Purpose

To investigate the utility of diffusion-weighted arterial spin labeling (DW-ASL) for detecting the progression of brain white matter lesions.

Materials and methods

A total of 492 regions of interest (ROIs) in 41 patients were prospectively analyzed. DW-ASL was performed using the diffusion gradient prepulse of five b-values (0, 25, 60, 102, and 189) before the ASL readout. We calculated the water exchange rate (K_w) with post-processing using the ASL signal information for each b-value. The cerebral blood flow (CBF) was also calculated using b0 images. Using the signal information in FLAIR (fluid-attenuated inversion recovery) images, we classified the severity of white matter lesions into three grades: non-lesion, moderate, and severe. In addition, the normal K_w level was measured from DW-ASL data of 60 ROIs in five control subjects. The degree of variance of the K_w values (K_w-var) was calculated by squaring the value of the difference between each K_w value and the normal K_w level. All patient's ROIs were divided into non-progressive and progressive white matter lesions by comparing the present FLAIR images with those obtained 2 years before this acquisition.

Results

Compared to the non-progressive group, the progressive group had significantly lower CBF, significantly higher severity grades in FLAIR, and significantly greater K_w-var values. In a receiver operator characteristic curve analysis, a high area under the curve (AUC) of 0.89 was obtained with the use of K_w-var. In contrast, the AUCs of 0.59 for CBF and 0.72 for severity grades in FLAIR were obtained.

Conclusions

The DW-ASL technique can be useful to detect the progression of brain white matter lesions. This technique will become a clinical tool for patients with various degrees of white matter lesions.

中文翻译：

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实用程序：扩散加权动脉自旋标记（DW-ASL）技术用于评估脑白质病变的进展。

目的

目的探讨弥散加权动脉自旋标记（DW-ASL）在检测脑白质病变进展中的作用。

材料和方法

前瞻性分析了41位患者中的492个感兴趣区域（ROI）。在ASL读出之前，使用五个b值（0、25、60、102和189）的扩散梯度预脉冲执行DW-ASL。我们使用每个b值的ASL信号信息进行后处理，计算出水交换率（K _w）。还使用b0图像计算了脑血流量（CBF）。使用FLAIR（流体衰减反转恢复）图像中的信号信息，我们将白质病变的严重性分为三个等级：非病变，中度和严重。此外，从五个对照组的60个ROI的DW-ASL数据中测量了正常K _w水平。K _w值的方差程度（K _w-var通过对每个K _w值和正常K _w水平之间的差值进行平方来计算。通过将当前的FLAIR图像与采集前2年获得的图像进行比较，将所有患者的ROI分为非进行性和进行性白质病变。

结果

与非进行性组相比，进行性组的CBF明显较低，FLAIR的严重程度明显较高，K _w-var值明显较高。在接收器操作员特征曲线分析中，使用K _w-var可获得0.89的曲线下较大面积（AUC）。相反，FLAIR中CBF的AUC为0.59，严重等级的AUC为0.72。

结论

DW-ASL技术可用于检测脑白质病变的进展。该技术将成为具有各种程度的白质病变的患者的临床工具。