Introduction
In clinical practice, defining the progression of fracture healing involves, most
commonly, either serial radiography or serial computed tomography (CT), combined with
an assessment of clinical wellness. These measures rely on qualitative and quantitative
interpretations as to the state of repair and response in healing.
Measures of wellness provide an important aspect in human clinical medicine and are
commonly based on patient questionnaire responses or clinician impressions.[1]
[2] In veterinary medicine, a key indicator of patient wellness is their willingness
to ambulate. Objective measurement and analysis of locomotory function in animals[3] involves either kinematic (temporal and geometric motion characteristics) or kinetics
(forces producing or modifying motion). A locomotion scoring scale has been developed
specifically for the postoperative assessment of sheep based primarily on observable
characteristics of their gait and posture.[4] As in human clinical medicine, the qualitative data obtained from measures of wellness
are considered in conjunction with quantitative measures.
Diagnostic radiography provides insight as to whether a fracture has healed. It should
also underscore the progression of healing, enabling inference as to whether non-union
might occur allowing for early reintervention.[5] Several options are available where standardized, plain radiographs can provide
both qualitative and quantitative measures of fracture healing progress. The percentage
of bridging callus has been used to track the performance of various treatments in
animal models of long bone segmental defects.[6]
[7]
[8]
[9] Four circumferential quadrants were established requiring craniocaudal and lateromedial
radiographs allowing the measurement of callus formation over time and the comparison
of treatments. Scoring the degree of fusion apparent is another semi-quantitative
method. As with bridging callus quantitation, the radiographic union score for tibial
fractures (RUST) applies a score to each of four quadrants with the minimum score
indicative of failed union and a maximum score indicating the fracture has healed.[10] With both % bridging callus and RUST determinations, there is considerable inter-operator
variability (20–25%), impacting both the accuracy and precision of the measures obtained
which detracts from their use in clinical cases.[11]
[12]
Quantitation of optical density (OD) has been utilized in both clinical and research
environments.[13]
[14]
[15]
[16]
[17]
[18] The methods employed ultimately provide a value for OD in a given region of interest
(ROI). This has been achieved using two primary methodologies, which have allowed
comparison of OD across multiple radiographic images while controlling for factors
that may influence the results, such as exposure factors.
Some have used a reference penetrometer (aluminium step wedge) to obtain baseline
values with which to compare the progression of bone healing over the period of evaluation.[13]
[15]
[19]
[20]
[21] Evidence of strong linearity between steps (penetrometer) is essential to confer
high accuracy and precision when comparing different images. Other studies have based
their determination of OD on the manipulation and standardization of intensity (greyscale)
magnitudes.[5]
[22]
[23] A high level of association was found when comparing computer algorithm measures
and the visual interpretation made by clinicians (R
2 = 0.94). The average inter-observer variation in computer algorithm measures was
4% while clinician-based observations had a variation of 22%. By limiting any subjective
contribution, the computer algorithm has displayed a substantially lower variability
when compared with visual clinical observations.[5]
[22]
[24]
The hypothesis of the current study was that change in OD, during bone regeneration,
could be adequately quantified, using computer-based algorithms in the greyscale environment
and which would reflect the progression of bone regeneration. This study presents
data derived from plain radiographs, manipulated using different approaches and compares
these with volumetric data obtained by CT from the same sample set over a 16-week
in vivo period. The degree of linear association (correlation) between the measures
has been used to determine if the quantitation of OD may have a role in defining regeneration
of bone in fracture repair.
Materials and Methods
Data obtained from an in vivo study were utilized to evaluate the utility of using
qualitative or quantitative data as a means of tracking bone regeneration following
surgical reconstruction of a mid-diaphyseal, tibial segmental defect. The study involved
the use of skeletally mature, 3-year castrated male Merino sheep. The animal utilization
protocol was approved by the Animal Care and Use Review Committee, Department of the
Army (US – DARPA-FY08–019) and the undertaking of Institutional Animal Care Committees
(SA Path: 111.12).
Study Protocol
A unilateral, 3.5-cm mid-diaphyseal tibial segmental defect (n = 8), was created and reconstructed using a locking intramedullary nail in combination
with autograft bone using methodologies developed elsewhere.[6]
[7]
[9]
[10]
[11] It has been shown that a 3.0-cm defect in the tibial diaphysis is a ‘critical defect’
resulting in 100% non-union when void-fillers are not used.[9]
Following pre-medication (xylazine: 0.1 mg/kg intramuscularly), anaesthesia was induced
using thiopentone [50–70 mg/kg body weight intravenously (i.v.)]. A cuffed endotracheal
tube allowed the maintenance of gaseous anaesthesia with isoflurane (2%) in oxygen
(flow rate: 15 L/min). All sheep received pre-emptive cephalosporin (Kefzol: 22 mg/kg
body weight, i.v. daily; Sdpen Pharmacare Australia Pty Ltd, St. Leonards, NSW, Australia)
and meloxicam (0.2 mg/kg i.v. daily: Boehringer Ingelheim Pty Ltd, North Ryde, NSW,
Australia) during surgical preparation and analgesia, via a constant infusion backpack
pump (xylazine: 0.5 mg/h i.v.) initiated at the time of extubation; all drugs were
administered to all sheep for an initial 3-day period postoperatively and continued
if deemed necessary.
In all sheep, a 24 cm × 8.5 mm titanium Trigen Metanail (Advanced Surgical Devices,
Smith and Nephew Surgical, Memphis, Tennessee, United States) was used in reconstructing
the 3.5-cm mid-shaft defect. A standardized mid-diaphyseal defect, using known anatomical
landmarks (proximal medial tibia and distal medial malleolus) was created prior to
reconstruction; a 3.5-mm cutting guide provided precise and reproducible defect dimensions.
Autograft bone was obtained by morselizing the segment of cortical bone removed into
3 to 4 mm chips (Aesculap Bone Mill, B. Braun, Bella Vista, NSW, Australia). Bone
chips were combined with medullary content (fat) forming a gruel, which was packed
into the defect following the application of four 4.0-mm titanium locking screws (Trigen
internal hex capture screw, Advanced Surgical Devices, Smith and Nephew Surgical),
two proximal and two distal. Wound closure was performed using 3.5 metric polyglactin
910 suture (Vicryl: Ethicon Inc., Cornelia, Georgia, United States). Metal staples
were used for skin closure (Covidien, Medtronic, Minneapolis, Minnesota, United States).
All sheep were recovered in a weight-bearing sling in which they remained for 3 weeks;
thereafter, they were maintained in soil-floored pens allowing unrestricted movement.
Serial in vivo examinations (radiology and CT) occurred immediately postoperatively
and at 4, 8, 12 and 16 weeks while the sheep were under general anaesthesia.
Data from serial radiographic and CT examinations were incorporated into the analysis
performed. Comparisons were made between qualitative clinical measures (% bridging
callus, RUST and locomotory function) and quantitative measures (volumetric analysis,
OD) obtained from each ROI or volume of interest (VOI).
Using standardized radiographic technique (Villa Visitor mobile X-ray, Buccinasco,
Italy: 54–56 kVp, 6–8 mA, focal length 120 cm), both craniocaudal and lateromedial
DICOM (Digital Imaging and Communications in Medicine) images were obtained (Carestream
Vita LA processor, Carestream, Rochester, New York, United States). Computed tomography
was performed (Phillips Brilliance, North Ryde, NSW, Australia) using the acquisition
parameters 120 kVp, 200 mA/slice, 1-mm slice thickness and 200 mm field of view, producing
a matrix of 512 × 512. Primary manipulation of image files was performed using the
OSIRIX MD software (v2.9, 64-bit, Pixmeo, Switzerland).
For accurate and reproducible determination of both the radiographic ROI and the computer
tomographic VOI, the immediate postoperative images provided a template for all subsequent
ROI and VOI delineation; this relied on the known dimensions of the nail and the distance
(mm or pixels) from the locking screw proximal and distal to the defect ([Fig. 1]). For both radiographic and CT evaluations, the ROI and VOI related specifically
to the defect created and did not involve either proximal or distal cortical bone.
Fig. 1 A schematic depiction of immediate postoperative (A) and 16-week (B) 3-D reconstructions (i) and mutually orthogonal views used in the analysis showing
craniocaudal (ii) and lateromedial (iii) projections. The yellow-lined rectangles
highlight the volumes of interest used in the analysis. Reference locations (proximal
and distal locking screws) are depicted.
Following collection of raw data, image sets were evaluated to build a picture of
the progression of defect healing and to evaluate the degree of association between
the methods employed using Pearson product–moment correlation.
Qualitative Assessments
Bridging Callus
The craniocaudal radiographic view allowed quantitation of % bridging callus along
the lateral and medial aspects of the defect.[6]
[7]
[25]
[26] Similarly, the latero-medial view allowed quantitation of the bridging callus along
the cranial and caudal aspects. Because of possible differences in image magnification,
pixel values were used to enable quantitation. A value of 0% indicated no bridging
callus, while 100% indicated complete bridging. For each individual animal, at each
time point (postoperative, 4, 8, 12 and 16 weeks), and for each anatomical location
(cranial, caudal, lateral and medial), the mean and standard deviation of data were
compiled allowing comparison with the other methodologies under consideration.
Modified Radiographic Union Score for Tibial Fractures
Using the same radiographic projections and anatomical locations as above, visual
scoring assigned a numerical value for each anatomical location. A modified version
of RUST (mRUST) was used, providing more appropriate scoring for callus formation
in the current segmental defect study, as opposed to that which is used in clinical
cases. A score of 1 reflected no evidence of callus; a score of 2, minimal callus
formation; a score of 3, moderate callus formation; a score of 4, advanced callus
formation; and a score of 5, complete bridging. Individual quadrant scores were summed
to give a total for that particular examination (4 being the minimum score indicating
poor healing or non-union and 20 being the maximum score with all quadrants indicating
complete bridging). The mean circumferential value was compiled by pooling data obtained
from each quadrant.
Locomotory Function
A validated 7-point numeric scale (0 to −6) was used to grade the postoperative locomotory
performance of sheep enrolled in the study.[4] The scale ranged from ‘normal’ (zero) to ‘unable’ to stand or move with descriptions
of locomotion for each increase in score severity. Scores were recorded preoperatively
and at 4, 8, 12 and 16 weeks postoperatively for all individuals.
Quantitative Assessments
Volumetric Analysis
Computed tomography was used to generate DICOM files of the VOI (defect). This was
performed immediately post-surgery and at 4, 8, 12 and 16 weeks postoperatively for
all individuals. Pixel resolution of the images obtained was 0.408 mm with a slice
interval of 0.5 mm. The images were processed using custom software (GPU Volumetric
re-sampler; GRIT, Adelaide, Australia) to remove variations in the VOI, resolution
and voxel shape. Raw binary files containing the voxel data were subject to a 3-D
Gaussian blur, with sub-voxel radius applied to the datasets to remove speckle and
artefact contributed by the nail. Re-sampling was then undertaken using 3-D bilinear
sampling to maximize the data quality and minimize information loss. The final output
was a raw 16-bit greyscale image stack with a voxel size of 0.123 mm3 (0.5 mm × 0.5 mm × 0.5 mm). Automated thresholding, based on a histogram of each
single bone volume (BV), was performed. This removed subjectivity that might have
been present had the threshold been manually selected; a value of 108% was chosen
ensuring the lowest possible threshold was selected so as to include bone from which
the soft tissue was excluded.
Two, mutually orthogonal axial views ([Fig. 1]), within the intensity threshold range, formed the basis for voxel counts and the
quantitation of bone regeneration. Scaling to one cubic centimetre of the VOI allowed
for direct comparison of treatments using equivalent data for change in bone density
(BD; ∆BD – gr/cm3), BV (∆BV – cm3) and bone mass (BM; ∆BM – gr). Voxel intensity (grey-level) is proportional to density; this value was multiplied
by voxel count (volume) to provide an estimate of BM.
All data were ‘normalized’; each of the data counts obtained were divided by the first
data output (postoperative); as all VOIs were the same, it was reasonable to make
comparisons of the data between the different sheep.
Optical Density
All standard radiographic images (DICOM) were converted to greyscale (GIMP, GNU Image
Manipulating Program v.2.8.20, https://www.gimp.org). The intensity of each pixel was expressed within a given range between a minimum
(0 = black) and a maximum (255 = white) with fractional values of grey in between.
Following conversion to greyscale, each image was re-introduced to the analytical
software (OSIRIX MD v2.9, 64-bit, Pixmeo) for delineation of ROIs and generation of
OD values ([Fig. 2]). One observer (J.R.F.) performed the analysis; intra-observer kappa values were
generated.
Fig. 2 A schematic depiction of the radiographic projection (lateromedial or craniocaudal)
and anatomic location (cranial, caudal, lateral or medial) of measures obtained. Regions
of interest (ROIs) are defined for each projection; the solid rectangles reflect the
ROI for quantitation of greyscale value for the nail. The ROIs for autograft, within
the defect, are also highlighted (yellow line).
All data were normalized with regards to the range of greyscale values (0–255). Assuming
a linear relationship between 0 and 255, the raw OD value of the nail was normalized
to OD 255 for both radiographic views (cranial, caudal, lateral and medial), at each
time point and in each individual. Regions of interest from raw images were defined
using the draw function of the OSIRIX MD software. The number of outlined pixels was
converted to a metric area and the mean OD of that area automatically quantitated.
The resultant raw OD values were normalized using the factor defined in normalizing
the OD of the nail. The normalized OD value of the nail in the craniocaudal projection
was used to normalize the ROI data in the lateral and medial anatomical aspects of
the reconstruction, while normalized OD values of the nail in the lateromedial projection
were used to normalize the ROI data in the cranial and caudal anatomical aspects of
the reconstruction. Normalizing OD data from each quadrant allowed the development
of a circumferential impression of normalized OD for each treatment at each time point
considered (postoperatively, 4, 8 and 12 weeks) and for each individual, on which
to make comparisons. The normalized, raw data were also modified defining the immediate
postoperative values to time zero; this assisted in removing possible artefact associated
with the nail.
All data were subject to multivariate analysis of variance with Bonferroni post hoc
assessment; a probability of p < 0.05 was deemed significant. An assessment of association was undertaken by submitting
the data to a Pearson product–moment correlation (Data Desk v6.3, Data Description,
Ithaca, New York, United States). Quantitative data measures (volumetric analysis
and OD) were repeated in a blinded manner and evaluated for intra-observer variation
(kappa statistic).
Results
Qualitative and quantitative data were collected from eight animals that underwent
creation and reconstruction of a tibial segmental defect using a locking intramedullary
nail combined with autograft bone.
There were no surgical complications, nor withdrawals from the study.
Qualitative Assessments
Visual appraisal of plain radiographs, documenting bridging callus formation ([Fig. 3A]) and compilation of mRUST scores ([Fig. 3B]), combined with assessment of locomotory function ([Fig. 3C]), allowed description of qualitative data as follows.
Fig. 3 A graphical depiction of the trends observed in qualitative data (% bridging callus,
A; mRUST, B; and locomotory score, C). Individual measures have been labelled either union or delayed union; individuals
defined as delayed union are shown in blue. The mean and standard deviation of the
pooled individual data are presented.
Bridging Callus
There was a steady increase in the amount of bridging callus formation over 8 to 12
weeks post-reconstruction ([Fig. 3A]). In all but two animals, bridging was complete by 16 weeks. The performance of
two sheep, with delayed union, is highlighted graphically. Initially, there was large
variation around the means as might be expected in rapidly forming new bone. By 12
weeks, this variation was largely eliminated. The passage of time proved a significant
factor in the formation of bridging callus (p = 0.0001). Pearson product–moment correlation was r = 0.999 in consideration of bridging callus (%) and mRUST, indicating a strong association
between these two qualitative measures.
Modified Radiographic Union Score for Tibial Fractures
Similarly, there was a steady increase in mRUST scores through 12 weeks post-reconstruction
([Fig. 3B]). The performance of two individuals with delayed union, is also highlighted graphically.
The passage of time proved a significant factor in the scores (p = 0.0001).
Locomotory Function
Conversely, locomotory function ([Fig. 3C]) showed poor association with bridging callus (r = 0.029) and mRUST (r = 0.046). As expected postoperatively, there was a rapid decrease in locomotory function
over 4 to 8 weeks post-reconstruction. Thereafter, there was a gradual return to preoperative
levels by 16 weeks. The passage of time was a significant factor in the scores obtained
(p = 0.0001).
Quantitative Assessments
A graphical depiction of volumetric parameters (∆BD, ∆BV, ∆BM) is shown in [Figs. 4]
[5]
[6]. Optical density measures are depicted graphically in [Fig. 7]. For each measure, the trend was similar, with a decrease apparent through 4 weeks
post-reconstruction followed by a gradual and consistent increase to the time of retrieval.
Fig. 4 A graphical depiction of changes in bone density (∆BD), over the in vivo period post-reconstruction. The raw data (A) and normalized data (B) are shown. Individual measures have been labelled either union or delayed union;
individuals defined as delayed union are shown in blue. The mean and standard deviation
of the pooled individual data are presented.
Fig. 5 A graphical depiction of changes in bone volume (∆BV), over the in vivo period post-reconstruction. The raw data (A) and normalized data (B) are shown. Individual measures have been labelled either union or delayed union;
individuals defined as delayed union are shown in blue. The mean and standard deviation
of the pooled individual data are presented.
Fig. 6 A graphical depiction of changes in bone mass (∆BM), over the in vivo period post-reconstruction. The raw data (A) and normalized data (B) are shown. Individual measures have been labelled either union or delayed union;
individuals defined as delayed union are shown in blue. The mean and standard deviation
of the pooled individual data are presented.
Fig. 7 A graphical depiction of the trend in optical density measures for individuals over
the in vivo period post-reconstruction. The raw data (A) and normalized data (B) are shown. Individual measures have been labelled either union or delayed union;
individuals defined as delayed union are shown in blue. The mean and standard deviation
of the pooled individual data are presented.
Volumetric Analysis
Changes in BD ([Fig. 4A, B]) were not uniform with the passage of time and were not significant (p = 0.089). Bone density had strong correlation with both BV (r = 0.814) and BM (r = 0.818). Bone volume ([Fig. 5A, B]) and BM ([Fig. 6A, B]) displayed significant differences with the passage of time (BV: p = 0.001, BM: p = 0.002) and were strongly associated (r = 1.000).
For each parameter, those specimens adjudged to be delayed union have been highlighted
graphically.
Optical Density
The passage of time was shown to have a significant impact on the measured OD (p = 0.0001) reflecting the regenerative process. [Table 1] presents Pearson product–moment correlation values for all interactions within and
between the qualitative and quantitative data.
Table 1
Pearson's product–moment correlation (r) values within and between qualitative and quantitative datasets
|
Qualitative data
|
Quantitative data
|
|
Callus
|
mRUST
|
LOCOMOTION
|
|
BD
|
BV
|
BM
|
OD
|
|
Callus
|
1.000
|
|
|
|
0.775
|
0.728
|
0.731
|
0.802
|
|
mRUST
|
0.999
|
1.000
|
|
|
0.791
|
0.743
|
0.746
|
0.823
|
|
LOCOMOTION
|
0.029
|
0.046
|
1.000
|
|
0.449
|
0.684
|
0.681
|
0.501
|
|
BD
|
1.000
|
|
|
|
|
BV
|
0.814
|
1.000
|
|
|
|
BM
|
0.818
|
1.000
|
1.000
|
|
|
OD
|
0.824
|
0.957
|
0.959
|
1.000
|
Abbreviations: BD, bone density; BM, bone mass; BV, bone volume; mRUST, modified radiographic
union score for tibial fracture; OD, optical density.
Note: Italicized text reflects poor to moderate correlation.
Measures of OD have shown strong correlation with the qualitative measures of bridging
callus (r = 0.802) and mRUST (r = 0.823). Likewise, OD was strongly correlated with BD (r = 0.824), BV (r = 0.957) and BM (r = 0.959). A graphical depiction of the changes in OD show a similar trend, as seen
in other quantitative values, with an initial decrease, during the resorptive phase,
followed by a steady increase in value between 8 and 16 weeks post-reconstruction
([Fig. 7A, B]). Of note are the OD changes observed for both delayed union individuals, although
they could not be shown to be significantly different from ‘union’ individuals (p > 0.05).
[Fig. 8] depicts the plot of qualitative data ([Fig. 8A]) and quantitative data ([Fig. 8B]) versus OD; correlation values are highlighted and are strong.
Fig. 8 A graphical depiction of the data points for qualitative data (A: % bridging callus, mRUST) and quantitative data (B: bone density, BD; bone volume, BV; and bone mass, BM) when plotted against optical
density (greyscale). The lines represent best fit to the data with the resultant Pearson
product–moment correlation value for each of the correlations depicted.
Discussion
The establishment of standardized clinical measures of fracture healing remains elusive.
The key aspects of fracture repair are the following: when is the repair complete
and when can normal ambulation be undertaken?
No currently available qualitative or quantitative measure is capable of accurately
defining these requirements. We continue, therefore, to place reliance on a compilation
of qualitative and quantitative measures to provide insight, but these are not definitive.
Recent studies[27]
[28]
[29] have used differentially loaded radiostereometric analysis as a means of providing
a non-invasive quantitation of construct stiffness for healing tibial fractures. From
this, reconstruction strength can be extrapolated, but it does not provide a measure
of tolerance to loading, which is critical in defining an appropriate end to convalescence.
The current study has investigated what, if any, contribution measures of OD could
make in the assessment of fracture healing. The potential utility of this method was
its reliance on serial plain radiographs, simply analysed using computer-based algorithms
in the greyscale environment. A key factor in developing this method was based on
the normalization of OD data using the metallic fixation device to represent the maximum
OD value (255) while assuming a linear relationship between 0 and 255 greyscale units.
The OD data obtained were then correlated with both qualitative and quantitative measures
from the same specimens. In this regard, OD was strongly correlated with the other
measures (bridging callus, r = 0.802; mRUST, r = 0.823; ∆BD, r = 0.824; ∆BV, r = 0.957; and ∆BM, r = 0.959).
Qualitative measures (bridging callus and mRUST) suffer from poor inter- and intra-observer
agreement.[4]
[12]
[13]
[14] This variability is diminished with the removal of operator effects through the
use of computer-based algorithms. To evaluate this aspect, both the volumetric and
OD data measures were repeated to determine the degree of intra-observer agreement,[30] which was substantial (k = 0.82). Any future study should address inter-observer agreement to confirm the
utility of these measures.
At the time of retrieval, two of eight specimens were adjudged as delayed union; this
was based on their radiographic appearance, response to torsional loading and histology
(loading and histological data presented elsewhere). These specimens have been highlighted
in each of the graphical depictions of the data ([Figs. 3]
[4]
[5]
[6]
[7]). For bridging callus, mRUST scores, volumetric measures and OD, these two individuals
have displayed variable responses in all the parameters measured and which could not
be utilized to confirm delayed union. This highlights the fact that, even in the face
of strong radiographic and CT evidence for union, it is ultimately the tolerance to
loading that provides the conclusive assessment.
There are several issues that require further investigation to obtain a more complete
picture as to the state of fracture healing:
-
The determination of bone union is fraught; current clinical practice relies on subjective
assessments of radiographs and CT. A key element is load-bearing capacity; serial
measures of torsional stiffness in human patients is currently being evaluated using
differentially loaded radiostereometric analysis[27]
[28]
[29] and shows great promise; however, it also is used in combination with radiographic
and CT imaging to make a final judgement as to the state of healing.
-
It can be asserted that the presence of autograft bone in the defect and the presence
of the locking nail may interfere with the accuracy of the measures obtained (bridging
callus and mRUST). In evaluating radiographs for bridging callus formation, the new
bone growth along the outer aspect of the defect was evaluated and compared with the
postoperative images. New bone immediately adjacent to the nail could not be evaluated
in these measures.
In performing the volumetric analysis, the potential ‘artefact’ provided by either
the nail or the autograft bone has been taken into account by normalizing all later
time point data to the data outputs obtained immediately postoperatively. The initial
decrease in parameter value over the first 4 weeks likely reflects the resorptive
process commonly associated with the use of bone autograft. Bone density varied with
the passage of time and was most likely a consequence of substantial variations in
BD between individuals with resultant large variations about the means. This may have
been impacted through variability inherent in the autograft bone although a standardized
amount of bone was used in each animal.
This study has enabled the evaluation of fracture healing in a sheep tibial critical
defect model. Both qualitative (% bridging callus, mRUST and locomotion score) and
quantitative data (CT volumetric analysis and OD) have been utilized to build a picture
of the progression of healing over a 16-week in vivo period post-reconstruction. None
of the measures provide a comprehensive assessment as to the state of healing in isolation
but do allow trends to be delineated. The degree of association between the parameters
measured has been shown to be variable ranging from poor to strong. Ultimately, however,
it is the response to load bearing that provides the ultimate test of fracture healing
in combination with the measures undertaken in this study. As discussed, differentially
loaded radiostereometric analysis is one possible means of determining fracture stiffness,
in a serial manner, in the clinical setting; this is the subject of an on-going evaluation.
Changes in OD have been evaluated as a clinical tool,[15]
[16]
[17]
[18]
[19]
[20] but its utilization is not widespread. This study lends support to the concept that
measures of OD can contribute to our understanding of bone regeneration in fracture
healing and warrants consideration for use in the clinical setting.
