O'Sullivan Mike, Jouvent Eric, Saemann Philipp G, Mangin Jean-Francois, Viswanathan Anand, Gschwendtner Andreas, Bracoud Luc, Pachai Chahin, Chabriat Hugues, Dichgans Martin
Neurologische Klinik, Klinikum Grobetahadern, Ludwig Maximilians University, Munich, Germany.
Neuroimage. 2008 Nov 1;43(2):312-20. doi: 10.1016/j.neuroimage.2008.07.049. Epub 2008 Aug 5.
Measurement of brain atrophy has been proposed as a surrogate marker in MS and degenerative dementias. Although cerebral small vessel disease predominantly affects white and subcortical grey matter, recent data suggest that whole brain atrophy is also a good indicator of clinical and cognitive status in this disease. Automated methods to measure atrophy are available that are accurate and reproducible in disease-free brains. However, optimal methods in small vessel disease have not been established and the impact of ischaemic lesions on different techniques has not been explored systematically. In this study, three contrasting techniques -- Statistical Parametric Mapping 5 (SPM5), SIENAX and BrainVisa -- were applied to measure cross-sectional atrophy (brain parenchymal fraction or BPF) in a large (n=143) two-centre cohort of patients with CADASIL, a genetic model of small vessel disease. All three techniques showed similar sensitivity to trends in BPF associated with age and lesion load. No single technique was particularly vulnerable to error as a result of lesions. Provided major errors in registration were excluded by visual inspection, manual correction of segmentations had a negligible impact with mean errors of 0.41% for SIENAX and 0.46% for BrainVisa. BPF correlated strongly with global cognitive function and physical disability, independent of the technique used. Correlation coefficients with the Minimental State Examination score were: BrainVisa 0.58, SIENAX 0.58, SPM5 0.60 (for all, p<0.001). These results suggest that all three methods can be applied reliably in patients with ischaemic lesions. Choice of analysis approach for this kind of clinical question will be determined by factors other than their robustness and precision, such as a desire to explore subtle localised changes using extensions of these processing tools.
脑萎缩测量已被提议作为多发性硬化症(MS)和退行性痴呆的替代标志物。尽管脑小血管疾病主要影响白质和皮质下灰质,但最近的数据表明,全脑萎缩也是该疾病临床和认知状态的良好指标。现已有可用于测量萎缩的自动化方法,这些方法在无疾病的大脑中准确且可重复。然而,小血管疾病的最佳测量方法尚未确立,缺血性病变对不同技术的影响也未得到系统研究。在本研究中,我们应用了三种不同的技术——统计参数映射5(SPM5)、SIENAX和BrainVisa——来测量一个大型(n = 143)两中心CADASIL患者队列的横断面萎缩(脑实质分数或BPF),CADASIL是一种小血管疾病的遗传模型。所有这三种技术对与年龄和病变负荷相关的BPF趋势显示出相似的敏感性。没有一种技术因病变而特别容易出错。通过视觉检查排除主要的配准错误后,手动校正分割的影响可忽略不计,SIENAX的平均误差为0.41%,BrainVisa的平均误差为0.46%。BPF与整体认知功能和身体残疾密切相关,与所使用的技术无关。与简易精神状态检查表评分的相关系数分别为:BrainVisa为0.58,SIENAX为0.58,SPM5为0.60(所有p < 0.001)。这些结果表明,所有这三种方法都可可靠地应用于有缺血性病变的患者。对于这类临床问题,分析方法的选择将由其稳健性和精确性之外的因素决定,例如是否希望使用这些处理工具的扩展来探索细微的局部变化。