Close Correlation between Quantitative and Qualitative Assessments of White Matter Lesions
Close Correlation between Quantitative and Qualitative Assessments of White Matter Lesions
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DOI：
10.1159/000341859
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发表时间：
2013-01-01
影响因子：
5.7
通讯作者：
Wardlaw, Joanna M.
中科院分区：
文献类型：
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作者：
Hernandez, Maria del C. Valdes;Morris, Zoe;Wardlaw, Joanna M.
背景：白色病变（WML）随年龄增长而增加，并与卒中、认知能力下降和痴呆有关。它们可以通过视觉评级或计算评估。研究方法：我们比较了1936年洛锡安出生队列的672名参与者的磁共振成像中使用经验证的多光谱图像融合技术确定的WML Fazekas视觉评分和体积，并寻求相关性的受试者的解释。总Fazekas评分（深度和脑室周围评分总和，0-6）和WML体积之间的（斯皮尔曼p）不一致（z评分差异>1）。单独鉴定了药物。结果如下：中位WML Fazekas评分为2 [四分位距（IQR）：2]，中位WML体积为7.7 ml（IQR：13.6 ml），中位梗死体积（n = 95）为0.98 ml。评分和体积高度相关（斯皮尔曼p = 0.78，p < 0.001）。但这并没有改变相关性。在94/672例（14%）受试者中发生了轻微不一致，大多数受试者的Fazekas总分为1（n = 20，WML体积= 4.5-14.8 ml）或2（n = 50，WML体积= 0.1-34.4 ml）。主要原因是：肉眼可识别出细微的WML，但从体积中忽略;突出的心室帽，但薄的体衬，脑室周围评分为1/2，但WML体积较大，以及小的深部局灶性病变，当开始合并时，评分增加，WML体积变化不大。结论：WML评级分数和卷提供WML负担的近似相等的估计，因此可以根据研究情况使用。通过改进细微WML的计算检测和修改视觉评级，以区分突出的心室帽和薄的室周衬里，以及小的非合并的早期合并的深WML，可能会导致更接近的协议。版权所有（C）2012 S. Karger AG，巴塞尔
Background: White matter lesions (WML) increase with age and are associated with stroke, cognitive decline and dementia. They can be visually rated or computationally assessed. Methods: We compared WML Fazekas visual rating scores and volumes, determined using a validated multi-spectral image-fusion technique, in Magnetic Resonance Imaging from 672 participants of the Lothian Birth Cohort 1936 and sought explanations for subjects in whom the correlation (Spearman's p) between the total Fazekas score (summed deep and periventricular ratings, 0-6) and WML volume did not concur (z-score difference >1). Infarcts were identified separately. Results: The median WML Fazekas score was 2 [inter-quartile range (IQR): 2], median WML volume 7.7 ml (IQR: 13.6 ml) and median infarct volume (n = 95) 0.98 ml. Score and volume were highly correlated (Spearman's p = 0.78, p < 0.001). Infarcts did not alter the correlation. Minor discordance occurred in 94/672 (14%) subjects, most with total Fazekas score of 1 (n = 20, WML volume = 4.5-14.8 ml) or 2 (n = 50, WML volume = 0.1-34.4 ml). The main reasons were: subtle WML identified visually but omitted from the volume; prominent ventricular caps but thin body lining giving a periventricular score of 1/2 but large WML volume, and small deep focal lesions which increase the score disproportionally when beginning to coalesce with little change in WML volume. Conclusions: WML rating scores and volumes provide near-equivalent estimates of WML burden, therefore either can be used depending on research circumstances. Even closer agreement could result from improved computational detection of subtle WML and modified visual ratings to differentiate prominent ventricular caps from thin periventricular linings, and small non-coalescent from early coalescent deep WML. Copyright (C) 2012 S. Karger AG, Basel