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核磁共振弥散加权成像在急性脑梗死诊断中的临床价值
http://www.100md.com 《齐齐哈尔医学院学报》 2006年第4期
急性脑梗死,,急性脑梗死,弥散加权成像,1资料与方法,2结果,3讨论,参考文献
     【摘要】 目的 探讨核磁共振弥散加权成像(DWI)在急性脑梗死,尤其是对超早期脑梗死的诊断和治疗中的作用。方法 对高度怀疑脑梗死的患者,分别做头CT、MRI、DWI检查,根据发病时间分3组进行比较,并比较发病<12小时和12~24小时两组DWI阳性病例弥散系数(ADC)。结果 6小时之内的DWI检查阳性率为66.7%,发病6~12 小时阳性率为73.1%,其中,脑干、小脑梗死7例中DWI检查阳性的4例,阳性率为59.1%,发病12~24小时阳性率为100%。从12小时以内与12~24小时两组脑梗死DWI阳性病例弥散系数(ADC)的比较看出<12小时组与12~24小时组首先进行方差齐性检验,计算结果显示两组方差齐。两组间ADC 值有显著性差异,12~24小时组与<12小时组比较ADC 值降低更为明显。结论 DWI扫描可以明确的诊断早期脑梗死,尤其对脑干和小脑的早期梗死诊断更有临床价值,能正确的指导临床治疗及评估预后。

    【关键词】 急性脑梗死 弥散加权成像

    Impact on Cerebral Thrombosis Diagnosis of early Diffusion-Weighted Magnetic Resonance Imaging

    Cao Wenbing,et al.

    (Internal Medicine Department,Tang-Xia People’s Hospital,Dongguan,Guangdong 523721,China)

    【Abstract】 Objective To study the diagnostic and therapy directive effect of diffusion-weighted MRI(DWI) in acute cerebral thrombosis,especially in super acute state.Methods DWI,CT and MRI were performed respectively on the hyper suspected cerebral thrombosis,which were divided into three groups according to the symptom duration,and the results were compared.ADC(apparent diffusion coefficient) value of two groups with positive DWI were compared too.One group was the patients who had symptom duration within 12 hours,the other was 12~24 hours.Results DWI-detected abnormality within 6 hours after symptom onset was 66.7%,6~12 hours was 73.1%,(among these,abnormality was present in 4 of 7 cases who suffered brainstem or cerebellar thrombosis),while 12~24 hours was as high as 100%.The ADC value of the ≤12 hours and 12~24 hours groups,which with positive DWI scans,suggested that the variance of two groups was Homogeneity.It showed that ADC value of these two groups had significant difference.The reduction in 12~24 hours group was more remarkable than <12 hours group.Conclusions DWI scan have a confirm effect of clear diagnosing in early cerebral thrombosis,especially in brainstem and cerebellar thrombosis.It also has an important status in clinical therapy and clinical outcome predicting. ......

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