Multi-Modal Neuroimaging in Premanifest and Early Huntington’s Disease: 18 Month Longitudinal Data from the IMAGE-HD Study

壳核 部分各向异性 磁共振成像 尾状核 神经影像学 亨廷顿病 磁共振弥散成像 医学 萎缩 白质 成像生物标志物 核医学 灰质 生物标志物 病理 内科学 放射科 疾病 生物 精神科 生物化学
作者
Juan F. Domínguez D,Gary F. Egan,Marcus A. Gray,Govinda Poudel,Andrew Churchyard,Phyllis Chua,Julie C. Stout,Nellie Georgiou‐Karistianis
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:8 (9): e74131-e74131 被引量:89
标识
DOI:10.1371/journal.pone.0074131
摘要

IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI) study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively). In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume) and microstructural (diffusivity) longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter) and in caudate and putamen (volume and diffusivity change). Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years), close to diagnosis (<15 years) and after diagnosis. Of the two diffusion metrics (mean diffusivity, MD; fractional anisotropy, FA), only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.

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