Department of Neurosurgery, Shiga Medical Center for Adults, Shiga, Japan.
Eur J Neurol. 2012 Jan;19(1):98-104. doi: 10.1111/j.1468-1331.2011.03451.x. Epub 2011 Jun 4.
Taking an advantage of the high sensitivity of 3D T2*-weighted gradient-recalled-echo (GRE) imaging to cerebral microbleeds, we investigated the relationship between cerebral microbleeds and leukoaraiosis.
Participants aged 40 years or more have been evaluated for the presence of cerebral microbleeds using 3D T2*-GRE sequence since 2006. The severity of periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH) on fluid attenuated inversion recovery images was assessed using Fazekas rating scales. Multivariate logistic regression analyses were conducted after adjustment for stroke subtype, age, PVH, DWMH, hypertension, dementia, and use of platelet aggregation inhibitors. Additionally, we examined the association between cerebral microbleeds and other covariates using a Pearson's correlation analysis.
Amongst 389 patients, 67 patients had a single microbleed and 93 had multiple microbleeds. The prevalence of microbleeds was 83% amongst 53 patients with intracerebral hemorrhage (ICH), 49% amongst 173 with infarction, and 20% amongst 163 without any type of stroke. In the multivariate analyses, the odds ratio (95% CIs) of microbleed detection was 10.1, (4.12-24.8) for ICH, 2.33 (1.12-4.85) for atherosclerotic infarction, 1.66 (1.10-2.48) for PVH, and 1.49 (1.02-2.19) for DWMH. In the Pearson's correlation analysis, cerebral microbleeds were closely related to PVH (Pearson's correlation coefficient; 0.48) and DWMH (0.37), compared with age (0.16).
High-grade PVH, high-grade DWMH, ICH, and atherosclerotic infarction were significantly independent predictors for cerebral microbleeds. In addition, we found that the grades of PVH and DWMH have a closer association with the number of cerebral microbleeds than age.
利用 3D T2*-梯度回波（GRE）成像对脑微出血的高灵敏度，我们研究了脑微出血与脑白质疏松症之间的关系。
自 2006 年以来，我们使用 3D T2*-GRE 序列评估了年龄在 40 岁及以上的参与者是否存在脑微出血。在液体衰减反转恢复图像上，使用 Fazekas 评分量表评估脑室周围高信号（PVH）和深部白质高信号（DWMH）的严重程度。在调整了中风亚型、年龄、PVH、DWMH、高血压、痴呆和血小板聚集抑制剂的使用后，进行了多变量逻辑回归分析。此外，我们使用 Pearson 相关分析检查了脑微出血与其他协变量之间的关系。
在 389 名患者中，67 名患者有单个微出血，93 名患者有多个微出血。在 53 名脑出血（ICH）患者中，微出血的患病率为 83%，在 173 名梗死患者中为 49%，在 163 名无任何类型中风的患者中为 20%。在多变量分析中，微出血检测的优势比（95%CI）为 ICH 患者 10.1（4.12-24.8），动脉粥样硬化性梗死患者 2.33（1.12-4.85），PVH 患者 1.66（1.10-2.48），DWMH 患者 1.49（1.02-2.19）。在 Pearson 相关分析中，脑微出血与 PVH（Pearson 相关系数为 0.48）和 DWMH（0.37）密切相关，而与年龄（0.16）相关较弱。
高级别 PVH、高级别 DWMH、ICH 和动脉粥样硬化性梗死是脑微出血的显著独立预测因子。此外，我们发现 PVH 和 DWMH 的严重程度与脑微出血的数量比年龄更密切相关。
