Vasco Sousa Abreu, João Tarrio, José Silva, Francisco Almeida, Catarina Pinto, Davide Freitas, João Pedro Filipe
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AUCs were 0.79 (PCNSL vs. glioblastoma), 0.91 (PCNSL vs. metastasis), and 0.78 (glioblastoma vs. metastasis).</p>\n \n <p>DS and US parameters were statistically significant between glioblastoma (−109.92; IQR: 152.71 and 59.06; IQR: 52.87) and PCNSL (−47.36; IQR: 44.30 and 21.68; IQR: 16.85), presenting AUCs of 0.86 and 0.87.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>Metastasis and glioblastoma can be better differentiated from PCNSL through rCBV. PSR demonstrated higher differential performance compared to the other parameters and seemed useful, allowing a proper distinction among all, particularly between metastasis and glioblastoma, where rCBV failed. 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引用次数: 0
摘要
背景和目的：动态易感对比度增强（DSC）磁共振灌注是区分脑肿瘤的重要技术。通过前负荷泄漏校正 DSC-MRI 得出的可测量参数的诊断潜力仍未得到充分开发。本研究旨在评估这些参数在区分原发性中枢神经系统淋巴瘤（PCNSL）、胶质母细胞瘤和转移瘤方面的作用：分析了 39 例经病理证实的 PCNSL（14 例）、胶质母细胞瘤（14 例）和转移瘤（11 例）患者。五个 DSC 参数--相对 CBV (rCBV)、信号恢复百分比 (PSR)、下行斜率 (DS)、上行斜率 (US) 和一过斜率比--来自肿瘤强化区域。使用接收者操作特征曲线分析评估诊断性能：转移瘤（4.58；四分位数间距 [IQR]：2.54）和胶质母细胞瘤（3.98；IQR：1.87）的 RCBV 高于 PCNSL（1.46；IQR：0.29；两者的 p = .00006）。PCNSL 的 PSR（88.11；IQR：21.21）高于转移瘤（58.30；IQR：22.28；p = .0002），而胶质母细胞瘤（74.54；IQR：21.23）与其他肿瘤相比几乎呈现显著的趋势性差异（p≈.05）。AUC分别为0.79（PCNSL vs. 胶质母细胞瘤）、0.91（PCNSL vs. 转移瘤）和0.78（胶质母细胞瘤 vs. 转移瘤）。DS和US参数在胶质母细胞瘤（-109.92；IQR：152.71和59.06；IQR：52.87）和PCNSL（-47.36；IQR：44.30和21.68；IQR：16.85）之间具有统计学意义，AUC分别为0.86和0.87：转移瘤和胶质母细胞瘤可以通过 rCBV 与 PCNSL 进行更好的鉴别。与其他参数相比，PSR显示出更高的鉴别性能，而且似乎很有用，可以正确区分所有参数，尤其是rCBV失效的转移瘤和胶质母细胞瘤。最后，DS 和 US 只有助于区分胶质母细胞瘤和 PCNSL。
Multiparametric analysis from dynamic susceptibility contrast-enhanced perfusion MRI to evaluate malignant brain tumors
Background and Purpose
Dynamic susceptibility contrast-enhanced (DSC) MR perfusion is a valuable technique for distinguishing brain tumors. Diagnostic potential of measurable parameters derived from preload leakage-corrected-DSC-MRI remains somewhat underexplored. This study aimed to evaluate these parameters for differentiating primary CNS lymphoma (PCNSL), glioblastoma, and metastasis.
Methods
Thirty-nine patients with pathologically proven PCNSL (n = 14), glioblastoma (n = 14), and metastasis (n = 11) were analyzed. Five DSC parameters—relative CBV (rCBV), percentage of signal recovery (PSR), downward slope (DS), upward slope (US), and first-pass slope ratio—were derived from tumor-enhancing areas. Diagnostic performance was assessed using receiver operating characteristic curve analysis.
Results
RCBV was higher in metastasis (4.58; interquartile range [IQR]: 2.54) and glioblastoma (3.98; IQR: 1.87), compared with PCNSL (1.46; IQR: 0.29; p = .00006 for both). rCBV better distinguished metastasis and glioblastoma from PCNSL, with an area under the curve (AUC) of 0.97 and 0.99, respectively.
PSR was higher in PCNSL (88.11; IQR: 21.21) than metastases (58.30; IQR: 22.28; p = .0002), while glioblastoma (74.54; IQR: 21.23) presented almost significant trend-level differences compared to the others (p≈.05). AUCs were 0.79 (PCNSL vs. glioblastoma), 0.91 (PCNSL vs. metastasis), and 0.78 (glioblastoma vs. metastasis).
DS and US parameters were statistically significant between glioblastoma (−109.92; IQR: 152.71 and 59.06; IQR: 52.87) and PCNSL (−47.36; IQR: 44.30 and 21.68; IQR: 16.85), presenting AUCs of 0.86 and 0.87.
Conclusion
Metastasis and glioblastoma can be better differentiated from PCNSL through rCBV. PSR demonstrated higher differential performance compared to the other parameters and seemed useful, allowing a proper distinction among all, particularly between metastasis and glioblastoma, where rCBV failed. Finally, DS and US were only helpful in differentiating glioblastoma from PCNSL.
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