This study aimed to train and validate deep learning systems (DLS) to differentiate between microvascular ischemic ocular motor nerve palsy (v-OMNP) and inflammatory ocular motor nerve palsy (i-OMNP). The method involves using clearly diagnosed v-OMNP and i-OMNP patients from the Department of Neurology database at Beijing Tongren Hospital for further DLS validation, aiding in the differential diagnosis of the aforementioned diseases.
Study Type
OBSERVATIONAL
Enrollment
299
Tongren Hospital
Beijing, Beijing Municipality, China
The diagnosis of acute bilateral diplopia, microvascular ischemic ocular motor nerve palsy or inflammatory ocular motor nerve palsy.
This study aimed to train and validated deep learning systems to differentiate between v-OMNP and i-OMNP. Clinical information, including sex, age at onset, clinical manifestations, inflammatory factors (including C-reactive protein, erythrocyte sedimentation rate, autoimmune antibody in the cerebrospinal fluid), cavernous sinus MRIs, and prognosis, was obtained from hospitalization and follow-up records. The following information was recorded: (1) intracavernous sinus: abnormal side, thickness of cavernous sinus, thickening enhancement, enlargement and enhancement of CN III, CN IV and CN VI, and narrowing of intracavernous internal carotid artery and (2) extracavernous sinus: enhancing adjacent lesions, lacrimal prolapsus, orbital fascial lipocele, eyeball protrusion, thickened eyelids, and dilatation of superior orbital veins.
Time frame: 6 months
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