Abstract

To investigate the alterations in extraocular muscles (EOMs) by magnetic resonance imaging (MRI) among patients diagnosed with Duane retraction yndrome (DRS) and congenital fibrosis of the extraocular muscles (CFEOM), who present with various cranial nerve anomalies in an attempt to enhance the clinical diagnostic process. A case-control study was conducted to evaluate 27 patients with DRS and 14 patients with CFEOM. All patients underwent MRI scans of the brainstem and orbital examination. Neurodevelopmental assessments were conducted through MRI, and maximum cross-sectional area and volumes of EOMs were obtained. Three types of models were constructed using machine learning decision tree algorithms based on EOMs to predict disease diagnosis, cranial nerve abnormalities, and clinical subtypes. Patients with bilateral CN VI abnormalities had smaller volumes of LR, MR, and IR muscles compared to those with unilateral involvement (P < 0.05). Similarly, patients with CFEOM and unilateral third cranial nerve abnormalities had a smaller maximum cross-section of the affected eye's SR compared to the contralateral eye (P < 0.05). In patients with both CN III and CN VI abnormalities, the volume of SR was smaller than in patients with CN III abnormalities alone (P < 0.05). The prediction model using EOMs volume showed a diagnostic precision of 82.5% for clinical cases and 60.1% for predicting cranial nerve abnormalities. Nonetheless, the precision for identifying clinical subtypes was relatively modest, at only 41.7%. The distinctive volumetric alterations in EOMs among individuals exhibiting distinct cranial nerve anomalies associated with DRS or CFEOM provide valuable diagnostic insights into to Congenital Cranial Neurodevelopmental Disorders (CCDDs). MRI analysis of EOMs should thus be regarded as a crucial diagnostic modality.

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