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阿尔茨海默病中脊髓的隐匿性受累

Unsuspected Involvement of Spinal Cord in Alzheimer Disease.

作者信息

Lorenzi Roberta Maria, Palesi Fulvia, Castellazzi Gloria, Vitali Paolo, Anzalone Nicoletta, Bernini Sara, Cotta Ramusino Matteo, Sinforiani Elena, Micieli Giuseppe, Costa Alfredo, D'Angelo Egidio, Gandini Wheeler-Kingshott Claudia A M

机构信息

Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.

Neuroradiology Unit, Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy.

出版信息

Front Cell Neurosci. 2020 Jan 30;14:6. doi: 10.3389/fncel.2020.00006. eCollection 2020.

Abstract

: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer's disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important imaging biomarker contributing to understanding neurodegeneration associated with dementia. : 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features ( > 0.7) were removed, and the best subset identified for patients' classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups ( ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. : Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. : Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.

摘要

脑萎缩是痴呆症公认的生物标志物,但迄今为止尚未对脊髓受累情况进行研究。由于脊髓在将感觉运动控制信号从皮层传递到外周神经系统以及反之亦然的过程中发挥作用,因此评估它是否会因一种首先以累及认知领域而闻名且运动症状也会进行临床评估的疾病而受到萎缩影响,确实是一个非常有趣的问题。因此,我们假设在阿尔茨海默病(AD)中,严重萎缩也会影响脊髓,并且脊髓萎缩确实是有助于理解与痴呆症相关的神经退行性变的重要影像学生物标志物。对31名AD患者和35名健康对照(HC)受试者的3DT1图像进行处理,以计算脑结构体积以及颈髓的横截面积(CSA)和体积(CSV)[每个椎体以及C2 - C3节段(CSA23和CSV23)]。去除相关性大于0.7的特征,并使用随机森林算法确定用于患者分类的最佳子集。使用一般线性模型回归来发现组间的显著差异(P≤0.05)。实施线性回归以评估简易精神状态检查表(MMSE)评分作为因变量,以最佳特征作为预测因子时的解释方差。

AD患者的脊髓特征显著减少,与脑体积无关。当将CSA23与海马体、左侧杏仁核、白质和灰质的体积一起纳入时,患者分类准确率达到76%,敏感性为74%,特异性为78%。单独的CSA23解释了MMSE方差的13%。

我们的研究结果表明,C2 - C3脊髓萎缩与更成熟的特征一起有助于将AD与HC区分开来。结果表明,从与所有其他脑体积(包括左右海马体)相同的3DT1扫描中计算出的CSA23在分类任务中具有相当大的权重,值得进一步研究。连同最近揭示AD萎缩超出颞叶的研究一起,我们的结果将脊髓添加到了该疾病所累及的许多未被怀疑的区域中。有趣的是,脊髓萎缩也解释了认知评分,这可能会显著影响我们对主要累及认知领域的退行性疾病中的感觉运动控制进行建模的方式。应该专门设计前瞻性研究来了解萎缩机制以及脊髓在AD中的作用。

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