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The Use of Tomosynthesis in the Global Study of Knee Subchondral Insufficiency Fractures

Rationale and Objectives

Subchondral insufficiency fractures (SIF), previously termed spontaneous osteonecrosis of the knee, are marked by a sudden onset of severe pain. Other than the size of the lesion, prediction for progression to joint replacement is difficult. The objective was to determine if quantitative analysis of bone texture using digital tomosynthesis imaging would be useful in predicting more rapid progression to joint replacement.

Materials and Methods

Tomosynthesis studies of 30 knees with documented SIF were quantified by fractal, mean intercept length (MIL), and line fraction deviation analyses. Fractal dimension, lacunarity, MIL, and line fraction deviation variables measured from these analyses were then correlated to short interval progression to joint replacement surgery.

Results

Higher odds for joint replacement were related to higher values of the standard deviation of slope lacunarity and to morphometric measures (eg, MIL).

Conclusions

Using digital tomosynthesis images for bone texture assessment may help distinguish condylar bone response in SIF, potentially acting as a clinically relevant predictive tool. In the future, contrasting SIF to the more gradual long-term process of osteoarthritis, there may be a better understanding of the different mechanisms for the two conditions.

Introduction

Subchondral Insufficiency Fractures (SIF)

The term spontaneous osteonecrosis of the knee was first described as a finding in osteoarthritis . The condition usually presents with a sudden onset of severe, acute, unilateral knee pain, mostly in women more than 50 years old. It has been renamed as there is usually no history of trauma and the majority of patients have no risk factors for osteonecrosis . Many patients have a very painful course that can be followed by resolution of symptoms over months. Progressive collapse can occur and may lead to early surgical interventions, including joint replacement . Insufficiency fractures have been linked with osteoarthritis . In broader use, the term insufficiency fracture has been defined as a fracture that occurs due to the inability of the bone to support normal loads . The term implies that an insufficiency fracture would occur only in individuals with poor bone quality or mass. However, review of a larger series of patients with SIF reveals a systemic bone mass that is above normal for age . This is in contrast to patients with early osteoarthritis who appear to have decreased bone perfusion and osteocyte activity in the femoral condyle . Histology of SIF has shown that in six of eight cases, there was no osteonecrosis, and the only areas of osteonecrosis in the remaining two were in regions of bone collapse . Four stages have been described comparing plain radiographs to histology . The radiographic stage ranged from no abnormality to a lucent area surrounded by sclerotic bone with osteoarthritic changes. Histology ranged from areas of granulation with fracture healing and no osteonecrosis, to cases of focal necrosis or complete separation. These patterns are very different from the patterns seen in secondary osteonecrosis.

Clinical Imaging in SIF

When radiographs are obtained within weeks of the onset of severe pain, they may appear normal with little or no evidence of osteoarthritic changes . The biologic activity within and outside of these lesions has been documented with fluorine-18 positron emission tomography . The overall size of the lesion correlates to what is seen on magnetic resonance imaging (MRI). The T1 or proton density-weighted image typically has a curvilinear area of decreased signal that parallels the articular margin of the subchondral bone of the proximal tibial plateaus and femoral condyles . All lesions have direct connection to the articular subchondral bone. In one review, the average surface area was 431 mm 2 (standard deviation [SD]: 218 mm 2 ) (range: 210–1025 mm 2 ) and the volume was 4.8 cm 3 (SD: 3.1 cm 3 ), placing the diameter between 0.5 and 2 cm . There are a variety of MRI bone marrow lesions seen in osteoarthritis . However, none of these have the clear line of demarcation that is seen in SIF ( Fig 1 ). Albeit the size of the lesion is predictive for progression to total knee replacement , smaller lesions can progress to rapid articular cartilage changes. Given that bone changes are not apparent in conventional radiology, we have not had an imaging tool that can better predict clinical outcome or help define the biologic process.

Figure 1, Coronal magnetic resonance image slice of a more advanced lesion in the medial femoral condyle. The black arrow denotes an area of subchondral collapse and fracture within the lesion. The white arrow marks an area of more proximal bone changes.

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Tomosynthesis to Evaluate SIF

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Figure 2, Standing views were obtained with the knee moved forward to press on the table pad. A table tilt of 70° with a waist restraint was used for safety reasons. A sequence of digital radiographs is obtained as the detector translates down and the x-ray tube moves up with the central beam directed at the joint surface at an angle that varies from −20° to +20° (indicated by arrows ). Coronal slice images are formed from projection images via filtered back-projection reconstruction.

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Materials and Methods

Patient Population, Demographics, and Clinical Imaging

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Tomosynthesis Image Analyses

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Figure 3, Eight regions were cropped from digital tomosynthesis stack images corresponding to (1) distal femoral metaphysis, (2) medial femoral condyle, (3) lateral femoral condyle, (4) distal femoral metaphysis/physis, (5) medial tibial plateau, (6) lateral tibial plateau, (7) proximal tibial metaphysis, and (8) proximal tibial metaphysis/physis. In statistical analyses, regions were defined as lateral (3 and 6), medial (2 and 5), central (4 and 8), and distal (1 and 7) to the joint surface.

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Figure 4, ( a ) Each of the eight square regions cropped from digital tomosynthesis images was analyzed using the fractal, MIL, and LFD analysis methods. LFD and MIL were calculated in all directions of the image. ( b ) A typical polar plot representation of the data treated as a statistical distribution, from which an average, standard deviation, maximum, and anisotropy (LFD at 90°/LFD at 0°) were calculated for each slice, giving intraslice variables such as LFD.Av, LFD.SD, etc. Fractal analysis was not directional and produced FD, λ, and S λ for each slice. ( c ) Each slice in the stack was analyzed, giving interslice distribution of the intraslice variables. Final study variables representing three-dimensional microstructure within the bone were calculated as the stack average and standard deviation of the intraslice variables, hence the notation Av(LFD.Av), Av(LFD.SD), Av(LFD.Av), etc. λ, mean lacunarity; Av, mean; FD, fractal dimension; LFD, line fraction deviation; MIL, mean intercept length; S λ , slope lacunarity; SD, standard deviation.

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Table 1

Measured Texture Parameters from DTS Images and Definitions

DTS Variable Description Slice FD Fractal dimension: measure of complexity in gray-level texture λ Lacunarity: measure of heterogeneity in the size of holes in gray-level texture S λ Slope lacunarity: rate of change in λ with size scale LFD.Av LFD average: measure of average orientation in all directions in gray-level texture LFD.SD LFD standard deviation: measure of variability in the orientation of gray-level texture LFD.Max LFD maximum: measure of maximum orientation in gray-level texture LFD.DA LFD degree of anisotropy: measure of anisotropy in gray-level texture MIL.Av MIL average: measure of average feature size in all directions of binarized texture MIL.SD MIL standard deviation: measure of variability of feature size in all directions of binarized texture MIL.Max MIL maximum: measure of maximum feature size in binarized texture MIL.DA MIL degree of anisotropy: measure of anisotropy in binarized texture Stack Av(FD) Interslice average of respective fractal parameters, representing a volume average Av(λ) Av(S λ ) Av(LFD.Av) Interslice average of respective LFD parameters, representing a volume average Av(LFD.SD) Av(LFD.Max) Av(LFD.DA) Av(MIL.Av) Interslice average of respective MIL parameters, representing a volume average Av(MIL.SD) Av(MIL.Max) Av(MIL.DA) SD(FD) Interslice heterogeneity of respective fractal parameters, representing plane to plane variation in the respective parameter SD(λ) SD(S λ ) SD(LFD.Av) Interslice heterogeneity of respective LFD parameters, representing plane to plane variation in the respective parameter SD(LFD.SD) SD(LFD.Max) SD(LFD.DA) SD(MIL.Av) Interslice heterogeneity of respective MIL parameters, representing plane to plane variation in the respective parameter SD(MIL.SD) SD(MIL.Max) SD(MIL.DA)

Parameters from fractal, mean intercept length (MIL), and line fraction deviation (LFD) analyses were measured both in whole stack (from which stack average [Av] and standard deviation [SD] were calculated) and a central slice.

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Statistical Analyses

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Results

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Table 2

Summary of the Associations Between Digital Tomosynthesis-derived Bone Texture and Lesion Site, After Accounting for Significant Anatomic Variation (Marginal Mean ± Standard Error) \*

DTS Variable At Lesion Away From Lesion_P_ Bone † P Site ‡ P Lesion § λ 0.064 ± 0.005 0.073 ± 0.003 <0.02 <0.0001 0.061 Av(λ)0.068 ± 0.0030.073 ± 0.002 NS <0.0001<0.05 SD(λ) 0.0097 ± 0.0015 0.0123 ± 0.0007 <0.02 <0.0001 0.053 SD(S λ ) 0.0043 ± 0.0004 0.0050 ± 0.0002 <0.0001 <0.0001 0.080 Av(LFD.DA)1.88 ± 0.192.30 ± 0.05 <0.0001 <0.0001<0.04 SD(LFD.DA)0.35 ± 0.090.58 ± 0.03 NS <0.004<0.02 SD(MIL.Max)−0.039 ± 0.1390.315 ± 0.049 NS <0.0003<0.02 SD(MIL.Av)−0.057 ± 0.1260.268 ± 0.042 NS <0.001<0.02 SD(MIL.DA)0.069 ± 0.0060.057 ± 0.003 NS <0.0001<0.02 SD(MIL.SD) 0.027 ± 0.020 0.062 ± 0.007 NS <0.0001 0.075

For ease of viewing, table entries are bolded if the effect of primary interest ( P lesion) is statistically significant.

λ, mean lacunarity; Av, mean; DA, degree of anisotropy; DTS, digital tomosynthesis; LFD, line fraction deviation; Max, maximum; MIL, mean intercept length; NS, not significant; SD, standard deviation; S λ , slope lacunarity.

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Table 3

Summary of Digital Tomosynthesis-derived Bone Texture Variables Associated with Odds for TKA (Mean ± Standard Error) \*

DTS Variable Resolved TKA_P_ for Odds SD(FD) ( at lesion ) 0.0093 ± 0.0005 0.0118 ± 0.0010 0.076 S λ 0.052 ± 0.0010.055 ± 0.002<0.03 Av(S λ ) 0.052 ± 0.001 0.054 ± 0.002 0.077 SD(λ) 0.012 ± 0.001 0.010 ± 0.001 0.092 SD(S λ ) 0.0050 ± 0.0003 0.0044 ± 0.0003 0.068 SD(LFD.SD) 0.00069 ± 0.00012 0.00045 ± 0.00006 0.064 SD(MIL.Av) 0.255 ± 0.046 0.123 ± 0.014 0.081 SD(MIL.DA) 0.056 ± 0.003 0.070 ± 0.007 0.094

For ease of viewing, the statistically significant result is bolded.

λ, mean lacunarity; Av, mean; DA, degree of anisotropy; DTS, digital tomosynthesis; FD, fractal dimension; LFD, line fraction deviation; MIL, mean intercept length; SD, standard deviation; S λ , slope lacunarity; TKA, total knee arthroplasty.

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Discussion

Specific Findings and the Rare Incidence of SIF

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Figure 5, Representative pairs of MRI and DTS images from ( a and b ) a 74-year-old woman who did not progress to TKA and from ( c and d ) a 70-year-old woman who required TKA at 5 months. Lesion was on the left medial femoral condyle in both cases (region of interest adjacent to lesion magnified). For each, the DTS slice with the largest area of lesion is presented, with regional values of S λ shown in white . Note similar lesion size. DTS, digital tomosynthesis; MRI, magnetic resonance imaging; TKA, total knee arthroplasty.

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Interpretation of the Findings

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Study Deficiencies

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Conclusions

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Acknowledgment

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