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急性肠系膜缺血:多排 CT 表现与血管内治疗。

Acute Mesenteric Ischemia: Multidetector CT Findings and Endovascular Management.

机构信息

From the Department of Radiology, Koseikai Takeda Hospital, 841-5 Higashishiokoji-cho, Shimogyo-ku, Kyoto, Japan 600-8558 (S.K., K.F., Y.H.); Department of Radiological Sciences, Tokyo Metropolitan University, Tokyo, Japan (A.F., T.S., L.D.H.N., S.T.); Department of Radiology, Shiga University of Medical Science, Otsu, Japan (S.O., A.I.); and Department of Radiology, Osaka Saiseikai Noe Hospital, Osaka, Japan (T.H.).

出版信息

Radiographics. 2018 May-Jun;38(3):945-961. doi: 10.1148/rg.2018170163.

Abstract

Acute mesenteric ischemia is a rare life-threatening condition that accounts for approximately one in 1000 hospital admissions. The mortality rate is 50%-69% owing to the absence of specific symptoms and laboratory data, which makes early detection of this condition difficult. If the use of contrast material is possible, biphasic contrast material-enhanced multidetector computed tomography (CT) is the first-line imaging test for early diagnosis of the disease and for differentiation from other causes of acute abdomen. Multidetector CT can depict mesenteric ischemia, its underlying causes, and its severity. Mesenteric ischemia is classified as either acute or chronic. The causes of AMI include arterial embolism, arterial thrombosis, venous thrombosis, and nonocclusive mesenteric ischemia, among which arterial causes are far more common than venous causes. Recently, endovascular procedures such as thrombolysis, thrombectomy, thrombus fragmentation, and stent placement have been successfully and safely performed when the ischemia is reversible. Online DICOM image stacks are available for this article. RSNA, 2018.

摘要

急性肠系膜缺血是一种罕见的危及生命的疾病,约占住院患者的 1/1000。由于缺乏特定的症状和实验室数据,死亡率为 50%-69%,这使得早期发现这种疾病变得困难。如果可以使用造影剂,双期对比增强多排 CT(CT)是早期诊断该病和与其他急性腹痛病因鉴别的一线影像学检查方法。多排 CT 可以描述肠系膜缺血、其潜在原因和严重程度。肠系膜缺血分为急性和慢性两种。AMI 的病因包括动脉栓塞、动脉血栓形成、静脉血栓形成和非闭塞性肠系膜缺血,其中动脉原因比静脉原因常见得多。最近,当缺血可逆时,溶栓、血栓切除术、血栓碎裂和支架置入等血管内治疗已成功和安全地进行。本文提供在线 DICOM 图像堆栈。RSNA,2018 年。

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