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POS1408 REPRODUCIBILITY OF A NEW AUTOMATIC SYSTEM (CAPILLARY.IO) IN THE ANALYSIS OF NAILFOLD CAPILLAROSCOPY IMAGES
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  1. B. Gracia Tello1,2,
  2. E. Ramos3,
  3. C. P. Simeón-Aznar4,
  4. V. Fonollosa Pla4,
  5. A. Guillén-Del-Castillo4,
  6. A. Selva-O’callaghan4,
  7. L. Sáez-Comet5,
  8. E. Martínez Robles6,
  9. J. J. Rios6,
  10. G. Espinosa7,
  11. J. A. Todolí Parra8,
  12. J. L. Callejas-Rubio9,
  13. N. Ortego9,
  14. B. Marí-Alfonso10,
  15. M. Freire11,
  16. P. Fanlo12
  1. 1Hospital Clínico Universitario Lozano Blesa, Zaragoza. Spain, Internal Medicine, Zaragoza, Spain
  2. 2Zaragoza, Instituto de investigación Sanitaria de Aragón (ISSA), Zaragoza, Spain
  3. 3Zaragoza, Computer Science Graduate by University of Zaragoza, Zaragoza, Spain
  4. 4Hospital Universitari Vall d’Hebron, Unit of Autoimmune Diseases, Department of Internal Medicine, Barcelona, Spain
  5. 5Hospital Universitario Miguel Servet, Department of Internal Medicine, Zaragoza, Spain
  6. 6Hospital General Universitario La Paz, Department of Internal Medicine, Madrid, Spain
  7. 7Hospital Clínic, Department of Internal Medicine, Unit of Autoimmune Diseases, Barcelona, Spain
  8. 8Hospital La Fe, Department of Internal Medicine, Valencia, Spain
  9. 9Hospital Universitario Virgen de las Nieves, Unit of Autoimmune Diseases, Department of Internal Medicine, Granada, Spain
  10. 10Hospital Universitario Parc Taulí, Department of Internal Medicine, Sabadell, Spain
  11. 11Complejo Hospitalario Universitario de Santiago, Department of Internal Medicine, Santiago de Compostela, Spain
  12. 12Complejo Hospitalario de Navarra, Pamplona, Department of Internal Medicine, Pamplona, Spain

Abstract

Background: Nailfold Capillaroscopy is a simple, inexpensive and non-invasive technique that allows microvascular damage to be observed, gaining recent importance in the diagnosis, monitoring and prognosis of many diseases with microangiopathy. However, the variability in the results interpretation has led to the development of new computerized systems that allow the automatic analysis of capillaroscopic images.

Objectives: to compare the degree of agreement between the automatic system Capillary.io and a gold standard obtained from the agreement of 9 expert capillaroscopists and to know the degree of the interobserver reliability To demonstrate the validity of the system to detect normal and enlarged capillaries, hemorrhages, megacapillaries, ramifications and tortuosities.

Methods: a cross-sectional study was performed in which 300 random and anonymous nailfold capillaroscopic images (1165 capillaries) were analyzed by 9 experienced observers. The degree of interobserver agreement was calculated from the 5 users. Likewise, the system performed an automatic assessment of the images and their agreement with the gold standard was calculated (interobserver agreement greater than 5, 6, 7, 8 and 9 successively). The validity of the program for each variable was also analyzed using sensitivity and specificity, positive and negative predictive values, and likelihood ratios, as well as their degree of agreement using the weighted kappa statistic (95% CI, p <0.05). The programs used for statistical calculations were SPSS 22.0 and EPIDAT 3.0.

Results: the degree of interobserver agreement was 76.5% for the agreement of 5 or more observers, progressively decreasing to 15.4% for the 9 observers. Capillary.io obtained higher levels of agreement, reaching 97.7% for the 9 observers. Statistically significant results were obtained in the automated detection of all the morphological alterations analyzed Capillary.io presented a sensitivity (S) of 79.82% and a specificity (E) of 82% in the recognition of normal capillaries. The automatized system was able to recognize enlarged capillaries with a sensitivity of 86.97% and a specificity of 81.38%. Megacapillaries were detected with 89.41% sensitivity and 78.75% specificity. Similarly, the system was able to detect tortuosities (S 66.94%; E 67.71%), ramifications (S 54.34%; E 58.61%) and hemorrhages (S 71.36; E 73.97%).

Conclusion: Capillary.io demonstrated a high degree of agreement with the gold standard, stronger with greater consensus among observers. It was able to detect with great sensitivity and specificity hemorrhages and megacapillaries, very relevant alterations in microangiopathies.

References: [1]Roldán LMC, Franco CJV, Navas MAM. Capillaroscopy in systemic sclerosis: A narrative literature review. Rev Colomb Reumatol; 2016; 23: 250-8.

[2]Ingegnoli F, Gualtierotti R, Lubatti C, Bertolazzi C, Gutierrez M, Boracchi P, et al. Nailfold capillary patterns in healthy subjects: A real issue in capillaroscopy. Microvasc Res. 2013;90:90-5.

[3]Cutolo M, Pizzorni C, Secchi ME, Sulli A. Capillaroscopy. Best Pract Res Clin Rheumatol. 2008; 22:1093-108.

[4]Tavakol ME, Fatemi A, Karbalaie A, Emrani Z, Erlandsson BE. Nailfold Capillaroscopy in Rheumatic Diseases: Which Parameters Should Be Evaluated? BioMed Res Int. 2015; 2015: 974530.

[5]Smith V, Herrick AL, Ingegnoli F, Damjanov N, De Angelis R, Denton CP, et al. Standardisation of nailfold capillaroscopy for the assessment of patients with Raynaud’s phenomenon and systemic sclerosis. Autoimmunity Reviews. 2020; 19: 102458.

Disclosure of Interests: Borja Gracia Tello Shareholder of: Co-founder and shareholder of Capillary.io., Eduardo Ramos Shareholder of: Co-founder and shareholder of Capillary.io., Carmen Pilar Simeón-Aznar: None declared, Vicent Fonollosa Pla: None declared, Alfredo Guillén-Del-Castillo: None declared, Albert Selva-O’Callaghan: None declared, Luis Sáez-Comet: None declared, Elena Martínez Robles: None declared, Juan José Rios: None declared, Gerard Espinosa: None declared, Jose Antonio Todolí Parra: None declared, Jose Luis Callejas-Rubio: None declared, Norberto Ortego: None declared, Begoña Marí-Alfonso: None declared, Mayka Freire: None declared, Patricia Fanlo: None declared

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