Full Papers
External clinical validation of automated software to identify structural abnormalities and microhaemorrhages in nailfold videocapillaroscopy images
B.C. Gracia Tello1, E. Ramos Ibañez2, L. Saez Comet3, A. Guillén Del Castillo4, C.P. Simeón Aznar5, A. Selva-O'callaghan6, G. Espinosa7, G. Lledó8, M. Freire Dapena9, E. Martinez Robles10, J.J. Ríos11, J.A. Todolí Parra12, B. Marí Alfonso13, N. Ortego Centeno14, A. Marín Ballvé15, J.L. Callejas Rubio16, V. Fonollosa Plá17, P. Fanlo18
- Unit of Autoimmune Diseases, Lozano Blesa University Hospital, Zaragoza, and Instituto de Investigación Sanitaria Aragón (ISSA), Aragón, Spain. bcgracia@salud.aragon.es
- Software Engineer, Computer Science Graduate, University of Zaragoza, Spain.
- Autoimmune Department, Hospital Universitario Miguel Servet, Zaragoza, and Sociedad Española de Medicina Interna, Grupo de Enfermedades Autoinmunes Sistémicas (GEAS), Spain.
- Unit of Autoimmune Diseases, Hospital Vall d’Hebron, Barcelona, Spain.
- Unit of Autoimmune Diseases, Hospital Vall d’Hebron, Barcelona, Spain.
- Unit of Autoimmune Diseases, Hospital Vall d’Hebron, Barcelona, Spain.
- Department of Autoimmune Diseases, Hospital Clínic, Barcelona, Spain.
- Department of Autoimmune Diseases, Hospital Clínic, Barcelona, Spain.
- Department of Internal Medicine, Complejo Hospitalario Universitario de Vigo, Spain.
- Unit of Autoimmune Diseases, Hospital Universitario La Paz, Madrid, Spain.
- Unit of Autoimmune Diseases, Hospital Universitario La Paz, Madrid, Spain.
- Unit of Autoimmune Diseases, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
- Internal Medicine, Hospital Parc Tauli, Barcelona, Spain.
- Unit of Autoimmune Diseases, Hospital Clínico San Cecilio, Granada, Spain.
- Unit of Autoimmune Diseases, Lozano Blesa University Hospital, Zaragoza, and Instituto de Investigación Sanitaria Aragón (ISSA), Aragón, Spain.
- Unit of Autoimmune Diseases, Hospital Clínico San Cecilio, Granada, Spain.
- Unit of Autoimmune Diseases, Hospital Vall d’Hebron, Barcelona, Spain.
- Unit of Autoimmune Diseases, Hospital Virgen del Camino, Pamplona, and Sociedad Española Multidisciplinar de Enfermedades Autoinmunes Sistémicas (SEMAIS), Spain.
CER16420
2023 Vol.41, N°8
PI 1605, PF 1611
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PMID: 37140670 [PubMed]
Received: 01/12/2022
Accepted : 02/03/2023
In Press: 04/05/2023
Published: 03/08/2023
Abstract
OBJECTIVES:
Automated systems to analyse nailfold videocapillaroscopy (NVC) images are needed to promptly and comprehensively characterise patients with systemic sclerosis (SSc) or Raynaud’s phenomenon (RP). We previously developed, and validated in-house, a deep convolutional neural network-based algorithm to classify NVC-captured images according to the presence/absence of structural abnormalities and/or microhaemorrhages. We present its external clinical validation.
METHODS:
A total of 1,164 NVC images of RP patients were annotated by 5 trained capillaroscopists according to the following categories: normal capillary; dilation; giant capillary; abnormal shape; tortuosity; microhaemorrhage. The images were also presented to the algorithm. Matches and discrepancies between algorithm predictions and those annotations obtained by consensus of ≥3 or ≥4 interobservers were analysed.
RESULTS:
Consensus among ≥3 capillaroscopists was achieved in 86.9% of images, 75.8% of which were correctly predicted by the algorithm. Consensus among ≥4 experts occurred in 52.0% of cases, in which 87.1% of the algorithm’s results matched with those of the expert panel. The algorithm’s positive predictive value was >80% for microhaemorrhages and unaltered, giant or abnormal capillaries. Sensitivity was >75% for dilations and tortuosities. Negative predictive value and specificity were >89% for all categories.
CONCLUSIONS:
This external clinical validation suggests that this algorithm is useful to assist in the diagnosis and follow-up of SSc or RP patients in a timely manner. It may also be helpful in the management of patients with any pathology presenting with microvascular changes, as the algorithm has been designed to also be useful for research aiming at extending the usage of nailfold capillaroscopy to more conditions.
