Academic radiology · 2023
Surface-Based Neuroimaging Pattern of Multiple System Atrophy.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Wang Zhan, Mo Jiajie, Zhang Jianguo, Feng Tao, Zhang Kai
Аннотация
RATIONALE AND OBJECTIVES: Overlapping parkinsonism, cerebellar ataxia, and pyramidal signs render challenges in the clinical diagnosis of multiple system atrophy (MSA). The neuroimaging pattern is valuable to understand its pathophysiology and improve its diagnostic effect.
MATERIALS AND METHODS: We retrospectively obtained magnetic resonance imaging and susceptibility-weighted imaging in patients with MSA (including parkinsonian type [MSA-P] and cerebellar type [MSA-C]), Parkinson's disease, and normal controls. We quantified neuroimaging features to identify the optimal threshold for diagnosis. Furthermore, we explore neuroimaging patterns of MSA by mapping the subcortical morphological alterations and constructing a diagnostic model.
RESULTS: Compared to controls, normalized putaminal volume significantly decreased in patients with MSA-P (P < .001) and normalized pontine volume significantly decreased in patients with MSA-C (P < .001). The Youden index of the threshold-based clinical prediction model was 0.871-0.928 in patients with MSA. The neuroimaging pattern in patients with MSA was jointly located in the lateral putamen, and the neuroimaging pattern prediction model achieved a classification accuracy of 83.9%-100%.
CONCLUSION: The quantitative neuroimaging features and surface-based morphologic anomalies represent the markers of MSA and open new avenues for personalized clinical diagnosis.
MATERIALS AND METHODS: We retrospectively obtained magnetic resonance imaging and susceptibility-weighted imaging in patients with MSA (including parkinsonian type [MSA-P] and cerebellar type [MSA-C]), Parkinson's disease, and normal controls. We quantified neuroimaging features to identify the optimal threshold for diagnosis. Furthermore, we explore neuroimaging patterns of MSA by mapping the subcortical morphological alterations and constructing a diagnostic model.
RESULTS: Compared to controls, normalized putaminal volume significantly decreased in patients with MSA-P (P < .001) and normalized pontine volume significantly decreased in patients with MSA-C (P < .001). The Youden index of the threshold-based clinical prediction model was 0.871-0.928 in patients with MSA. The neuroimaging pattern in patients with MSA was jointly located in the lateral putamen, and the neuroimaging pattern prediction model achieved a classification accuracy of 83.9%-100%.
CONCLUSION: The quantitative neuroimaging features and surface-based morphologic anomalies represent the markers of MSA and open new avenues for personalized clinical diagnosis.