical screws as opposed to 5-mm locking screws used in the present study; however, despite the methodologic difference, these data are consistent with our results. To our knowledge, no previous studies correlating CT HU and BMD in the distal femur have been reported. However, the screw pull-out strength in cadaveric spines has been shown to correlate with CT HU [22] and DXA BMD [23]. The reason that CT HU and DXA BMD did not correlate with the screw pull-out strength in our study is unknown. We speculate that the distal femur may behave differently because of its relative composition of trabecular vs. cortical bone; however, our literature review reveals no published data for the cortical/trabecular composition of this region of interest. As opposed to a pedicle screw model in which the screw is squeezed between cortical bone along the course of the pedicle, the distal femur has a thin layer over the cortical bone, but is otherwise largely trabecular.
The question of whether these results will translate into a clinical postoperative mechanical failure of implants is yet to be determined. In a clinical study of the screw pull-out and preoperative CT HU, Aichmair et al. found a trend toward increasing screw failure with decreasing HU; however, this did not reach a statistical significance (p = 0.061) [16]. In a study of 150 patients with preoperative CT undergoing thoracolumbar fusion, patients with lower HU at the upper instrumented vertebrae had a higher rate of the proximal junctional failure. More studies are needed, specifically in the appendicular skeleton, to examine the correlation between mechanical failure and preoperative CT HU, DXA BMD, and TBS.
Limitations
There are limitations of this study that should be considered when interpreting the findings. First, screws can fail in ways other than the pull-out (such as cyclic loading and shear) which were not represented in this study. Second, the screw type and screw configuration used in the distal femur are commonly used to fix distal femoral fractures, but the results may not be applicable to other fixation constructs in the femur or other bones. Third, isolated cadaver bones were tested, requiring a soft tissue surrogate for DXA assessment. Fourth, donor ages ranged from 50 to 90 s, and thus, these data may not be applicable to younger adults or pediatric patients. Finally, TBSortho technology, particularly with the non-standard DXA region of interest, is unlikely to be available in all practice settings.
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Conclusions
This study found that TBSortho correlates more strongly with the screw pull-out strength than other commonly used metrics (i.e., cortical index, CT HU, and DXA BMD) in a cadaveric distal femur model. These results suggest that TBSortho is a promising surrogate for bone strength and could be used to model the mechanical integrity of bone preoperatively. Future studies are needed to clinically validate this finding in the distal femur, explore TBSortho in other commonly fractured bones (e.g., proximal humerus, proximal femur, and tibial plateau), and correlate TBS in human patients to postoperative clinical and radiographic outcomes.
Declarations
Conflicts of interest
Bernatz, Sandhu, Krueger, Borchardt, Knurr, Binkley, Roth, and Anderson declare that they have no conflict of interest.
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