Keywords: Head & Neck/ENT, Head & Neck/ENT, Normative Modeling; Meige syndrome; Facial Paralysis; Machine Learning
Motivation: This study delves into the variations in gray matter volume among patients with Meige Syndrome (MS), facial paralysis (FP), and healthy controls.
Goal(s): It aims to unveil the neurological mechanisms underlying these conditions. With a sample of 53 FP patients, 31 MS patients, and 102 healthy controls, the research assesses disease severity and conducts high-resolution MRI imaging.
Approach: Normative modeling and machine learning algorithms are employed to identify differences in specific brain regions.
Results: Results reveal significant variations in gray matter volume, particularly in the anterior cingulate region, shedding light on the importance of this area in understanding these conditions.
Impact: This study's outcomes could transform clinical practice and research in Ménière's Syndrome and facial paralysis. Enhanced diagnostic and treatment methods may significantly improve patients' quality of life, fostering exploration of innovative therapies and a deeper understanding of these conditions.
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