摘要
目的:分析肝海绵状血管瘤不同b值的MRI弥散加权成像特性,提高病变检出率和图像质量。方法:对连续的MRI平扫和增强明确诊断的13例肝海绵状血管瘤,比较弥散加权成像b值分别为0s/mm2,100s/mm2和700s/mm2时的特征。结果:MRI平扫和增强分别显示34个(87%)和29个(74%)病变;在弥散加权成像中,b为0s/mm2时显示21个(54%),小的病变与血管和胆管易混淆;b为100s/mm2时显示39个(100%),病变与周围组织界限清晰;b为700s/mm2时显示33个(85%)。正常肝组织的信噪比以b值为100s/mm2最高(19.15±0.85);病变的信噪比以b值为0s/mm2时最高(12.89±0.96);病变与周围正常肝组织的对比度以b为700s/mm2时最低(0.37±0.02)。结论:MRI弥散加权成像进一步提高了对肝海绵状血管瘤的敏感性,以b值为100s/mm2时,病变检出率和图像质量最高。
Objective：To analyze the characterization of cavernous hemangiomas of the liver on diffusion weighted imaging of MRI in order to improve the detection rates of lesions and quality of images.Methods：Thirteen cases were diagnosed definitely in cavernous hemangiomas of the liver in plain and contrast scans of MRI consecutively.Their characterization of diffusion weighted imaging were compared in different b values,such as 0 s/mm2,100 s/mm2 and 700 s/mm2 individually.Results：In these 13 patients,the exhibition of cavernous hemangiomas of the liver were 34 lesions（87%） on plain scans,29 lesions（74%） on kinetic contrast enhancement scans.On diffusion weighted imaging,21 lesions（54%） were found clearly in 0 s/mm2 of b value,and 39 lesions（100%） in 100 s/mm2 of b value and 33 lesions（85%） in 700 s/mm2 of b value.While small lesions were easily confused with blood vessels and bile ducts in 0 s/mm2 of b value,the margins of lesions were delineated clearly in 100 s/mm2 of b value.The signal to noise of normal liver was on the highest in 100 s/mm2 of b value（19.15±0.85）,as the signal to noise of cavernous hemangiomas of the liver was on the highest in 0 s/mm2 of b value（12.89±0.96）.The contrast between cavernous hemangiomas of the liver and the surrounding normal liver was on the lowest in 700 s/mm2 of b value（0.37±0.02）.Conclusion：The diffusion weighted imaging of MRI promotes the sensitivity of MRI further in detection of cavernous hemangiomas of the liver.When b value is in 100 s/mm2,the diffusion weighted imaging has the highest sensitivity of lesions and quality of images.
出处
《医学影像学杂志》
2010年第7期996-999,共4页
Journal of Medical Imaging
