Virtual skin biopsy by optical coherence tomography: The first quantitative imaging biomarker for scleroderma

Annals of the Rheumatic Diseases

Volumn 72, Issue 11, 2013, Pages 1845-1851

  Abignano, Giuseppina ^a,b,c   Aydin, Sibel Zehra ^d   Castillo Gallego, Concepción ^e   Liakouli, Vasiliki ^a,b,f   Woods, Daniel ^g   Meekings, Adam ^g   Wakefield, Richard J ^a,b   McGonagle, Dennis G ^a,b   Emery, Paul ^a,b   Galdo, Francesco Del ^a,b  

^a UNIVERSITY OF LEEDS   (United Kingdom)

^b LEEDS TEACHING HOSPITALS NHS TRUST   (United Kingdom)

^c SECOND UNIVERSITY OF NAPLES   (Italy)

^d ISTANBUL MEDENIYET UNIVERSITY   (Turkey)

^e HOSPITAL UNIVERSITARIO LA PAZ   (Spain)

^f UNIVERSITY OF L'AQUILA   (Italy)

^g 11A Grays Farm Production Village   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; CHILD; CLINICAL ARTICLE; CLINICAL ASSESSMENT; COMPARATIVE STUDY; COMPUTER PROGRAM; CONTROLLED STUDY; CORRELATION ANALYSIS; CORRELATION COEFFICIENT; DERMIS; DERMOEPIDERMAL JUNCTION; DIAGNOSTIC IMAGING; DISEASE MARKER; FEMALE; FOREARM; HAND; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; INTRARATER RELIABILITY; MALE; OPTICAL COHERENCE TOMOGRAPHY; OPTICAL COHERENCE TOMOGRAPHY DEVICE; OPTICAL DENSITY; PAPILLARY DERMIS; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; RETICULAR DERMIS; RODNAN SKIN SCORE; SCHOOL CHILD; SCLERODERMA; SCORING SYSTEM; SKIN BIOPSY; SKIN FIBROSIS; VIRTUAL SKIN BIOPSY;

AUTOIMMUNE DISEASES; OUTCOMES RESEARCH; SYSTEMIC SCLEROSIS;

BIOPSY; CASE-CONTROL STUDIES; FEMALE; FIBROSIS; HUMANS; MALE; MIDDLE AGED; REPRODUCIBILITY OF RESULTS; SCLERODERMA, SYSTEMIC; SKIN; TOMOGRAPHY, OPTICAL COHERENCE;

EID: 84885178299     PISSN: 00034967     EISSN: 14682060     Source Type: Journal    
DOI: 10.1136/annrheumdis-2012-202682     Document Type: Article

References (24)

1. Jimenez SA, Derk CT. Following the molecular pathways toward an understanding of the pathogenesis of systemic sclerosis. Ann Intern Med 2004;140:37-50.
2. Varga J, Abraham D. Systemic sclerosis: a prototypic multisystem fibrotic disorder. J Clin Invest 2007;117:557-67.
3. Gabrielli A, Avvedimento EV, Krieg T. Scleroderma. N Engl J Med 2009;360:1989-2003.
4. Clements PJ, Hurwitz EL, Wong WK, et al. Skin thickness score as a predictor and correlate of outcome in systemic sclerosis: high-dose versus low-dose penicillamine trial. Arthritis Rheum 2000;43:2445-54.
5. Steen VD, Medsger TA Jr. Improvement in skin thickening in systemic sclerosis associated with improved survival. Arthritis Rheum 2001;44:2828-35.
6. Pope JE, Baron M, Bellamy N, et al. Variability of skin scores and clinical measurements in scleroderma. J Rheumatol 1995;22:1271-6.
7. Clements PJ, Lachenbruch PA, Seibold JR, et al. Skin thickness score in systemic sclerosis: an assessment of interobserver variability in 3 independent studies. J Rheumatol 1993;20:1892-6.
8. Akesson A, Hesselstrand R, Scheja A, et al. Longitudinal development of skin involvement and reliability of high frequency ultrasound in systemic sclerosis. Ann Rheum Dis 2004;63:791-6.
9. Moore TL, Lunt M, McManus B, et al. L. Seventeen-point dermal ultrasound scoring system-a reliable measure of skin thickness in patients with systemic sclerosis. Rheumatology (Oxford) 2003;42:1559-63.
10. Kaloudi O, Bandinelli F, Filippucci E, et al. High frequency ultrasound measurement of digital dermal thickness in systemic sclerosis. Ann Rheum Dis 2010;69:1140-3.
11. Aden N, Shiwen X, Aden D, et al. Proteomic analysis of scleroderma lesional skin reveals activated wound healing phenotype of epidermal cell layer. Rheumatology (Oxford) 2008;47:1754-60.
12. Aden N, Nuttall A, Shiwen X, et al. Epithelial Cells Promote Fibroblast Activation via IL-1alpha in Systemic Sclerosis. J Invest Dermatol 2010;130:2191-200.
13. Gambichler T, Jaedicke V, Terras S. Optical coherence tomography in dermatology: technical and clinical aspects. Arch Dermatol Res 2011;303:457-73.
14. Marschall S, Sander B, Mogensen M, et al. Optical coherence tomography-current technology and applications in clinical and biomedical research. Anal Bioanal Chem 2011;400:2699-720.
15. Coleman AJ, Richardson TJ, Orchard G, et al. Histological correlates of optical coherence tomography in non-melanoma skin cancer. Skin Res Technol 2013;19: e10-9.
16. Preliminary criteria for the classification of systemic sclerosis (scleroderma). Subcommittee for scleroderma criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee. Arthritis Rheum 1980;23:581-90.
17. Collins TJ. Image J for microscopy. Biotechniques 2007;43:25-30.
18. Clendenon JL, Phillips CL, Sandoval RM, et al. Voxx: a PC-based, near real-time volume rendering system for biological microscopy. Am J Physiol Cell Physiol 2002;282:C213-18.
19. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307-10.
20. LeRoy EC, Black C, Fleischmajer R, et al. Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 1988;15:202-5.
21. Merkel PA, Silliman NP, Clements PJ, et al. Patterns and predictors of change in outcome measures in clinical trials in scleroderma: an individual patient metaanalysis of 629 subjects with diffuse cutaneous systemic sclerosis. Arthritis Rheum 2012;64:3420-9.
22. Farina G, Lafyatis D, Lemaire R, et al. A four-gene biomarker predicts skin disease in patients with diffuse cutaneous systemic sclerosis. Arthritis Rheum 2010;62:580-8.
23. Milano A, Pendergrass SA, Sargent JL, et al. Molecular subsets in the gene expression signatures of scleroderma skin. PLoS One 2008;3:e2696.
24. Pendergrass SA, Lemaire R, Francis IP, et al. Intrinsic gene expression subsets of diffuse cutaneous systemic sclerosis are stable in serial skin biopsies. J Invest Dermatol 2012;132:1363-73.