Journal of Orthopaedic Research 9452-462 Raven Press, Ltd., New York 0 1991 Orthopaedic Research Society
An Anatomic Basis for Spinal Instability: A Porcine Trauma Model T. R. Oxland, M. M. Panjabi, E. P. Southern, and J. S. Duranceau Biomechanics Laboratory, Department of Orthopaedics and Rehabilitation, Yale University School of Medicine, New Haven, Connecticut, U.S.A.
Summary: To determine the anatomic basis for spinal instabilities, 16 porcine cervical spine specimens were subjected to a well-defined sagittal plane trauma. The multidirectional instability of each specimen was measured before and after trauma. Detailed anatomic dissections were performed on each traumatized specimen to quantitate the extent of injury to several distinct anatomic structures and columns. Multiple regression models were constructed to determine which anatomic structures and columns correlated best with each multidirectional instability. Flexion instability correlated best with injury to the interspinous/supraspinous ligaments and the ligamentum flavum. Extension instability correlated best with anterior longitudinal ligament and pedicle injury. Axial rotation instability correlated best with anterior disc-end-plate and capsular ligament injuries, while lateral bending instability correlated best with posterior disc-end-plate injuries. Anterior column injuries correlated best with extension, axial rotation, and lateral bending instabilities, while posterior column injuries correlated best with flexion instability. Finally, individual anatomic structural injuries had higher correlations with multidirectional instabilities than did the injuries defined by the anatomic columns. Key Words: Spinal injuries-Trauma biomechanics-Spinal instabilities.
ture, and the quality of the tissues under stress (15,18). To the clinician, these injuries present a significant diagnostic problem. The final diagnosis must assess the stability or instability of the spine. In reaching an assessment of the instability, the clinician first hypothesizes which anatomic structures are injured, using a variety of available imaging techniques. Based on this anatomic injury information, the instability of the spine is assessed, and the appropriate treatment is chosen. The classification of a spinal injury as stable or unstable is often based on retrospective clinical studies and subjective clinical judgment, but with little supporting experimental data. One method, as described by Denis (8), evaluates the structural in-
High-speed traumatic injuries to the spine are a great economic cost to society and a tremendous physical burden to the patient. These injuries have been well documented and include various combinations of vertebral fractures, dislocations, ligament stretch or rupture, and intervertebral disc/ end-plate lesions (4,16,23). Which anatomic structures are damaged in trauma depends on many factors that include the load magnitude, direction and point of application, loading rate, spinal pos-
Received June 7, 1990; accepted November 8, 1990. Address correspondence and reprint requests to T. Oxland at Biomechanics Laboratory, Department of Orthopaedics and Rehabilitation, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, U.S.A.
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tegrity of each of the three anatomic columns. The method was derived from extensive study of clinical cases and is used for the evaluation of thoracolumbar injuries. Concerning the evaluation of cervical spine injuries, a checklist has been proposed to determine spinal instability in a clinical setting (28). The method incorporates biomechanically derived parameters, neurological assessment, and other clinical factors. Biomechanical studies provide the thresholds of physiological motions and conclude that the cervical spine becomes mechanically unstable if either all posterior elements plus an additional anterior component or all anterior elements plus one posterior component are destroyed or rendered nonfunctional (19). Similar component transection studies have been performed in the lumbar spine (22). However, in these studies, the injuries were produced by transecting structures sequentially using a scalpel. In real-life trauma, it may be expected that many different combinations of anatomic structures are injured. In such traumatic injuries, it is important to document the anatomic injuries and the resulting multidirectional instabilities. The purpose of this study was to determine which anatomic injuries, produced by experimental highspeed trauma, correlate best with the multidirectional instabilities in an in vitro porcine cervical spine model. In addition, the correlation of the instabilities with each of the three anatomic columns was determined. MATERIALS AND METHODS Experimental Overview The experimental procedure consisted of several steps. Each specimen was tested to determine its intact, three-dimensional physiological motions. This is referred to as the instability test. Following this test, the specimen was subjected to one of three high-speed trauma modes in the sagittal plane. To describe the injury objectively, the specimen was reevaluated by the instability test. The final step involved a detailed anatomic dissection of each specimen to document all observable injuries. Specimen Preparation Sixteen freshly frozen, porcine cervical spine segments (two C5-C7, 14 C2-C4) were used in this study. The animals were male and female, 1-1.5 years old, sexually mature but not full weight (55-70
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kg). The specimens were dissected of all nonligamentous soft tissue. The top and bottom vertebrae were mounted in polyester resin molds, with their body centroids (i.e., the point where body diagonals intersect) vertically aligned. The specimens were stored in plastic bags at -20°C until tested.
Porcine Vertebral Anatomy Since this article concerns anatomic lesions, a familiarity with the pig cervical spine is imperative. Axial and lateral radiographs of a typical pig cervical vertebra are shown in Fig. 1 along with human cervical and lumbar vertebrae. The porcine cervical vertebra is larger than the human cervical vertebra but smaller than the human lumbar vertebra. The processes in the pig that extend anterolaterally do not appear to have a significant mechanical role. The pig articular facets are oriented vertically in a manner similar to the human lumbar vertebra. The pig vertebral body and spinous process have a shape more similar to the human lumbar than the human cervical vertebra. Another similarity with the human lumbar vertebra is the consistency of the posterior interspinous-supraspinous ligaments, which is in contrast to their relatively insignificant role in the human cervical spine (13,21). Of particular note in the axial radiograph of the pig vertebra in Fig. 1 are the ossification centers in the middle of the vertebral body. This is representative of a child’s or adolescent’s spine (lo), which is consistent with the fact, noted earlier, that these pigs are not at full adult weight. Therefore, this porcine cervical vertebral model appears to be most similar to the lumbar spine of a human adolescent. Instability Test In preparation for this test, a marker containing three metal balls was attached to the top vertebral mount. No markers were attached to the middle vertebra so as not to damage it. Six pure moments (flexion, extension, rightlleft lateral bending, and rightlleft axial rotation) were applied individually to the upper mount. Each moment was applied stepwise in four equal increments to a maximum of 3.6 Nm. At each load step, the specimen was allowed to creep for 30 s . Three load-unload cycles were performed, and stereophotographs of the vertebral marker were taken on the third load cycle. The stereophotographs were digitized, and the threedimensional coordinates of each marker point were
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FIG. 1. Axial and lateral radiographic comDarisons of a human cervical vertebra (left), a porcine cervical vertebra (center), and a human lumbar vertebra (right).
determined. The three-dimensional kinematics of the top vertebra with respect to the bottom vertebra were calculated using appropriate computer software. For all six degrees of freedom, motion parameters of neutral zone (NZ) and range of motion (ROM) were determined. High-speed Trauma Production
A specially designed apparatus was constructed to produce the traumatic injuries. The injury-producing component was a free-falling mass that descended through a Plexiglas cylinder to hit the specimen. The mass was 14.5 kg and was dropped from a height of 1.1 m. To apply different load vectors to the specimen, a cylinder (2.5 cm in diameter) was attached to the superior surface of the top mount. To produce pure compression loading, the cylinder was placed directly above the geometric center of the top vertebral body. For flexion-compression or extension-compression trauma modes, the cylinder was translated 1 cm anteriorly or posteriorly, respectively, from the center position. The specimens were distributed among the three different trauma modes. In this paper, the results for all three trauma modes were pooled. A high-speed movie camera monitored the specimen deformations during the trauma at 1,000 frame&. The loads of axial compression, anteriorposterior shear force, and sagittal plane bending
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moments were measured by a load cell placed beneath the specimen and recorded by a microcomputer at 3,000 reading& Anatomic Dissections
After the high-speed trauma and instability measurements, each specimen was subjected to a meticulous anatomic dissection, with the purpose of quantifying the specimen injury., This dissection involved three parts. First, the anatomic components on the exterior of the specimen were described: anterior longitudinal ligament (ALL), intertransverse ligament (ITL), interspinous and supraspinous ligaments (ISS), facet capsular ligaments (CAP), pedicles (PED), and lamina and spinous processes (SPL). Next, the pedicles were cut in the frontal plane such that structures inside the spinal canal were observable, these being the posterior longitudinal ligament (PLL), ligamentum flavum (LF), and facet articular processes (FAC). To determine the integrity of the end plate/disc/end plate, the disc was injected with a dye to a maximum pressure of 250 kPa (40 psi) or a maximum volume of 1 ml. Finally, the vertebral bodies and intervertebral discs were cut in the midsagittal plane. Since the specimens used in this study were three-vertebrae segments, the anatomic structures mentioned above were located at three vertebral levels and two intervertebral levels, with each substructure being re-
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ferred to as an anatomic component. A graphic representation of the anatomic structures studied is shown in Fig. 2. Injury Grading To obtain quantitative injury scores for each anatomic structure or column from the injury descriptions, the basic principle that two or more anatomic components form an anatomic structure, and two or more anatomic structures form an anatomic column, was used. Furthermore, the injury score of an anatomic structure or an anatomic column was obtained simply by adding together the injury scores of the anatomic components. For example, the anterior vertebral body (AVB) anatomic structure consisted of three anatomic components, one from each of the three vertebral bodies (i.e., AVB V1, AVB V2, AVB V3). In a similar manner, for example, the anterior column consisted of the anatomic structures ALL, AVB, and anterior disdend plate (ADE). Using this scheme, the entire specimen was divided into 13 anatomic structures (Fig. 2). Each anatomic component was assigned an injury score on a scale of 0 to 2: 0, 1, or 2 representing intact, partial injury, or complete injury, respectively. Since each anatomic structure was graded as
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the sum of its anatomic components, the maximum injury score for an anatomic structure was the number of anatomic components making up the structure multiplied by 2. As an example, the ISS structure was assigned an injury score of 0, 1, or 2 for each of its components (i.e., top and bottom levels). Its subsequent anatomic structure score was the sum of these component injury scores on a scale of 0 to 4. As described earlier, the anatomic column injury scores were determined by adding the injury scores from the anatomic structures. Since the injury scale for each anatomic structure was dependent on the number of anatomic components of the structure, the anatomic structural injury scores were normalized such that the most severe injury observed for each structure had an injury score of 10. The most severe injuries observed in this study were ALL, PLL, ITL, LF, and ISS complete rupture at one level; CAP complete rupture at both levels (left and right); AVB, ADE, posterior vertebral body (PVB), and posterior disc-end plate (PDE) fractures in two of three vertebrae or disc/end plates; PED, SPL fracture at level 1; and FAC fracture of two articular facets. The normalized anatomic structural injury scores were added together to determine each anatomic column injury score. The anatomic column injury scores were normalized further (maximum value of 10) to allow comparison of the injury magnitudes among the anterior, middle, and posterior columns. Statistical Analysis
FIG. 2. Pictorial representation of the anatomic structures that make up the porcine spine. ALL, anterior longitudinal ligament; AVB, anterior vertebral body; ADE, anterior disc/ end plate; PVB, posterior vertebral body; PDE, posterior disc/ end plate; PLL, posterior longitudinal ligament; ITL, intertransverse ligament (not shown); PED, pedicle; FAC, articular facet; CAP, capsular ligaments, LF, ligamentum flavum; SPL, spinous process/lamina; ISS, interspinous/supraspinous ligaments.
As stated earlier, the goal of this study was to determine which anatomic structures correlated best with various multidirectional instabilities in this porcine trauma model. Statistically, such determination requires a multivariate analysis that selects the anatomic variables that correlate with each instability (i.e., those that explain the greatest amount of variance in the instability). This analysis is best done by multiple regression. However, a trade-off exists between explaining the greatest percentage of variance in the dependent variable and using the fewest number of independent variables in the analysis. Ideally, few independent variables would explain most of the variance in the dependent variable, but this is not always true. Alternatively, one could perform a regression for all possible combinations of independent variables, but this method is usually not feasible. A better method to deter-
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mine the appropriate regression equation is stepwise regression (9). In this method, independent variables are entered into the equation if they possess a correlation with the dependent variable above a certain user-specified significance level. In this study, a significance level of 5% was used. It is important to realize that this significance level refers to the slope of the last variable entered into the regression and that the significance of the entire equation was generally much higher. To understand the correlations between the injuries to specific anatomic structures and the multidirectional instabilities, simple pairwise productmoment correlations were calculated for all combinations of anatomic structures and instabilities. Following this analysis, a multiple regression was performed for each instability to determine which combination of anatomic structural injuries correlated best with each instability. These steps of calculating the simple correlation matrix followed by multiple regressions were repeated to determine the relationships between the anatomic column injuries and each instability. RESULTS In this study, the multidirectional instabilities were defined as the ratios of the injured to intact ROMs in flexion, extension, lateral bending (average of right and left), and axial rotation (average of right and left). Correlations of Instabilities with Anatomic Structures Simple correlation coefficients between all anatomic structural injuries and multidirectional instabilities were calculated. Values of l, 0, and - l indicate 100% positive correlation, no correlation, and 100% negative correlation, respectively. The anatomic structures that had the highest correlation coefficients relative to the multidirectional instabilities were flexion (ISS: 0.74, LF: 0.57), extension (ALL: 0.65, PED: 0.56), axial rotation (ADE: 0.76, CAP: 0.74, PDE: 0.69, ALL: 0.67), and lateral bending (PDE: 0.73, CAP: 0.62, ADE: 0.59). Multiple regressions were performed to determine which group of anatomic structures best explained the variation in each of the instabilities. The results of these regressions are shown in Figs. 3-6 for flexion, extension, axial rotation, and lateral
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bending instabilities, respectively. Injuries to the ISS correlated best with flexion instability. In addition, LF injuries were entered into the regression model as shown in Fig 3. Together, the two anatomic variables explained 69% of the variation in flexion instability (p = .003). For extension instability, ALL had the highest Correlation. PED was the next variable entered into the multiple regression equation (Fig. 4). Both variables together accounted for 53% of the variation in extension instability (p = .016). For the axial rotation instability, ADE injuries had the greatest correlation, explaining approximately 57% of axial rotation instability (p = .001). This was the only anatomic structure entered into the regression model (Fig. 5). Injuries to the PDE had the highest correlation with lateral bending instability. PDE was the only anatomic structure entered into the regression model, accounting for 54% of the variance in lateral bending instability (p = .002) (Fig. 6). Correlations of Instabilities with the Anatomic Columns In a manner analogous to the anatomic structures, the anatomic column analysis was done by first determining a simple correlation followed by multiple regression. The anatomic columns that had the highest simple correlation coefficients with the instabilities were flexion (posterior: O S O ) , extension (anterior: 0.64, posterior: 0.58), axial rotation (anterior: 0.73, posterior: 0.67), and lateral bending (anterior: 0.58, posterior: 0.52). For the multiple regressions, only one anatomic column was entered into each regression model. Obviously, that column was the one with the highest simple correlation with each instability. The posterior column had the highest correlation with flexion instability, explaining only 25% of the variance in the injured motion (p = .08). The anterior column had the highest correlation with extension instability, accounting for 25% of the variance in extension instability (p = .Ol). The anterior column had the greatest correlation with axial rotation instability, explaining 54% of the variance in the instability (p = .001). For the lateral bending instability, only the anterior column was entered into the equation. It explained 34% of the variance in the instability (p = .02).
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Regression
R 2D
Model
Flexion Instability = 0.09 (ISS)
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+ 0.09 (LF) +
0.92
0.69
0.003
FIG. 3. Pictorial representation of the anatomic structures that correlated with flexion instability.
DISCUSSION
In this study, the anatomic injuries Produced in a high-speed trauma model were correlated to the resultant multidirectional instabiiities. Tie approach was unique in that the injuries produced by three well-defined sagittal plane load vectors were not predetermined. This was in contrast to previous studies, in which the anatomic structures were transected sequentially and their effect on the instability measured. Several different injury combinations resulted from approximately identical impact loads. In these cases, the variation in the injuries was probably due to the variability in the failure properties of the different spinal tissues of the sample studied. Limitations of the Study
A porcine cervical spine model was used; its similar anatomic appearance to the human lumbar spine was described earlier (Fig. 1). We are pres-
ently conducting investigations to compare its biomechanical characteristics to that of the human spine in vitro. Other researchers have used bovine spines in a trauma model (6). However, we ob. . served a relatively immature veneDrai p*hYSEmth~ bovine spine, which is in agreement with the recent findings of Allan and colleagues (1). They have suggested that a porcine spine is a better model for trauma studies. To quantify the anatomic injuries of each spine, a subjective injury grade on a scale of 0-2 was assigned to each individual anatomic component (e.g., capsular ligament of the upper left intervertebra1joint). This type of discrete injury-grading may suggest a nonparametric form of data analysis. However, since we divided each anatomic structure into several discrete anatomic components, we obtained a relatively wide injury scale for each anatomic structure. As a result, the parametric type of data analysis, as used herein, was valid. The number of specimens is of critical importance in any study for which a multiple regression
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Anterior Longitudinal Ligament
Regression
R 2D
Model
Extension Instability = 0.07 (ALL)
+ 0.06 (PED) +
1.5
0.53
0.016
FIG. 4. Pictorial representation of the anatomic structures that correlated with extension instability.
model is constructed. If too many independent variables are allowed into the equation, one may arrive at a model that has very little physical significance. A well-accepted statistical guideline in regression model-building is to introduce approximately one variable for every 10 specimens (S. Walter, personal communication). Since we used 16 specimens in this study, the number of independent variables allowed into each regression model was limited to two. Relevance of Anatomic Injuries Produced
To ascertain the relevance of our trauma model to the human condition, several studies that documented pathoanatomical injuries were reviewed. (3-5,7,11,14,17,23,26,27). Although the injury mechanisms in these studies were speculative, typical spinal injuries were well documented. In the present study, the flexion and extension
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trauma produced distinctive lesions, as documented by Southern and associates (25), while compression alone resulted in less severe injuries. In flexion trauma, the greatest injuries were to the posterior ligamentous complex. These injuries were similar to the injuries described by Allen and co-workers (2) in his distractive flexion group and by Davis and colleagues (7) in their autopsy series. In extension trauma, typical failure was an “opening up” of the vertebral d i d e n d plate, possibly due to an immature epiphyseal plate. The appearance of the end plate was similar to that shown by Edelson and Nathan (10) for a typical adolescent. In addition, this injury has been described by Taylor and Blackwood (27), Marar (17), Harris and associates (14) and Aufdermaur (3), among others. Regression Model as a Predictor of Instability One potential use for these types of regression equations is predicting multidirectional instabilities.
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Anterior Disc/ End -Plate
-
ession
R
Model
Axial Rotation Instability = 0.28 (ADE)
+
1.68
2
0.57
r
> 0.001
FIG. 5. Pictorial representation of the anatomic structures that correlated with axial rotation instability.
As stated earlier, all anatomic structures used in the analysis were normalized such that the most severe injuries had a value of 10. If the anatomic structure in question was injured severely, as described, the anatomic injury score would be 10. To predict flexion instability, for example, if the ISS was completely ruptured at one intervertebrallevel while the LF remained intact, the predicted flexion instability ratio would be 1.82 [0.09 (10) + 0.09 (0) + 0.92 = 1.82, Fig. 31. Since spinal instability is a nonlinear phenomenon, we cannot extrapolate the regression models for injuries more severe than those described.
Flexion Instability
Injuries to the ISS and the LF were included in the multiple regression equation for flexion instability. Using biomechanical principles, since the cen-
ter of rotation is in the region of the intervertebral disc, as described by White and Panjabi (29), both these ligamentous structures would be loaded in tension under flexion moments. Therefore, it was expected that they would provide the greatest stability under applied flexion moments. As described earlier, one can estimate the flexion instability that would result from injury to the ISS and LF. Total rupture of the ISS at one vertebral level would increase motion 90% over the intact level, while complete injury to both the ISS and the LF at a single level would result in flexion motion of 180% over the intact motion. This type of analysis does not imply that other anatomic structures do not contribute to flexion instability, but rather that they do not linearly correlate with the instability as well as the ISS or the LF injuries. For example, in many specimens with LF injury, the CAP were also disrupted, causing severe instability. However, in
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---
q-
---
Posterior Disc/ End-Plate
Pegression
2
R r ,
M o d e1
Lateral Bending Instability = 0.06 (PDE)
+
1.07
0.54
0.002
FIG. 6. Pictorial representation of the anatomic structures that correlated with lateral bending instability.
other specimens, the CAP were injured without the LF injury, and the resultant instability was much lower, implying that the LF injury had a greater effect on flexion instability. The regression equation suggests that the flexion instability may be estimated best by looking at the injuries sustained by the ISS and LF structures.
cur under the same load. The regression coeficients for these anatomic structures were such that if each were damaged (i.e., ALL rupture and PED fracture), the extension rotation would increase 130% over the intact levels (70% ALL and 60% PED, Fig. 4). Axial Rotation Instability
Extension Instability
The ALL and PED were included in the multiple regression equation for extension instability. Again, a reasonable biomechanical explanation may be provided. The ALL was correlated most with this instability because of its important role as a tension structure in extension moments. Next were the PED, which carry bending loads between the anterior and posterior structures. With some anterior structures damaged, the posterior elements and pedicles would support the extension moment. If the pedicles were damaged, more motion would oc-
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Only the ADE was entered into the multiple regression equation for the axial rotation instability. That it was the only factor was rather surprising, since there were four anatomic structures that had simple correlations greater than 0.60 (CAP: 0.74, PDE: 0.69, ALL: 0.67). The reason for the absence of any of these structures from the regression model was their relatively high intercorrelation with the ADE, the first variable entered into the equation (CAP: 0.82, PDE: 0.74, ALL: 0.64). This finding implies that specimens with ADE injury have a high probability for associated injuries to the CAP, PDE,
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and ALL. The ADE had a highly significant correlation, suggesting that loss of its torsional resistance directly affected the rotational stability of the spine. This was consistent with the results presented by White and Panjabi (29), who found that the axial center of rotation was located within the intervertebral disc, so damage to anterior components would result in excessive motion increases. In addition, Haher and colleagues (12) documented that anterior soft-tissue structures were most important in maintaining rotational stability in the thoracolumbar spine. Although not included in the regression model, the CAP had a high simple correlation, which identified these ligaments as important structures in providing rotational stability to the spine. The regression coefficients for the ADE were such that damage at all levels would increase motion by approximately 280% over intact levels. Lateral Bending Instability
The correlation of lateral bending instability was best with the PDE, and it was the only anatomic structure entered into the regression equation. The lateral bending instability was much less than that of flexion, extension, or axial rotation, as documented by Panjabi and co-workers (20). By observing the regression coefficients, if the PDE were severely injured (i-e., two end-plate fractures), the motion after injury would be approximately 60% greater than the intact rotation. Contrast this to the motion increases in flexion, extension, and axial rotation of 180, 130, and 280%, respectively, if the structures included in their regression models were all severely injured. The concept of estimating multidirectional instabilities from known anatomic injuries has interesting clinical implications. With the advent of improved diagnostic techniques (CT scan, magnetic resonance imaging), a clinician can assess the anatomic damage to a trauma patient much more accurately than in the past, especially for soft-tissue injuries (24). Eventually, if the injury status of each anatomic component can be determined, it may be possible to estimate each multidirectional instability and thus contribute to the choice of treatment. Anatomic Column Correlations The multiple regression equations included only one anatomic column for each instability. Therefore, simple correlations were sufficient to docu-
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ment the most important anatomic columns. Flexion instability was predicted best by posterior column injury, although the statistical significance was relatively low (p = 0.08). This finding was consistent with the anatomic structural regression model as both ISS and LF are part of the posterior column. Extension instability correlated best with anterior column injury. The anterior column was particularly important as a supporting tension structure. Similarly, axial rotation instability correlated best with anterior column injury. The anterior column was shown by Haher and associates (12) to be most significant in affecting the axial rotational stability of the thoracolumbar spine. Lateral bending instability also correlated best with anterior column injury. This was inconsistent with the anatomic structure correlations that found that the most significant structure was the PDE, part of the middle column. This demonstrates the lack of a clear message concerning lateral bending instability in this sagittal plane trauma model. Studies using more complex impact load vectors (including axial rotation and lateral bending trauma modes) should provide additional insight into the structures and columns affecting lateral bending instability. Anatomic Structures versus Anatomic Columns The percentage of variance in the multidirectional instabilities explained by the anatomic columns was generally less than that explained by the individual anatomic structures. For flexion instability, the anatomic structures accounted for 69% of the variance, compared with 25% for the columns. Similarly, for extension instability, the anatomic structures explained 53%, compared with 25% for the columns. For lateral bending, the individual structures accounted for 54% of the variance, compared with 34%for the columns. The two methods of analysis were approximately equal in predicting axial rotation instability, with the structures explaining 53% of the variance and the columns explaining 54%. If one wants to estimate the biomechanical instability of a spine, it seems that knowledge of the individual anatomic structural injuries is superior to an assessment of injury to each anatomic column. This result does not imply that a column concept such as that proposed by Denis is an ineffective method of assessing clinical spinal instability. As described by White and Panjabi (29), clinical instability includes several factors besides abnormal mo-
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tions, such as neurological deficit, pain, and deformity, both acute and chronic. In the present study, only the excessive motion component of the clinical instability was considered. A major focus of the three-column concept of Denis (8) is the potential neurologic consequences of middle column injuries. The middle column injuries reported herein had the lowest correlation coefficients to each of the biomechanical instabilities. This finding suggests that the middle column is not of great importance to biomechanical instability. However, injury to the middle column may be the most important determinant for clinical instability, due to the proximity of this column to the spinal cord and nerve roots. CONCLUSIONS
Flexion instability correlates best with injury to the interspinous/supraspinous ligaments and the ligamentum flavum. Extension instability correlates best with injury to the anterior longitudinal ligament and pedicles. Axial rotation correlates best with injury to the anterior d i d e n d plate and capsular ligaments. Lateral bending instability correlates best with injury to the posterior disc/end plate. Knowledge of injuries to specific anatomic structures, as compared with specific anatomic columns, is a better predictor of flexion, extension, and lateral bending instabilities of the spine. Acknowledgment: Support was provided in part by National Institute of Health grants AR30361 and AR39209 and Public Health Service Centers for Disease Control grant R49KCR103551.
REFERENCES I. Allan DG, Russell GG, Moreau MJ, Rasso VJ, Budney D: Short communication: Vertebral endplate failure in porcine and bovine models of spinal fracture instrumentation. J Orthop Res 8:154-156, 1990 2. Allen BL Jr, Ferguson RL, Lehmann TR, O’Brien RP: A mechanistic classification of closed, indirect fractures and dislocations of the lower cervical spine. Spine 7:l-27, 1982 3. Aufdermaur M: Spinal injuries in juveniles. Necropsy findings in twelve cases. J Bone Joint Surg 56-B:S13-519, 1974 4. Bohlman HH: Acute fractures and dislocations of the cervical spine. An analysis of three hundred hospitalized patients and review of the literature. J Bone Joint Surg 61-A: I1 19-1 142, 1979 5 . Burke DC: Hyperextension injuries of the spine. J Bone Joint Surg 53-B:3-12, 1971 6. Cotterill PC, Kostuik JP, D’Angelo G, Fernie GR, Maki BE: An anatomical comparison of the human and bovine thoracolumbar spine. J Orthop Res 4:298-303, 1986 7. Davis D, Bohlman H, Walker AE, Fisher R, Robinson R: The pathological findings in fatal craniospinal injuries. J Neurosurg 34:603413, 1971
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8. Denis F: The three column spine and its significance in the classification of acute thoracolumbar spin4 injuries. Spine 8:8174331, 1983 9. Draper NR, Smith H: Applied Regression Analysis. 2nd ed. New York, John Wiley & Sons, 1981, pp 294-313, 505-513 10. Edelson JG, Nathan H: Stages in the natural history of the vertebral end-plate. Spine 13(1):21-26, 1988 11. Forsyth HF: Extension injuries of the cervical spine. J Bone Joint Surg 46-A: 1792-1797, 1964 12. Haher TR, Felmy W, Baruch H, Devlin V, Welin D, O’Brien M, Ahmad J, Valenza J, Parish S: The contribution of the three columns of the spine to rotational stability. A biomechanical model. Spine 14:663-669, 1989 13. Halliday DR, Sullivan CR, Hollinshead WH, Bahn RC: Tom cervical ligaments: Necropsy examination of the normal cervical region of the spinal column. J Trauma 4:219-232, 1964 14. Hams WH, Hamblen DL, Ojemann RG: Traumatic disruption of cervical intervertebral disk from hyperextension injury. Clin Orthop 60:163-167, 1968 15. Hodgson VR, Thomas LM: Mechanisms of cervical spine injury during impact to the protected head. 24th Stapp Car Crash Conference, SAE Technical Paper 801300, 1980, pp 1742 16. Holdsworth F: Fractures, dislocations, and fracture-dislocations of the spine. J Bone Joint Surg 52-A:1534-1551, 1970 17. Marar BC: Hyperextension injuries of the cervical spine. The pathogenesis of damage to the spinal cord. J Bone Joint Surg 56-A: 1655-1662, 1974 18. Nusholtz GS, Melvin JW, Huelke DF, Alem NM, Blank JG: Response of the cervical spine to superior-inferior head impact. 27th Stapp Car Crash Conference, SAE Technical Paper 811005, 1983, pp 197-237 19. Panjabi MM, White, AA, Johnson RM: Cervical spine mechanics as a function of transection of components. J Biomech 8:327-336, 1975 20. Panjabi MM, Duranceau JS, Oxland TR, Bowen CE: Multidirectional instabilities of traumatic cervical spine injuries in a porcine model. Spine 14: 1I1 1-1 115, 1989 21. Panjabi M, Oxland T, Parks E: Quantitative anatomy of cervical spine ligaments. 11. Middle and lower cervical spine. J Spin Disord (submitted) 22. Posner I, White A, Edwards T, Hayes W: A biomechanical analysis of the clinical stability of the lumbar and lumbosacral spine. Spine 7(4):374-389, 1982 23. Rauschning W, McAfee PC, Jonsson H Jr: Pathoanatomical and surgical findings in cervical spinal injuries. J Spin Disord 21213-222, 1989 24. Schaeffer DM, Flanders A, Northrup BE, Doan HT, Osterholm JL: Magnetic resonance imaging of acute cervical spine trauma. Correlation with severity of neurologic injury. Spine 14:1090-1095, 1989 25. Southern EP, Oxland TR, Panjabi MM, Duranceau JS: Cervical spine injury patterns in three modes of high speed trauma: A biomechanical porcine model. J Spin Disord 3:316-328, 1990 26. Stauffer ES, Kelly EG: Fracture-dislocations of the cervical spine. Instability and recurrent deformity following treatment by anterior interbody fusion. J Bone Joint Surg 59A(1):4548, 1977 27. Taylor AR, Blackwood W: Paraplegia in hyperextension cervical injuries with normal radiographic appearances. J Bone Joint Surg 30-B(2):245-248, 1948 28. White AA, Southwick WO, Panjabi MM: Clinical instability in the lower cervical spine: A review of past and current concepts. Spine 1:15-27, 1976 29. White AA, Panjabi MM: Clinical Biomechanics of the Spine. 2nd ed. Philadelphia, JB Lippincott, 1990
An Anatomic Basis for Spinal Instability: A Porcine Trauma Model T. R. Oxland, M. M. Panjabi, E. P. Southern, and J. S. Duranceau Biomechanics Laboratory, Department of Orthopaedics and Rehabilitation, Yale University School of Medicine, New Haven, Connecticut, U.S.A.
Summary: To determine the anatomic basis for spinal instabilities, 16 porcine cervical spine specimens were subjected to a well-defined sagittal plane trauma. The multidirectional instability of each specimen was measured before and after trauma. Detailed anatomic dissections were performed on each traumatized specimen to quantitate the extent of injury to several distinct anatomic structures and columns. Multiple regression models were constructed to determine which anatomic structures and columns correlated best with each multidirectional instability. Flexion instability correlated best with injury to the interspinous/supraspinous ligaments and the ligamentum flavum. Extension instability correlated best with anterior longitudinal ligament and pedicle injury. Axial rotation instability correlated best with anterior disc-end-plate and capsular ligament injuries, while lateral bending instability correlated best with posterior disc-end-plate injuries. Anterior column injuries correlated best with extension, axial rotation, and lateral bending instabilities, while posterior column injuries correlated best with flexion instability. Finally, individual anatomic structural injuries had higher correlations with multidirectional instabilities than did the injuries defined by the anatomic columns. Key Words: Spinal injuries-Trauma biomechanics-Spinal instabilities.
ture, and the quality of the tissues under stress (15,18). To the clinician, these injuries present a significant diagnostic problem. The final diagnosis must assess the stability or instability of the spine. In reaching an assessment of the instability, the clinician first hypothesizes which anatomic structures are injured, using a variety of available imaging techniques. Based on this anatomic injury information, the instability of the spine is assessed, and the appropriate treatment is chosen. The classification of a spinal injury as stable or unstable is often based on retrospective clinical studies and subjective clinical judgment, but with little supporting experimental data. One method, as described by Denis (8), evaluates the structural in-
High-speed traumatic injuries to the spine are a great economic cost to society and a tremendous physical burden to the patient. These injuries have been well documented and include various combinations of vertebral fractures, dislocations, ligament stretch or rupture, and intervertebral disc/ end-plate lesions (4,16,23). Which anatomic structures are damaged in trauma depends on many factors that include the load magnitude, direction and point of application, loading rate, spinal pos-
Received June 7, 1990; accepted November 8, 1990. Address correspondence and reprint requests to T. Oxland at Biomechanics Laboratory, Department of Orthopaedics and Rehabilitation, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, U.S.A.
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tegrity of each of the three anatomic columns. The method was derived from extensive study of clinical cases and is used for the evaluation of thoracolumbar injuries. Concerning the evaluation of cervical spine injuries, a checklist has been proposed to determine spinal instability in a clinical setting (28). The method incorporates biomechanically derived parameters, neurological assessment, and other clinical factors. Biomechanical studies provide the thresholds of physiological motions and conclude that the cervical spine becomes mechanically unstable if either all posterior elements plus an additional anterior component or all anterior elements plus one posterior component are destroyed or rendered nonfunctional (19). Similar component transection studies have been performed in the lumbar spine (22). However, in these studies, the injuries were produced by transecting structures sequentially using a scalpel. In real-life trauma, it may be expected that many different combinations of anatomic structures are injured. In such traumatic injuries, it is important to document the anatomic injuries and the resulting multidirectional instabilities. The purpose of this study was to determine which anatomic injuries, produced by experimental highspeed trauma, correlate best with the multidirectional instabilities in an in vitro porcine cervical spine model. In addition, the correlation of the instabilities with each of the three anatomic columns was determined. MATERIALS AND METHODS Experimental Overview The experimental procedure consisted of several steps. Each specimen was tested to determine its intact, three-dimensional physiological motions. This is referred to as the instability test. Following this test, the specimen was subjected to one of three high-speed trauma modes in the sagittal plane. To describe the injury objectively, the specimen was reevaluated by the instability test. The final step involved a detailed anatomic dissection of each specimen to document all observable injuries. Specimen Preparation Sixteen freshly frozen, porcine cervical spine segments (two C5-C7, 14 C2-C4) were used in this study. The animals were male and female, 1-1.5 years old, sexually mature but not full weight (55-70
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kg). The specimens were dissected of all nonligamentous soft tissue. The top and bottom vertebrae were mounted in polyester resin molds, with their body centroids (i.e., the point where body diagonals intersect) vertically aligned. The specimens were stored in plastic bags at -20°C until tested.
Porcine Vertebral Anatomy Since this article concerns anatomic lesions, a familiarity with the pig cervical spine is imperative. Axial and lateral radiographs of a typical pig cervical vertebra are shown in Fig. 1 along with human cervical and lumbar vertebrae. The porcine cervical vertebra is larger than the human cervical vertebra but smaller than the human lumbar vertebra. The processes in the pig that extend anterolaterally do not appear to have a significant mechanical role. The pig articular facets are oriented vertically in a manner similar to the human lumbar vertebra. The pig vertebral body and spinous process have a shape more similar to the human lumbar than the human cervical vertebra. Another similarity with the human lumbar vertebra is the consistency of the posterior interspinous-supraspinous ligaments, which is in contrast to their relatively insignificant role in the human cervical spine (13,21). Of particular note in the axial radiograph of the pig vertebra in Fig. 1 are the ossification centers in the middle of the vertebral body. This is representative of a child’s or adolescent’s spine (lo), which is consistent with the fact, noted earlier, that these pigs are not at full adult weight. Therefore, this porcine cervical vertebral model appears to be most similar to the lumbar spine of a human adolescent. Instability Test In preparation for this test, a marker containing three metal balls was attached to the top vertebral mount. No markers were attached to the middle vertebra so as not to damage it. Six pure moments (flexion, extension, rightlleft lateral bending, and rightlleft axial rotation) were applied individually to the upper mount. Each moment was applied stepwise in four equal increments to a maximum of 3.6 Nm. At each load step, the specimen was allowed to creep for 30 s . Three load-unload cycles were performed, and stereophotographs of the vertebral marker were taken on the third load cycle. The stereophotographs were digitized, and the threedimensional coordinates of each marker point were
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FIG. 1. Axial and lateral radiographic comDarisons of a human cervical vertebra (left), a porcine cervical vertebra (center), and a human lumbar vertebra (right).
determined. The three-dimensional kinematics of the top vertebra with respect to the bottom vertebra were calculated using appropriate computer software. For all six degrees of freedom, motion parameters of neutral zone (NZ) and range of motion (ROM) were determined. High-speed Trauma Production
A specially designed apparatus was constructed to produce the traumatic injuries. The injury-producing component was a free-falling mass that descended through a Plexiglas cylinder to hit the specimen. The mass was 14.5 kg and was dropped from a height of 1.1 m. To apply different load vectors to the specimen, a cylinder (2.5 cm in diameter) was attached to the superior surface of the top mount. To produce pure compression loading, the cylinder was placed directly above the geometric center of the top vertebral body. For flexion-compression or extension-compression trauma modes, the cylinder was translated 1 cm anteriorly or posteriorly, respectively, from the center position. The specimens were distributed among the three different trauma modes. In this paper, the results for all three trauma modes were pooled. A high-speed movie camera monitored the specimen deformations during the trauma at 1,000 frame&. The loads of axial compression, anteriorposterior shear force, and sagittal plane bending
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moments were measured by a load cell placed beneath the specimen and recorded by a microcomputer at 3,000 reading& Anatomic Dissections
After the high-speed trauma and instability measurements, each specimen was subjected to a meticulous anatomic dissection, with the purpose of quantifying the specimen injury., This dissection involved three parts. First, the anatomic components on the exterior of the specimen were described: anterior longitudinal ligament (ALL), intertransverse ligament (ITL), interspinous and supraspinous ligaments (ISS), facet capsular ligaments (CAP), pedicles (PED), and lamina and spinous processes (SPL). Next, the pedicles were cut in the frontal plane such that structures inside the spinal canal were observable, these being the posterior longitudinal ligament (PLL), ligamentum flavum (LF), and facet articular processes (FAC). To determine the integrity of the end plate/disc/end plate, the disc was injected with a dye to a maximum pressure of 250 kPa (40 psi) or a maximum volume of 1 ml. Finally, the vertebral bodies and intervertebral discs were cut in the midsagittal plane. Since the specimens used in this study were three-vertebrae segments, the anatomic structures mentioned above were located at three vertebral levels and two intervertebral levels, with each substructure being re-
ANATOMIC BASIS FOR SPINAL INSTABILITY
ferred to as an anatomic component. A graphic representation of the anatomic structures studied is shown in Fig. 2. Injury Grading To obtain quantitative injury scores for each anatomic structure or column from the injury descriptions, the basic principle that two or more anatomic components form an anatomic structure, and two or more anatomic structures form an anatomic column, was used. Furthermore, the injury score of an anatomic structure or an anatomic column was obtained simply by adding together the injury scores of the anatomic components. For example, the anterior vertebral body (AVB) anatomic structure consisted of three anatomic components, one from each of the three vertebral bodies (i.e., AVB V1, AVB V2, AVB V3). In a similar manner, for example, the anterior column consisted of the anatomic structures ALL, AVB, and anterior disdend plate (ADE). Using this scheme, the entire specimen was divided into 13 anatomic structures (Fig. 2). Each anatomic component was assigned an injury score on a scale of 0 to 2: 0, 1, or 2 representing intact, partial injury, or complete injury, respectively. Since each anatomic structure was graded as
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the sum of its anatomic components, the maximum injury score for an anatomic structure was the number of anatomic components making up the structure multiplied by 2. As an example, the ISS structure was assigned an injury score of 0, 1, or 2 for each of its components (i.e., top and bottom levels). Its subsequent anatomic structure score was the sum of these component injury scores on a scale of 0 to 4. As described earlier, the anatomic column injury scores were determined by adding the injury scores from the anatomic structures. Since the injury scale for each anatomic structure was dependent on the number of anatomic components of the structure, the anatomic structural injury scores were normalized such that the most severe injury observed for each structure had an injury score of 10. The most severe injuries observed in this study were ALL, PLL, ITL, LF, and ISS complete rupture at one level; CAP complete rupture at both levels (left and right); AVB, ADE, posterior vertebral body (PVB), and posterior disc-end plate (PDE) fractures in two of three vertebrae or disc/end plates; PED, SPL fracture at level 1; and FAC fracture of two articular facets. The normalized anatomic structural injury scores were added together to determine each anatomic column injury score. The anatomic column injury scores were normalized further (maximum value of 10) to allow comparison of the injury magnitudes among the anterior, middle, and posterior columns. Statistical Analysis
FIG. 2. Pictorial representation of the anatomic structures that make up the porcine spine. ALL, anterior longitudinal ligament; AVB, anterior vertebral body; ADE, anterior disc/ end plate; PVB, posterior vertebral body; PDE, posterior disc/ end plate; PLL, posterior longitudinal ligament; ITL, intertransverse ligament (not shown); PED, pedicle; FAC, articular facet; CAP, capsular ligaments, LF, ligamentum flavum; SPL, spinous process/lamina; ISS, interspinous/supraspinous ligaments.
As stated earlier, the goal of this study was to determine which anatomic structures correlated best with various multidirectional instabilities in this porcine trauma model. Statistically, such determination requires a multivariate analysis that selects the anatomic variables that correlate with each instability (i.e., those that explain the greatest amount of variance in the instability). This analysis is best done by multiple regression. However, a trade-off exists between explaining the greatest percentage of variance in the dependent variable and using the fewest number of independent variables in the analysis. Ideally, few independent variables would explain most of the variance in the dependent variable, but this is not always true. Alternatively, one could perform a regression for all possible combinations of independent variables, but this method is usually not feasible. A better method to deter-
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mine the appropriate regression equation is stepwise regression (9). In this method, independent variables are entered into the equation if they possess a correlation with the dependent variable above a certain user-specified significance level. In this study, a significance level of 5% was used. It is important to realize that this significance level refers to the slope of the last variable entered into the regression and that the significance of the entire equation was generally much higher. To understand the correlations between the injuries to specific anatomic structures and the multidirectional instabilities, simple pairwise productmoment correlations were calculated for all combinations of anatomic structures and instabilities. Following this analysis, a multiple regression was performed for each instability to determine which combination of anatomic structural injuries correlated best with each instability. These steps of calculating the simple correlation matrix followed by multiple regressions were repeated to determine the relationships between the anatomic column injuries and each instability. RESULTS In this study, the multidirectional instabilities were defined as the ratios of the injured to intact ROMs in flexion, extension, lateral bending (average of right and left), and axial rotation (average of right and left). Correlations of Instabilities with Anatomic Structures Simple correlation coefficients between all anatomic structural injuries and multidirectional instabilities were calculated. Values of l, 0, and - l indicate 100% positive correlation, no correlation, and 100% negative correlation, respectively. The anatomic structures that had the highest correlation coefficients relative to the multidirectional instabilities were flexion (ISS: 0.74, LF: 0.57), extension (ALL: 0.65, PED: 0.56), axial rotation (ADE: 0.76, CAP: 0.74, PDE: 0.69, ALL: 0.67), and lateral bending (PDE: 0.73, CAP: 0.62, ADE: 0.59). Multiple regressions were performed to determine which group of anatomic structures best explained the variation in each of the instabilities. The results of these regressions are shown in Figs. 3-6 for flexion, extension, axial rotation, and lateral
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bending instabilities, respectively. Injuries to the ISS correlated best with flexion instability. In addition, LF injuries were entered into the regression model as shown in Fig 3. Together, the two anatomic variables explained 69% of the variation in flexion instability (p = .003). For extension instability, ALL had the highest Correlation. PED was the next variable entered into the multiple regression equation (Fig. 4). Both variables together accounted for 53% of the variation in extension instability (p = .016). For the axial rotation instability, ADE injuries had the greatest correlation, explaining approximately 57% of axial rotation instability (p = .001). This was the only anatomic structure entered into the regression model (Fig. 5). Injuries to the PDE had the highest correlation with lateral bending instability. PDE was the only anatomic structure entered into the regression model, accounting for 54% of the variance in lateral bending instability (p = .002) (Fig. 6). Correlations of Instabilities with the Anatomic Columns In a manner analogous to the anatomic structures, the anatomic column analysis was done by first determining a simple correlation followed by multiple regression. The anatomic columns that had the highest simple correlation coefficients with the instabilities were flexion (posterior: O S O ) , extension (anterior: 0.64, posterior: 0.58), axial rotation (anterior: 0.73, posterior: 0.67), and lateral bending (anterior: 0.58, posterior: 0.52). For the multiple regressions, only one anatomic column was entered into each regression model. Obviously, that column was the one with the highest simple correlation with each instability. The posterior column had the highest correlation with flexion instability, explaining only 25% of the variance in the injured motion (p = .08). The anterior column had the highest correlation with extension instability, accounting for 25% of the variance in extension instability (p = .Ol). The anterior column had the greatest correlation with axial rotation instability, explaining 54% of the variance in the instability (p = .001). For the lateral bending instability, only the anterior column was entered into the equation. It explained 34% of the variance in the instability (p = .02).
ANATOMIC BASIS FOR SPINAL INSTABILITY
Regression
R 2D
Model
Flexion Instability = 0.09 (ISS)
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+ 0.09 (LF) +
0.92
0.69
0.003
FIG. 3. Pictorial representation of the anatomic structures that correlated with flexion instability.
DISCUSSION
In this study, the anatomic injuries Produced in a high-speed trauma model were correlated to the resultant multidirectional instabiiities. Tie approach was unique in that the injuries produced by three well-defined sagittal plane load vectors were not predetermined. This was in contrast to previous studies, in which the anatomic structures were transected sequentially and their effect on the instability measured. Several different injury combinations resulted from approximately identical impact loads. In these cases, the variation in the injuries was probably due to the variability in the failure properties of the different spinal tissues of the sample studied. Limitations of the Study
A porcine cervical spine model was used; its similar anatomic appearance to the human lumbar spine was described earlier (Fig. 1). We are pres-
ently conducting investigations to compare its biomechanical characteristics to that of the human spine in vitro. Other researchers have used bovine spines in a trauma model (6). However, we ob. . served a relatively immature veneDrai p*hYSEmth~ bovine spine, which is in agreement with the recent findings of Allan and colleagues (1). They have suggested that a porcine spine is a better model for trauma studies. To quantify the anatomic injuries of each spine, a subjective injury grade on a scale of 0-2 was assigned to each individual anatomic component (e.g., capsular ligament of the upper left intervertebra1joint). This type of discrete injury-grading may suggest a nonparametric form of data analysis. However, since we divided each anatomic structure into several discrete anatomic components, we obtained a relatively wide injury scale for each anatomic structure. As a result, the parametric type of data analysis, as used herein, was valid. The number of specimens is of critical importance in any study for which a multiple regression
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Anterior Longitudinal Ligament
Regression
R 2D
Model
Extension Instability = 0.07 (ALL)
+ 0.06 (PED) +
1.5
0.53
0.016
FIG. 4. Pictorial representation of the anatomic structures that correlated with extension instability.
model is constructed. If too many independent variables are allowed into the equation, one may arrive at a model that has very little physical significance. A well-accepted statistical guideline in regression model-building is to introduce approximately one variable for every 10 specimens (S. Walter, personal communication). Since we used 16 specimens in this study, the number of independent variables allowed into each regression model was limited to two. Relevance of Anatomic Injuries Produced
To ascertain the relevance of our trauma model to the human condition, several studies that documented pathoanatomical injuries were reviewed. (3-5,7,11,14,17,23,26,27). Although the injury mechanisms in these studies were speculative, typical spinal injuries were well documented. In the present study, the flexion and extension
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trauma produced distinctive lesions, as documented by Southern and associates (25), while compression alone resulted in less severe injuries. In flexion trauma, the greatest injuries were to the posterior ligamentous complex. These injuries were similar to the injuries described by Allen and co-workers (2) in his distractive flexion group and by Davis and colleagues (7) in their autopsy series. In extension trauma, typical failure was an “opening up” of the vertebral d i d e n d plate, possibly due to an immature epiphyseal plate. The appearance of the end plate was similar to that shown by Edelson and Nathan (10) for a typical adolescent. In addition, this injury has been described by Taylor and Blackwood (27), Marar (17), Harris and associates (14) and Aufdermaur (3), among others. Regression Model as a Predictor of Instability One potential use for these types of regression equations is predicting multidirectional instabilities.
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Anterior Disc/ End -Plate
-
ession
R
Model
Axial Rotation Instability = 0.28 (ADE)
+
1.68
2
0.57
r
> 0.001
FIG. 5. Pictorial representation of the anatomic structures that correlated with axial rotation instability.
As stated earlier, all anatomic structures used in the analysis were normalized such that the most severe injuries had a value of 10. If the anatomic structure in question was injured severely, as described, the anatomic injury score would be 10. To predict flexion instability, for example, if the ISS was completely ruptured at one intervertebrallevel while the LF remained intact, the predicted flexion instability ratio would be 1.82 [0.09 (10) + 0.09 (0) + 0.92 = 1.82, Fig. 31. Since spinal instability is a nonlinear phenomenon, we cannot extrapolate the regression models for injuries more severe than those described.
Flexion Instability
Injuries to the ISS and the LF were included in the multiple regression equation for flexion instability. Using biomechanical principles, since the cen-
ter of rotation is in the region of the intervertebral disc, as described by White and Panjabi (29), both these ligamentous structures would be loaded in tension under flexion moments. Therefore, it was expected that they would provide the greatest stability under applied flexion moments. As described earlier, one can estimate the flexion instability that would result from injury to the ISS and LF. Total rupture of the ISS at one vertebral level would increase motion 90% over the intact level, while complete injury to both the ISS and the LF at a single level would result in flexion motion of 180% over the intact motion. This type of analysis does not imply that other anatomic structures do not contribute to flexion instability, but rather that they do not linearly correlate with the instability as well as the ISS or the LF injuries. For example, in many specimens with LF injury, the CAP were also disrupted, causing severe instability. However, in
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---
q-
---
Posterior Disc/ End-Plate
Pegression
2
R r ,
M o d e1
Lateral Bending Instability = 0.06 (PDE)
+
1.07
0.54
0.002
FIG. 6. Pictorial representation of the anatomic structures that correlated with lateral bending instability.
other specimens, the CAP were injured without the LF injury, and the resultant instability was much lower, implying that the LF injury had a greater effect on flexion instability. The regression equation suggests that the flexion instability may be estimated best by looking at the injuries sustained by the ISS and LF structures.
cur under the same load. The regression coeficients for these anatomic structures were such that if each were damaged (i.e., ALL rupture and PED fracture), the extension rotation would increase 130% over the intact levels (70% ALL and 60% PED, Fig. 4). Axial Rotation Instability
Extension Instability
The ALL and PED were included in the multiple regression equation for extension instability. Again, a reasonable biomechanical explanation may be provided. The ALL was correlated most with this instability because of its important role as a tension structure in extension moments. Next were the PED, which carry bending loads between the anterior and posterior structures. With some anterior structures damaged, the posterior elements and pedicles would support the extension moment. If the pedicles were damaged, more motion would oc-
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Only the ADE was entered into the multiple regression equation for the axial rotation instability. That it was the only factor was rather surprising, since there were four anatomic structures that had simple correlations greater than 0.60 (CAP: 0.74, PDE: 0.69, ALL: 0.67). The reason for the absence of any of these structures from the regression model was their relatively high intercorrelation with the ADE, the first variable entered into the equation (CAP: 0.82, PDE: 0.74, ALL: 0.64). This finding implies that specimens with ADE injury have a high probability for associated injuries to the CAP, PDE,
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and ALL. The ADE had a highly significant correlation, suggesting that loss of its torsional resistance directly affected the rotational stability of the spine. This was consistent with the results presented by White and Panjabi (29), who found that the axial center of rotation was located within the intervertebral disc, so damage to anterior components would result in excessive motion increases. In addition, Haher and colleagues (12) documented that anterior soft-tissue structures were most important in maintaining rotational stability in the thoracolumbar spine. Although not included in the regression model, the CAP had a high simple correlation, which identified these ligaments as important structures in providing rotational stability to the spine. The regression coefficients for the ADE were such that damage at all levels would increase motion by approximately 280% over intact levels. Lateral Bending Instability
The correlation of lateral bending instability was best with the PDE, and it was the only anatomic structure entered into the regression equation. The lateral bending instability was much less than that of flexion, extension, or axial rotation, as documented by Panjabi and co-workers (20). By observing the regression coefficients, if the PDE were severely injured (i-e., two end-plate fractures), the motion after injury would be approximately 60% greater than the intact rotation. Contrast this to the motion increases in flexion, extension, and axial rotation of 180, 130, and 280%, respectively, if the structures included in their regression models were all severely injured. The concept of estimating multidirectional instabilities from known anatomic injuries has interesting clinical implications. With the advent of improved diagnostic techniques (CT scan, magnetic resonance imaging), a clinician can assess the anatomic damage to a trauma patient much more accurately than in the past, especially for soft-tissue injuries (24). Eventually, if the injury status of each anatomic component can be determined, it may be possible to estimate each multidirectional instability and thus contribute to the choice of treatment. Anatomic Column Correlations The multiple regression equations included only one anatomic column for each instability. Therefore, simple correlations were sufficient to docu-
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ment the most important anatomic columns. Flexion instability was predicted best by posterior column injury, although the statistical significance was relatively low (p = 0.08). This finding was consistent with the anatomic structural regression model as both ISS and LF are part of the posterior column. Extension instability correlated best with anterior column injury. The anterior column was particularly important as a supporting tension structure. Similarly, axial rotation instability correlated best with anterior column injury. The anterior column was shown by Haher and associates (12) to be most significant in affecting the axial rotational stability of the thoracolumbar spine. Lateral bending instability also correlated best with anterior column injury. This was inconsistent with the anatomic structure correlations that found that the most significant structure was the PDE, part of the middle column. This demonstrates the lack of a clear message concerning lateral bending instability in this sagittal plane trauma model. Studies using more complex impact load vectors (including axial rotation and lateral bending trauma modes) should provide additional insight into the structures and columns affecting lateral bending instability. Anatomic Structures versus Anatomic Columns The percentage of variance in the multidirectional instabilities explained by the anatomic columns was generally less than that explained by the individual anatomic structures. For flexion instability, the anatomic structures accounted for 69% of the variance, compared with 25% for the columns. Similarly, for extension instability, the anatomic structures explained 53%, compared with 25% for the columns. For lateral bending, the individual structures accounted for 54% of the variance, compared with 34%for the columns. The two methods of analysis were approximately equal in predicting axial rotation instability, with the structures explaining 53% of the variance and the columns explaining 54%. If one wants to estimate the biomechanical instability of a spine, it seems that knowledge of the individual anatomic structural injuries is superior to an assessment of injury to each anatomic column. This result does not imply that a column concept such as that proposed by Denis is an ineffective method of assessing clinical spinal instability. As described by White and Panjabi (29), clinical instability includes several factors besides abnormal mo-
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tions, such as neurological deficit, pain, and deformity, both acute and chronic. In the present study, only the excessive motion component of the clinical instability was considered. A major focus of the three-column concept of Denis (8) is the potential neurologic consequences of middle column injuries. The middle column injuries reported herein had the lowest correlation coefficients to each of the biomechanical instabilities. This finding suggests that the middle column is not of great importance to biomechanical instability. However, injury to the middle column may be the most important determinant for clinical instability, due to the proximity of this column to the spinal cord and nerve roots. CONCLUSIONS
Flexion instability correlates best with injury to the interspinous/supraspinous ligaments and the ligamentum flavum. Extension instability correlates best with injury to the anterior longitudinal ligament and pedicles. Axial rotation correlates best with injury to the anterior d i d e n d plate and capsular ligaments. Lateral bending instability correlates best with injury to the posterior disc/end plate. Knowledge of injuries to specific anatomic structures, as compared with specific anatomic columns, is a better predictor of flexion, extension, and lateral bending instabilities of the spine. Acknowledgment: Support was provided in part by National Institute of Health grants AR30361 and AR39209 and Public Health Service Centers for Disease Control grant R49KCR103551.
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