Department of Radiology, VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, USA.
Division of Cardiology and Radiology, VA Greater Los Angeles Healthcare System and David, Geffen School of Medicine at UCLA, USA.
J Clin Neurosci. 2022 Nov;105:131-136. doi: 10.1016/j.jocn.2022.09.014. Epub 2022 Sep 29.
Current methods for quantitative assessment of cerebral small vessel disease (CSVD) ignore critical aspects of the disease, namely lesion type and regionality. We developed and tested a new scoring system for CSVD, "regional Cerebral Small Vessel Disease" (rCSVD) based on regional assessment of magnetic resonance imaging (MRI) features.
141 patients were retrospectively included with a derivation cohort of 46 consecutive brain MRI exams and a validation cohort of 95 patients with known cerebrovascular disease. We compared the predictive value of rCSVD against existing scoring methods. We determined the predictive value of rCSVD score for all-cause mortality and recurrent strokes.
46 (44 male) veteran patients (age: 66-93 years), were included for derivation of the rCSVD score. A non-overlapping validation cohort consisted of 95 patients (89 male; age: 34-91 years) with known cerebrovascular disease were enrolled. Based on ROC analysis with comparison of AUC (Area Under the Curve), "rCSVD" score performed better compared to "total SVD score" and Fazekas score for predicting all-cause mortality (0.75 vs 0.68 vs 0.69; p = 0.046). "rCSVD" and total SVD scores were predictive of recurrent strokes in our validation cohort (p-values 0.004 and 0.001). At a median of 5.1 years (range 2-17 years) follow-up, Kaplan-Meier survival analysis demonstrated an rCSVD score of 2 to be a significant predictor of all-cause-mortality.
"rCSVD" score can be derived from routine brain MRI, has value in risk stratification of patients at risk of CSVD, and has potential in clinical trials once fully validated in a larger patient cohort.
目前用于评估脑小血管疾病(CSVD)的定量方法忽略了该疾病的一些关键方面,即病变类型和区域性。我们开发并测试了一种基于磁共振成像(MRI)特征的区域性脑小血管疾病(rCSVD)的新评分系统。
回顾性纳入 141 名患者,其中 46 名连续脑 MRI 检查患者纳入推导队列,95 名已知脑血管疾病患者纳入验证队列。我们比较了 rCSVD 与现有评分方法的预测价值。我们确定了 rCSVD 评分对全因死亡率和复发性卒中的预测价值。
46 名(44 名男性)退伍军人患者(年龄:66-93 岁)纳入 rCSVD 评分推导。一个非重叠的验证队列包括 95 名(89 名男性;年龄:34-91 岁)已知脑血管疾病的患者。基于 ROC 分析比较 AUC(曲线下面积),“rCSVD”评分在预测全因死亡率方面优于“总 SVD 评分”和 Fazekas 评分(0.75 对 0.68 对 0.69;p=0.046)。“rCSVD”和总 SVD 评分可预测我们验证队列中的复发性卒中(p 值分别为 0.004 和 0.001)。在中位 5.1 年(范围 2-17 年)的随访中,Kaplan-Meier 生存分析表明 rCSVD 评分 2 是全因死亡率的显著预测因素。
“rCSVD”评分可从常规脑 MRI 得出,对 CSVD 风险患者的风险分层有价值,一旦在更大的患者队列中得到充分验证,它就有可能在临床试验中得到应用。