数字语言标记区分额颞叶痴呆症中的额叶和右颞叶前部萎缩

Jet M.J. Vonk, Brittany T. Morin, Janhavi Pillai, David Rosado Rolon, Rian Bogley, David Paul Baquirin, Zoe Ezzes, Boon Lead Tee, Jessica DeLeon, Lisa Wauters, Sladjana Lukic, Maxime Montembeault, Kyan Younes, Zachary Miller, Adolfo M. García, Maria Luisa Mandelli, Virginia E. Sturm, Bruce L. Miller, Maria Luisa Gorno-Tempini
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引用次数: 0

摘要

背景和目的 在额颞叶痴呆症(FTD)中,以额叶萎缩为特征的行为变异型(bvFTD)和以右前颞叶(rATL)萎缩为特征的语义行为变异型(sbvFTD)由于症状和神经解剖学上的重叠,给诊断带来了挑战。准确的鉴别对于纳入针对TDP-43蛋白病的临床试验至关重要。本研究调查了自动语音分析是否能区分与FTD相关的rATL和额叶萎缩,从而提供一种非侵入性诊断工具。
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Digital language markers distinguish frontal from right anterior temporal lobe atrophy in frontotemporal dementia
Background and Objectives Within frontotemporal dementia (FTD), the behavioral variant (bvFTD) characterized by frontal atrophy, and semantic behavioral variant (sbvFTD) characterized by right anterior temporal lobe (rATL) atrophy, present diagnostic challenges due to overlapping symptoms and neuroanatomy. Accurate differentiation is crucial for clinical trial inclusion targeting TDP-43 proteinopathies. This study investigated whether automated speech analysis can distinguish between FTD-related rATL and frontal atrophy, potentially offering a non-invasive diagnostic tool.
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