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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_6011_Библиотеки_им_академика_М_И_Перельмана.pdf
Non-Invasive Strength Analysis
of the Spine Using Clinical
CT Scans
Tony M. Keaveny
9
k e y p o i n t s
Most spine surgery candidates over age 50 are either osteopenic or
osteoporotic.
Biomechanical computed tomography (BCT) techniques can be used on
clinical CT scans to provide measures of both vertebral density and strength.
Clinical research studies have shown that the biomechanical outcomes from
BCT are more highly associated with fracture risk for the spine than is bone
mineral density.
Vertebral strength as measured by BCT can provide earlier and additional
insight compared to dual-energy absorptiometry (DXA) for monitoring
therapeutic treatment effects at the spine.
It may be possible in the future to use BCT to assess the strength and
stability of various bone-implant systems for surgical planning and patient
monitoring.
INTRODUCTION
Osteoporosis is widely recognized as an underdiagnosed and undertreated
disease. According to the National Osteoporosis Foundation and the
National Institutes of Health, 10 million Americans are estimated to have
osteoporosis, and another 34 million are at increased risk due to low bone
mass, but only about 20% of those eligible to be screened are actually tested
and only a fraction of those are positively diagnosed and treated. Above age
50, the density of vertebral trabecular bone decreases at a rate of about 2.2%
to 3.0% per year for women, depending on age, and by about 1.7% to 2.5%
per year for men,
ring annually in the united States
Management of osteoporosis in the over-50 age group is important
both to avoid such fractures and to optimize spine surgery outcomes.
A recent study from Taiwan
cases, not including vertebroplasty or kyphoplasty, 47% of women and 46%
of men over age 50 had low bone mass or “osteopenia” — a BMD T-score
of between −1.0 and −2.5 — and 44% of women and 12% of men had
osteoporosis — a BMD T-score of less than −2.5. As the size of the aging
population continues to increase, a huge and growing proportion of spine
surgery patients may have compromised bone strength. This presents a
challenge to the spine surgeon using any sort of instrumentation or implant
for stabilization, since the underlying bone and the bone-implant interface
need to be strong enough to sustain the stresses both from daily activities
and spurious overloads.
From a patient-management perspective, it would be desirable clinically
to be able to identify more patients at high risk of vertebral fracture. These
patients can then be placed on an appropriate therapeutic treatment, which
typically reduces fracture risk by about 50%. For spine surgery, surgical
1
with about 700,000 osteoporotic spine fractures occur-
2
.
3
estimated that for all major spine surgical
planning and postoperative patient management might be improved by
identifying patients with compromised bone strength. Improved information on vertebral strength on a patient-specific basis might provide an objective basis for evaluation of actual surgical options, including type and size
of implant. In addition to the condition being treated surgically, many spine
surgery patients have compromised vertebral strength, which, if recognized,
could be treated postoperatively with appropriate therapeutic agents.
A number of different types of imaging modalities are now available for
noninvasive assessment of bone density, structure, and strength.
energy x-ray (DXA) scan is the current clinical standard for bone density
assessment. However, DXA for the spine has a number of limitations. Being
a 2D imaging modality, a DXA scan combines all bone morphology in the
anterior-posterior direction. Thus, arthritic changes in the posterior elements, degenerative osteophytic growths around the endplates, and aortic
calcification all produce bone mineral density increases in the DXA scan
— increases that confound the measurement of bone mineral density in the
load-bearing vertebral body. DXA scans also provide very limited information on the morphology, density, or strength of the pedicles. As a result of
these limitations, DXA of the spine is less predictive of the risk of osteoporotic fractures than is DXA of the hip, DXA of the spine can be highly misleading in terms of measuring actual bone mineral density of the vertebrae
or pedicles, and there remains a need for improved strength and fracture risk
assessment of the spine.
Computed tomography (CT), being a 3D imaging modality, provides
a powerful alternative to DXA and is preferable to magnetic resonance
imaging (MRI) for bone strength assessment since it provides quantitative
information on bone mineral density.
the difficulty of interpreting the large amount of information in the scan
in terms of a clinically relevant outcome such as bone strength. This is
because a low value of bone mineral density at a particular location within
the bone does not necessarily indicate a problem with overall bone strength.
Conversely, such a local decrease in density may not show up in an averaged measure of bone mineral density, but may be problematic if that local
decrease in density occurs in such a location as to appreciably compromise
strength. To overcome this limitation, a sophisticated engineering structural
computational analysis technique known as “finite element analysis” can be
applied to CT scans to provide an estimate of vertebral strength,
the same way as engineers perform computational strength analysis of such
complex 3D structures as bridges, aircraft components, and engine parts
(Figure 9-1). The resulting “biomechanical computed tomography” (BCT)
technology, which represents a post hoc analysis of a clinical CT exam, is
now being used in a variety of clinical research studies that address vertebral
strength, aging, osteoporosis and its various therapeutic treatments. Because
BCT creates a mechanical model of the patient’s bone, it can also be adapted
to include a virtual implant and in that way provide estimates of strength
and stability of various bone-implant constructs — all from analysis of a
patient’s preoperative CT scan.
4
One limitation with CT analysis is
4
The dual-
5
in much
45
46
P A R T I I Basic Science of the Aging Spine
Clinical Case
e following analysis of proximal junction kyphosis is a hypothetical case
to illustrate how strength estimates from BCT analysis could eventually be
used clinically to provide spine surgeons with quantitative information as
part of the decision-making process in preoperative surgical planning. is
case also illustrates how BCT can currently be used for diagnosis of vertebral osteoporosis using clinical CT scans.
A 68-year-old woman presented with an overtly unstable spine involving
circumferential disruption of the spinal column around the level of the thoracolumbar junction, including insults to both the vertebral body and posterior elements. Based on a physical exam and review of x-rays and CT and
MRI scans of T10 through L2, the surgeon decided to decompress and fuse
the T12-L1 disc and provide support by rigid pedicle screw fixation. Because
of the patient’s age, the surgeon was unsure about the possibility of osteoporosis. A review of this patient’s medical record revealed that she had a DXA
exam of both the hip and spine two years previously, which showed a T-score
at the hip (femoral neck) of −2.2 and of the (total) spine of −1.8. us,
this patient just missed being diagnosed as having osteoporosis as defined
by WHO guidelines (any T-score of less than −2.5), but it was unclear as
to the status of her osteoporosis classification at the time of surgery, particularly for her spine which had appeared to have a more normal T-score than
the hip. To address these issues, the surgeon ordered a BCT analysis to be
BASIC SCIENCE
Aging of the Spine
Substantial changes occur to vertebrae with aging. Cadaver studies have
shown that whole vertebral strength decreases by about 12% per decade
from ages 25 to 85 (Figure 9-2). Although these changes are due primarily
to a loss of bone density, which is offset in part by subtle increases in bone
performed on the preoperative CT exam, focusing on the undamaged levels
in order to assess risk of vertebral fracture for the postoperative situation.
e BCT analysis was used to estimate the vertebral strength for T10
and L2 in order to better assess the osteoporotic status of the vertebrae
(Table 9-1). Analysis of the scans showed substantial posterior arthritic
changes and that the bone strength was three standard deviations lower
than the mean value for a young reference population. e volumetric
density scores of the trabecular bone based on the CT data indicated low
trabecular bone density — almost in the osteoporosis range — but they
did not reflect that this patient had low cortical density and relatively small
bones, both of which also contributed to her very low bone strength. e
DXA spinal T-scores were therefore misleading because of the substantial posterior calcification, arthritic changes, low cortical density, and small
bone size. Calculations of the strength-capacity — which take into consideration the expected magnitude of the in vivo forces acting on the patient’s
spine (see later in the chapter for more details) — were in the 60% range,
indicating that the strength of this patient’s vertebra was only about 60%
of what it should be in order to safely lift a 10-kg object with back bent
(a “worst case” strenuous loading condition). Based on these findings, the
surgeon instrumented from T12-L1, advised the patient of her elevated
risk of vertebral fracture, and referred her for an endocrine consultation.
size, the loss of cortical bone is generally not as pronounced as the loss of the
trabecular bone.
1
DXA generally is unable to distinguish between cortical
and trabecular bone in the spine, due to its projectional nature. Aging of
the spine is also accompanied by osteoarthritic changes (formation of osteophytes, etc.) around the disc and endplates. Again, due to projectional limitations, such degenerative changes are manifested as increases in BMD on
DXA exams — effectively adding noise to the BMD signal from the more
Strength (MPa)
70 y.o.
64 y.o.
F IG UR E 9 -1 Details of BCT models for two women, showing sectioned view of the finite element model and two cross-sections for each. The colors indicate
different values of material strength assigned to the individual finite elements within each model, which are obtained from quantitative analysis of the calibrated gray
scale information in the patient’s CT scan. (Reproduced from Melton LJ, Riggs BL, Keaveny TM, Achenbach SJ, Hoffmann PF, Camp JJ, Rouleau PA, Bouxsein ML,
Amin S, Atkinson EJ, Robb RA, Khosla S: Structural determinants of vertebral fracture risk, J Bone Miner Res 22:1885-1892, 2007, Fig 1.)
4.9
3.4
2.0
0.9
0.1
C H A P T E R 9 Non-Invasive Strength Analysis of the Spine Using Clinical CT Scans
Whole vertebral strength (N)
7
47
biomechanically relevant vertebral body portion of the spine. There is also
substantial heterogeneity in trabecular strength across the population at any
age (Figure 9-2). Thus, although advanced age is associated with low bone
strength, age, sex, and DXA information are inadequate for clinical assessment of vertebral strength for an individual patient.
Finite Element Analysis of CT Scans — Biomechanical Computed Tomography
Because of the above-mentioned concerns over the fidelity of DXA scans
for the spine and the substantial heterogeneity across patients in vertebral
bone, quantitative CT is preferred for bone density assessment in the spine.
However, CT alone provides density measures in preselected regions of
interest within the vertebra, e.g., trabecular centrum vs. trabecular bone near
the endplates vs. all trabecular bone vs. all trabecular bone plus the cortex,
etc., and such outcomes can be difficult to interpret with respect to actual
strength of either the isolated vertebra or a vertebral bone-implant construct. In addition, use of CT-derived density data alone would be difficult
for assessment of different surgical options because there would be no way
to measure any biomechanical effect of the implant on stresses in the bone.
To overcome these limitations, clinical CT scans can now be converted into
biomechanical structural models of the patient’s bones in a highly automated
and repeatable fashion using a combination of sophisticated imaging processing and finite element modeling. This technology, termed biomechanical
TA BL E 9- 1 Outp ut Data from the B CT Analysis
for Levels T1 0 to L2
CT Density BCT Strength
3
Level
T10 105 −2.3 1050 −2.9 62
L2 102 −2.4 1140 −3.0 60
*
T-scores calculated as number of standard deviations below young reference mean.
mg/cm
T*Newtons T* %
Strength Capacity
computed tomography (BCT) because it represents a biomechanical analysis of a CT scan, has the main advantage of providing a strength outcome
that is integrative in nature, not requiring specification of any particular
region of interest with the bone. It can also account for typical in vivo loading conditions and can be used on isolated vertebrae, motion segments, or
bones with virtually implanted prostheses. With appropriate comparison
versus population reference values and biomechanical threshold values, such
information can be used to assist the physician in various stages of the decision-making process during patient management.
The BCT technique, first introduced clinically in the early 1990s but
substantially refined since then, starts by converting the gray scale Hounsfield Unit data in the standard DICOM-formatted CT image into calibrated
4
values of bone mineral density. External calibration phantoms are typically
placed underneath the patient during imaging in osteoporosis research studies, but phantomless calibration can be used clinically. After calibration of
the gray scale values, the bone of interest is separated from the surrounding
tissue via a variety of image processing techniques. The finite element mesh
is then created from this processed bone image in which each finite element is assigned local material properties based on the calibrated gray scale
information in the CT scan. Such material properties-density relations are
derived from cadaver experiments. The final step is to apply loading conditions typical of habitual activities or more spurious overloads, depending
on the clinical application. A finite element stress analysis is performed to
compute the strength of the vertebra under the applied loading conditions
— in essence, a virtual stress test. Models can be created of the vertebra
alone, of the vertebra with surrounding soft tissue, of multiple vertebrae, or
of a vertebra with a virtually implanted prosthesis, and analyses can be run
for single or multiple loading conditions.
BCT has been used for over two decades in orthopedic laboratory
research to study the mechanical behavior of such bones as the femur,
humerus, radius, tibia, cranium, and vertebra, with and without implants,
and more recently has found use in a number of clinical research studies. It
has been well validated in cadaver studies, for both the hip and spine, and
has consistently been found to be a better predictor of measured cadaveric
strength than is BMD as measured by either DXA or quantitative CT
alone. The technique is now undergoing extensive clinical validation for
a variety of osteoporosis clinical applications. In the first published study
of clinical BCT,
6
it was found that a measure of lumbar vertebral strength
better discriminated between osteoporotic and non-osteoporotic subjects
F I GU RE 9 -2 A, Cadaveric biomechanical testing values of L2 vertebral strength (expressed in N), for women and men, plotted versus age. (Adapted from
Mosekilde L, Mosekilde L: Sex differences in age-related changes in vertebral body size, density and biomechanical competence in normal individuals, Bone 11:67-73, 1990.)
B, Ultimate compressive stress of human vertebral trabecular bone cores (expressed in MPa), versus age, obtained by biomechanical testing of cadaveric material.
Despite the clear trend for decreasing strength with advancing age, age is not a very sensitive indicator of bone strength for any given individual. For example,
subject A, although older than subject B, has trabecular strength more typical of a 37-year-old, whereas subject B’s trabecular strength is closer to that of a typical
75-year-old. (Adapted from Mosekilde L, Mosekilde L; Normal vertebral body size and compressive strength: relations to age and to vertebral and iliac trabecular
bone compressive strength, Bone 7:207-212, 1986.)
A
10,000
8,000
6,000
4,000
2,000
Female
Male
0
0 20 40 60 80 100
Age (years)
Y = 5.47 0.0541 [Age]
2
R
6
5
4
3
2
Trabecular ultimate stress (MPa)
1
0
0 20 40 60 80 100
B
Age (years)
A
B
= 0.65
48
2.5
Vertebral yield stress (MPa)
P A R T I I Basic Science of the Aging Spine
than did bone density (Figure 9-3). In a more recent study, BCT has been
shown to differentiate those with prevalent vertebral fractures from those
without, after accounting for age and despite areal BMD not being able
to differentiate the fracture from no-fracture groups.
7
BCT has also been
used to assess the effects of various drug treatments at the spine and can
detect statistically significant between-treatment effects in the spine earlier
than can DXA.
8
In addition to providing measures of vertebral density and strength, BCT
can also be used to implement controlled variations of the patient-specific
models to produce additional strength outcomes of potential clinical significance. For example, by virtually peeling away the outer layer of bone and then
running a second virtual stress test for strength analysis of the remaining
bone, it is possible to quantify the strength effects associated with just the trabecular or cortical compartment.
8
Such studies have shown, for example, that
strength associated with the outer two millimeters of bone in the vertebral
body (which encompasses the cortical shell) is highly predictive of fracture
at the spine groups
compartment by various drug treatments.
7
and can be differentially affected versus the trabecular
8,9
The BCT technique so far has
been used only in clinical research studies and is not yet FDA-approved.
CLINICAL PRACTICE GUIDELINES
Given that there are no clinical practice guidelines available yet for BCT,
a number of general issues related to interpretation are discussed instead.
Results from the BCT analysis can be interpreted in a number of ways. As
with the approach for bone density analysis with DXA or quantitative CT,
values of bone strength can be compared against age-matched population
values (so-called Z-scores) and against young normal reference values (socalled T-scores). A Z-score of −2.0, for example, indicates that the patient
has a bone strength of two standard deviations below the mean of their sexmatched age group. A T-score of −2.0 indicates that the patient has a bone
strength of two standard deviations below the mean of their sex-matched
“young” (aged 20 to 30 years) reference group. A decision to treat can be
based on where a patient stands with respect to such population reference
values. Bone density values, which are measured as part of the BCT analysis,
No FX
FX
can also be used in the patient evaluation. Another approach is to treat based
on biomechanical threshold values, much as a DXA BMD T-score of −2.5
is commonly used to define osteoporosis.
Another outcome from the BCT analysis beyond strength is the
“strength-capacity” (aka the “safety factor” in engineering analysis), defined
as the ratio of the strength of the bone to the magnitude of the estimated
applied in vivo force acting on the bone. This is the reciprocal of the “loadto-strength” ratio often used in biomechanics research studies.
10
The lower
the value of the strength-capacity, the higher is the likelihood of fracture in
the event of the simulated event, e.g., for the spine, bending over and lifting
10 kg. For example, if the vertebral strength for a patient’s L2 was computed
to be 2000 N, and the estimated in vivo force for lifting a 10 kg object with
back bent was 3000 N, the strength-capacity of the patient’s L2 vertebra for
this activity would be 2000/3000 = 66%. This indicates that the patient’s
bone has only 66% of the strength necessary to safely engage in this lifting activity. While, in theory, strength-capacity values less than 100% would
indicate that the bone is too weak to withstand the applied in vivo forces,
because of the difficulty of estimating in vivo forces in an absolute accurate
sense, strength-capacity values are, at present, best interpreted in relative
terms. The in vivo force for a given activity can be calculated as part of the
BCT analysis using such patient-specific information as weight and height,
and various skeletal measurements obtained from the patient’s CT exam
including muscle size and location.
A third approach is to base treatment decisions on an absolute risk of
fracture, which can be obtained based on analysis of fracture surveillance or
other clinical outcome studies. Based on cost-effectiveness or other criteria,
the physician can decide to treat if the absolute risk exceeds some critical
value. As with all new technologies, as BCT is used more in the clinic, the
accumulated evidence in support of how the outcomes can be best used
for clinical decision making will accumulate, which in turn should lead to
more objective and evidence-based guidelines for patient management and
surgical planning.
CLINICAL CASE EXAMPLES
A number of examples are presented to illustrate how BCT has been used
so far in clinical research studies to assess vertebral strength responses to
different types of drug therapies for osteoporotic and rheumatoid arthritis
patients, and also to assess risk of osteoporotic vertebral fracture.
2.0
1.5
0.95 MPa
1.0
0.5
0.0
0 2
F IG UR E 9 -3 Relation between vertebral compressive yield stress (ver-
tebral strength divided by its cross-sectional area) as measured by BCT and total
bone mineral content of the vertebra as measured by quantitative CT, for individuals either having a radiographically confirmed osteoporotic vertebral fracture (FX) or having normal bone without any vertebral fracture (No FX). Note
that between BMC values of about 4 to 6 g, most patients with osteoporosis
had lower values of vertebral yield stress. A threshold point of 0.95 MPa for
vertebral yield stress (shown above) was identified as having greater diagnostic
accuracy than a traditional trabecular bone mineral density threshold. (Adapted
from Faulkner KG, Cann CE, Hasegawa BH: Effect of bone distribution on vertebral strength: assessment with patient-specific nonlinear finite element analysis,
Radiology 179:669-674, 1991.)
4 6 8 10
BMC (g)
Comparing Teriparatide and Alendronate for Treatment of Osteoporosis
Teriparatide and alendronate increase bone mineral density through opposite effects on bone remodeling, namely via anabolic and antiresorptive
actions, respectively. In this study
8
, two randomly assigned groups of postmenopausal osteoporotic women (N=28 teriparatide; N=25 alendronate)
who had quantitative CT scans of the spine at baseline and postbaseline (6
months and 18 months) were analyzed with BCT for L3 vertebral compressive strength. At 18 months, patients in both treatment groups had
increased vertebral strength, the median percentage increase being over fivefold greater for teriparatide (Figure 9-4). Larger increases in the ratio of
strength to density were observed for teriparatide, and these were primarily
attributed to preferential increases in trabecular strength that occurred only
for this treatment. At 6 months, the between-treatment effect was statistically significant for vertebral strength but not for BMD, demonstrating the
ability of BCT to differentiate treatment effects earlier than DXA. Further,
median changes in the BCT-measured vertebral strength for the teriparatide
and alendronate groups were 4.9% and 13.0%, respectively, and for DXAmeasured spine BMD were 2.0% and 3.4%, respectively, indicating that
changes were generally much larger for BCT than for DXA.
Alendronate Treatment in Rheumatoid Arthritic Patients
In this study,9 BCT analysis was applied to 29 rheumatoid arthritic patients,
randomly assigned to be treated or not with either alendronate for their
osteoporosis, but most of whom were on some sort of steroidal medication for their rheumatoid arthritis. Results indicated that, after 12 months
C H A P T E R 9 Non-Invasive Strength Analysis of the Spine Using Clinical CT Scans
50
30
30
49
Alendronate
0
Vertebral
strength
Teriparatide
††
*
*
NS
*
Average
density
40
30
20
10
% change from baseline
(with interquartile range)
-10
*
Strength/
††
*
**
density
†
*
NS
Vertebral
strength
Average
density
6 months 18 months
F IG UR E 9 - 4 Median percent change in BCT-predicted whole verte-
bral compressive strength, average vertebral density as measured by quantitative CT, and the ratio of whole vertebral compressive strength to average
vertebral density in teriparatide-treated and alendronate-treated women, after
6 and 18 months of treatment. In each box, the line represents the median,
the upper end of the box is the 75th interquartile range, and the lower end of
box is the 25th interquartile range. *p < 0.001 and **p < 0.05 within group
from baseline; †p < 0.001, ††p < 0.01 between group; NS, nonsignificant. At
6 months, between-treatment effects were statistically significant for strength
but not for average density. Changes in the ratio of strength to density were
also statistically different between treatments, indicating a between-treatment
effect beyond an average density effect. (Adapted from Keaveny TM, Donley
DW, Hoffmann PF, Mitlak BH, Glass EV, San Martin JA: Effects of teriparatide
and alendronate on vertebral strength as assessed by finite element modeling of
QCT scans in women with osteoporosis, J Bone Miner Res 22:149-157, 2007.)
of treatment, there was on average a loss in the nontreated group of 10.6%,
which was completely arrested with alendronate treatment, primarily by its
positive effect on the outer 2 mm of vertebral bone (Figure 9-5). These results
demonstrate the substantial loss of vertebral strength that can occur in RA
patients and the usefulness of alendronate treatment for arresting such loss.
Assessing Risk of Vertebral Fracture in Postmenopausal Women
Data from a cross-section study on vertebral fracture prevalence were used
to compare the abilities of BMD by DXA vs. vertebral strength and the
strength-capacity by BCT for vertebral fracture risk assessment
postmenopausal women with a clinically-diagnosed vertebral fracture (confirmed semiquantitatively) due to moderate trauma (cases: mean age, 78.6 ±
9.0 years) were identified from an age-stratified sample of Rochester, MN
women, and were compared to 40 controls with no osteoporotic fracture
(70.9 ± 6.8 years). Results indicated that DXA-based BMD for the spine
or total hip were not significantly different between fractures and controls,
but age-adjusted BCT-measures of vertebral strength and load-to-strength
ratio (the reciprocal of strength-capacity) were 23% lower and 36% higher,
respectively. The age-adjusted odds ratio per standard deviation increase for
the load-to-strength ratio measure was 3.2 (p < 0.05), versus a nonsignificant value of 0.70 for spine region BMD by DXA. Thus, if an individual presented to the clinic with a load-to-strength ratio that was 2.5 SD above the
age-matched average value for his or her sex, she or he would be at an 18-fold
2.5
(= 3.2
) elevated risk of fracture compared to the age-matched average.
This study demonstrates the ability of the BCT-measured load-to-strength
ratio (and thus its reciprocal, the strength-capacity) to provide additional
fracture predictive ability compared to DXA-measured BMD.
DISCUSSION
The combination of finite element modeling with clinical CT scans —
biomechanical computed tomography — is a powerful research technique
to noninvasively assess vertebral strength and is now finding its way into
NS
†
*
†
*
NS
Strength/
density
7
. Forty
20
10
0
-10
-20
-30
-40
A
30
20
10
0
-10
-20
-30
DTRAB_strength (%) DStrength (%)
-40
C
F IG UR E 9 -5 Percent ch ange over 12 months from baseline in BCT-
predicted vertebral strength (A), DXA-measured areal BMD (B), trabecular compartment (TRAB) strength (C) and peripheral compartment (PERIPH) strength
(D), in alendronate-treated (ALN) and not-treated (CTL) groups of rheumatoid
arthritic patients. The peripheral compartment comprises the outer 2 mm of
bone, including the thin cortical shell and adjacent trabecular bone. Data are
presented as box plots, where the boxes represent the 25th to 75th percentiles, the lines within the boxes represent the median, and the lines outside
the boxes represent the 10th and 90th percentiles. *P < 0.05 versus baseline,
NS — not significant; between-treatment effects sho wn with other p-values,
when p resent. These data indicate that there is more variation seen in the
patient resp onse as captured by BCT-str ength compared to DXA-BMD. Further, the protective effect of alendronate treatment is due primarily to its positive effect on the peripheral bone. Note also the substantial loss in vertebral
strength for the untreated group: just over 10%, on average, and much higher
for some individuals. (Adapted from Mawatari T, Miura H, Hamai S, Shuto T,
Nakashima Y, Okazaki K, Kinukawa N, Sakai S, Hoffmann PF, Iwamoto Y,
Kea veny TM: Vertebral strength changes in rheumatoid arthritis patients
treated with alendronate, as assessed by finite element analysis of clinical
computed tomography scans: a prospective randomized clinical trial, Arthritis
Rheum 58:3340-3349, 2008.)
p<0.01
*
CTL
CTL ALN
ALN
N.S.
*
20
10
0
-10
-20
-30
-40
B
30
20
10
0
-10
-20
-30
DPERIPH_strength (%) DDXA_aBMD (%)
-40
D
p<0.0001
*
CTL ALN
p<0.002
*
*
CTL ALN
clinical studies. Well supported by cadaver studies, the technique is providing substantial new insight into drug treatment effects in the spine and can
show treatment effects earlier than DXA. Early clinical results are providing evidence of the superiority of BCT over DXA for fracture risk assessment, although additional clinical studies are necessary to establish this
more definitively. The technique is well suited for clinical use since it can be
performed on preoperative and most preexisting CT exams. It also has the
potential to be used in various surgical planning applications.
One clinical challenge with using BCT for fracture risk assessment is the
actual need for a CT scan and the associated cost and radiation exposure.
For an assessment of osteoporosis fracture risk, this leads to more radiation
and a more expensive test than a traditional DXA exam. However, if the
technique is used to analyze a previously-acquired CT exam, then the BCT
fracture risk assessment analysis per se becomes less expensive than a DXA
exam, more convenient than a DXA exam, and requires no extra radiation,
because no new CT exam is required. Such previously-acquired CT exams
would include a pelvic, spine, or abdomen CT, or such specialized CT exams
as CT colonography, CT angiography, or CT for calcium scoring. Further
development could lead to the application of BCT to such low-energy
CT scanning techniques as intraoperative C-arm and O-arm scanning,
which would be advantageous particularly for intraoperative osteoporosis
screening and surgical planning.
50
P A R T I I Basic Science of the Aging Spine
For monitoring purposes, given the substantial advantage of using BCT
to monitor treatment effects compared to DXA, performing a follow-up
BCT analysis on just one vertebral level or just the proximal femur would
be well-justified and could be performed earlier than a DXA exam to provide faster feedback on the patient’s response to treatment. One important
limitation of any CT-based exam, including BCT, is that the CT scan can
be corrupted by the presence of metal hardware due to streaking artifacts,
although it may be possible in the future to alleviate such artifacts within
the 3D reconstruction algorithms. For the purposes of surgical planning,
it is currently possible with BCT to virtually implant a prosthesis into the
bone in a research setting, and in that way compute the stability or strength
of the resulting bone-implant construct. Basic cadaver and clinical research
studies are required to further develop such applications of BCT to the
clinic and validate them with clinical outcomes. Related clinical applications
for BCT include stability assessment of fracture healing and fusion constructs and strength assessment of metastasized or otherwise structurally
compromised vertebrae. Given recent advances in CT technology, computer
hardware power, and 3D image processing, it is expected that a variety of
such advanced analysis techniques for CT scans will be available in the near
future. Their integration into clinical practice where CT scans are being
used should help improve management of patients with suspected osteoporosis or otherwise compromised vertebral strength.
Acknowledgements
The author acknowledges support from the National Institutes of Health
(grant AR49828). Dr. Keaveny has a financial interest in O.N. Diagnostics,
and both he and the company may benefit from the results of this work.
References
1. B.L. Riggs, L.J. Melton, R.A. Robb, J.J. Camp, E.J. Atkinson, L. McDaniel, et al., A populationbased assessment of rates of bone loss at multiple skeletal sites: evidence for substantial
trabecular bone loss in young adult women and men, J. Bone Miner. Res. 23 (2) (2008)
205–214.
2. L.J. Melton, Epidemiology of spinal osteoporosis, Spine 22 (Suppl. 24) (1997) 2S–11S.
3. D.K. Chin, J.Y. Park, Y.S. Yoon, S.U. Kuh, B.H. Jin, K.S. Kim, et al., Prevalence of osteoporosis in patients requiring spine surgery: incidence and significance of osteoporosis in spine
disease, Osteoporosis Int. 18 (9) (2007) 1219–1224.
4. M.L. Bouxsein, Technology insight: noninvasive assessment of bone strength in osteoporosis,
Nat. Clin. Pract. 4 (6) (2008) 310–318.
5. R.P. Crawford, C.E. Cann, T.M. Keaveny, Finite element models predict in vitro vertebral
body compressive strength better than quantitative computed tomography, Bone 33 (4)
(2003) 744–750.
6. K.G. Faulkner, C.E. Cann, B.H. Hasegawa, Effect of bone distribution on vertebral strength:
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669–674.
7. L.J. Melton, B.L. Riggs, T.M. Keaveny, S.J. Achenbach, P.F. Hoffmann, J.J. Camp, et al., Structural determinants of vertebral fracture risk, J. Bone Miner. Res. 22 (12) (2007) 1885–1892.
8. T.M. Keaveny, D.W. Donley, P.F. Hoffmann, B.H. Mitlak, E.V. Glass, J.A. San Martin, Effects
of teriparatide and alendronate on vertebral strength as assessed by finite element modeling of
QCT scans in women with osteoporosis, J. Bone Miner. Res. 22 (1) (2007) 149–157.
9. T. Mawatari, H. Miura, S. Hamai, T. Shuto, Y. Nakashima, K. Okazaki, et al., Vertebral
strength changes in rheumatoid arthritis patients treated with alendronate, as assessed by
finite element analysis of clinical computed tomography scans: a prospective randomized
clinical trial, Arthritis Rheum. 58 (11) (2008) 3340–3349.
10. T.M. Keaveny, M.L. Bouxsein, Theoretical implications of the biomechanical fracture threshold, J. Bone Miner. Res. 23 (10) (2008) 1541–1547.
10
Kinematics of the Aging Spine: A Review
of Past Knowledge and Survey of
Recent Developments, with a Focus
on Patient-Management Implications
for the Clinical Practitioner
Adam K. Deitz, Alan C. Breen, Fiona E. Mellor, Deydre S. Teyhen, Kris W.N. Wong, Monohar M. Panjabi
k e y p o i n t s
Functional testing of the spine (the flexion/extension and lateral bending
x-rays that have been the standard of care for over 60 years) is used clinically
in the detection of hypermobility and pseudarthrosis.
Over the years, many investigators have published normative ranges of
intervertebral range of motion (RoM) from asymptomatic subjects using the
current standard of care; however, all of these studies have been conducted
at a single clinical site and thus have not accounted for the RoM variability
attributable to use of different imaging equipment and testing methods that
can be found in today’s clinical practice.
By performing a meta-analysis of these studies to account for this variability
among clinical sites, the authors put forward a new set of lumbar and
cervical RoM thresholds for both ruling in and ruling out normal motion,
hypermobility, and hypermobility.
Many new technologies for assessing spine function have been proposed in
the literature, and several of these have demonstrated the ability to deliver
improved diagnostic efficacy. ese newer technologies have also revealed
important new insights into the function of the aging spine that have
implications for the clinical practitioner.
e authors put forward a set of suggested guidelines for the clinical use of
functional testing, including suggested guidelines for the current standard of
care for functional testing as well as for the newer technologies that have been
proposed in the literature.
AN INTRODUCTION TO FUNCTIONAL DIAGNOSTICS OF THE SPINE
Generally speaking, functional diagnostics are used to assess organ systems
for the purpose of detecting dysfunction, identifying the underlying physiological defects, and indicating options for therapeutic intervention. For
example, blood chemistry tests are used to assess liver function, while pulse
rate monitoring and blood pressure testing are used to assess cardiovascular function. The spine is a series of multiarticulating joints whose primary
functions are threefold: (1) to allow multidirectional motions between individual vertebrae, (2) to carry multidirectional external and internal loads,
and (3) to protect the delicate spinal nerves and spinal cord. Therefore, functional diagnostics of the spine focus on the assessment and measurement of
intervertebral motion under various environmental and movement conditions. The results are then used to help guide the management of patients
suffering from various conditions of the spine.
In discussing spinal function as it relates to the aging spine, it is
worthwhile to begin with a critical analysis of past knowledge and recent
developments regarding spinal functional testing to establish a baseline
understanding of the current state of orthopedic science. Such an analysis
reveals that the functional testing method used in today’s clinical practice —
the standard flexion/extension and lateral side bending radiographs with
which all practitioners are familiar — fails to deliver much useful diagnostic information, and is particularly poorly suited to the management of the
aging spine. This analysis further reveals that there has never before been a
comprehensive set of evidence-based guidelines put forward for the interpretation of functional testing results. This lack of a comprehensive set of
evidence-based guidelines is especially problematic given that the clinical
standard of care for functional testing has been part of the medical practice
for seven decades, has been widely adopted by the vast majority of spine
practitioners, and is routinely used on a large number of patients suffering
from a wide array of spine diseases.
Therefore the objectives of this chapter are to present this critical analysis of past knowledge and recent developments regarding functional testing of the spine for the purpose of highlighting for the clinical practitioner:
(1)recommendations on how best to interpret functional testing results,
(2)how the interpretation of these testing results is best applied to gain
insights into the kinematics of the aging spine, and (3) how newer functional testing technologies should be assessed and adopted to improve the
management of the aging spine.
THE CURRENT STATE OF THE ART: DIAGNOSTIC EFFICACY OF TODAY’S FUNCTIONAL TESTING METHOD
The current clinical standard of care for performing functional testing of
the spine was introduced in the 1940s
scores of published investigations. Today’s method is beset by multiple performance problems
fact, has been proven useless in differentiating normal from abnormal spinal
function.
critical that, as a starting point, practitioners understand the limitations of
this method so testing results are interpreted appropriately.
4–7
2,3
and, although many practitioners are unaware of the
In holding true to the tenets of evidence-based medicine it is
1
and has since been the subject of
Range of Motion (RoM) Measurements
Today’s method for conducting functional testing of the spine (flexion/
extension and lateral bending radiographs, which are referred to in this text
as the clinical standard of care) involves capturing standard radiographs of
51
52
P A R T I I Basic Science of the Aging Spine
the spine as subjects bend, and then hold their spines fixed in the extremes
of motion in either the sagittal (in the case of flexion/extension) or coronal
(in the case of lateral bending) planes. These studies are separate to, but
often used as an adjunct with, other medical imaging studies such as plain
radiographs or CT scans in the diagnostic assessment of a patient’s spine.
When performing these motions, each subject bends in each direction to his
or her own maximum voluntary bending angle (MVBA).
These two images taken at the extremes of trunk bending within a single plane are then interpreted — either manually using a pen, ruler, and
protractor or more recently, with the advent of digital imaging, an imaging
workstation — to derive range of motion (RoM) measurements. RoM measurements represent the total displacement between any two vertebrae during MVBA bending, and are expressed as both angulations, as measured in
degrees and referred to in this text as the intervertebral angle (IVA) in either
the coronal or sagittal plane, and translations in the sagittal plane, measured
in millimeters and referred to in this text as the intervertebral translation
(IVT). See Figure 10-1 for a simplified diagram showing how IVA and
IVT are derived from radiographic images.
RoM is defined by the rotation of the body (IVA) and the transla-
tion of a point on the body (IVT). While the rotation is unambiguous,
the translation is not. The translation is different for different points of the
vertebral body and, additionally, it is subject to magnification and distortion
MVBA:
extension
on radiographs. This ambiguity has led to: (1) the introduction of multiple techniques for selecting points on the vertebral body and measuring
2,4,8,21,22
IVT;
for what constitutes translational instability;
tiple systems for scoring and classifying translational instabilities (there have
been the Myerding scale,
scale
(2) attempts to define standardized displacement thresholds
10
12
for scoring translational instabilities, as well as the Wiltse13 system
the Newman Scale,11 and the modified Newman
9
and (3) the proposal of mul-
for classifying them).
Despite the multiplicity of different methods that have been proposed over the years, the Myerding system has become the most widely
used in clinical practice and has thus emerged as the standard system by
which translational instability is graded. The Myerding system categorizes
the severity of a translational instability based upon IVT measurements
expressed as a percentage of the total superior vertebral body length (also
measured in millimeters): grade 1 is 0% to 25%, grade 2 is 25% to 50%, and
grade 3 is 50% to 75%;
Grade 4 is 75% to 100%; over 100% is spondyloptosis, when the vertebra completely falls off the supporting vertebra. One key advantage of the
Myerding system is that it is a relative grading system, meaning that it helps
to control for distortion and magnification errors that can be associated
with absolute measurements of displacement (millimeters) derived from
radiographic images.
Neutral
MVBA:
flexion
Flexion-extension
bending to MVBA
Standard radiographs
(lateral lumbar views)
Derive IVA measurement
(° of rotation)
Derive IVT measurement
(millimeters of translation)
IVT (mm)
IVA°
Intervertebral translation apparent in bending radiographs
Intervertebral translation apparent in a neutral radiograph
IVT (mm)
IVA°
IVT (mm)
F IG UR E 1 0- 1 Simplified diagram of how IVA and IVT are derived from radiographic images.
Although IVT measurements have been the subject of intense investigation over the years, it is not a topic about which there is currently much
debate. This topic was thoroughly explored in studies published in the 1970s
through 1990s; however, in the past 15 to 20 years a de facto consensus has
emerged with respect to the use of the Myerding system as the clinical gold
standard for grading translational instability cases. The same is not true for
IVA measurements, as no consensus has emerged with respect to the clinical application of IVA despite a very large volume of recent investigational
activity. Therefore the remainder of this chapter will present a review of
past and current knowledge with respect to IVA, with a particular focus on
patient-management implications for treatment of the aging spine.
IVA is used clinically to assess intervertebral articulation in either the
sagittal or coronal planes, and as such should theoretically be capable of
detecting six specific types of intervertebral functional presentations (see
Figure 10-2):
1. Normal Motion: IVA that is considered normal (i.e., between the
second and ninety-eighth percentile of what is observed among normal healthy subjects)
2. Hypomobility: IVA that is abnormally low (i.e., below the second
percentile). Note that stiffness and hypomobility are not the same
thing; stiffness is a mechanical characteristic of the functional spinal
unit (FSU), while hypomobility is a measurement representing the
observed response of the FSU to gross spine bending. In that sense,
hypomobility can be viewed as a proxy measurement of stiffness.*
3. Rotational Hypermobility: IVA that is abnormally large (i.e., above
the ninety-eighth percentile). In today’s medical practice, rotational
hypermobility is considered a form of instability.
4. Immobility: e lack of any motion at all (IVA = 0°). In practice,
the U.S. Food and Drug Administration (FDA) considers any IVA
in the lumbar or cervical spine of up to 5° as effectively immobile
for the purpose of evaluating arthrodesis status following a fusion,
although the literature is equivocal and contradictory regarding the
use of this 5° threshold,
lines endorse this use of IVA in assessing arthrodesis status only as
an adjunct.
16
14,15
and recently published treatment guide-
5. Pseudarthrosis: e presence of motion in a level for which a fusion
has been previously attempted. Although theoretically this would
include any IVA greater than 0°, according to the FDA standards
described above, this only includes IVA of greater than 5°.
6. Paradoxical Motion: e presence of motion in the direction
opposite to that of the spine bend (IVA < 0°). e term “paradoxical motion” was coined by Kirkaldy-Willis,
observed by Knutsson. It has been more recently discussed in other
published studies.
would be considered a form of instability.
18
In today’s medical practice, paradoxical motion
17
although it was first
However, there is a large gap between those six presentations that should
theoretically be detectable, and those that are actually detectable with the cur-
rent clinical standard of care. This gap is thoroughly explored in the following sections, and must be understood by the clinical practitioner in order to
properly interpret functional testing results.
Measurement Variability in Range of Motion (RoM) Measurements
As with any quantitative diagnostic measurement parameter, measurement variability is the key driver of diagnostic efficacy in the application
of such measurements to differentiate between the various types of patient
presentations. Simply stated, measurement variability is the enemy of effective diagnosis: the higher the measurement variability, the less effective the
resulting diagnosis. In the case of RoM measurements, it has been shown
that measurement variability is high
causes and effects of this measurement variability are well understood; however, the implications for the clinical practitioner have rarely been discussed
*In engineering terms, stiffness is measured in Newton-meters per degree (N·m/°) while
hypomobility is measured in degrees (°). However if one views the motion response of the FSU
to a spine bend as an indicator of the mechanical stiffness of the FSU, then hypomobility can be
viewed as a proxy measurement of stiffness.
2,3
and diagnostic efficacy is low.
4–7
The
C H A P T E R 1 0 Kinematics of the Aging Spine
Observed
relative
frequency
among a
population of
asymptomatic
subjects
~2nd percentile Mean0°
IVA: Degrees of Intervertebral Rotation
Paradoxical Hypomobile
Immobile Pseudarthrosis
F IG UR E 1 0- 2 Theoretical framework for the detection of six func-
tional presentations based on IVA measurements.
95.5% of subjects
2SD +2SD
~98th percentile
Normal Hypermobile
(for previously fused levels)
53
in the published literature. Therefore one of the main goals of this section is
to present a data-driven analysis of RoM measurement variability and how
this variability should be taken into account in the interpretation of functional testing results used in the diagnosis of spine disease and management
of the aging spine.
RoM measurement variability is composed of variability between/
within observers, and variability between/within subjects. Variability between
observers is referred to as interobserver variability, while variability associated with a single observer taking multiple measurements at different points
in time is called intraobserver variability (also called test/re-test variability).
Similarly, variability between patients is referred to as intersubject variability,
while the variability of any given patient between multiple tests taken at
different points in time is referred to intrasubject variability. For example,
intersubject variability can include the effects of physiologic differences from
patient to patient, whereas intrasubject variability can include variability in
the willingness of a patient to perform bending motions from test to test
(which can often be due to the influence of pain and/or fear of pain among
other things).
There is also a third component of RoM measurement variability that
relates to the variability that exists between different testing sites. Different
testing sites utilize different radiography platforms, and different imaging
platforms can produce different types of image distortion, magnification,
and other image variants. Further, different sites utilize different practices
for patient positioning and image analysis. These variations among testing
sites can directly contribute to RoM measurement variability and therefore
must also be taken into account. For the purpose of this discussion, this variability among different testing sites will be referred to as intersite variability.
The different types of RoM measurement variability mentioned in the
preceding paragraphs are interrelated in several ways that can be best understood through the concept of “accumulating” variability. As previously discussed, intra-subject variability is a measurement of the test/re-test variation
within a given subject, while inter-subject variability is a measurement of the
variability across a population of subjects. However, since the RoM measurement from any given subject is affected by intra-subject variation, then
any measurement of inter-subject RoM variability across multiple subjects
would necessarily “accumulate” the combined effects of intra-subject variation and inter-subject variation. The same concept holds true for measurements of inter-observer RoM variability, namely that these measurements
accumulate the effects of both intra-observer and inter-observer variation.
This concept of “accumulation” of variability also applies to the overall
relationship between observer-related variability (interobserver and intraobserver variability) and subject-related variability (intersubject and intrasubject variability). Subject-related variation in intervertebral motion exists as
an inherent property of the physiology of the spine. In other words, there is a
certain amount of variation that is inherent to the way the spines of different
people move, or in the way a given person’s spine moves at different points in
time. For this discussion, we will refer to this inherent variation as the “pure”
intrasubject and intersubject variability. However it is impossible to measure
54
Diagram of “Accumulating” Measurement Variability
P A R T I I Basic Science of the Aging Spine
“Pure” Intra-subject
(Test/re-test
variation)
Intra-observer
Inter-observer Observed
“Pure” Inter-subject
(natural physiologic
variation)
Inter-subject
Observed
=
(variation in imaging
equip & processes)
Intra-site
this “pure” intrasubject and intersubject variability without constructing an
observational system to take measurements, and any observational system
constructed to take measurements is also subject to both intraobserver and
interobserver variability. Therefore any measurement of intersubject variability, for this discussion called “observed intersubject variability,” necessarily
“accumulates” the combined effects of both observer-related variability and
subject-related variability.
See Figure 10-3 for a simplified conceptual diagram of how selected
types of RoM measurement variability interrelate through the accumulation of measurement variability.
Using Normative IVA Data to Detect Normal Motion, Hypomobility, and Hypermobility
As previously discussed, it is theoretically possible to use normative IVA data
from a population of asymptomatic subjects to differentiate normal from
hypomobile and hypermobile intervertebral motion (see Figure 10-2). How-
ever, with the current standard of care for conducting spinal functional testing, only hypermobility and pseudarthrosis can be detected with an acceptable
level of statistical confidence. This fact, although not widely discussed, has
very significant implications in terms of patient management, which are discussed later in this section. However as a starting point to this discussion, it
is necessary to first re-examine the conventional wisdom regarding what is
currently considered “normal healthy” intervertebral rotation.
As a general biostatistical principle, a quantitative diagnostic value is considered an outlier and therefore abnormal if it lies above or below two standard deviations of the mean value that is observed among a representative
sample of normal healthy subjects (the mean plus and minus two standard
deviations represents approximately 95.5% of all observed values). Therefore,
the magnitude of such standard deviations will determine the specific ranges
or IVA that should be considered normal versus hypomobile or hypermobile.
Many investigators over the years have conducted studies of IVA values across
asymptomatic populations for the purpose of producing such ranges, yet all of
these investigators are plagued by the same Achilles’ heel: they are all singlesite studies and therefore fail to account for intersite variability. Thus every
single-site study underestimates IVA measurement variability and therefore
produces unreliable ranges of what constitutes normal versus hypomobile or
hypermobile intervertebral rotation. However, by conducting a meta-analysis
of these studies it is possible to account for this intersite variability and produce more representative ranges of what constitutes normal IVA.
In conducting this meta-analysis, a total of 22 published IVA datasets
were identified (15 lumbar and 7 cervical). Each dataset was carefully examined and screened to ensure that: (1) the method for measuring IVA was
consistent with the current clinical standard of care, and (2) the variability (standard deviation, or SD) among observed IVA values was published
along with the mean. After applying this screen, three lumbar datasets and
four cervical datasets qualified for this meta-analysis. See Table 10-1 for a
list of all 22 datasets that were considered.
After including all qualifying datasets, the following values were tabulated for the mean and standard deviation of observed IVA values taken
from multiple populations of asymptomatic subjects across multiple sites
“Pure” Inter-site
F IG UR E 1 0- 3 Simplified conceptual diagram of
the “accumulation” of RoM measurement variability, which
applies to both IVA and IVT measurements. Note that this diagram is considered simplified because it does not represent
every possible type of measurement variability. For example,
observed intrasubject variability is not represented. This simplified diagram represents the interrelationships between
those types of measurement variability that are most important for the clinical practitioner to understand in evaluating
the performance of today’s in vivo methods of spinal functional testing.
Observed
Inter-site
(Table 10-2). The standard deviation values in the “Aggregated Across Sites”
column at the far right of each table represent the standard deviation of the
superset created by combining the observed values from all sites, and represents the observed intersite variability associated with the current standard
of care for measuring IVA at each level, while the standard deviation values
for each investigator represent that investigator’s site’s observed intersubject/
intrasite variability.
Using these normative values that account for the effects of intersite variability, it is possible to produce threshold IVA values that represent hypomobility and hypermobility, as given in Table 10-3.
Effects of IVA Measurement Variability
on the Diagnostic Efficacy of Functional
Testing of the Spine
To quantitatively assess the diagnostic efficacy of using IVA to detect different functional presentation (hypomobility, hypermobility, normal motion,
etc.), it would be necessary to have a gold standard method for identifying true
positives and true negatives for each type of functional presentation. If such
a gold standard method existed, it would then be possible to quantitatively
assess diagnostic efficacy with the traditional diagnostic efficacy parameters
of sensitivity (Sn), Specificity (Sp), and the positive/negative likelihood ratios
(+LR and –LR). however, the authors are unaware of that any such gold
standard exists* and it is therefore impossible to measure these traditionally
used diagnostic efficacy parameters. Therefore in this discussion of diagnostic efficacy associated with IVA measurements, these efficacy parameters will
be described qualitatively in lieu of being able to quantitatively measure them.
As reflected in the hypomobility and hypermobility thresholds given in
Table 10-3, the current standard of care for measuring IVA involves a high
degree of measurement variability. This high degree of measurement variability, in turn, has disastrous consequences on the diagnostic efficacy of
using IVA to detect intervertebral motion dysfunction. The first problem
lies with the very low thresholds for detecting intervertebral hypomobility.
Vertebral levels with IVA measurements of less than 2° to 5° are generally considered to be fused.
any IVA of up to 5° as effectively immobile for the purpose of evaluating
arthrodesis status following a fusion. Therefore, because the hypomobility
thresholds are all below the FDA’s 5° threshold for what is considered a fused
FSU (except at C4/C5; Table 10-3), it is impossible to use IVA to differen-
tiate hypomobile motion from a fusion, effectively rendering hypomobility
an undetectable condition. A second consequence of this overlap between
what is considered normal and hypomobile motion with what is considered a fused FSU is that one is guaranteed reduced specificity in detecting immobility as well as reduced sensitivity in detecting normal motion
(because a “true normal” with an observed IVA of less than 5° is both a false
*is is true for immobility, hypomobility, normal motion, and hypermobility. However, there
is a “gold standard” available for the detection of pseudarthrosis, which involves the intraoperative examination of a previously fused level during a revision surgery. Using this “gold standard,”
Sn, Sp, -LR and +LR for the use of IVA in detecting pseudarthrosis have been measured and
reported.
14,15
As previously discussed, the FDA considers