磁敏感成像和灌注成像评估星形细胞肿瘤病理级别及血管生成的研究
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摘要
一、星形细胞肿瘤SWI半量化评估与病理分级的相关性研究
目的：评估星形细胞肿瘤磁敏感成像(susceptibility-weighted imaging,SWI)在病理分级方面的临床应用价值,提出能准确反映肿瘤病理分级且简单实用的半量化指标。
对象和方法：98例经手术病理证实的星形细胞肿瘤患者,男56例,女42例,年龄8-79岁。其中,毛细胞型星形细胞瘤(Ⅰ级)8例,多形性黄色星形细胞瘤(Ⅱ级)1例,弥漫性星形细胞瘤(Ⅱ级)23例,间变性星形细胞瘤(Ⅲ级)22例,胶质母细胞瘤(Ⅳ级)44例。所有患者于术前应用Siemens3.OT磁共振成像仪行MRI平扫和增强检查及SWI检查。SWI数据经后处理形成幅度图(magnitude image)、相位图(phase image)、磁敏感图(susceptibility image)及最小密度投影图(minimums intensity projection, SWIMinIP),观察肿瘤内磁敏感低信号区(intratumor susceptibility hypo intensity area, ITSHIA)并按照相应的标准评分,得到ITSHIA半量化数据。具体指标如下：最大ITSHIA直径(厘米)、ITSHIA的频数、最大ITSHIA直径评分、ITSHIA频数评分、ITSHIA面积比率评分、综合评分、围绕肿瘤坏死灶分布的点状ITSHIA、肿瘤边缘或坏死边缘串珠样或/线样ITSHIA、ITSHIA形态分类。比较不同级别星形细胞肿瘤间ITSHIA半量化数值的差异,并分析其与肿瘤病理的相关性。绘制ROC曲线,比较不同ITSHIA半量化方法区分高、低级别星形细胞肿瘤的效能、给出推荐阈值和相应的敏感度、特异性,找到效能最好的指标。
结果：不同级别星形细胞肿瘤ITSHIA半量化数值存在明显差异。高级别(Ⅲ级、Ⅳ级)明显高于低级别(Ⅱ级)。毛细胞型星形细胞瘤(Ⅰ级)ITSHIA半量化数值与高级别星形细胞肿瘤存在重叠。SWI半量化指标中,“围绕肿瘤坏死灶分布的点状ITSHIA"(rs=0.691)、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA(rs=0.627)”与星形细胞肿瘤分级相关性最高。综合评分(rs=0.652)不需要增强扫描即可获得,与分级的相关性高于其他未增强SWI半量化指标,略低于增强SWI半量化指标。各种SWI半量化指标区分高、低级别星形细胞肿瘤(不包括毛细胞型星形细胞瘤)的效能由高至低依次为：综合评分ROC曲线下面积为0.926,推荐界值为3时,灵敏度80.30%,特异度87.5%；“肿瘤边缘或坏死边缘串珠样/线样ITSHIA曲线下面积为0.924”,推荐界值为1时,敏感性84.8%,特异性100%；“围绕肿瘤坏死灶分布的点状ITSHIA"曲线下面积为0.911敏感度86.4%,推荐界值为1时,特异度95.8%。
结论：ITSHIA半量化数据能够反映星形细胞的肿瘤血管生成。在去除毛细胞型星形细胞瘤的影响后,SWI半量化指标与星形细胞肿瘤的级别显著相关。综合评分以及“围绕肿瘤坏死灶分布的点状ITSHIA"、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"等半量化指标,对于术前评估星形细胞肿瘤的病理分级具有较高价值。
二、星形细胞肿瘤SWI半量化评估与灌注成像的相关性研究
目的：评估星形细胞肿瘤SWI与磁共振灌注加权成像(peffusion weighted imaging,PI)的相关性。比较SWI与PI对于术前星形细胞肿瘤病理分级的价值。
对象和方法：研究对象与第一部分相同。所有患者于术前应用Siemens3.OT磁共振成像仪行MRI平扫、增强检查、SWI检查及PI检查。PI图像经后处理后获得局部CBV(regional cerebral blood volume,rCBV)伪彩图,应用热点分析方法,获得肿瘤内实性部分最大相对局部CBV值(relative regional rCBV瘤内max, rrCBV瘤内max)和瘤周区最大相对局部CBV值(rrCBV瘤周max)。比较不同级别星形细胞肿瘤间rrCBV瘤内max与rrCBV瘤周max的差别；比较不同级别星形细胞肿瘤间灌注热点区与ITSHIA形态的对应情况；比较不同级别星形细胞肿瘤间SWI中各半量化指标与PI中rrCBV瘤内max与rrCBV瘤周max的相关性。应用ROC曲线,比较SWI半量化指标与灌注成像评估星形细胞肿瘤效能的差异。
结果：星形细胞肿瘤rrCBV瘤内max值(rs=0.662,P=0.000)及rrCBV瘤周max(rs=0.794,P=0.000)值与分级显著相关。毛细胞型星形细胞瘤,rrCBV瘤内max高于Ⅱ级星形细胞瘤,与Ⅲ级肿瘤类似,而rrCBV瘤周max与Ⅱ级星形细胞瘤无明显差异,却低于高级别肿瘤。星形细胞肿瘤的ITSHIA半量化指标与rrCBV瘤内max值呈明显线性正相关；星形细胞肿瘤的ITSHIA半量化指标与rrCBV瘤周max值呈显著线性正相关。星形细胞肿瘤内灌注热点区与ITSHIA不完全对应。PI区分高、低级别星形细胞肿瘤效能由高到低依次为：rrCBV瘤内max值,ROC曲线下面积为0.951,推荐界值3.300,其灵敏度为90.9%,特异度为91.7%；rrCBV瘤内max值,ROC曲线下面积为0.939,推荐界值1.000时,其灵敏度为97.3%,特异度为83.3%。rrCBV瘤内max值作为评估病理分级的标准,要优于rrCBV瘤周max值的评估效果以及SWI半量化指标的评估效果。
结论：星形细胞肿瘤SWI指标与PI指标密切相关,二者对于术前评估星形细胞肿瘤的病理分级同样具有较高价值,PI略优于SWI。灌注热点区与ITSHIA并不完全相同,可能与二者显示肿瘤内血管生成的机制不同有关。
三、星形细胞肿瘤SWI.PI与MVD计数、VEGF表达程度的相关性研究
目的：通过比较星形细胞肿瘤患者SWI.PI各指标与MVD.VEGF结果,探讨肿瘤SWI半量化指标、PI指标与星形细胞肿瘤血管生成的相关性,进一步阐明SWI与PI的临床应用价值。
对象和方法：研究对象和方法及图像后处理同第一、二部分。术后病理切片行MVD及VEGF免疫组织化学染色,进行MVD计数,以及VEGF半定量评分。比较不同级别星形细胞肿瘤间MVD计数、VEGF表达程度的差异。分析MVD及VEGF与PI各指标的相关性,分析MVD与VEGF与SWI各指标的相关性。比较VEGF高表达组与低表达组间,PI各指标与SWI各指标的差异。
结果：星形细胞肿瘤的级别与MVD计数呈线性正相关(rs=0.550,P=0.000)。VEGF表达程度与肿瘤级别存在的相关性(rs=0.456P=0.000)。PI中,rrrCBV瘤内max及rrCBV瘤周max均与MVD明显相关。SWI中,诸半量化参数与MVD计数呈显著正相关。SWI中“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"与MVD的相关度(0.497)略高于P1中的rrCBV瘤内max(0.467)。PI中,rrCBV瘤内max及rrCBV瘤周max与VEGF表达程度呈显著正相关。SWI中,“围绕肿瘤坏死灶分布的点状ITSHIA"(0.334)、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"(0.271)等指标与VEGF表达程度呈显著正相关(P<0.01)。VEGF高、低表达组间的SWI半量化指标中,只有“围绕肿瘤坏死灶分布的点状ITSHIA"、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"两个指标存在统计学差异。
结论：PI与肿瘤的血管生成存在相关性,均可用于活体评估星形细胞肿瘤的的血管生成程度。VEGF的高表达不但与肿瘤内和瘤周的高灌注区域相关,而且与SWI中“围绕肿瘤坏死灶分布的点状ITSHIA"、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"征象相关。
Part I:Correlation between semi-quantitative evaluations of susceptibility-weighted imaging and pathological grading in patients with astocytic tumor
Objective:To assess the clinical value of susceptibility-weighted imaging (SWI) for astrocytic tumor of histological grade and to find a simply and efficient semiquantitative indexes of SWI which can accurately reflect pathologic grade.
Materials and Methods:98patients with astrocytic tumors confirmed by surgery and pathology were analyzed. Male,56and female42, The age range was8-79. According to the World Health Organization (WHO) classification of central nervous system tumors and grading criteria:8cases of pilocytic astrocytoma (grade Ⅰ),1case of Pleomorphic Xanthoastrocytoma (grade Ⅱ),23cases of astrocytoma (grade Ⅱ),22cases of anaplastic astrocytoma (grade Ⅲ) and44cases of glioblastoma (grade IV) were included. All cases underwent conventional, contrast MRI scan and SWI examination by using Siemens3.0T magnetic resonance imaging system before the operation. Magnitude image, phase image, susceptibility image and minimums intensity projection image were obtained by SWI on the post-processing workstation. Intratumor susceptibility hypo intensity area(ITSHIA) was observed and semiquantitative data were acquired in accordance with the different grading indexes as follows:ITSHIA biggest diameter (cm), ITSH1A frequency, ITSHIA biggest diameter score, ITSHIA frequency score, ITSHIA area ratio score, ITSHIA comprehensive score (The product of the frequency score and area ratio score), focal distribution punctiform ITSHIA around the tumor necrosis, beaded/line ITSHIA on the tumor edge or necrosis edge, ITSHIA morphology description. Semiquantitative ITSHIA data of astrocytic tumors with various grades were compared and their relationships with pathologic grade were analyzed. Area under the curve (AUC) was used to compare the effectiveness of different methods in distinguish the high grade tumors from the lows with recommended threshold and the corresponding sensitivity and specificity and to select the best index reflecting grading.
Results:There exists an obvious difference in the semiquantitative data of ITSHIA among different levels of astrocytic tumor. The values of ITSHIA for malignant astrocytic tumors (Ⅲ,Ⅳ) were higher than that in low level, whereas values of ITSHIA exist a general overlapping between the pilocytic astrocytma and the high level astrocytic tumor."Focal distribution punctiform ITSHIA around the tumor necrosis"(rs=0.691) and "beaded/line ITSHIA on the tumor edge or necrosis edge"(rs=0.627) showed highest relevance with pathological grading among all the indexes of ITSHIA. The relevance between comprehensive score, obtained from the SWI with no contrast, and pathological grading was highest of all the other indexes obtained by SWI with no contrast, whereas was slightly lower than that of enhanced SWI indexes. According to the performance of various semiquantitative indexes which can be used to distinguish high level astrocytic tumor by ROC, comprehensive score(area under curve, AUC=0.926) was the highest, the cutoff point was3,the rate for sensitivity was80.3%,for specificity87.5%; the " beaded/line ITSHIA on the tumor edge or necrosis edge "(0.924) was the second, the cutoff point is l,the rate for sensitivity was84.8%,for specificity100%; and the "focal distribution point like ITSHIA around the tumor necrosis "(0.911) was also useful, the cutoff point was1, the rate for sensitivity was86.4%, for specificity95.8%.
Conclusion:The semiquantitative indexes of SWI could reflect angiogenesis in astrocytic tumors, and the semiquantitative data was linear related with the histological grade markedly after excluding the cases of pilocytic astrocytoma. The indexes such as "comprehensive score", the " beaded/line ITSHIA on the tumor edge or necrosis edge", the "focal distribution punctiform ITSHIA around the tumor necrosis" of astrocytic tumors had a higher value for pathologic grading.
Part II:Correlation between the semiquantitative evaluations of susceptibility-weighted imaging and perfusion imaging in patients with astrocytic tumor
Objective:To evaluate the correlations between the indexes of SWI and those of PI in astrocytic tumors and to compare the clinic value in pathological grading before the operation.
Materials and Methods:The study objects and image processing methods were similar to those in the first part. All patients were underwent conventional, contrast MR scan, SWI and PI scan by Siemens3.0T magnetic resonance imaging system. Pseudo color pictures of CBV were obtained by PI on the post-processing workstation. ROI placement was placed through application of hot spots analysis. Maximum relative rCBV values of solid part within the tumor (rrCBVintra max), surrounding area of tumor (rrCBVperi max) were calculated. Comparison of the rrCBVintra max and rrCBVperi max in astrocytic tumor of different grade were performed. The corresponding situation between hot spot of PI and ITSHIA were evaluated and correlation between SWI and PI were compared. To analyze SWI and PI in the diagnostic value of high level of astrocytic tumor with ROC curves analysis.
Results:rrCBVmtramax (rs=0.662, P=0.000) of astrocytic tumors was related positively linearly with pathological grade. rrCBVperi max (rs=0.794, P=0.000) was also markedly related. The rrCBVintra max of pilocytic astrocytoma was higher than that of astrocytoma(Ⅱ), which was similar to that of grade Ⅲ, whereas rrCB Vperi max showed no differences compared with astrocytoma(Ⅱ) and markedly lower than the tumor of high grade. The semiquantitative data of ITSHIA had a typical positive correlation with rrCBVintra max and rrCBVperimsx respectively. The area including hot spot in PI was not to be able completely correspondent with ITSHIA. According to the performance of various PI indexes which could be used to distinguish high level astrocytic tumor by ROC, rrCBVintra max (area under curve, AUC=0.951) was the highest, the cutoff point is3.300, the rate for sensitivity was90.3%, for specificity91.7%; the rrCBVperi max was the second, the cutoff point was1.000, the rate for sensitivity was97.3%,for specificity83.3%. The rrCBVintra max showed some advantages over semiquantitative indexes of SWI in evaluating the pathological grade of astrocytic tumor.
Conclusion:semiquantitative indexes of SWI were closely related to that of PI. Both PI and SWI may be used as sensitive indexes of evaluating pathological grade of astrocytic tumor. PI was correlated with grading closely than SWI. The incompletely correspondent between hot spot and ITSHIA may be due to an association with different machismos of PI and SWI.
Part Ⅲ:Correlation between indexes of SWI、PI and MVD、 VEGF expression in astrocytic tumor
Objective:To detect the expression of MVD and VEGF in astrocytic tumor and their correlation with the semiquantivative indictors of SWI and rrCBVintra max, rrCBVperi max of PI for further clarifying the mechanism and clinical application.
Materials and Methods:The study objects and image processing methods were similar to those in the first and second part. Pathological sections were obtained after operation. Immunohistochemical assay was employed to detect the expression of VEGF and to make a MVD count. According to the degrees of VEGF expression, patients in our study were divided into two groups:VEGF expression degree including high expression and low expression. Correlation between MVD、VEGF and indexes of PI and SWI were analyzed.
Results:The MVD count (rs=0.550, P=0.000) and VEGF expression (rs=0.456P=0.000) were positive correlated with pathologic grading of astrocytic tumor. rrCBVintra max and rrCBVperi max of PI、most semiquantitative indexes of SWI showed markedly correlation with MVD and VEGF, respectively. Correlation analysis suggested a close relationship among the expression of VEGF and "beaded/line ITSHIA on the tumor edge or necrosis edge", the "focal distribution punctiform ITSHIA around the tumor necrosis" of astrocytic tumors shown on SWI with contrast. The above indexes were found significantly different between the2groups of VEGF expression degree with high expression and low expression (P<0.01) except for other semiquantitative indexes of SWI (P>0.05).
Conclusion:Both PI and SWI showed obviously correlation with angiogenesis and both are effective marker in evaluation angiogenesis preoperatively. High expression of VEGF was not only relevant to high perfusion area within or around the tumor, but also related to " beaded/line ITSHIA on the tumor edge or necrosis edge", the "focal distribution punctiform ITSHIA around the tumor necrosis".
目的：评估星形细胞肿瘤磁敏感成像(susceptibility-weighted imaging,SWI)在病理分级方面的临床应用价值,提出能准确反映肿瘤病理分级且简单实用的半量化指标。
对象和方法：98例经手术病理证实的星形细胞肿瘤患者,男56例,女42例,年龄8-79岁。其中,毛细胞型星形细胞瘤(Ⅰ级)8例,多形性黄色星形细胞瘤(Ⅱ级)1例,弥漫性星形细胞瘤(Ⅱ级)23例,间变性星形细胞瘤(Ⅲ级)22例,胶质母细胞瘤(Ⅳ级)44例。所有患者于术前应用Siemens3.OT磁共振成像仪行MRI平扫和增强检查及SWI检查。SWI数据经后处理形成幅度图(magnitude image)、相位图(phase image)、磁敏感图(susceptibility image)及最小密度投影图(minimums intensity projection, SWIMinIP),观察肿瘤内磁敏感低信号区(intratumor susceptibility hypo intensity area, ITSHIA)并按照相应的标准评分,得到ITSHIA半量化数据。具体指标如下：最大ITSHIA直径(厘米)、ITSHIA的频数、最大ITSHIA直径评分、ITSHIA频数评分、ITSHIA面积比率评分、综合评分、围绕肿瘤坏死灶分布的点状ITSHIA、肿瘤边缘或坏死边缘串珠样或/线样ITSHIA、ITSHIA形态分类。比较不同级别星形细胞肿瘤间ITSHIA半量化数值的差异,并分析其与肿瘤病理的相关性。绘制ROC曲线,比较不同ITSHIA半量化方法区分高、低级别星形细胞肿瘤的效能、给出推荐阈值和相应的敏感度、特异性,找到效能最好的指标。
结果：不同级别星形细胞肿瘤ITSHIA半量化数值存在明显差异。高级别(Ⅲ级、Ⅳ级)明显高于低级别(Ⅱ级)。毛细胞型星形细胞瘤(Ⅰ级)ITSHIA半量化数值与高级别星形细胞肿瘤存在重叠。SWI半量化指标中,“围绕肿瘤坏死灶分布的点状ITSHIA"(rs=0.691)、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA(rs=0.627)”与星形细胞肿瘤分级相关性最高。综合评分(rs=0.652)不需要增强扫描即可获得,与分级的相关性高于其他未增强SWI半量化指标,略低于增强SWI半量化指标。各种SWI半量化指标区分高、低级别星形细胞肿瘤(不包括毛细胞型星形细胞瘤)的效能由高至低依次为：综合评分ROC曲线下面积为0.926,推荐界值为3时,灵敏度80.30%,特异度87.5%；“肿瘤边缘或坏死边缘串珠样/线样ITSHIA曲线下面积为0.924”,推荐界值为1时,敏感性84.8%,特异性100%；“围绕肿瘤坏死灶分布的点状ITSHIA"曲线下面积为0.911敏感度86.4%,推荐界值为1时,特异度95.8%。
结论：ITSHIA半量化数据能够反映星形细胞的肿瘤血管生成。在去除毛细胞型星形细胞瘤的影响后,SWI半量化指标与星形细胞肿瘤的级别显著相关。综合评分以及“围绕肿瘤坏死灶分布的点状ITSHIA"、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"等半量化指标,对于术前评估星形细胞肿瘤的病理分级具有较高价值。
二、星形细胞肿瘤SWI半量化评估与灌注成像的相关性研究
目的：评估星形细胞肿瘤SWI与磁共振灌注加权成像(peffusion weighted imaging,PI)的相关性。比较SWI与PI对于术前星形细胞肿瘤病理分级的价值。
对象和方法：研究对象与第一部分相同。所有患者于术前应用Siemens3.OT磁共振成像仪行MRI平扫、增强检查、SWI检查及PI检查。PI图像经后处理后获得局部CBV(regional cerebral blood volume,rCBV)伪彩图,应用热点分析方法,获得肿瘤内实性部分最大相对局部CBV值(relative regional rCBV瘤内max, rrCBV瘤内max)和瘤周区最大相对局部CBV值(rrCBV瘤周max)。比较不同级别星形细胞肿瘤间rrCBV瘤内max与rrCBV瘤周max的差别；比较不同级别星形细胞肿瘤间灌注热点区与ITSHIA形态的对应情况；比较不同级别星形细胞肿瘤间SWI中各半量化指标与PI中rrCBV瘤内max与rrCBV瘤周max的相关性。应用ROC曲线,比较SWI半量化指标与灌注成像评估星形细胞肿瘤效能的差异。
结果：星形细胞肿瘤rrCBV瘤内max值(rs=0.662,P=0.000)及rrCBV瘤周max(rs=0.794,P=0.000)值与分级显著相关。毛细胞型星形细胞瘤,rrCBV瘤内max高于Ⅱ级星形细胞瘤,与Ⅲ级肿瘤类似,而rrCBV瘤周max与Ⅱ级星形细胞瘤无明显差异,却低于高级别肿瘤。星形细胞肿瘤的ITSHIA半量化指标与rrCBV瘤内max值呈明显线性正相关；星形细胞肿瘤的ITSHIA半量化指标与rrCBV瘤周max值呈显著线性正相关。星形细胞肿瘤内灌注热点区与ITSHIA不完全对应。PI区分高、低级别星形细胞肿瘤效能由高到低依次为：rrCBV瘤内max值,ROC曲线下面积为0.951,推荐界值3.300,其灵敏度为90.9%,特异度为91.7%；rrCBV瘤内max值,ROC曲线下面积为0.939,推荐界值1.000时,其灵敏度为97.3%,特异度为83.3%。rrCBV瘤内max值作为评估病理分级的标准,要优于rrCBV瘤周max值的评估效果以及SWI半量化指标的评估效果。
结论：星形细胞肿瘤SWI指标与PI指标密切相关,二者对于术前评估星形细胞肿瘤的病理分级同样具有较高价值,PI略优于SWI。灌注热点区与ITSHIA并不完全相同,可能与二者显示肿瘤内血管生成的机制不同有关。
三、星形细胞肿瘤SWI.PI与MVD计数、VEGF表达程度的相关性研究
目的：通过比较星形细胞肿瘤患者SWI.PI各指标与MVD.VEGF结果,探讨肿瘤SWI半量化指标、PI指标与星形细胞肿瘤血管生成的相关性,进一步阐明SWI与PI的临床应用价值。
对象和方法：研究对象和方法及图像后处理同第一、二部分。术后病理切片行MVD及VEGF免疫组织化学染色,进行MVD计数,以及VEGF半定量评分。比较不同级别星形细胞肿瘤间MVD计数、VEGF表达程度的差异。分析MVD及VEGF与PI各指标的相关性,分析MVD与VEGF与SWI各指标的相关性。比较VEGF高表达组与低表达组间,PI各指标与SWI各指标的差异。
结果：星形细胞肿瘤的级别与MVD计数呈线性正相关(rs=0.550,P=0.000)。VEGF表达程度与肿瘤级别存在的相关性(rs=0.456P=0.000)。PI中,rrrCBV瘤内max及rrCBV瘤周max均与MVD明显相关。SWI中,诸半量化参数与MVD计数呈显著正相关。SWI中“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"与MVD的相关度(0.497)略高于P1中的rrCBV瘤内max(0.467)。PI中,rrCBV瘤内max及rrCBV瘤周max与VEGF表达程度呈显著正相关。SWI中,“围绕肿瘤坏死灶分布的点状ITSHIA"(0.334)、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"(0.271)等指标与VEGF表达程度呈显著正相关(P<0.01)。VEGF高、低表达组间的SWI半量化指标中,只有“围绕肿瘤坏死灶分布的点状ITSHIA"、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"两个指标存在统计学差异。
结论：PI与肿瘤的血管生成存在相关性,均可用于活体评估星形细胞肿瘤的的血管生成程度。VEGF的高表达不但与肿瘤内和瘤周的高灌注区域相关,而且与SWI中“围绕肿瘤坏死灶分布的点状ITSHIA"、“肿瘤边缘或坏死边缘串珠样/线样ITSHIA"征象相关。
Part I:Correlation between semi-quantitative evaluations of susceptibility-weighted imaging and pathological grading in patients with astocytic tumor
Objective:To assess the clinical value of susceptibility-weighted imaging (SWI) for astrocytic tumor of histological grade and to find a simply and efficient semiquantitative indexes of SWI which can accurately reflect pathologic grade.
Materials and Methods:98patients with astrocytic tumors confirmed by surgery and pathology were analyzed. Male,56and female42, The age range was8-79. According to the World Health Organization (WHO) classification of central nervous system tumors and grading criteria:8cases of pilocytic astrocytoma (grade Ⅰ),1case of Pleomorphic Xanthoastrocytoma (grade Ⅱ),23cases of astrocytoma (grade Ⅱ),22cases of anaplastic astrocytoma (grade Ⅲ) and44cases of glioblastoma (grade IV) were included. All cases underwent conventional, contrast MRI scan and SWI examination by using Siemens3.0T magnetic resonance imaging system before the operation. Magnitude image, phase image, susceptibility image and minimums intensity projection image were obtained by SWI on the post-processing workstation. Intratumor susceptibility hypo intensity area(ITSHIA) was observed and semiquantitative data were acquired in accordance with the different grading indexes as follows:ITSHIA biggest diameter (cm), ITSH1A frequency, ITSHIA biggest diameter score, ITSHIA frequency score, ITSHIA area ratio score, ITSHIA comprehensive score (The product of the frequency score and area ratio score), focal distribution punctiform ITSHIA around the tumor necrosis, beaded/line ITSHIA on the tumor edge or necrosis edge, ITSHIA morphology description. Semiquantitative ITSHIA data of astrocytic tumors with various grades were compared and their relationships with pathologic grade were analyzed. Area under the curve (AUC) was used to compare the effectiveness of different methods in distinguish the high grade tumors from the lows with recommended threshold and the corresponding sensitivity and specificity and to select the best index reflecting grading.
Results:There exists an obvious difference in the semiquantitative data of ITSHIA among different levels of astrocytic tumor. The values of ITSHIA for malignant astrocytic tumors (Ⅲ,Ⅳ) were higher than that in low level, whereas values of ITSHIA exist a general overlapping between the pilocytic astrocytma and the high level astrocytic tumor."Focal distribution punctiform ITSHIA around the tumor necrosis"(rs=0.691) and "beaded/line ITSHIA on the tumor edge or necrosis edge"(rs=0.627) showed highest relevance with pathological grading among all the indexes of ITSHIA. The relevance between comprehensive score, obtained from the SWI with no contrast, and pathological grading was highest of all the other indexes obtained by SWI with no contrast, whereas was slightly lower than that of enhanced SWI indexes. According to the performance of various semiquantitative indexes which can be used to distinguish high level astrocytic tumor by ROC, comprehensive score(area under curve, AUC=0.926) was the highest, the cutoff point was3,the rate for sensitivity was80.3%,for specificity87.5%; the " beaded/line ITSHIA on the tumor edge or necrosis edge "(0.924) was the second, the cutoff point is l,the rate for sensitivity was84.8%,for specificity100%; and the "focal distribution point like ITSHIA around the tumor necrosis "(0.911) was also useful, the cutoff point was1, the rate for sensitivity was86.4%, for specificity95.8%.
Conclusion:The semiquantitative indexes of SWI could reflect angiogenesis in astrocytic tumors, and the semiquantitative data was linear related with the histological grade markedly after excluding the cases of pilocytic astrocytoma. The indexes such as "comprehensive score", the " beaded/line ITSHIA on the tumor edge or necrosis edge", the "focal distribution punctiform ITSHIA around the tumor necrosis" of astrocytic tumors had a higher value for pathologic grading.
Part II:Correlation between the semiquantitative evaluations of susceptibility-weighted imaging and perfusion imaging in patients with astrocytic tumor
Objective:To evaluate the correlations between the indexes of SWI and those of PI in astrocytic tumors and to compare the clinic value in pathological grading before the operation.
Materials and Methods:The study objects and image processing methods were similar to those in the first part. All patients were underwent conventional, contrast MR scan, SWI and PI scan by Siemens3.0T magnetic resonance imaging system. Pseudo color pictures of CBV were obtained by PI on the post-processing workstation. ROI placement was placed through application of hot spots analysis. Maximum relative rCBV values of solid part within the tumor (rrCBVintra max), surrounding area of tumor (rrCBVperi max) were calculated. Comparison of the rrCBVintra max and rrCBVperi max in astrocytic tumor of different grade were performed. The corresponding situation between hot spot of PI and ITSHIA were evaluated and correlation between SWI and PI were compared. To analyze SWI and PI in the diagnostic value of high level of astrocytic tumor with ROC curves analysis.
Results:rrCBVmtramax (rs=0.662, P=0.000) of astrocytic tumors was related positively linearly with pathological grade. rrCBVperi max (rs=0.794, P=0.000) was also markedly related. The rrCBVintra max of pilocytic astrocytoma was higher than that of astrocytoma(Ⅱ), which was similar to that of grade Ⅲ, whereas rrCB Vperi max showed no differences compared with astrocytoma(Ⅱ) and markedly lower than the tumor of high grade. The semiquantitative data of ITSHIA had a typical positive correlation with rrCBVintra max and rrCBVperimsx respectively. The area including hot spot in PI was not to be able completely correspondent with ITSHIA. According to the performance of various PI indexes which could be used to distinguish high level astrocytic tumor by ROC, rrCBVintra max (area under curve, AUC=0.951) was the highest, the cutoff point is3.300, the rate for sensitivity was90.3%, for specificity91.7%; the rrCBVperi max was the second, the cutoff point was1.000, the rate for sensitivity was97.3%,for specificity83.3%. The rrCBVintra max showed some advantages over semiquantitative indexes of SWI in evaluating the pathological grade of astrocytic tumor.
Conclusion:semiquantitative indexes of SWI were closely related to that of PI. Both PI and SWI may be used as sensitive indexes of evaluating pathological grade of astrocytic tumor. PI was correlated with grading closely than SWI. The incompletely correspondent between hot spot and ITSHIA may be due to an association with different machismos of PI and SWI.
Part Ⅲ:Correlation between indexes of SWI、PI and MVD、 VEGF expression in astrocytic tumor
Objective:To detect the expression of MVD and VEGF in astrocytic tumor and their correlation with the semiquantivative indictors of SWI and rrCBVintra max, rrCBVperi max of PI for further clarifying the mechanism and clinical application.
Materials and Methods:The study objects and image processing methods were similar to those in the first and second part. Pathological sections were obtained after operation. Immunohistochemical assay was employed to detect the expression of VEGF and to make a MVD count. According to the degrees of VEGF expression, patients in our study were divided into two groups:VEGF expression degree including high expression and low expression. Correlation between MVD、VEGF and indexes of PI and SWI were analyzed.
Results:The MVD count (rs=0.550, P=0.000) and VEGF expression (rs=0.456P=0.000) were positive correlated with pathologic grading of astrocytic tumor. rrCBVintra max and rrCBVperi max of PI、most semiquantitative indexes of SWI showed markedly correlation with MVD and VEGF, respectively. Correlation analysis suggested a close relationship among the expression of VEGF and "beaded/line ITSHIA on the tumor edge or necrosis edge", the "focal distribution punctiform ITSHIA around the tumor necrosis" of astrocytic tumors shown on SWI with contrast. The above indexes were found significantly different between the2groups of VEGF expression degree with high expression and low expression (P<0.01) except for other semiquantitative indexes of SWI (P>0.05).
Conclusion:Both PI and SWI showed obviously correlation with angiogenesis and both are effective marker in evaluation angiogenesis preoperatively. High expression of VEGF was not only relevant to high perfusion area within or around the tumor, but also related to " beaded/line ITSHIA on the tumor edge or necrosis edge", the "focal distribution punctiform ITSHIA around the tumor necrosis".
引文
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[1]Haacke EM, Xu Y, Cheng YC, et al. Susceptibility weighted imaging (SWI). Magn Reson Med[J],2004,52:612-618.
[2]Haacke E.M, Mittal S, Wu Z, et al. Susceptibility-Weighted Imaging:Technical Aspects and Clinical Applications, Part 1. AJNR Am. J. Neuroradiol[J],Jan 2009,30:19-30.
[3]Mittal S, Wu Z, Neelavalli J, et al. Susceptibility-Weighted Imaging:Technical Aspects and Clinical Applications, Part 2 AJNR Am. J. Neuroradiol[J],Feb 2009,30:232-252.
[4]Fernandez-Seara MA, Techawiboonwong A, Detre JA, et al. MR susceptometry for measuring global brain oxygen extraction. Magn Reson Med[J],2006, 55:967-973.
[5]Reichenbach JR, Venkatesan R, Schillinger DJ, et al. Small vessels in the human brain:MR venography with deoxyhemoglobin as an intrinsic contrast agent.Radiology[J],1997,204:272-277.
[6]Reichenbach JR, Haacke EM. High-resolution BOLD venographic imaging; a window into brain function. NMR Biomed[J],2001,14:453-467.
[7]Reichenbach JR, Jonetz-Mentzel L, Fitzek C, et al. High-resolution blood oxygen-level dependent MR venography (HRBV):a new technique. Neuroradiology[J],2001,43:364-369.
[8]Haddar D, Haacke E, Sehgal V, et al. Susceptibility weighted imaging:theory and applications. J Radiol[J],2004,85:1901-1908.
[9]Thomas B, Somasundaram S, Thamburaj K, et al. Clinical applications of susceptibility weighted MR imaging of the brain:a pictorial review. Neuroradiology[J],2008,50:105-116.
[10]Hu J, Yu Y, Juhasz C, et al. MR susceptibility weighted imaging (SWI) complements conventional contrast enhanced T1 weighted MRI in characterizing brain abnormalities of Sturge-Weber syndrome. J Magn Reson Imaging[J],2008,28:300-307.
[11]Kaya D, Dincer A, Yildiz ME, et al.Acute ischemic infarction defined by a region of multiple hypointense vessels on gradient-echo T2* MR imaging at 3T. AJNR Am. J. Neuroradiol[J],2009,30:1227-1232.
[12]Zhang W, Zhao J, Guo D,et al. Application of susceptibility weighted imaging in revealing intratumoral blood products and grading gliomas. J Radiol.2010 Apr; 91(4):485-490.
[13]Chavhan GB, Babyn PS, Thomas B, et al. Principles, Techniques, and Applications of T2*-based MR Imaging and Its Special Applications. Radiographics[J],2009,29:1433-1449.
[14]Tong K.A, Ashwal S, Obenaus A, et al. Susceptibility-Weighted MR Imaging:A Review of Clinical Applications in Children AJNR Am. J. Neuroradiol[J],Jan 2008,29:9-17.
[15]Nandigam R.N.K, Viswanathan A, Delgado P, et al. MR Imaging Detection of Cerebral Microbleeds:Effect of Susceptibility-Weighted Imaging, Section Thickness, and Field Strength.AJNR Am. J. Neuroradiol[J],Feb 2009,30:338-343.
[16]Akter M,Hirai T,Kitajima M.et al.Detection of hemorrhagic hypointense foci in the brain on susceptibility-weighted imaging clinical and phantom studies.Acad Radiol[J],2007,14(9):1011-1019.
[17]Vajkoczy P,Menger MD. Vascular microenvironment in gliomas. J Neurooncol[J],2000,50(1-2):99-108.
[18]Zama A, Tamura M, Inoue H. Three-dimensional observations on microvascular growth in rat glioma using a vascular casting method. J Cancer Res Clin Oncol[J],1991,117:396-402.
[19]Christoforidis GA, Kangarlu A, Abduljalil AM, et al. Susceptibility-based imaging of glioblastoma microvascularity at 8 T:correlation of MR imaging and postmortem pathology. AJNR Am J Neuroradiol[J],2004,25:756-760.
[20]Bhujwalla ZM, Artemov D, Natarajan K, Solaiyappan M, Kollars P, Kristjansen PE. Reduction of vascular and permeable regions in solid tumors detected by macromolecular contrast magnetic resonance imaging after treatment with antiangiogenic agent TNP-470.Clin Cancer Res [J],2003,9(1):355-362.
[21]Degani H, Chetrit-Dadiani M, Bogin L, Furman-Haran E. Magnetic resonance imaging of tumor vasculature.Thromb Haemost[J],2003,89(1):25-33.
[22]Bagley LJ, Grossman RI, Judy KD, et al. Gliomas:correlation of magnetic susceptibility artifact with histologic grade. Radiology[J],1997,202:511-516.
[23]Haacke Haacke EM, Herigault G, Yu Y, et al. Observing tumor vascularity noninvasively using magnetic resonance imaging. Image Analysis and Stereology[J],2002,21:107-113.
[24]Sehgal V, Delproposto Z, Haacke EM, et al. Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging[J],2005,22:439-450.
[25]Rauscher A, Sedlacik J, Barth M, et al. Noninvasive asseasment of vascular architecture and function during modulated blood oxygenation using susceptibility weighted magnetic resonance imaging. Magn Reson Med [J],2005, 54:87-95.
[26]Grabner G, Haubenberger D, Rath J, et al. A Population-Specific Symmetric Phase Model to Automatically Analyze Susceptibility-Weighted Imaging (SWI) Phase Shifts and Phase Symmetry in the Human Brain. J Magn Reson Imaging[J],2010,31:215-220.
[27]Rauscher A, Sedlacik J, Barth M, et al. Magnetic susceptibility-weighted MR phase imaging of the human brain. AJNR Am J Neuroradiol[J], 2005,26:736-742.
[28]Pinker K, Noebauer-Huhmann IM, Stavrou I. High-Resolution Contrast-Enhanced, Susceptibility-Weighted MR Imaging at 3T in Patients with Brain Tumors:Correlation with Positron-Emission Tomography and Histopathologic Findings. AJNR Am J Neuroradiol[J],2007,28:1280-1286.
[29]Park MJ, Kim HS, Jahng GH, et al. Semiquantitative Assessment of Intratumoral. Susceptibility Signals Using Non-Contrast-Enhanced High-Field High-Resolution Susceptibility-Weighted Imaging in Patients with Gliomas: Comparison with MR Perfusion Imaging. AJNR Am J Neuroradiol[J],2009,30:1402-1408.
[30]Deistung A, Rauscher A, Sedlacik, J,et al. Informatics in Radiology GUIBOLD: A Graphical User Interface for Image Reconstruction and Data Analysis in Susceptibility-weighted MR Imaging. RadioGraphics[J],2008,28:639-651.
[31]Sehgal V, Delproposto Z, Haddar D, et al. Susceptibility-Weighted Imaging to Visualize Blood Products and Improve Tumor Contrast in the Study of Brain Masses [J]. J Magn Reson Imaging[J],2006,24:41-51.
[32]Wu Z, Mittal S, Kish K, et al. Identification of calcification with magnetic resonance imaging using susceptibility-weighted imaging:a case study. J Magn Reson Imaging[J],2009,29:177-182.
[33]Noebauer-Huhmann IM, Pinker K, Barth M, et al. Contrast-enhanced, highresolution, susceptibility-weighted magnetic resonance imaging of the brain: dose-dependent optimization at 3 Tesla and 1.5 Tesla in healthy volunteers. Invest Radiol[J],2006,41:249-255.
[34]Kim HS, Jahng GH, Ryu CW, et al. Added Value and Diagnostic Performance of Intratumoral Susceptibility Signals in the Differential Diagnosis of Solitary Enhancing Brain Lesions:Preliminary Study. AJNR Am J Neuroradiol[J],2009,30:1574-1579.
[35]Nandigam R.N.K, Viswanathan A, Delgado P, et al. MR Imaging Detection of Cerebral Microbleeds:Effect of Susceptibility-Weighted Imaging, Section Thickness, and Field Strength.AJNR Am. J. Neuroradiol[J],2009,30:338-343.
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[1]Haacke EM, Xu Y, Cheng YC, et al. Susceptibility weighted imaging (SWI). Magn Reson Med[J],2004,52:612-618.
[2]Haacke E.M, Mittal S, Wu Z, et al. Susceptibility-Weighted Imaging:Technical Aspects and Clinical Applications, Part 1. AJNR Am. J. Neuroradiol[J],Jan 2009,30:19-30.
[3]Mittal S, Wu Z, Neelavalli J, et al. Susceptibility-Weighted Imaging:Technical Aspects and Clinical Applications, Part 2 AJNR Am. J. Neuroradiol[J],Feb 2009,30:232-252.
[4]Fernandez-Seara MA, Techawiboonwong A, Detre JA, et al. MR susceptometry for measuring global brain oxygen extraction. Magn Reson Med[J],2006, 55:967-973.
[5]Reichenbach JR, Venkatesan R, Schillinger DJ, et al. Small vessels in the human brain:MR venography with deoxyhemoglobin as an intrinsic contrast agent.Radiology[J],1997,204:272-277.
[6]Reichenbach JR, Haacke EM. High-resolution BOLD venographic imaging; a window into brain function. NMR Biomed[J],2001,14:453-467.
[7]Reichenbach JR, Jonetz-Mentzel L, Fitzek C, et al. High-resolution blood oxygen-level dependent MR venography (HRBV):a new technique. Neuroradiology[J],2001,43:364-369.
[8]Haddar D, Haacke E, Sehgal V, et al. Susceptibility weighted imaging:theory and applications. J Radiol[J],2004,85:1901-1908.
[9]Thomas B, Somasundaram S, Thamburaj K, et al. Clinical applications of susceptibility weighted MR imaging of the brain:a pictorial review. Neuroradiology[J],2008,50:105-116.
[10]Hu J, Yu Y, Juhasz C, et al. MR susceptibility weighted imaging (SWI) complements conventional contrast enhanced T1 weighted MRI in characterizing brain abnormalities of Sturge-Weber syndrome. J Magn Reson Imaging[J],2008,28:300-307.
[11]Kaya D, Dincer A, Yildiz ME, et al.Acute ischemic infarction defined by a region of multiple hypointense vessels on gradient-echo T2* MR imaging at 3T. AJNR Am. J. Neuroradiol[J],2009,30:1227-1232.
[12]Zhang W, Zhao J, Guo D,et al. Application of susceptibility weighted imaging in revealing intratumoral blood products and grading gliomas. J Radiol.2010 Apr; 91(4):485-490.
[13]Chavhan GB, Babyn PS, Thomas B, et al. Principles, Techniques, and Applications of T2*-based MR Imaging and Its Special Applications. Radiographics[J],2009,29:1433-1449.
[14]Tong K.A, Ashwal S, Obenaus A, et al. Susceptibility-Weighted MR Imaging:A Review of Clinical Applications in Children AJNR Am. J. Neuroradiol[J],Jan 2008,29:9-17.
[15]Nandigam R.N.K, Viswanathan A, Delgado P, et al. MR Imaging Detection of Cerebral Microbleeds:Effect of Susceptibility-Weighted Imaging, Section Thickness, and Field Strength.AJNR Am. J. Neuroradiol[J],Feb 2009,30:338-343.
[16]Akter M,Hirai T,Kitajima M.et al.Detection of hemorrhagic hypointense foci in the brain on susceptibility-weighted imaging clinical and phantom studies.Acad Radiol[J],2007,14(9):1011-1019.
[17]Vajkoczy P,Menger MD. Vascular microenvironment in gliomas. J Neurooncol[J],2000,50(1-2):99-108.
[18]Zama A, Tamura M, Inoue H. Three-dimensional observations on microvascular growth in rat glioma using a vascular casting method. J Cancer Res Clin Oncol[J],1991,117:396-402.
[19]Christoforidis GA, Kangarlu A, Abduljalil AM, et al. Susceptibility-based imaging of glioblastoma microvascularity at 8 T:correlation of MR imaging and postmortem pathology. AJNR Am J Neuroradiol[J],2004,25:756-760.
[20]Bhujwalla ZM, Artemov D, Natarajan K, Solaiyappan M, Kollars P, Kristjansen PE. Reduction of vascular and permeable regions in solid tumors detected by macromolecular contrast magnetic resonance imaging after treatment with antiangiogenic agent TNP-470.Clin Cancer Res [J],2003,9(1):355-362.
[21]Degani H, Chetrit-Dadiani M, Bogin L, Furman-Haran E. Magnetic resonance imaging of tumor vasculature.Thromb Haemost[J],2003,89(1):25-33.
[22]Bagley LJ, Grossman RI, Judy KD, et al. Gliomas:correlation of magnetic susceptibility artifact with histologic grade. Radiology[J],1997,202:511-516.
[23]Haacke Haacke EM, Herigault G, Yu Y, et al. Observing tumor vascularity noninvasively using magnetic resonance imaging. Image Analysis and Stereology[J],2002,21:107-113.
[24]Sehgal V, Delproposto Z, Haacke EM, et al. Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging[J],2005,22:439-450.
[25]Rauscher A, Sedlacik J, Barth M, et al. Noninvasive asseasment of vascular architecture and function during modulated blood oxygenation using susceptibility weighted magnetic resonance imaging. Magn Reson Med [J],2005, 54:87-95.
[26]Grabner G, Haubenberger D, Rath J, et al. A Population-Specific Symmetric Phase Model to Automatically Analyze Susceptibility-Weighted Imaging (SWI) Phase Shifts and Phase Symmetry in the Human Brain. J Magn Reson Imaging[J],2010,31:215-220.
[27]Rauscher A, Sedlacik J, Barth M, et al. Magnetic susceptibility-weighted MR phase imaging of the human brain. AJNR Am J Neuroradiol[J], 2005,26:736-742.
[28]Pinker K, Noebauer-Huhmann IM, Stavrou I. High-Resolution Contrast-Enhanced, Susceptibility-Weighted MR Imaging at 3T in Patients with Brain Tumors:Correlation with Positron-Emission Tomography and Histopathologic Findings. AJNR Am J Neuroradiol[J],2007,28:1280-1286.
[29]Park MJ, Kim HS, Jahng GH, et al. Semiquantitative Assessment of Intratumoral. Susceptibility Signals Using Non-Contrast-Enhanced High-Field High-Resolution Susceptibility-Weighted Imaging in Patients with Gliomas: Comparison with MR Perfusion Imaging. AJNR Am J Neuroradiol[J],2009,30:1402-1408.
[30]Deistung A, Rauscher A, Sedlacik, J,et al. Informatics in Radiology GUIBOLD: A Graphical User Interface for Image Reconstruction and Data Analysis in Susceptibility-weighted MR Imaging. RadioGraphics[J],2008,28:639-651.
[31]Sehgal V, Delproposto Z, Haddar D, et al. Susceptibility-Weighted Imaging to Visualize Blood Products and Improve Tumor Contrast in the Study of Brain Masses [J]. J Magn Reson Imaging[J],2006,24:41-51.
[32]Wu Z, Mittal S, Kish K, et al. Identification of calcification with magnetic resonance imaging using susceptibility-weighted imaging:a case study. J Magn Reson Imaging[J],2009,29:177-182.
[33]Noebauer-Huhmann IM, Pinker K, Barth M, et al. Contrast-enhanced, highresolution, susceptibility-weighted magnetic resonance imaging of the brain: dose-dependent optimization at 3 Tesla and 1.5 Tesla in healthy volunteers. Invest Radiol[J],2006,41:249-255.
[34]Kim HS, Jahng GH, Ryu CW, et al. Added Value and Diagnostic Performance of Intratumoral Susceptibility Signals in the Differential Diagnosis of Solitary Enhancing Brain Lesions:Preliminary Study. AJNR Am J Neuroradiol[J],2009,30:1574-1579.
[35]Nandigam R.N.K, Viswanathan A, Delgado P, et al. MR Imaging Detection of Cerebral Microbleeds:Effect of Susceptibility-Weighted Imaging, Section Thickness, and Field Strength.AJNR Am. J. Neuroradiol[J],2009,30:338-343.