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Abstract Number: 223

Clinical Predictors For Subcutaneous Power Doppler Signals Detected By Ultrasound  in Hands Of Scleroderma Patients

Anat Scheiman-Elazary1, Ami Ben-Artzi2, V.K. Ranganath3, Nabeel Borazan4, Philip J. Clements5, Suzanne Kafaja2 and Daniel Furst6, 1Rheumatology, Rheumatology UCLA, Los Angeles, CA, 2David Geffen School of Medicine, UCLA, Los Angeles, CA, 3Medicine, Division of Rheumatology, David Geffen School of Medicine, UCLA, Los Angeles, CA, 4Medicine, Rheumatology UCLA, Los Angeles, CA, 5University of California, Los Angeles, Department of Medicine, Los Angeles, CA, 6Rheumatology, David Geffen School of Medicine, UCLA, Los Angeles, CA

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: scleroderma and ultrasound

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Session Information

Title: Imaging of Rheumatic Diseases I: Imaging in Gout, Pediatric, Soft and Connective Tissue Diseases

Session Type: Abstract Submissions (ACR)

Clinical Predictors for subcutaneous Power Doppler signals detected by ultrasound  in scleroderma patients

Background/Purpose:

Skin thickening in scleroderma was demonstrated previously in US studies, although subcutaneous tissue was not yet evaluated. We evaluated  scleroderma patients for subcutaneous Power Doppler signal (SCPD) on the dorsal aspect of the MCPs of the dominant hand. Out of 74  patients, 17 (22.9%) had a positive signal. Our aim was to compare SCPD positive (N= 17, 22.9%) versus SCPD negative (N=57, 77.1%) patients and to look for clinical and laboratory predictors for SCPD.

Methods:

Seventeen SCPD positive patients were compared with 57 SCPD negative patients. US exam was performed using GE logic E9 scanner with a linear array (5-16 MHz) for PD in subcutaneous tissue. SCPD was  defined as a positive PD signal in the subcutaneous tissue on the dorsal aspect of either MCPs 2-5 in both longitudinal and short views that was not involving the tendon. At least one MCP had to be involved.  A binary grading was used to score SCPD (0-1). Patients were divided into 2 groups, with or without SCPD. GS and PD examinations of 13 joints (wrist, MCP 2-5, PIPs 2-5) and tendons were done.  A step wise linear regression model was used   to identify predictors for SCPD. The following parameters were included: age, gender, disease duration, disease type  (limited or diffuse), modified Rodnan skin score (MRSS), lung involvement (symptoms, pulmonary function test and high resolution CT) , pulmonary hypertension (echo), ESR, CRP, ulcers, calcinosis, sclerodactaly  and contractures.

 Results:

After univariate analysis with P<0.2 cut-off, MRSS, disease duration and lung involvement  were included. MRSS (OR=0.93, p=0.14)  and lung disease(OR=0.28, p=0.047) decreased  the likelihood for SCPD while longer disease duration increased its likelihood (OR=1.117, p=0.036).   The final model included only lung and disease duration with a  ROC curve,  AUC of 0.77 (figure 1). There was no statistical difference in mean joint GS and PD between both groups (mean joint GS 0.34 and 0.31 in the negative and positive SCPD patients respectively, mean joint PD 0.08 and 0.04 in the negative and positive SCPD patients respectively). Mean ESR was 21 and 18 mm/h in the positive and negative SCPD patients respectively (P value 0.94).

Conclusion:

Twenty two percent of patients with scleroderma had positive subcutaneous power doppler signal above the dorsal aspect of the MCPs. Patients with this phenomenon had longer disease duration and less lung involvement with moderately good predictive value ( ROC AUC- 77). There was not increased synovitis or elevated ESR in this group. We therefore assume that this is not an inflammatory phenomenon. We speculate that SCPD may be related to increased blood flow to the skin during the resolution phase of the skin. Further studies are needed to understand the underling mechanism.


Disclosure:

A. Scheiman-Elazary,
None;

A. Ben-Artzi,
None;

V. K. Ranganath,
None;

N. Borazan,
None;

P. J. Clements,
None;

S. Kafaja,
None;

D. Furst,

AbbVie,

2,

Actelion Pharmaceuticals US,

2,

Amgen,

2,

BMS,

2,

Gilead,

2,

GSK,

2,

NIH,

2,

Novartis Pharmaceutical Corporation,

2,

Pfizer Inc,

2,

Roche/Genentech,

2,

UCB,

2,

Janssen Pharmaceutica Product, L.P.,

5.

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