脑血管疾病患者脑萎缩的MR随访研究

Serial MR evaluation of brain atrophy in patients with cerebral vascular disease

目的利用脑结构图像萎缩率标准化评价软件对脑血管病患者进行脑萎缩的随访评价,并探讨影响其发展的危险因素。方法138例脑血管病患者间隔一年先后进行两次头颅MRI检查。两次扫描的参数和定位保持一致。严格记录所有患者研究初始阶段的年龄、收缩压、血糖、血脂、烟酒嗜好以及有无高血压、糖尿病、高脂血症病史等情况,并进行了简易精神状态检查评分(MMSE)和美国国立卫生研究院卒中量表(NIHSS)评分。利用脑结构图像萎缩率标准化评价软件(SIENA)对前后两次的T1W图像进行自动化分析,计算患者的年脑体积变化率(PBVC);同时,采用半自动体积测量软件测量患者初始状态下的WMH体积以及新近脑梗死灶体积,然后采用多元回归方法筛选对PBVC存在影响的危险因素,并分析临床评分、梗死灶体积与PBVC之间的相关性。结果该组患者的PBVC为-0.77%±0.81%,初始WMH体积为(13155±18782)mm3,患者脑内灰白质梗死体积之和为(5081±12709)mm3。多元回归方程显示年龄、灰质梗死、白质梗死的存在对PBVC有影响作用。PBVC与MMSE评分存在低度正相关(r=0.27,P=0.001);脑体积变化率与NIH评分存在低度负相关(r=-0.18,P=0.036)。脑梗死体积与脑体积变化率相关系数为-0.44,存在低度负相关(P=0.000)。结论年龄和新近脑梗死是脑血管病患者脑萎缩的影响因素。应用SIENA软件可以准确地评价脑萎缩,为脑血管病的临床评价提供了一个有参考价值的指标。

Objective To estimate the brain atrophy rates in patients with cerebral vascular disease by using SIENA soft ware, and analyze the risk factors. Methods One hundred and thirty-eight patients with cerebral vascular disease underwent MR scanning twice one year apart, at the baseline and at the end of the follow up period. The clinical data of all pa tients, including age, systolic blood pressure, blood glucose level, serum lipid level and alcohol consumption and smoking were recorded at baseline, as well as historical information concerning hypertension, diabetes mellitus and hypercholesterolemia. Besides, clinical rating of Mini-mental State Examination （MMSE） and the National Institute of Health Stroke Scale were conducted for every patient. Their TlW images at both time points were processed automatically with SIENA software to determine the percent brain volume change （PBVC）. MRI measures included volume of newly onset gray matter and white matter infarction, and baseline volume of white matter hyperintensity （WMH）. The influence of risk factors on PBVC was analyzed by using regression analysis. Correlation coefficients were calculated between clinical scales and PBVC. Results The PBVC was -0. 77%±0.81% for the patients, and the initial WMH volume was （13 155±18 782）mm3 , the volume of newly-onset infarction was（5 081±12 709）mm^3 o Regression analysis revealed that PBVC was affected by the age, and the presence of newly-onset gray matter and white matter infarction. PBVC was correlated significantly with MMSE （r=0. 27, P=0. 001）, while it was correlated reversely with NIHSS （r =0.18, P=0. 036）. There was a significant relationship between the PBVC and volume of newly-onset infarction （r=0.44, P=0. 000）. Conclusion Age and newly-onset infarction may have an effect on the brain atrophy in patients with cerebral vascular disease. SIENA software identifies brain atrophy quantitatively, which may provide useful information for clinical evaluation.