Frontiers in medicine · 2026
Predicting phototherapy efficacy in vulvar lichen sclerosus using high-frequency ultrasound combined with superb microvascular imaging.
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Liu Yifei, Lu Yu, Guo Yujuan, Li Chuang, Shen Kaikai
Аннотация
OBJECTIVES: To develop a non-invasive model predicting narrow-band UVB (NB-UVB) phototherapy efficacy in vulvar lichen sclerosus (VLS) using high-frequency ultrasound (HF-US, 24 MHz) and superb microvascular imaging (SMI) parameters.
METHODS: Forty-seven biopsy-confirmed VLS patients undergoing standardized NB-UVB (24 weeks) were enrolled (2021-2024). Baseline vascular density (VD), vessel index (VI, SMI), and dermal thickness (HF-US) were measured. SMI parameters were assessed in the most vascularized lesion area (comprehensive lesion coverage was performed). Clinical response (6 months post-treatment) followed a modified ISSVD composite endpoint. Univariate/multivariate logistic regression and ROC analyses (AUC, sensitivity, specificity) were used, adjusted for age and disease duration.
RESULTS: Responders (27/47, 57.4%) had significantly higher baseline VD (10.34 ± 2.01 vs. 8.37 ± 3.93, P = 0.030) and VI (7.33 ± 1.55 vs. 5.48 ± 2.53, P = 0.003). Baseline VD (OR = 1.85) and VI (OR = 2.02) were independent predictors. The combined model showed superior performance (AUC = 0.849, 88.9% sensitivity, 80.0% specificity).
CONCLUSION: HF-US/SMI-derived baseline VD and VI enable accurate prediction of NB-UVB response in VLS, supporting individualized pre-treatment decisions.
METHODS: Forty-seven biopsy-confirmed VLS patients undergoing standardized NB-UVB (24 weeks) were enrolled (2021-2024). Baseline vascular density (VD), vessel index (VI, SMI), and dermal thickness (HF-US) were measured. SMI parameters were assessed in the most vascularized lesion area (comprehensive lesion coverage was performed). Clinical response (6 months post-treatment) followed a modified ISSVD composite endpoint. Univariate/multivariate logistic regression and ROC analyses (AUC, sensitivity, specificity) were used, adjusted for age and disease duration.
RESULTS: Responders (27/47, 57.4%) had significantly higher baseline VD (10.34 ± 2.01 vs. 8.37 ± 3.93, P = 0.030) and VI (7.33 ± 1.55 vs. 5.48 ± 2.53, P = 0.003). Baseline VD (OR = 1.85) and VI (OR = 2.02) were independent predictors. The combined model showed superior performance (AUC = 0.849, 88.9% sensitivity, 80.0% specificity).
CONCLUSION: HF-US/SMI-derived baseline VD and VI enable accurate prediction of NB-UVB response in VLS, supporting individualized pre-treatment decisions.