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A Comparative Investigation between MR Diffusion Weighted Imaging and Perfusion Weighted Imaging and Its Pathology in Meningioma

Author: WangZuoZuo
Tutor: ChengJingLiang
School: Zhengzhou University
Course: Medical Imaging and Nuclear Medicine
Keywords: meningioma magnetic resonance imaging diffusion weighted imaging perfusion weighted imaging vascular endothelial growth factor
CLC: R739.4
Type: Master's thesis
Year: 2009
Downloads: 77
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Abstract


Background and purposeMeningioma is one of the common tumors of central nervous system, and is the most common intracranial non-glial cells tumor which derives from neuroectoderm. It accounts for 14%-20% of the intracranial tumors. Meningiomas have a predilection to happen in 40-60 years of age. Incidence of female is twice than that of male. Although most of the meningiomas are benign tumors and slow-growth, there are about 2%-10% of them which have malignant growth behavior and prone to recurrence and extracranial metastasis. According to 2007 WHO classification and grading of meningiomas, it is divided into 15 kinds of histopathological types, 9 types in grade-I belong to benign tumor, 3 types in grade-II belong to low potential malignancy （atypical） and 3 types in grade-Ill belong to malignancy（anaplastic）. Medical imageology plays an important role in the diagnosis of meningioma. Imageology diagnoses of meningiomas mainly include X-ray plain skull films, angiography, CT and MRI. Because of the high resolution of soft tissue, multi-sequence, multi-axial imaging and functional imaging, MRI is one of great means in presenting the location and qualitation of meningiomas.At present, MRI can well show anatomy location of tumors. Conventional MRI can display enhancement, peritumoral edema, tumor hemorrhage, necrosis, bone and brain infiltration and distant metastasis, and so on. It is common that conventional MRI plays an important role in determining the tumor’s invasion, but can not provide a reliable pathophysical information, such as microvascular status, angiogenesis, metabolism, minimal necrosis, cell density, which target at the tumor grade is very important, and would be useful to distinguish among benign, atypical and malignant meningiomas before resection, because this would aid in surgical and treatment planning. This distinction between benign and atypical or malignant meningioma is neither easily nor reliably accomplished with the imaging features of meningiomas on conventional MR images.In recent years, investigation and application of senior MRI techniques in brain tumor is increasing. Diffusion weighted imaging（DWI） allows us to observe the microcosmic movement of the water molecules in the living tissues which bases on echo-planar imaging technology. It reflects the microstrcture of tissue and cell, it is so fast that one scan only needs several decades seconds. ADC value is common in expressing feature of hydrone movement. ADC value has high correlation with cell density and grading. Perfusion weighted imaging（PWI） can evaluate the cerebral hemodynamic status, which is developing with the presence of fast magnetic resonance imaging technique. It bases on tracing technology of contrast agent, and reflects perfusion information. Generally, we usually use rCBV（relative magnitude of cerebral blood volume and Contralateral conesponding normal brain white matter） as one of the measuring standards. Both of the two methods, as complementary methods for conventional MR examination, become an extensive research focus of academic image.Our studies introduce the value of DWI and PWI in preoperative diagnosis of meningioma, approach correlation among ADC value, rCBV value and molecular biology, in order to provid quantitative data and new imaging evidence.Materials and methods64 patients with meningioma were all confirmed by operation and pathology in the first affiliated hospital of Zhengzhou university. Among them, 14 cases were male and 50 cases were female. Aging from 13 to 80 years old, mean age is 49±14 years. Each patient was performed with precontrast T1 weighted imaging（T1WI）, T2 weighted imaging（T2WI）, DWI and Postcontrast T1WI before operation, and 34 cases of patients with PWI examination. Data acquisition of DWI and PWI was processed on postprocessing workstation after scanning. ADC and rCBV values were measured in the solid part of tumors, the peritumoral edema and Contralateral conesponding normal brain white matter and color pictures were drawed. According to the 2007 WHO classification of meningioma, grade I （9 types） including meningothelial, fibrous（fibroblastic）, transitional（mixed）, psammomatous, angiomatous, microcystic, secretory, lymphoplasma cyte-rich and metaplastic; grade II（3 types） including chordoid, clear cell and atypical; grade III（3 types） including papillary, rhabdoid and anaplastic （malignant） meningioma. In our research, grade I meningioma was divided into benign tumor （group A）, grade II and III meningiomas were divided into malignant tumor（group B）. After the meningiomas were operated, they were examined histologically using both hematoxylin and eosin（HE） patho-examination and immunohistochemical staining for vascular endothelial growth factor（VEGF）. Tumor cells and VEGF expression scores in each specimen was analyzed under light microscope.All the measurement results were demonstrated with mean±standard deviation （X|-±S）. Each set of data varied between the groups was compared using one-way ANOVA. Two-sample mean comparison used t test. Statistical comparisons of the tumor cells with the ADC values of the tumoral region, and VEGF expression score with maximal rCBV values of the tumoral region were made by Pearson correlation analysis. Statistical comparisons of the ADC values in tumoral region with tumor grade, and maximal rCBV values in tumoral region with tumoral grades were made by Spearman correlation analysis. Statistical analysises were performed with SPSS 13.0 software andα=0.05 was taken as test standard. Results（1） 64 patients can all tolerate and complete the DWI and PWI examinations of the whole brain. Good original images were obtained. Conventional MR imaging was completed.（2） Among 64 cases of meningioma, 59 cases were group A, 5 cases were group B. Among group A, 9 cases were endepidermis type, 10 cases were fibrous type, 22 cases were transitional type, 6 cases were psammomatous type, 6 cases were angiomatous type, 4 cases were microcystic type and 2 cases were metaplastic type. 5 cases of group B were all atypical meningioma. Among 34 cases of patient who have PWI examination, 29 cases were group A, 5 cases were group B. Among group A, 1 cases were endepidermis type, 7 cases were fibrous type, 10 cases were transitional type, 1 cases were psammomatous type, 6 cases were angiomatous type and 4 cases were microcystic type. 5 cases of group B were all atypical meningioma.（3） On DWI maps, the signal intensity in the solid part of meningioma of group A was disparity with the Contralateral conesponding normal brain white matter. Among them, 11 cases were obviously high signal intensity, 21 cases were slightly high signal intensity, 25 cases were iso-signal intensity and 2 cases were mixed low signal intensity. The signal intensity in the solid part of meningioma of group B was higher than the Contralateral corresponding normal brain white matter. Among them, 4 cases were obviously high signal intensity and 1 case was slightly high signal intensity. On ADC maps, the signal intensity in the solid part of meningioma of group A was also disparity with the Contralateral corresponding normal brain white matter. Among them, 31 cases were slightly high signal intensity, 20 cases were iso-signal intensity, 6 cases were slightly low signal intensity and 2 cases were mixed low signal intensity. The signal intensity in the solid part of meningioma of group B was lower than the Contralateral corresponding normal brain white matter and they all were low signal intensity. The peritumor edema of the meningioma was not clear on DWI maps and showed high signal intensity on ADC maps.（4） Statistical discrepancies of the ADC values in solid part of meningioma for both group A(0.916±0.157×10-3mm2/s) and group B(0.698±0.065×10-3mm2/s) were present（t=6.125, P<0.001）. Statistical discrepancies of the ADC values in solid part of meningioma for both group A and group B respectively with the Contralateral conesponding normal brain white matter(groupA:0.757±0.064×10-3mm2/s; groupB: 0.764±0.057×10-3mm2/s) were present（tA=-12.133, PA<0.001; tB=-4.097, PB=0.01）. No statistical discrepancies of the ADC values in peritumoral edema of meningioma for both group A(1.680±1.138×10-3mm2/s) and group B(1.235±0.137×10-3mm2/s) were present（t=0.865, P>0.05）. Statistical discrepancies of the ADC values in peritumoral edema of meningioma for both group A and group B respectively with the Contralateral corresponding normal brain white matter(groupA:0.764±0.057×10-3mm2/s; groupB:0.752±0.068×10-3mm2/s) were present（tA=-0.929, PA<0.001;tB= -0.506, PB<0.001）. Each subtypes’ ADC values in solid part of meningioma of group A from higher to lower were angiomatous(1.128±0.089×10-3mm2/s), secretory (1.116±0.027×10-3mm2/s), microcystic(1.067±0.074×10-3mm2/s), meningothelial (0.972±0.133×10-3mm2/s), transitional(0.866±0.132×10-3mm2/s), fibrous (0.864±0.093×10-3mm2/s), psammomatous(0.722±0.045×10-3mm2/s), statistical discrepancies of the ADC values for each subtypes of meningioma were present （F=10.369, P<0.05）, ADC values especially in meningothelial, transitional, fibrous, psammomatous and it between psammomatous meningioma and group B meningioma were overlapping. Statistical discrepancies of the tumor cells in solid part for both group A （5595.983±313.614/10HPF） and group B（6590,800±422.639/10HPF） were present （t=-6.638, P<0.05）. The ADC values in solid part of meningioma for both group A and group B were decreased with the increase of tumor cellularity, they were negatively correlated with tumor cells （rA=-0.774, PA<0.001; rB=-0.889, PB<0.05）. Negative correlation between the ADC value and tumor grade was present（r=-0.392, P<0.01）.（5） On rCBV color-maps, the greatest perfusion part in the solid part of 7 cases of meningioma of group A showed slight hypertransfusion corresponding to the Contralateral corresponding normal brain white matter and others showed hypertransfusion. The greatest perfusion part in the peritumor edema of meningioma of group A showed uneven hypoperfusion and they showed slight hypertransfusion in meningiomas of group B. From the time-signal intensity curves, the extent signal descent in the solid part of all of the meningioma was greater than the Contralateral corresponding normal brain white matter and time of the signal reback to the baseline level was prolongation, and at last baseline level lower in 17 cases, higher in 12 cases and iso in 5 cases. During the descent extent in the peritumor edema of meningioma of group A corresponding to the Contralateral conesponding normal brain white matter, low in 15 cases, iso in 12 cases and no descent wave can be seen in 2 cases. The descent extent in the peritumor edema of all the meningioma of group B is slight higher than the Contralateral corresponding normal brain white matter.（6） No statistical discrepancies of the maximum rCBV values in the solid part for both group A（10.070±4.045） and group B（11.922±2.080） meningiomas were present（t=-0.887, P>0.05） . Statistical discrepancies of the maximum rCBV values in the peritumoral region for both group A（1.079±0.642） and group B（2.776±1.550） meningiomas were present（t=-4.312, P<0.001）. Statistical discrepancies of the maximum rCBV values between the solid part and the peritumoral region for both group A and group B meningiomas were present（tA=5.192, PA<0.05; tB=3.291, Pb=0.009）. Each subtypes’ maximum rCBV values in the solid part of meningioma of group A from higher to lower were angiomatous（13.590±4.813）, transitional （10.880±3.480）, microcystic（8.628±1.062）, fibrous（8.329±4.898）, meningothelial （6.490）, psammomatous（2.400）, and no statistical discrepancies of the maximum rCBV values for each subtypes of meningioma were present（F=2.357, P>0.05）. Statistical discrepancies of the VEGF expression values in solid part for both group A（5.000±3.174） and group B（7.200±1.924） were present（t=-1.492, P<0.05）. The maximum rCBV value for the solid part of meningioma for both group A and group B was increased with the increase of VEGF expression, they had positive correlation with tumor VEGF expression values（rA=0.885, PB<0.001; rA=0.925, PB<0.05）. No correlation between the maximum rCBV value and tumor grade was present（r=0.241, P>0.05）. Conclusion（1） MRI is an effective means of diagnosis of meningioma and grading of meningioma.（2） ADC value has favourable correlation with tumor cell desity and tumor grade, and DWI should be an assist-mean for evaluating tumor cell density and identifying benign or malignant tumor.（3） rCBV value have favourable correlation with angiogenesis and tumor grade, combining it with time-signal curve, PWI should be an assist-mean for evaluating tumor microvascular status and identifying benign or malignant tumor.（4） DWI and PWI are important supplementary means of conventional MRI in diagnosis of meningioma.

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