Automated structure and flow measurement - a promising tool in nailfold capillaroscopy

Abstract

Objectives: Despite increasing interest in nailfold capillaroscopy, objective measures of capillary structure and blood flow have been little studied. We aimed to test the hypothesis that structural measurements, capillary flow, and a combined measure have the predictive power to separate patients with systemic sclerosis (SSc) from those with primary Raynaud's phenomenon (PRP) and healthy controls (HC).

Methods: 50 patients with SSc, 12 with PRP, and 50 HC were imaged using a novel capillaroscopy system that generates high-quality nailfold images and provides fully-automated measurements of capillary structure and blood flow (capillary density, mean width, maximum width, shape score, derangement and mean flow velocity). Population statistics summarise the differences between the three groups. Areas under ROC curves (A_Z) were used to measure classification accuracy when assigning individuals to SSc and HC/PRP groups.

Results: Statistically significant differences in group means were found between patients with SSc and both HC and patients with PRP, for all measurements, e.g. mean width (μm) ± SE: 15.0 ± 0.71, 12.7 ± 0.74 and 11.8 ± 0.23 for SSc, PRP and HC respectively. Combining the five structural measurements gave better classification (A_Z = 0.919 ± 0.026) than the best single measurement (mean width, A_Z = 0.874 ± 0.043), whilst adding flow further improved classification (A_Z = 0.930 ± 0.024).

Conclusions: Structural and blood flow measurements are both able to distinguish patients with SSc from those with PRP/HC. Importantly, these hold promise as clinical trial outcome measures for treatments aimed at improving finger blood flow or microvascular remodelling.

Keywords: Microcirculation; Nailfold capillaroscopy; Red blood cell velocity; Systemic sclerosis.

Fig. 1

Image capture, vessel detection, and flow sequence estimation. All video image frames are 640 × 480 pixels with a resolution of 1 μm per pixel. Frames are stitched in software to produce mosaic images across the whole nailfold. Panels are as follows: (1) An overview of the microscope system and capture software interface; (2) Diagram of motor positions and tracking data used to inform frame stitching and the mosaic creation process; (3) A fully-registered mosaic image with automatically detected vessels highlighted, counted and measured; (4) Individual regions from the mosaic in (3), showing vessel region detection (left) and vessel path orientation (right); (5) Structural mosaic from (3) overlaid with false colour flow information extracted from vessels using optical flow techniques.

Fig. 2

ROC curves for single capillary parameters (a: left), and combined models (b: right). Area under the curves (A_Z) and standard errors are shown for each colour-coded curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)