This study is a cross-sectional, observational investigation designed to develop and validate a noninvasive ocular imaging-based predictive model for major inflammatory skin diseases, including psoriasis, atopic dermatitis, and urticaria. Grounded in Traditional Chinese Medicine (TCM) ocular diagnostic theory and integrated with advanced computer vision techniques, the study aims to establish objective, quantifiable biomarkers derived from scleral and bulbar conjunctival images.
Approximately 950 participants (patients with psoriasis, atopic dermatitis, urticaria, and healthy controls) will be recruited from a tertiary academic hospital. Standardized high-resolution ocular images will be collected alongside comprehensive clinical, demographic, and comorbidity data. Disease severity will be assessed using validated clinical scoring systems (e.g., PASI, EASI, UAS7, DLQI).
Image analysis will combine traditional radiomics feature extraction with deep learning architectures, including a Vision State-Space (VMamba) module for global-local feature representation and a Multi-Gate Mixture-of-Experts (MMoE) framework for multi-task learning. The model is designed to simultaneously perform disease classification and predict comorbidity risks (such as metabolic syndrome, hepatic insulin resistance, and recurrence risk).
Primary outcomes include characterization of ocular feature patterns associated with inflammatory skin diseases. Secondary outcomes include correlations between ocular image-derived features and clinical severity indices. Model performance will be evaluated using ROC curves, AUC, calibration analysis, and decision curve analysis.
This study aims to provide an objective, digitalized, and clinically applicable ocular biomarker framework to support early diagnosis, risk stratification, and comorbidity screening in inflammatory skin diseases.
None
Healthy control - exclusion criteria
As an exploratory cross-sectional study involving high-dimensional image-omics modeling, we plan to enlarge the sample size. We intend to recruit 200 cases each of psoriasis, atopic dermatitis, and urticaria, and 150 healthy controls. The dataset will be split into training and internal validation sets at an 8:2 ratio. An external independent validation cohort of 200 subjects is planned. The total sample size is therefore approximately 950 participants.
Other
Cross-sectional
Questionnaire collection
Other interventionDuring the study visit investigators will conduct face-to-face interviews and collect the questionnaire data, with confirmation from family members where appropriate.
A TCM ocular diagnostic feature spectrum
A TCM ocular diagnostic feature spectrum: overall prevalence and pattern combinations of ocular features in the psoriasis group. Incidence rates of characteristic ocular change
Correlations (Spearman's rho) between ocular feature scores and clinical severity scales
Correlations (Spearman's rho) between ocular feature scores and clinical severity scales: PASI, BSA, DLQI, VAS, EASI, UAS, and UCT
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