Lichen sclerosus (LS) is a chronic inflammatory skin condition that predominantly affects anogenital skin in women. Despite its significant impact, the true prevalence of vulvar LS remains uncertain due to underdiagnosis and underreporting [1]. Studies estimate LS affects up to 3% of postmenopausal women, with an increasing incidence, though it also occurs in premenopausal women and children [2]. This condition is often underserved, and delays in diagnosis can severely impact patients' quality of life, leading to irreversible scarring, vulvar architectural distortion, genitourinary complications, and chronic pain syndromes [3]. Currently, there is limited understanding of LS pathogenesis and no FDA-approved treatments, with lifelong management being the standard approach. Skin biopsies are the gold standard for diagnosing LS; however, they are invasive, particularly in the sensitive vulvar region, and time-consuming. Additionally, approximately 5% of women with LS develop vulvar squamous cell carcinoma (SCC), and nearly half of all vulvar cancers are associated with LS [4]. This necessitates frequent monitoring and repeated biopsies to evaluate SCC development in longstanding LS lesions. To address the limitations of current diagnostic and monitoring methods, there is an urgent need for noninvasive, high-sensitivity, real-time imaging techniques. OCT has the potential to provide the best combination of benefits because of its high-resolution (1- 15 μm), its real-time cross-sectional imaging with a penetration depth of 1-2 mm, and its safe, non-invasive operation. Furthermore, our group has developed Doppler OCT/OCTA to visualize vascular networks and angiogenesis [5-9]. This study proposes the development of a 1.7-μm optical coherence tomography angiography (OCTA) technique to enable noninvasive diagnosis and monitoring of vulvar LS lesions. This approach aims to provide a sensitive, real-time imaging modality that can improve diagnostic accuracy, reduce patient burden, and facilitate early detection of malignant transformations in LS.