Abstract
Facial palsy, affecting 1 in 60 individuals, requires precise assessment for effective treatment and follow-up. Current grading systems are inconsistent due to redundant subjective factors. Discrete assessment of the whole face fails to address eyelid and mouth movements innervated by separate nerves. Herein, we proposed modified House-Brackmann (H-B) criteria with continuous and componentized measurements for the eyelids and mouth. Using a dataset of 274 patients with vestibular schwannoma (VS), we developed a dense facial landmark alignment model. This model outperformed existing algorithms in facial palsy detection and produced clinically interpretable asymmetric coefficients of eyelids and mouth correlated with consensus H-B grades (r = 0.892 and 0.890, P < 0.001). Thresholds from ROC analysis transformed these coefficients into grades, comparable to consensus H-B grades. Validated in a separate post-VS multi-center cohort, this model showed high accuracy (eyelid Grade 6 not observed; analyses restricted accordingly) and potential for continuous monitoring of facial palsy, offering a more precise and comprehensive assessment tool. Trial Registration Information the Chinese Clinical Trial Registry (ChiCTR1900024638; July 19, 2019).