Mitsumura Hidetaka, Miyagawa Shinji, Komatsu Teppei, Sakamoto Yuki, Kono Yu, Furuhata Hiroshi, Iguchi Yasuyuki
Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
J Stroke Cerebrovasc Dis. 2015 Jan;24(1):112-6. doi: 10.1016/j.jstrokecerebrovasdis.2014.07.027. Epub 2014 Oct 16.
The goal of this study was to investigate the relationship between white matter lesions on magnetic resonance imaging and flow parameters in the middle cerebral artery (MCA) measured by transcranial color flow imaging.
Patients with acute ischemic stroke or transient ischemic attack were included. The relationship between severities of periventricular hyperintensity (PVH) and ultrasonographic parameters in the MCA was investigated. The frequency of PVH was calculated for different categories according to the presence or absence of 2 considerable parameters according to the value of area under the receiver operating characteristic curve.
MCA flow was successfully measured in 203 temporal windows among 124 patients. After determining the cutoff value of end-diastolic velocity (EDV) and pulsatility index (PI) for the presence of PVH, 4 different categories were established: Category A, EDV more than 40 cm/second and PI less than .7; Category B, EDV more than 40 cm/second and PI more than .7; Category C, EDV less than 40 cm/second and PI less than .7; and Category D, EDV less than 40 cm/second and PI more than .7. The prevalence of PVH gradually increased along with category (P < .01).
The evaluation of MCA parameters using the combination of PI and EDV may be useful for the prediction of PVH.
本研究的目的是调查磁共振成像上的白质病变与经颅彩色血流成像测量的大脑中动脉(MCA)血流参数之间的关系。
纳入急性缺血性卒中或短暂性脑缺血发作患者。研究脑室周围高信号(PVH)严重程度与MCA超声参数之间的关系。根据受试者工作特征曲线下面积的值,根据两个重要参数的有无,计算不同类别的PVH频率。
在124例患者的203个颞窗中成功测量了MCA血流。确定PVH存在时舒张末期速度(EDV)和搏动指数(PI)的临界值后,建立了4个不同类别:A类,EDV大于40厘米/秒且PI小于0.7;B类,EDV大于40厘米/秒且PI大于0.7;C类,EDV小于40厘米/秒且PI小于0.7;D类,EDV小于40厘米/秒且PI大于0.7。PVH的患病率随类别逐渐增加(P < 0.01)。
联合使用PI和EDV评估MCA参数可能有助于预测PVH。