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Sammanfattning

Nailfold capillaroscopy (NC) is an invasive imaging technique that is used to assess the blood capillary network in the nailfold area. NC is routinely used for patients with microcirculation problems, such as systemic sclerosis and other connective tissue diseases. NC is repeatable and appears to be simple and harmless. However, there is a lack of established guidelines [QCE1] and instructions for both the acquisition and interpretation of the images obtained, which may lead to various ambiguities.

The general aim of this thesis was to reduce the inherent ambiguities in human judgment and diagnosis by introducing novel techniques for assessing the nailfold capillary density, which is an important parameter in NC. To achieve this goal, a toolkit was developed that includes a method to measure the capillary density, an image enhancement technique and a graphical user interface (GUI).

In the first study, a summary of the nailfold videocapillaroscopy procedure was presented, and the common techniques used to evaluate capillaroscopic parameters were reviewed. In the second study, common methods for calculating the capillary density were reviewed, and a survey of the relationship between the number of capillaries as well as the existence of digital ulcers, pulmonary arterial hypertension, autoantibodies, scleroderma patterns and the different scoring systems was performed. In the third study, a novel method was proposed to determine the nailfold capillary density, and this method is referred to as the elliptic broken line (EBL) method. In the fourth study, the EBL method for measuring capillary density was evaluated. In the fifth study, a new image enhancement technique was introduced and evaluated both subjectively and objectively. Finally, clinical applications of the EBL method and enhancement techniques were demonstrated in the sixth study. The result verifies the potential of the proposed EBL method to improve the reliability and repeatability of assessments. Additionally, improving the image quality, i.e., using the proposed enhancement method, can reveal more capillary details for an observer compared to the raw original image, and the results motivate the future development of automatic tools for the EBL method, e.g., automatic segmentation and capillary detection and characterization.

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