ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 1131

Peri-Articular Fractal Signature Analysis and Bone Mineral Density Measure Different Aspects Of Bone: Cross-Sectional Data From The Osteoarthritis Initiative

Jeffrey B. Driban1, Felix Liu2, Alina O'Brien3, Lori Lyn Price4, Grace H. Lo5, Michael C. Nevitt6, Charles Eaton7, Timothy E. McAlindon8 and John A. Lynch9, 1Rheumatology, Tufts Medical Center, Boston, MA, 2University of California at San Francisco, San Francisco, CA, 3Tufts Medical Center, Boston, MA, 4Biostatistics Research Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 5VA HSR&D Center for Innovations in Quality, Effectiveness and Safety; Medical Care Line and Research Care Line; Department of Medicine, Michael E. DeBakey VA Medical Center, Baylor College of Medicine, Houston, TX, 6Epidemiology & Biostatistics, UCSF (University of California, San Francisco), San Francisco, CA, 7Center for Primary Care and Prevention, Memorial Hospital of Rhode Island, Providence, RI, 8Division of Rheumatology, Tufts Medical Center, Boston, MA, 9Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: , , ,

Session Information

Session Title: Imaging of Rheumatic Diseases II: Imaging in Spondyloarthritis and Osteoarthritis

Session Type: Abstract Submissions (ACR)

Background/Purpose: Peri-articular fractal signature analysis (FSA) and bone mineral density (paBMD) are potentially cost-effective prognostic imaging markers for osteoarthritis (OA) progression. While we know that paBMD relates to trabecular morphology, it remains unclear whether FSA, which assesses the texture of bone on radiographs, measures a similar construct of bone structure as paBMD. Understanding this association is paramount for determining if these two measurements are redundant. Therefore, we evaluated the association between FSA, paBMD, and trabecular morphology.

Methods: The sample comprised 450 participants in the Osteoarthritis Initiative (OAI) progression cohort who had weight-bearing radiographs, magnetic resonance imaging (MRI), and knee dual-energy x-ray absorptiometry (DXA) at the 48-month OAI visit. The right knee was assessed unless MRI was contraindicated. Three separate readers measured the medial proximal tibia to generate 1) paBMD on DXA, 2) fractal dimensions with FSA on digital radiographs, and 3) MRI-based apparent trabecular morphology: bone volume fraction (aBV/TV), trabecular number (aTb.Tn), spacing (aTb.Sp), and thickness (aTb.Th). Fractal dimension data in the horizontal “tension” and vertical “compression” directions were reduced into 3 piece-wise, centered linear regression from 0 to 3mm radii.  We assessed univariate associations with Spearman correlations and conducted 5 robust regression models to determine the association between FSA-based data (compression and tension together; predictors) and the five other bone measures (paBMD and trabecular morphology) as outcomes. These models were adjusted for OAI clinical site.

Results:  The 450 participants were 47% female, 72% radiographic knee OA in the study knee (Kellgren-Lawrence > 2), and on average 66 (SD=9) years of age with a mean body mass index of 29.6 (SD=4.7) kg/m2. Table 1 shows that FSA-based data were not associated with paBMD. The significant associations between FSA-based data and trabecular morphology indicated that lower tension and compression gradients may be related to greater aBV/TV,  aTb.Th, aTb.Tn, but lower Tb.Sp (Table 1). In the multivariate analyses we found that FSA-based compression offsets had a small relationship with paBMD (R2 = 0.03). Furthermore, we found that lower FSA-based compression gradients were associated with greater aBV/TV (p=0.04) and aTb.Th (p=0.01) but lower aTb.Sp (p=0.01; R2 = 0.04-0.05). Lower FSA-based tension gradients were associated with greater aTb.Th (p= 0.02) but lower aTb.Sp (p=0.04).

Conclusion: We found that lower peri-articular FSA values were not associated with paBMD but had some small associations with trabecular morphology that is typical of greater OA severity (greater aBV/TV, aTb.Th, and aTb.N and lower aTb.Sp). This suggests that these are not redundant measures and both imaging markers warrant further evaluation.

 

Table 1. Cross-sectional Relationships Between Peri-articular FSA-Based Data and Other Apparent Bone Measures (n = 450 knees)

 FSA-Based Data

Bone Mineral Density

Bone Volume Fraction

Trabecular Thickness

Trabecular Number

Trabecular Spacing

r (95% CI)

r (95% CI)

r (95% CI)

r (95% CI)

r (95% CI)

Segment 1 (0 < radii ≤ 1mm)

     Compression gradient1

0.05(-0.05, 0.14)

0.02(-0.07, 0.11)

0.01(-0.09, 0.10)

0.02(-0.07, 0.11)

-0.01(-0.10, 0.08)

     Compression offset2

-0.03(-0.12, 0.06)*

0.02(-0.07, 0.11)

0.05(-0.04, 0.15)

0.01(-0.08, 0.10)

-0.01(-0.10, 0.09)

     Tension gradient1

-0.05(-0.15, 0.04)

-0.13(-0.22, -0.04)

-0.04(-0.13, 0.05)

-0.16(-0.25, -0.07)

0.16(0.06, 0.24)*

     Tension offset2

-0.05(-0.15, 0.04)

-0.05(-0.14, 0.04)

-0.05(-0.14, 0.05)

-0.05(-0.14, 0.04)

0.05(-0.04, 0.14)

Segment 2 (1 < radii ≤ 2mm)

     Compression gradient1

0.00(-0.10, 0.09)

-0.07(-0.16, 0.02)

-0.04(-0.13, 0.06)

-0.08(-0.17, 0.01)

0.07(-0.02, 0.16)

     Compression offset2

0.04(-0.05, 0.13)*

0.02(-0.07, 0.11)

0.04(-0.05, 0.13)

0.01(-0.08, 0.10)

-0.01(-0.10, 0.08)

     Tension gradient1

0.03(-0.07, 0.12)

0.02(-0.08, 0.11)

0.01(-0.09, 0.10)

0.02(-0.07, 0.11)

-0.02(-0.11, 0.08)

     Tension offset2

-0.01(-0.10, 0.09)

-0.04(-0.13, 0.05)

-0.02(-0.11, 0.07)

-0.05(-0.14, 0.04)

0.05(-0.04, 0.14)

Segment 3 (2 < radii ≤ 3mm)

     Compression gradient1

0.01(-0.08, 0.10)

-0.11(-0.20, -0.02)*

-0.12(-0.21, -0.03)*

-0.10(-0.19, -0.01)

0.10(0.01, 0.19)*

     Compression offset2

0.00(-0.10, 0.09)

-0.04(-0.14, 0.05)

0.00(-0.09, 0.09)

-0.06(-0.15, 0.04)

0.06(-0.03, 0.15)

     Tension gradient1

0.02(-0.07, 0.11)

-0.01(-0.10, 0.09)

-0.09(-0.18, 0.01)*

0.01(-0.08, 0.10)

-0.01(-0.11, 0.08)

     Tension offset2

0.02(-0.07, 0.11)

0.03(-0.06, 0.12)

-0.06(-0.16, 0.03)

0.04(-0.05, 0.13)

-0.05(-0.14, 0.05)

Note: FSA = Fractal Signature Analysis, r = Spearman rho, 95% CI = 95% confidence interval.

1 = gradients are defined as the x-coefficient in the 3 piece-wise, centered linear regressions from 0 to 3mm radii

2 = offsets are defined as the constants in the 3 piece-wise, centered linear regressions from 0 to 3mm radii

* = correlations that were significant in multivariate analyses with all of the FSA-based data included as predictors.

Disclosure:

J. B. Driban,
None;

F. Liu,
None;

A. O’Brien,
None;

L. L. Price,
None;

G. H. Lo,
None;

M. C. Nevitt,
None;

C. Eaton,
None;

T. E. McAlindon,

NIH,

2;

J. A. Lynch,
None.

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