CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, UK.
Eur J Neurosci. 2021 Apr;53(8):2788-2803. doi: 10.1111/ejn.15055. Epub 2020 Dec 11.
Previous studies investigating associations between white matter alterations and duration of temporal lobe epilepsy (TLE) have shown differing results, and were typically limited to univariate analyses of tracts in isolation. In this study, we apply a multivariate measure (the Mahalanobis distance), which captures the distinct ways white matter may differ in individual patients, and relate this to epilepsy duration. Diffusion MRI, from a cohort of 94 subjects (28 healthy controls, 33 left-TLE and 33 right-TLE), was used to assess the association between tract fractional anisotropy (FA) and epilepsy duration. Using ten white matter tracts, we analysed associations using the traditional univariate analysis (z-scores) and a complementary multivariate approach (Mahalanobis distance), incorporating multiple white matter tracts into a single unified analysis. For patients with right-TLE, FA was not significantly associated with epilepsy duration for any tract studied in isolation. For patients with left-TLE, the FA of two limbic tracts (ipsilateral fornix, contralateral cingulum gyrus) were significantly negatively associated with epilepsy duration (Bonferonni corrected p < .05). Using a multivariate approach we found significant ipsilateral positive associations with duration in both left, and right-TLE cohorts (left-TLE: Spearman's ρ = 0.487, right-TLE: Spearman's ρ = 0.422). Extrapolating our multivariate results to duration equals zero (i.e., at onset) we found no significant difference between patients and controls. Associations using the multivariate approach were more robust than univariate methods. The multivariate Mahalanobis distance measure provides non-overlapping and more robust results than traditional univariate analyses. Future studies should consider adopting both frameworks into their analysis in order to ascertain a more complete understanding of epilepsy progression, regardless of laterality.
先前研究调查了脑白质改变与颞叶癫痫(TLE)持续时间之间的关系,结果不尽相同,而且通常仅限于对孤立束的单变量分析。在这项研究中,我们应用了一种多变量测量方法(马氏距离),该方法可以捕捉个体患者脑白质的不同变化方式,并将其与癫痫持续时间相关联。我们使用弥散磁共振成像(DWI)对 94 名受试者(28 名健康对照者,33 名左侧 TLE 和 33 名右侧 TLE)的脑白质进行了评估,以评估束分数各向异性(FA)与癫痫持续时间之间的关联。我们使用十种白质束,通过传统的单变量分析(z 分数)和互补的多变量方法(马氏距离)进行了分析,将多个白质束纳入单个统一分析中。对于右侧 TLE 患者,孤立研究任何束时,FA 与癫痫持续时间均无显著相关性。对于左侧 TLE 患者,两条边缘束(同侧穹窿,对侧扣带回)的 FA 与癫痫持续时间呈显著负相关(Bonferroni 校正后 p <.05)。使用多变量方法,我们发现左侧和右侧 TLE 队列中均与持续时间存在显著的同侧正相关(左侧 TLE:Spearman's ρ=0.487,右侧 TLE:Spearman's ρ=0.422)。将我们的多变量结果外推到持续时间等于零(即发病时),我们发现患者与对照组之间没有显著差异。与单变量方法相比,多变量方法的相关性更稳健。多变量马氏距离测量方法提供了比传统单变量分析更不重叠且更稳健的结果。未来的研究应考虑在其分析中同时采用这两种框架,以便无论偏侧性如何,都能更全面地了解癫痫的进展。