Clinical Research Directory

The Diagnostic Accuracy of Advanced Imaging in Identifying Suspected Skin Cancer (Basal Cell Carcinoma) Around the Eyes

The purpose is to investigate the diagnostic value (sensitivity and specificity) of dermal-Optical Coherence Tomography (D-OCT, VivoSight Dx), in patients with clinically suspected BCC lesions inside the periocular region and compare these results to previous reports using D-OCT in diagnosing lesions outside the periocular area. The Hypotheses: * The sensitivity and specificity of D-OCT in diagnosing BCC inside the periocular region is comparable to previous reports on BCC lesions outside the periocular region when the standard D-OCT probe is used. * The sensitivity and specificity of D-OCT in diagnosing BCC inside the periocular region is increased when the customised D-OCT probe is used. * The sensitivity and specificity of D-OCT in diagnosing periocular BCC is comparable to punch biopsy when both standard and the customised D-OCT probes are used. * D-OCT with the 10 and 20-millimeter standoff is capable of subtyping periocular BCC. * The inter-observer variation in diagnosing and sub-typing periocular BCC decreases with increasing experience in the scanning procedure. * The number of scans to correctly interpret D-OCT decreases with increasing experience in the scanning procedure. * Delineation of periocular BCC tumour extension is possible using both D-OCT probes

Spacer Graft Study

To determine which of three types of spacer grafts (hard palate vs autologous ear cartilage vs Enduragen) are the most effective in lower eyelid retraction repair outcomes as measured by MRD2 (margin to reflex distance 2)

Assessment of Eyelid Topology and Kinetics Based on Deep Learning Method

This study plans to assess eyelid topology (such as margin reflex distance, eyelid contour, and corneal exposure area) and blinking (such as frequency, velocity, and duration), using deep learning method to automatically extract eyelid topological features, and to predict subtypes of levator function, using deep learning method to extract blinking features, in order to provide new ideas and means to assess eyelid topology and kinetics.