Department of Diagnostic Radiology, Ajou University School of Medicine, Mt. 5 Woncheon-dong, Yeongtong-gu, Suwon, Gyeonggi-do, Korea.
AJNR Am J Neuroradiol. 2010 Oct;31(9):1699-706. doi: 10.3174/ajnr.A2161. Epub 2010 Jun 25.
The histogram method has been shown to demonstrate heterogeneous morphologic features of tumor vascularity. This study aimed to determine whether whole-tumor histogram analysis of the normalized CBV for contrast-enhancing lesions and perienhancing lesions can differentiate among GBMs, SMTs, and lymphomas.
Fifty-nine patients with histopathologically confirmed GBMs (n = 28), SMTs (n = 22), or lymphomas (n = 12) underwent conventional MR imaging and dynamic susceptibility contrast-enhanced imaging before surgery. Histogram distribution of the normalized CBV was obtained from whole-tumor voxels in contrast-enhancing lesions and perienhancing lesions. The HW, PHP, and MV were determined from histograms. One-way ANOVA was used initially to test the overall equality of mean values for each type of tumor. Subsequently, posttest multiple comparisons were performed.
For whole-tumor histogram analyses for contrast-enhancing lesions, only PHP could differentiate among GBMs (4.79 ± 1.31), SMTs (3.32 ± 1.10), and lymphomas (2.08 ± 0.54). The parameters HW and MV were not significantly different between GBMs and SMTs, whereas the 2 histogram parameters were significantly higher in GBMs and SMTs compared with lymphomas. For the analyses of perienhancing lesions, only MV could differentiate among GBMs (1.90 ± 0.26), SMTs (0.80 ± 0.21), and lymphomas (1.27 ± 0.34). HW and PHP were not significantly different between SMTs and lymphomas.
Using a whole-tumor histogram analysis of normalized CBV for contrast-enhancing lesions and perienhancing lesions facilitates differentiation of GBMs, SMTs and lymphomas.
直方图方法已被证明可以显示肿瘤血管形态的异质性特征。本研究旨在确定对比增强病变和周边增强病变的全肿瘤直方图分析是否可以区分胶质母细胞瘤(GBM)、间变性星形细胞瘤(SMT)和淋巴瘤。
59 例经组织病理学证实的 GBM(n=28)、SMT(n=22)或淋巴瘤(n=12)患者在术前均进行了常规磁共振成像和动态对比增强磁共振成像。从对比增强病变和周边增强病变的全肿瘤体素中获得归一化 CBV 的直方图分布。从直方图中确定 HW、PHP 和 MV。首先使用单因素方差分析检验每种肿瘤类型的平均值总体是否相等。然后进行了事后多重比较。
对于对比增强病变的全肿瘤直方图分析,只有 PHP 可以区分 GBM(4.79±1.31)、SMT(3.32±1.10)和淋巴瘤(2.08±0.54)。HW 和 MV 在 GBM 和 SMT 之间没有显著差异,而这 2 个直方图参数在 GBM 和 SMT 中明显高于淋巴瘤。对于周边增强病变的分析,只有 MV 可以区分 GBM(1.90±0.26)、SMT(0.80±0.21)和淋巴瘤(1.27±0.34)。HW 和 PHP 在 SMT 和淋巴瘤之间没有显著差异。
使用对比增强病变和周边增强病变的全肿瘤直方图分析有助于区分 GBM、SMT 和淋巴瘤。