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Updated: Mar 9, 2026
A Reproducible Computerized Method for Quantitation of Capillary Density using Nailfold Capillaroscopy
Published on: October 27, 2015
Quantification of differences between nailfold capillaroscopy images with a scleroderma pattern and normal pattern
Samuel George Urwin1, Bridget Griffiths, John Allen
1Microvascular Diagnostics Service, Northern Medical Physics and Clinical Engineering Directorate, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
Quantitative analysis of nailfold capillaroscopy (NFC) images revealed that scleroderma patterns exhibit significantly lower fractal dimension (FD) and Kolmogorov complexity (KC) than normal patterns. This suggests FD and KC can help classify microvascular changes in systemic sclerosis.
Area of Science:
- Medical Imaging
- Biophysics
- Rheumatology
Background:
- Nailfold capillaroscopy (NFC) is crucial for diagnosing systemic sclerosis.
- Assessing microvascular alterations in scleroderma patterns requires objective quantification.
- Geometric and algorithmic complexity measures offer novel analytical approaches.
Purpose of the Study:
- To quantify and compare the geometric and algorithmic complexity of microvasculature in NFC images.
- To differentiate between scleroderma (clear microangiopathy - CM) and normal (not clear microangiopathy - NCM) patterns using these complexity measures.
- To evaluate the potential of fractal dimension (FD) and Kolmogorov complexity (KC) for objective classification of NFC images.
Main Methods:
- NFC images were classified by a specialist into CM (scleroderma pattern) and NCM (normal) groups.
- Image pre-processing and binarisation were performed.
- Fractal dimension (FD) and Kolmogorov complexity (KC) were calculated for each image.
- K-means cluster analysis was used to group images based on FD and KC values.
Main Results:
- Images with a scleroderma pattern (CM) showed significantly reduced FD and KC compared to normal patterns (NCM).
- Cluster analysis successfully differentiated between CM and NCM groups using FD and KC.
- These quantitative measures demonstrated potential for objective image classification.
Conclusions:
- FD and KC are promising quantitative biomarkers for microvascular changes in systemic sclerosis.
- Objective classification of NFC images using FD and KC is feasible.
- These methods offer a valuable tool for microvascular investigation in systemic sclerosis patients.
