scholarly journals The impact of thin section diffusion weighted MR imaging in acute cerebral infarction

Nosotchu ◽  
2016 ◽  
Vol 38 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Masanori Sawamura ◽  
Tsuyoshi Okawa ◽  
Wataru Oishi ◽  
Shinichiro Maruhama ◽  
Etsuro Nakanishi ◽  
...  
Radiology ◽  
2002 ◽  
Vol 225 (2) ◽  
pp. 551-555 ◽  
Author(s):  
Kirsten P. Forbes ◽  
James G. Pipe ◽  
John P. Karis ◽  
Joseph E. Heiserman

2003 ◽  
Vol 59 (5) ◽  
pp. 656-662
Author(s):  
KENGO HARADA ◽  
EIJI NISHIMARU ◽  
TAKEHARU YUKUTOMO ◽  
TAKAYUKI ISHIDA

2003 ◽  
Vol 44 (3) ◽  
pp. 343-346
Author(s):  
J. K. Hald ◽  
J. A. Brunberg ◽  
A. B. Dublin ◽  
S. L. Wootton-Gorges

Diffusion-weighted (DW) MR imaging usually identifies acute cerebral infarction injury in symptomatic patients. We report a patient with severe hypoxic brain injury following suicide attempt by hanging, but with normal DW MR imaging 5–6 h after the event. Follow-up DW MR imaging 3 days after the event, and subsequent autopsy, revealed extensive cerebral anoxic injury.


BMC Neurology ◽  
2009 ◽  
Vol 9 (1) ◽  
Author(s):  
Halvor Naess ◽  
Jan C Brogger ◽  
Titto Idicula ◽  
Ulrike Waje-Andreassen ◽  
Gunnar Moen ◽  
...  

Author(s):  
Jinxin Huang ◽  
Xingguang Zhang ◽  
Juan Li ◽  
Liya Tang ◽  
Xiumin Jiao ◽  
...  

Objective:This study aimed to describe the frequency and temporal profile of acute cerebral infarction (ACI) using a continuous glucose monitoring system (CGMS) in patients with and without type 2 diabetes mellitus (T2DM) and explore the impact of blood glucose fluctuations on the short-term prognosis of ACI.Methods:The subjects were divided into four groups: T2DM with acute cerebral infarction (DMCI, Group A, n=56); T2DM without acute cerebral infarction (DM-NCI, Group B, n=36); Acute cerebral infarction patients without T2DM (NDM-CI, Group C, n=54); Healthy control group (NG, Group D, n=36). The National Institutes of Health Stoke Scale (NIHSS) and modified Rankin scale (mRs) were collected in Group A and C. All subjects were monitored for 72 hours using the CGMS. Indices such as fasting blood glucose (FBG) and mean amplitude of glycemic excursions (MAGE) were calculated. Glycemic excursions were compared between Group A, B, C and Group D, respectively. Multiple linear regression analysis and logistic analysis was applied.Results:MAGE is related to NIHSS, homocysteine (HCY), HOMA-IR, FBG, CRP and IMT, while NIHSS is related to CRP, HCY, HOMA-IR, IMT. The factors impacting the short-term prognosis of ACI were NIHSS, HBA1C and MAGE.Conclusion:Larger glucose fluctuations are associated with more stroke risk factors and are associated with a poorer short-term prognosis. More attention should be paid to glucose fluctuations in patients with ACI and a history of T2DM.


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