The vestibular system is the sensory organ responsible for perceiving head rotational movements and maintaining postural balance of human body. The objectives of this study are to propose an innovative computational technique capable of automatically segmenting the vestibular system and to analyze its geometrical features from high resolution T2-weighted MR images. In this study, the proposed technique was used to test the hypothesis that the morphoanatomy of vestibular system in adolescent idiopathic scoliosis (AIS) patients is different from healthy control subjects. The findings could contribute significantly to the understanding of the etiopathogenesis of AIS. The segmentation pipeline consisted of extraction of region of interest, image pre-processing, K-means clustering, and surface smoothing. The geometry of this high-genus labyrinth structure was analyzed through automatic partition into genus-0 units and approximation using the best-fit circle and plane for each unit. The metrics of the best-fit planes and circles were taken as shape measures. The proposed technique was applied on a cohort of 20 right-thoracic AIS patients (mean age 14.7 years old) and 20 age-matched healthy girls. The intermediate results were validated by subjective scoring. The result showed that the distance between centers of lateral and superior canals and the angle with vertex at the center of posterior canal were significantly smaller in AIS than in healthy controls in the left-side vestibular system with p=0.0264 and p=0.0200 respectively, but not in the right-side counterparts. The detected morphoanatomical changes are likely to be associated with subclinical postural, vestibular and proprioceptive dysfunctions reported frequently in AIS. This study has demonstrated that the proposed method could be applied in MRI-based morphoanatomy studies of vestibular system clinically.
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