Dermoscopic Features of Cutaneous Vasculitis

INTRODUCTION

Dermoscopy has become widespread in the diagnosis of inflammatory skin diseases. Cutaneous vasculitis (CV) is characterized by inflammation of vessels, and a rapid and reliable technique is required for the diagnosis.

OBJECTIVES

We aimed to define CV dermoscopic features and increase the diagnostic accuracy of dermoscopy with machine learning (ML) methods.

METHODS

Eighty-nine patients with clinically suspected CV were included in the study. Dermoscopic images were obtained before biopsy using a polarized dermoscopy. Dermoscopic images were independently evaluated, and interobserver variability was calculated. Decision Tree, Random Forest, and K-Nearest Neighbors were used as ML classification models.

RESULTS

The histopathological diagnosis of 58 patients was CV. Three patterns were observed: homogeneous pattern, mottled pattern, and meshy pattern. There was a significant difference in background color between the CV and non-CV groups (P = 0.001). The milky red and livedoid background color were specific markers in the differential diagnosis of CV (sensitivity 56.7%, specificity 96.3%, sensitivity 29.4%, specificity 99.2%, respectively). Red blotches were significantly more common in CV lesions (P = 0.038). Red dots, comma vessels, and scales were more common in the non-CV group (P = 0.002, P = 0.002, P = 0.003, respectively). Interobserver agreement was very good for both pattern (κ = 0.869) and background color analysis (κ = 0.846) (P < 0.001). According to ML classifiers, the background color and lack of scales were the most significant dermoscopic aspects of CV.

CONCLUSIONS

Dermoscopy may guide as a rapid and reliable technique in CV diagnosis. High accuracy rates obtained with ML methods may increase the success of dermoscopy.

In chronic spontaneous urticaria, IgE and C-reactive protein are linked to distinct microRNAs and interleukin-31

BACKGROUND

Chronic spontaneous urticaria (CSU) is a common and disabling disease. Assessments of IgE and C-reactive protein (CRP) are recommended in the diagnostic work-up, but the role and clinical relevance of these biomarkers are not well characterized. Moreover, it remains unknown if elevated levels of IgE or CRP are linked to CSU microRNA (miRNA) signatures or interleukin 31 (IL-31).

METHODS

We measured IgE and CRP serum levels in 47 CSU patients (and 45 healthy controls) and determined CSU disease activity using the urticaria activity score (UAS7). Expression levels of miR-155 and miR-221 were assessed by RT-PCR, and IL-31 levels were determined by ELISA.

RESULTS

Total IgE and CRP levels were independently increased in CSU patients. IgE and CRP levels were highest and lowest in patients with high and mild disease activity. IgE levels correlated with miR-155 levels, whereas CRP levels correlated with miR-221 levels. miR-155 and miR-221 were significantly overexpressed in CSU patients. ROC analyses linked miRNA-155 and CSU with a sensitivity of 79% and specificity of 87%, and miRNA-221 and CSU with a sensitivity of 75% and specificity of 91%. High CRP and miR-221 expression levels were linked to elevated levels of IgG anti-TPO and IL-31.

CONCLUSION

IgE and CRP are useful biomarkers for disease activity in CSU, with distinct miRNA profiles. High CRP and miR-221 levels may point to autoimmune CSU and a role for IL-31.