Automated assessment of absolute nailfold capillary number on videocapillaroscopic images: Proof of principle and validation in systemic sclerosis

Abstract

Background: Absolute nailfold capillary number should be a putative biomarker in selected rheumatic diseases but could be time-consuming and not highly repeatable.

Objective: To validate an automated software for absolute nailfold capillary number and density evaluation, on NVC images in SSc.

Methods: An automated software to count nailfold capillary number (AUTOCAPI) had been constructed, through an exploratory image set. Subsequently, application rules have been created to define the ROI in NVC images, through a training images set. The software reliability was assessed through calculation of the ICC between automatic and manual counting, by four independent observers, on the same NVC images.

Results: The following ICC's were obtained per observer, for the patients with SSc (40 images), the healthy (20 images), and the PRP subgroups (20 images), respectively: 0.94, 0.81, and 0.62 (observer 1); 0.94, 0.91, and 0.67 (observer 2); 0.88, 0.56, and 0.64 (observer 3); and 0.88, 0.85, and 0.85 (observer 4).

Conclusions: The validation of an automated software for measuring absolute nailfold capillary number and density in SSc was achieved. The integration into the pre-existing imaging software should make the assessment of the capillary number in NVC easier, quicker, and standardized.

Keywords: Raynaud's phenomenon; automated capillary count; imaging; nailfold videocapillaroscopy; systemic sclerosis.