| PrefaceGliomas are the most common primary tumors of central nervous system ( CNS). Preoperative evaluation of tumor malignancy is important to determine the appropriate treatment and to learn prognosis of gliomas. A radiological method that accurately evaluate tumor malignancy in vivo is necessary to clinical therapy. The ability of conventional CT and MRI in reflecting the functional information of gliomas is limited. Some recently developed methods such as MR perfusion weighted imaging (PWI) ,MR spectroscopy ( MRS ) and positron emission tomography ( PET) are restricted in clinical application for some reasons such as complexity of processing, time consuming or large expense of examination .MR diffusion weighted imaging ( DWI) in vivo detects the microscopic diffusion of molecular in the tissue by special MR series . It has the advantage of fast imaging and easy processing. DWI has been used to detect brain ischemic lesion in super early stage successfully since it came into being. In recent years, DWI was used to study the diagnosis of tumor lesion of the brain, and many valuable results has been achieved . But previous research mainly applied one direction diffusion gradient, and mainly focused on the diffusion character of the solid part of gliomas , reports on diffusion character in peritumoral region is limited. To further study the application of diffusion weighted MR imaging in the diagnosis of gliomas, we evaluate the value of apparent diffusion coefficient ( ADC) in the pathological grading of gliomas, effecting factor of ADC value, and the relationship between diffusion character of peritumoral region and prog-nosis using three direction diffusion weighted MR imagingMaterials and MethodsSubjects;21 histologically verified gliomas were studied, including 6 benign gliomas ( grade I - II) ,9 anaplastic gliomas( grade III) and 6 glioblastomas(grade IV). 5 of 12 cases presented recurrence in postoperative follow up examination and no obvious recurrence was found in the other 7 cases. Conventional MRI and diffusion weighted MRI were performed in all patients.MR scanning methods2.0 Tesla superconducting MR scanner was used. Unenhanced axial T1 and T2 weighted MR images were acquired before diffusion weighted MRI, then Gadolinium enhanced Tl weighted images were acquired. Diffusion weighted im-ages were acquired by using spin - echo type echo - planar imaging (EPI) se-quence with following parameters: TR/TE : 500/108ms, slice thichness:6mmT FOV;37. 3 x 18. 1cm. Nex: 1 ,matrix:128 x 128, gradient factor b values were 700 s / mm2 0 s / mm2, diffusion gradients were applied in three directions (x,y,z axis).MR Image AnalysisRaw data of DWI was transferred to PC through PACS of Neurosofi Company. Dptools, a diffusion weighted image postprocessing software written by Dr. Denis Ducreux was used to generate ADC maps. 3 ROIs were placed over different parts of gliomas, including the solid part, cystic and necrotic part, peritu-moral region ( within 2mm beyond enhancing tumor edge ) and contralateral normal white matter. ADC and relative ADC(rADC) of these ROIs were calculated.Histological AnalysisHistological Images of tumors were analyzed with a medical image analyzing software named Scion Image. Cellularity, defined as die total areas of nuclei of tumor cells divided by the area of the histological section, was calculated. All the tumors were graded according to the WHO grading system by a pathologist.Statistical AnalysisComparison of the tumor ceUulatity with the ADC values were made using simple linear regression analysis. The relationship of the ADC values with tumor grade and the difference of peritumoral ADC values between recurrent and un-reccurennt groups was evaluated with the unpaired Student s t test. P value of less than 0.01 was considered to indicate statistical significance.Results1. ADC values of different parts of gliomasADC values of different tumor parts is as follow (from high to low) ; cystic and necrotic part 2520. 6 442. 7 ( 10...
|
PDF Full Text Request