Association Between Lateral Posterior Tibial Slope, Body Mass Index, and ACL Injury Risk

Abstract

Background:
While body mass index (BMI), a modifiable parameter, and knee morphology, a nonmodifiable parameter, have been identified as risk factors for anterior cruciate ligament (ACL) rupture, the interaction between them remains unknown. An understanding of this interaction is important because greater compressive axial force (perhaps due to greater BMI) applied to a knee that is already at an increased risk because of its geometry, such as a steep lateral posterior tibial slope, could further increase the probability of ACL injury.

Purpose:
To quantify the relationship between BMI and select knee morphological parameters as potential risk factors for ACL injury.

Study design:
Case-control study; Level of evidence, 3.

Methods:
Sagittal knee magnetic resonance imaging (MRI) files from 76 ACL-injured and 42 uninjured subjects were gathered from the University of Michigan Health System's archive. The posterior tibial slope (PTS), middle cartilage slope (MCS), posterior meniscus height (PMH), and posterior meniscus bone angle (MBA) in the lateral compartment were measured using MRI. BMI was calculated from demographic data. The association between the knee structural factors, BMI, and ACL injury risk was explored using univariate and multivariate logistic regression.

Results:
PTS (P = .043) and MCS (P = .037) significantly predicted ACL injury risk. As PTS and MCS increased by 1°, odds of sustaining an ACL injury increased by 12% and 13%, respectively. The multivariate logistic regression analysis, which included PTS, BMI centered around the mean (cBMI), and their interaction, showed that this interaction predicted the odds of ACL rupture (P = .050; odds ratio, 1.03). For every 1-unit increase in BMI from the average that is combined with a 1° increase in PTS, the odds of an ACL tear increased by 15%.

Conclusion:
An increase in BMI was associated with increased risk of ACL tear in the presence of increased lateral posterior tibial slope. Larger values of PTS or MCS were associated with an increased risk of ACL tear.

Full text

Original Research
Association Between Lateral Posterior Tibial
Slope, Body Mass Index, and ACL Injury Risk
Katherine M. Bojicic,*
†
BS, Me
´lanie L. Beaulieu,
‡
PhD, Daniel Y. Imaizumi Krieger,
§
MSE,
James A. Ashton-Miller,
§||
PhD, and Edward M. Wojtys,
{
MD
Investigation performed at the University of Michigan, MedSport, Ann Arbor, Michigan, USA
Background: While body mass index (BMI), a modifiable parameter, and knee morphology, a nonmodifiable parameter, have been
identified as risk factors for anterior cruciate ligament (ACL) rupture, the interaction between them remains unknown. An understanding of
this interaction is important because greater compressive axial force (perhaps due to greater BMI) applied to a knee thatis alreadyat an
increased risk because of its geometry, such as a steep lateral posterior tibial slope, could further increase the probability of ACL injury.
Purpose: To quantify the relationship between BMI and select knee morphological parameters as potential risk factors for ACL
injury.
Study Design: Case-control study; Level of evidence, 3.
Methods: Sagittal knee magnetic resonance imaging (MRI) files from 76 ACL-injured and 42 uninjured subjects were gathered from
the University of Michigan Health System’s archive. The posterior tibial slope (PTS), middle cartilage slope (MCS), posterior
meniscus height (PMH), and posterior meniscus bone angle (MBA) in the lateral compartment were measured using MRI. BMI was
calculated from demographic data. The association between the knee structural factors, BMI, and ACL injury risk was explored
using univariate and multivariate logistic regression.
Results: PTS (P¼.043) and MCS (P¼.037) significantly predicted ACL injury risk. As PTS and MCS increased by 1, odds of
sustaining an ACL injury increased by 12% and 13%, respectively. The multivariate logistic regression analysis, which included
PTS, BMI centered around the mean (cBMI), and their interaction, showed that this interaction predicted the odds of ACL rupture
(P¼.050; odds ratio, 1.03). For every 1-unit increase in BMI from the average that is combined with a 1increase in PTS, the odds
of an ACL tear increased by 15%.
Conclusion: An increase in BMI was associated with increased risk of ACL tear in the presence of increased lateral posterior tibial
slope. Larger values of PTS or MCS were associated with an increased risk of ACL tear.
Keywords: knee; ligament; ACL; BMI; anatomy; injury prevention
Anterior cruciate ligament (ACL) tears are debilitating,
especially for athletes and physically active individuals.
They are burdensome in terms of rehabilitation time,
treatment cost,
4,14
and, most important, an increased risk
of developing osteoarthritis within 10 to 15 years of
injury.
12,15
Injury prevention is the most efficacious inter-
vention strategy.
2
While various intervention programs do
exist, the rate of ACL injury remains significant, as shown
by injury rates in elite collegiate athletes over an 8-year
period (2004-2012) compared with an earlier 16-year
review (1988-2004).
1
Clearly, improving currently avail-
able intervention programs is a worthy goal.
7,20
Novel intervention strategies depend on the accurate
identification of risk factors, both modifiable and nonmodi-
fiable. Knowledge of nonmodifiable risk factors is impor-
tant for patients, athletes, clinicians, and coaches, but of
greater importance are those risk factors that can be
modified. Such factors may have the greatest potential for
*Address correspondence to Katherine M. Bojicic, Medical School,
University of Michigan, 41462 Strawberry Court, Canton, MI 48188, USA
(email: thompkat@umich.edu).
†
Medical School, University of Michigan, Ann Arbor, Michigan, USA.
‡
Department of Radiology, Universityof Michigan, Ann Arbor, Michigan,
USA.
§
Department of Mechanical Engineering, University of Michigan, Ann
Arbor, Michigan, USA.
||
Department of Biomedical Engineering, University of Michigan, Ann
Arbor, Michigan, USA.
{
MedSport, Department of Orthopedic Surgery, University of Michigan,
Ann Arbor, Michigan, USA.
One or more of the authorshas declared the following potentialconflict of
interest or source of funding: Funding for this study was provided by United
States Public Health Service grant R01 AR054821 and the University of
Michigan Medical School Student Biomedical Research Program.
Ethical approval for this study was waived by the University of
Michigan Medical School Institutional Review Board.
The Orthopaedic Journal of Sports Medicine, 5(2), 2325967116688664
DOI: 10.1177/2325967116688664
ªThe Author(s) 2017
1
This open-access article is published and distributed under the Creative Commons Attribution - NonCommercial - No Derivatives License (http://creativecommons.org/
licenses/by-nc-nd/3.0/), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are
credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For reprints and permission queries, please visit SAGE’s website at
http://www.sagepub.com/journalsPermissions.nav.

intervention to decrease injury risk. Of particular interest
is the interaction between modifiable and nonmodifiable
risk factors, which remains unknown.
A number of nonmodifiable anatomic ACL injury risk
factors have been identified to date. For example, an
increase in lateral posterior tibial slope (PTS) or middle
cartilage slope (MCS) has been associated with an
increased risk of ACL tear.
3,5,8,9,13,18,22,26
Similarly, a
decrease in the lateral meniscal height in the posterior com-
partment (PMH) can increase the risk of ACL injury in
females while a decrease in meniscal bone angle (MBA) can
increase ACL injury risk in males.
21,22
There is also evi-
dence of a significant positive association between body
mass index (BMI), a measure of weight in relation to
height, and ACL injury risk.
6,16,24
Although the association
between these morphological factors and ACL injury risk
has been studied, how these anatomic factors may interact
with BMI to affect injury risk is unknown.
This interaction between the nonmodifiable knee mor-
phological ACL risk factors and BMI, a modifiable factor,
is also important if one considers how PTS mechanically
increases one’s risk of sustaining an ACL injury. When an
axial compressive force is applied to the knee joint, an ante-
rior shear force and an internal tibial torque is produced
due to mechanical coupling induced by the geometry of the
tibial and femoral surfaces and their mechanical interac-
tion. The posteriorly directed tibial slope causes the axial
compressive force to have an anterior shear force compo-
nent, and the steeper lateral compared with medial tibial
slope
19
produces internal tibial rotation because the axial
force will cause the lateral side of the femur to slide poster-
iorly on the steeper slope of the lateral tibial plateau to a
greater degree than on the medial tibial plateau. It is well
accepted that anterior tibial translation and internal tibial
rotation increases ACL strain and thus ACL injury
risk.
17,25
Therefore, the combination of a greater axial knee
compressive force from greater body weight and/or greater
BMI with a greater lateral posterior tibial slope, all else
being equal, will increase ACL strain and most likely ACL
injury risk. A similar argument can be made for MCS,
PMH, and MBA. A body weight– or BMI-related increase
in compression forces applied to a knee that is already at an
increased risk could further increase the risk of ACL injury.
Consequently, it is of interest to assess the interaction
between BMI and the aforementioned knee morphological
parameters.
The aim of this study, therefore, was to quantify the rela-
tionship between BMI and the 4 selected knee morphologic
parameters, listed above, as potential risk factors for ACL
injury. Based on the mechanical principles considered, we
hypothesized that increased BMI in the presence of
increased PTS or MCS would increase the risk of ACL
injury; likewise, increased BMI in the presence of decreased
PMH or MBA would result in increased risk of ACL injury.
METHODS
A total of 118 knee magnetic resonance image (MRI) series
from 76 subjects with a complete disruption of the ACL
(grade 3) via a noncontact mechanism (36 females,
40 males; mean age, 24.6 ±7.1 years; mean BMI, 26.4 ±
4.1 kg/m
2
) and 42 controls (21 females, 21 males; mean age,
26.5 ±8.3 years; mean BMI, 26.2 ±5.3 kg/m
2
) were obtained
from the University of Michigan Health System. Given that
no patients with partial ACL injury (grades 1-2) were
included in this study, the terms “ACL tear” or “ACL
injury” will henceforth refer to a complete disruption of the
ACL, unless otherwise stated. Subjects were identified via
an institutional review board–exempt, retrospective search
of the University of Michigan Health System’s electronic
health record database that included BMI and demo-
graphic data. Control subjects were chosen based on
absence of ligamentous, meniscal, and articular cartilage
tearing (Table 1) and skeletal maturity (between 15 and
40 years).
The height and weight of the subjects were measured at
the time of their first visit to the University of Michigan
clinics; hence, these measures were not self-reported. They
were used to quantify BMI (weight in kg/height in m
2
).
Sagittal-plane MRIs were obtained using several MRI
systems within the University of Michigan but with the
same clinical protocol for knee imaging. The University of
Michigan Health System’s protocol for knee imaging uti-
lized a knee coil and a neutral knee position in the MRI
scanner. The sagittal plane images were used for measure-
ments (field of view, FH 160 mm; voxel size, AP 0.6 mm and
FH 0.6 mm; slice thickness/gap: 3 mm/0.3 mm; number of
slices, 29; fold over direction: AP; flip angle, 90; scan time,
3 minutes 45 seconds). All knee geometry measurements
were performed using OsiriX (version 6.5.1; open source,
www.osirix-viewer.com).
The circle method described by Hudek et al
11
was used to
find the tibial longitudinal axis for measurement of knee
geometries PTS, MCS, PMH, and MBA. This method
involved 2 steps. The first step was finding the central
TABLE 1
MRI Diagnoses of Control Subjects as Determined by
Radiologists and Orthopaedic Surgeons
a
Diagnosis Subjects, n
Normal 11
Cyst, including Baker cyst 5
Meniscal injury, nontear 5
Patellar tendon–lateral femoral condyle friction
syndrome/Hoffa fat pad
4
Patellar dislocation 4
MCL sprain 1
Patellar tendinosis 2
Suprapatellar fat pad syndrome 2
Semimembranous tendinosis 2
Joint effusion 1
Bipartite patella 1
Patellar subluxation 1
Femoral bone contusion 1
Tripartite patella 1
LCL sprain 1
a
LCL, lateral collateral ligament; MCL, medial collateral
ligament; MRI, magnetic resonance imaging.
2Bojicic et al The Orthopaedic Journal of Sports Medicine

sagittal-plane image that contains the posterior cruciate
ligament attachment on the tibia, the intercondylar emi-
nence, and the anterior and posterior tibial cortices both
displaying a concave shape. The second step was finding
the tibial axis by drawing 2 overlapping circles on the
proximal tibia (Figure 1). The first circle was proximal to
the second circle and incorporated the anterior, posterior,
and proximal portions of the tibia. The center of the second
(distal) circle was positioned on the most inferior portion of
the first (proximal) circle; the distal circle incorporated the
anterior and posterior tibial cortices. A line connecting
the center of each circle defined the longitudinal axis of
the tibia.
A second sagittal plane image, corresponding to the
center of the lateral tibial condyle, was identified for
measurement of the 4 knee geometric parameters PTS,
MCS, MBA, and PMH. On that image, a line (L1) connect-
ing the superior-anterior and superior-posterior cortices
3
was drawn (Figure 2A). Specifically, this line connected the
most anteriorly positioned superior point to the most pos-
terior point of the superior tibial cortical surface that
allowed the line to remain on the cortical surface, thus
without going through the tibia. PTS was defined as the
difference between 90and the angle made between the
tibial longitudinal axis and L1 (Figure 2A.). A second line
(L2) along the superior surface of the wedge-shaped poste-
rior meniscus was drawn.
21
MBA was defined as the angle
between L1 and L2 (Figure 2B). A third line (L3) that joins
the most superior portions of the anteriorly and posteriorly
located prominences of the middle articular cartilage
surface
21
was drawn. These anterior and posterior promi-
nences were defined as the intersection of the femoral and
tibial cartilage surfaces located anteriorly and posteriorly
in the middle portion (sagittal plane) of the cartilage
surface, respectively.
22
MCS was defined as the difference
between 90and the angle made between the tibial longi-
tudinal axis and L3 (Figure 2C). A fourth line (L4) was
drawn from the most superior point of the posterior menis-
cus to the point at which the posterior meniscus intersected
the middle articular cartilage.
22
L4 was drawn so that it
was parallel to the tibial longitudinal axis while still con-
necting the 2 aforementioned points. PMH was defined as
the length of L4 (Figure 2D).
The observer making the measurements was blinded to
the state of the ACL (tear or no tear) after the midsagittal
plane and central lateral tibial condyle images were found.
This was achieved by deleting all unnecessary images from
the MRI sequence. The observer was presented with only
the central sagittal and central lateral tibial condyle
Figure 1. Midsagittal image defined by the presence of the
posterior cruciate ligament (PCL) attachment, the intercondylar
eminence, and concave anterior and posterior tibial cortex.
The tibial longitudinal axis was found by drawing 2 overlapping
circles: 1 proximal and 1 distal.
Figure 2. Examples of the various knee structural measure-
ments. (A) The posterior tibial slope (PTS) was defined as the
difference between 90and the angle (y) between the longi-
tudinal axis of the tibia and a line (L1) that connects the
superior-anterior and superior-posterior cortices of the prox-
imal tibia. (B) The meniscal bone angle (MBA) was defined as
the angle (y) between L1 and a line (L2) that lies along the
superior surface of the wedge-shaped posterior meniscal
cartilage. (C) The middle cartilage slope (MCS) was defined
as the difference between 90and the angle (y) between the
longitudinal axis of the tibia and a line (L3) that joins the most
superior portions of the anteriorly and posteriorly located
prominences of the middle articular cartilage surfaces.
(D) The posterior meniscal height (PMH) was defined as the
length of a line (L4) parallel to the longitudinal axis of the tibia
and connects the top of the posterior meniscal cartilage and
the point at which the posterior meniscus intersects the
middle articular cartilage.
The Orthopaedic Journal of Sports Medicine A Modifiable ACL Injury Risk Factor 3

images for each subject in a random order. The ACL, either
torn or intact, was not viewable in either of these images.
The means, standard deviations, and 95%CIs were com-
puted for each measurement. Univariate logistic regres-
sions were used to analyze the association between risk of
ACL tear and the variables PTS, MCS, MBA, PMH, BMI,
height, and weight. Only variables found to significantly
predict ACL injury, via the aforementioned univariate
analyses, were further analyzed with multivariate logistic
regressions. Multivariate logistic regression analyses were
performed to predict ACL injury risk with BMI, each sig-
nificant knee geometry variable, and their interaction as
predictor variables to assess the relationship between each
geometry variable and BMI. These multivariate logistic
regressions were repeated with height as well as with
weight instead of BMI as a predictor variable to investigate
the individual contributions of these components of BMI to
injury risk. When computing interaction variables, BMI,
height, and weight were centered around the mean (cBMI,
cHeight, cWeight) to decrease multicollinearity between
the interaction variable and its effects.
Intraobserver reliability was examined using intraclass
coefficients (ICCs). The observer made 2 series of measure-
ments on MRIs from a subset of subjects (n ¼10) 3 months
apart. The ICC values of PTS (0.776), MCS (0.980), MBA
(0.904), and PMH (0.860) were all considered to have good
to excellent reliability, as all values exceeded 0.75.
RESULTS
Participant height, weight, BMI, and knee morphological
data are presented in Table 2. Results of univariate logistic
analyses revealed that PTS (P¼.043) and MCS (P¼.037)
were significant predictors of ACL injury while PMH
(P¼.072), MBA (P¼.246), BMI (P¼.424), height
(P¼.141), and weight (P¼.277) were not significant pre-
dictors (Table 2). As PTS and MCS increased by 1, there
was an associated increased risk of sustaining an ACL
injury of 12%and 13%, respectively.
A multivariate logistic regression model that included
PTS, cBMI, and their interaction (PTS * cBMI) was found
to significantly predict ACL injury risk (P¼.040) (model 1,
Table 3). The odds ratios (ORs) for PTS and PTS * cBMI
were 1.12 and 1.03, respectively. Specifically, for every 1
increase in PTS there was an 11%increase in the associated
odds of tearing the ACL, keeping cBMI constant. Interpre-
tation of the interaction term is that for a 1-unit increase in
BMI from the mean in combination with a 1increase in
PTS, the associated odds of an ACL tear increased by 15%
(ie, OR
PTS
OR
PTS * cBMI
¼1.12 1.03) when compared
with a 0increase in PTS at the same BMI. Predicted
increases in ACL injury risk associated with other combi-
nations of increases in PTS and BMI can be found in Table
4. The 2 additional multivariate logistic regression models
aimed at exploring the interactions between cHeight and
PTS and cWeight and PTS, and thus, to explore the indi-
vidual contributions of height and weight instead of BMI,
were not found to significantly predict risk of ACL tear
(models 2 and 3, Table 3). It is worth mentioning, however,
that the model that included PTS, cWeight, and PTS *
cWeight did approach significance (P¼.055).
A multivariate regression model that included MCS,
cBMI, and their interaction (MCS * cBMI) was not found
to significantly predict ACL rupture risk (P¼.132). How-
ever, the model showed significance of MCS in predicting
tear (P¼.037) but no significance of the interaction vari-
able (P¼.395) or cBMI (P¼.707) (model 4, Table 3). The
odds ratio for MCS was 1.13. As MCS increased by 1, the
associated odds of experiencing an ACL tear increased 14%,
when accounting for BMI. There was no significant effect of
BMI. The 2 additional multivariate logistic regression mod-
els that investigated the interactions between cHeight and
MCS and cWeight and MCS were not found to significantly
predict ACL injury risk (models 5 and 6, Table 3).
DISCUSSION
This research demonstrates the important role that BMI
played in determining the risk of ACL injury in these sub-
jects. This is the first demonstration of how an individual’s
BMI can combine with their knee morphology to increase
their risk of sustaining an ACL injury. Since BMI is a mod-
ifiable factor, it presents an opportunity to improve ACL
injury prevention strategies.
Our results showed that BMI is associated with an
increase in the odds of ACL injury in the presence of an
increased lateral posterior tibial slope. In other words, BMI
appears to exacerbate the positive relation between PTS
TABLE 2
BMI, Knee Morphological Data, and Results From
Univariate Logistic Regression Models
a
Mean ±SD PValue Odds Ratio (95%CI)
Height, m .141 17.536 (0.386-797.669)
ACL tear 1.75 ±0.10
No ACL tear 1.72 ±0.09
Weight, kg .277 1.012 (0.990-1.035)
ACL tear 81.2 ±17.5
No ACL tear 77.5 ±17.9
BMI, kg/m
2
.429 0.973 (0.908-1.042)
ACL tear 26.4 ±4.1
No ACL tear 26.2 ±5.3
PTS, deg .043 1.118 (1.003-1.247)
ACL tear 6.7 ±3.9
No ACL tear 5.4 ±3.4
MCS, deg .037 1.125 (1.007-1.254)
ACL tear 4.4 ±3.7
No ACL tear 2.9 ±3.3
MBA, deg .246 0.949 (0.868-1.037)
ACL tear 28.6 ±4.1
No ACL tear 29.6 ±4.6
PMH, mm .072 0.692 (0.463-1.033)
ACL tear 6.3 ±0.9
No ACL tear 6.5 ±1.0
a
ACL, anterior cruciate ligament; BMI, body mass index; MBA,
meniscus bone angle; MCS, middle cartilage slope; PMH, posterior
meniscus height; PTS, posterior tibial slope.
4Bojicic et al The Orthopaedic Journal of Sports Medicine

and ACL injury risk. Additional analyses revealed that it is
mainly weight that is driving this significant relationship
between BMI and PTS and its association with ACL injury
risk. This is a key finding because BMI can be quantified
easily from measures of height and weight, which are stan-
dard elements of most athletic and medical assessments,
and can be modified via weight loss/gain. Although PTS is
not readily modifiable, it may be beneficial to screen for this
contributing factor to ACL injury risk because of the mod-
ulating role played by BMI within this PTS–ACL injury
risk relationship. This is especially significant in college
athletics, an environment in which many athletes, includ-
ing those in sports where noncontact ACL injuries are
common, are encouraged to increase weight, and conse-
quently, BMI, to increase sports performance. ACL preven-
tion efforts could target individuals with both an increased
PTS and BMI. Whether these individuals should be advised
to decrease their weight as a strategy to limit their risk of
sustaining an ACL injury is to be determined. For one, it is
unknown whether greater weight due to greater lean body
mass or greater fat body mass, or an increase in the combi-
nation of these mass types, has different effects on injury
risk when combined with an increased PTS. This is because
BMI only accounts for overall weight but not where the
extra weight lies. It is possible that an increase in fat body
mass increases one’s risk of ACL injury in combination with
a steep PTS, while an increase in lean body mass may not
affect one’s risk or might even decrease it. The interaction
of weight, BMI, and lean body mass (eg, muscle) may be
complex in terms of ACL injury risk. Increasing muscle
mass is often the goal of many athletes with the anticipa-
tion of increased strength and power, both of which may
help prevent knee injuries.
10
The increase in weight due
to muscle gain may need to be balanced against its
increased ACL injury risk when combined with “risky”
structural factors (PTS) identified herein. On the other
hand, it may only be an increase in fat body mass that is
detrimental. This may explain why the interaction of
weight and PTS and its association with ACL injury risk
did not quite reach significance. Many questions, such as
what kind of weight (lean vs fat body mass) and how much
weight gain is hazardous, remain unanswered and could be
the target of future research. Regardless, a high BMI
appears to be an important modifiable ACL risk factor in
the presence of an increased PTS.
As lateral PTS and lateral MCS increased, irrespective of
BMI, the odds of experiencing an ACL tear also increased in
the present study. These findings concur with results from
previous research that suggest increases in PTS
5,8,9,13,18,26
and MCS
5,21
increase the risk for ACL injury. In the pre-
sent study, PTS and MCS appeared to have similar effects
on the odds of sustaining an ACL rupture (variables had
odds ratio of 1.12 and 1.13, respectively).
Recent literature
21,22
suggests that PMH and MBA are
significant risk factors in females and males, respectively.
However, PMH and MBA were not shown to be significant
TABLE 3
Multivariate Logistic Regression Models Predicting
Anterior Cruciate Ligament Injury Risk
Predictor Variables PValue Odds Ratio
Model 1
a
PTS .061 1.12
cBMI .140 0.88
PTS * cBMI .050 1.03
Model 2
b
PTS .049 1.12
cHeight .754 3.07
PTS * cHeight .497 1.42
Model 3
c
PTS .045 1.13
cWeight .348 0.83
PTS * cWeight .055 1.06
Model 4
d
MCS .037 1.13
cBMI .707 0.98
MCS * cBMI .395 1.19
Model 5
e
MCS .020 1.15
cHeight .288 32.98
MCS * cHeight .904 1.08
Model 6
f
MCS .029 1.14
cWeight .812 1.04
MCS * cWeight .345 1.03
a
Model 1: Results of the multivariate logistic regression
model including posterior tibial slope (PTS), body mass index
centered around the mean (cBMI), and the interaction variable
(PTS * cBMI).
b
Model 2: Results of the multivariate logistic regression model
including PTS, height centered around the mean (cHeight), and
the interaction variable (PTS * cHeight).
c
Model 3: Results of the multivariate logistic regression model
including PTS, weight centered around the mean (cWeight), and
the interaction variable (PTS * cWeight).
d
Model 4: Results of the multivariate logistic regression model
including middle cartilage slope (MCS), cBMI, and the interaction
variable (MCS * cBMI).
e
Model 5: Results of the multivariate logistic regression
model including MCS, cHeight, and the interaction variable
(MCS * cHeight).
f
Model 6: Results of the multivariate logistic regression
model including MCS, cWeight, and the interaction variable
(MCS * cWeight).
TABLE 4
Predicted Increases in ACL Injury Risk
a
PTS, deg
c
BMI, kg/m
2b
þ1þ2þ3
þ0 122540
þ1 152945
þ2 193349
þ3 223754
þ4 264158
þ5 304563
a
Values are expressed as percentages. ACL, anterior cruciate
ligament; BMI, body mass index; PTS, posterior tibial slope.
b
One-unit increases in BMI from the mean BMI (26.3 kg/m
2
).
c
One-degree increases in PTS from the mean PTS (6.2).
The Orthopaedic Journal of Sports Medicine A Modifiable ACL Injury Risk Factor 5

ACL risk factors in this study. The discrepancy in these
findings may be explained by a variety of factors. First, the
methods used to measure both PMH and MBA have not
been validated using the method of Hudek et al
11
for obtain-
ing the tibial longitudinal axis. The measurement methods
were based on the work of Sturnick et al
21,22
but could not
be duplicated exactly due to the lack of higher resolution
MRIs. This is also a study strength, however, because lower
resolution MRIs, as are often acquired clinically, can be
used to predict ACL risk. Second, the effects of these 4 knee
anatomic parameters on ACL injury risk could not be cal-
culated independently for the female and male subjects due
to the small sample size. Our combined analysis probably
masked the sex-specific effects of PMH and MBA on injury
risk previously reported.
21,22
Further method development
and sex-specific analysis may be necessary to achieve the
results obtained by Sturnick et al.
21,22
This study has several limitations. First, the retrospec-
tive nature of this study does not allow us to account for any
changes in knee morphology after injury, such as tibiofe-
moral articular thickness changes,
23
which may affect mea-
sures of the middle cartilage slope.
3
Although our results
pertaining to this measure should be interpreted with cau-
tion, similar results have been reported using the unin-
jured knee of patients with injured ACLs.
22
Furthermore,
there is no evidence that sustaining an ACL injury modifies
the other 3 knee morphological factors we measured or
BMI. Second, a selection bias may have existed in our con-
trol group because it consisted of patients who had obtained
an MRI due to complaints of knee pain, which might have
altered the morphologic features measured in this study.
However, many (26%) of these MRIs were interpreted as
normal by radiologists and clinicians. None of them showed
ligament or meniscal pathology. Given the varied nature of
the diagnoses, they are unlikely the source of the signifi-
cant associations between ACL injury risk and PTS, MCS,
and BMI found herein. Some other underlying knee pathol-
ogies, however, could have been present and thus con-
founded our results. Third, the ACL-injured group and
the control group may have differed in terms of their expo-
sure to ACL injury risk. This is unknown, however, given
the retrospective nature of this study. Fourth, the clinical
MR images available for measurement were of lower reso-
lution than those used in prior studies
3,5,21,22
to measure
knee geometries such as PTS. This, however, may also be a
strength of the study. If the measurement of knee geome-
tries such as PTS is implemented in clinical practice, clin-
icians will not have access to the high-resolution MRIs
often used in research settings. Fifth, although careful
efforts were made by the MRI technicians to ensure that
each patient’s knee was in a neutral position (0of knee
flexion) during the MRI scan, slight variations in knee flex-
ion angles may have occurred. We have no reason to
believe, however, that these variations were more than
minimal or that they would have biased 1 group, thereby
accounting for the significant results we reported. Last,
these clinical MR images were obtained from various
systems within the University of Michigan Health System,
which may have added variability to our data. This vari-
ability, however, appears to be insignificant in terms of the
differences in the knee morphologic parameters found
between groups.
CONCLUSION
The effect of an increase in lateral PTS on ACL injury risk
is affected by BMI. An increase in BMI was found to be
associated with an increase in the risk of ACL tear in the
presence of an increased lateral PTS. An increase in lateral
PTS or MCS was associated with an increased risk of an
ACL tear, irrespective of BMI.
ACKNOWLEDGMENT
The authors thank Elizabeth Sibilsky Enselman (University
of Michigan); University of Michigan Consulting for Statis-
tics, Computing, and Analytics Research; and the University
of Michigan MedSport Department of Radiology.
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The Orthopaedic Journal of Sports Medicine A Modifiable ACL Injury Risk Factor 7