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The Value Of Diffusion-Weighted MR Imaging And Diffusion-Tensor MR Imaging In Cerebral Infarction

Posted on:2010-10-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y Q HanFull Text:PDF
GTID:2144360302968609Subject:Medical imaging and nuclear medicine
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ObjectiveTo explore the value of the diffusion-weighted MR imaging (DWI) and diffusion tensor MR imaging (DTI)in cerebral infarction.Conventional magnetic resonance imaging combined with DWI can help to determine the stage of the cerebral infarction clearly and the lesion which is responsible for this pathogenesis,and to explore the relationship between the white matter fiber bundles involved and the damage of the patients,motor function after DTI,in order to provide a reliable basis for clinical development of individual treatment programs.Materials and Methods106 cases of patients(65 males and 41 females,the age range from 40Y to 82Y,average age 63.5Y),in the Emergency Department and the Department of Neurology in Taian Central Hospital from April 2008 to January 2009 with typical clinical symptoms and signs are highly suspected and diagnosed with cerebral infarction in follow-up observation,or some patients had history of cerebral infarction.They are divided into 4 groups according to the history.There are 15 cases in the first group,onset time less than six hours,defined as hyperacute cerebral infarction;40 cases in the second group,onset time between 6 hours and 72 hours,defined as acute cerebral infarction;28 cases in the third group,onset time between 3 days and 2 weeks,defined as subacute cerebral infarction;and 23 cases in the fourth group,onset time at least one month,defined as chronic cerebral infarction.All patients underwent conventional magnetic resonance imaging as well as DWI and DTI.Lesions are observed in all the series of images and their ADC(appearance diffusion coefficient),rADC(ratio of the ADC) and FA(fractional anisotropy) are measured respectively in ADC and FA maps.The matter fiber bundles involved around the leisions are divided into three types according to the relationship between lesions and fiber bundles in DTT(diffution tensor tractography)images.â… type:the fiber bundles around the leision are compressed;â…¡type:some fiber bundles are interrupted by the leision;â…¢type:Most or all of fiber bundles are infiltrated or interrupted by the leision.ResultDWI is much more sensitive to show hyperacute and acute cerebral infarction(display rate is 100%)than other series of images,and it is superior to conventional magnetic resonance imaging in showing the contrast and the boundary of lesions,but it is inferior to show subacute and chronic infarction.The ADC value of leisions from the first group to the fourth group gradually ascend and there is significant difference,P<0.05.The lesions and the fiber bundles involved around lesions can be observed in FA maps and in DTT after DTI.34 cases of typeâ… ,with FA reducing or increasing slightly,the motor dysfunction in patients with non-performance or minor damage,muscle strength of these patients is generally 4 or 5 rank;33 cases of typeâ…¡,with FA reducing obviously,patients with hyperacute and acute infarction in this type appear impaired motor function,but patients with subacute and chronic infarction have relatively good muscle strength,usually 4 rank;39 cases of typeâ…¢,with the most obvious reduction in FA value,patients with severe motor dysfunction,their muscle strength is usually under 3 rank.ConclusionDWI can increase the display rate of hyperacute and acute cerebral infarction.The change of cerebral infarction in pathology and its stage can be defined by measuring ADC,rADC and FA value combined with reviewing conventional magnetic resonance images.The relationship between white matter fiber bundles involved and the damage of patients, motor function can be evaluated with DTI.The combination of DWI and DTI is significant to guide the clinical doctors to determine programs of individual treatment.
Keywords/Search Tags:cerebral infarction, magnetic resonance imaging, diffusion weighted-imaging, diffusion tensor imaging
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