Differentiation of progressive disease from pseudoprogression using 3D PCASL and DSC perfusion MRI in patients with glioblastoma
应用 3D PCASL 和 DSC 灌注 MRI 鉴别胶质母细胞瘤患者疾病进展与假性进展
- 作者列表："Manning, Paul","Daghighi, Shadi","Rajaratnam, Matthew K.","Parthiban, Sowmya","Bahrami, Naeim","Dale, Anders M.","Bolar, Divya","Piccioni, David E.","McDonald, Carrie R.","Farid, Nikdokht
Purpose To use 3D pseudocontinuous arterial spin labeling (3D PCASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion MRI to differentiate progressive disease from pseudoprogression in patients with glioblastoma (GBM). Methods Thirty-two patients with GBM who developed progressively enhancing lesions within the radiation field following resection and chemoradiation were included in this retrospective, single-institution study. The updated modified RANO criteria were used to establish progressive disease or pseudoprogression. Following 3D PCASL and DSC MR imaging, perfusion parameter estimates of cerebral blood flow (ASL-nCBF and DSC-nrCBF) and cerebral blood volume (DSC-nrCBV) were calculated. Additionally, contrast enhanced volumes were measured. Mann–Whitney U tests were used to compare groups. Linear discriminant analysis (LDA) and area under receiver operator characteristic curve (AUC) analyses were used to evaluate performance of each perfusion parameter and to determine optimal cut-off points. Results All perfusion parameter measurements were higher in patients with progressive disease (mean, 95% CI ASL-nCBF 2.48, [2.03, 2.93]; DSC-nrCBF = 2.27, [1.85, 2.69]; DSC-nrCBV = 3.51, [2.37, 4.66]) compared to pseudoprogression (mean, 95% CI ASL-nCBF 0.99, [0.47, 1.52]; DSC-nrCBF = 1.05, [0.36, 1.74]; DSC-nCBV = 1.19, [0.34, 2.05]), and findings were significant at the p < 0.0125 level (p = 0.001, 0.003, 0.002; effect size: Cohen’s d = 1.48, 1.27, and 0.92). Contrast enhanced volumes were not significantly different between groups (p > 0.447). All perfusion parameters demonstrated high AUC (0.954 for ASL-nCBF, 0.867 for DSC-nrCBF, and 0.891 for DSC-nrCBV), however, ASL-nCBF demonstrated the highest AUC and misclassified the fewest cases (N = 6). Lesions correctly classified by ASL but misclassified by DSC were located along the skull base or adjacent to large resection cavities with residual blood products, at areas of increased susceptibility. Conclusion Both 3D PCASL and DSC perfusion MRI techniques have nearly equivalent performance for the differentiation of progressive disease from pseudoprogression in patients with GBM. However, 3D PCASL is less sensitive to susceptibility artifact and may allow for improved classification in select cases.
目的应用 3D 假连续动脉自旋标记 (3D PCASL) 和动态磁敏感对比增强 (DSC) 灌注 MRI 鉴别胶质母细胞瘤 (GBM) 患者的疾病进展和假性进展。方法本回顾性、单机构研究纳入了 32 例 GBM 患者，这些患者在切除和放化疗后在放射野内出现进行性强化病变。使用更新的改良 RANO 标准确定疾病进展或假性进展。3D PCASL 和 DSC MR 成像后，计算脑血流灌注参数估计值 (ASL-nCBF 和 DSC-nrCBF) 和脑血容量 (DSC-nrCBV)。此外，测量对比剂增强体积。使用 Mann-Whitney U 检验比较各组。线性判别分析 (LDA) 和受试者操作特征曲线下面积 (AUC) 分析用于评价每个灌注参数的性能并确定最佳截点。结果所有灌注参数测量在进行性疾病患者中均较高 (平均值，95% CI asl-ncbf 2.48，[2.03，2.93]; DSC-nrcbf = 2.27，[1.85, 2.69]; DSC-nrcbv = 3.51，[2.37，4.66]) 与假性进展相比 (平均值，95% CI ASL-nCBF 0.99，[0.47，1.52]; DSC-nrcbf = 1.05，[0.36,1.74]; DSC-ncbv = 1.19，[0.34，2.05])，结果在 p <0.0125 水平上显著 (p = 0.001，0.003，0.002; 效应量: Cohen's d = 1.48 、 1.27 和 0.92)。对比剂增强体积在组间无显著差异 (p> 0.447)。所有灌注参数均显示高 AUC (ASL-nCBF 为 0.954，DSC-nrCBF 为 0.867，DSC-nrCBV 为 0.891)，然而,ASL-nCBF 显示 AUC 最高，错分病例最少 (n = 6)。病变按 ASL 正确分类，但按 DSC 错误分类，位于颅底或邻近大切除腔及残留血液制品，易感性增加的区域。结论 3D PCASL 和 DSC 灌注 MRI 技术对 GBM 患者的疾病进展和假性进展的鉴别具有几乎等效的性能。然而，3D PCASL 对易感性伪影的敏感性较低，在选定的情况下可能允许改进分类。
METHODS::Glioma growth can cause pervasive changes in the functional connectivity (FC) of brain networks, which has been associated with re-organization of brain functions and development of functional deficits in patients. Mechanisms underlying functional re-organization in brain networks are not understood and efforts to utilize functional imaging for surgical planning, or as a biomarker of functional outcomes are confounded by the heterogeneity in available human data. Here we apply multiple imaging modalities in a well-controlled murine model of glioma with extensive validation using human data to explore mechanisms of FC disruption due to glioma growth. We find gliomas cause both local and distal changes in FC. FC changes in networks proximal to the tumor occur secondary to hemodynamic alterations but surprisingly, remote FC changes are independent of hemodynamic mechanisms. Our data strongly implicate hemodynamic alterations as the main driver of local changes in measurements of FC in patients with glioma.
METHODS::Mutations in LZTR1, already known to be causal in familial schwannomatosis type 2, have been recently involved in a small proportion of patients with autosomal dominant and autosomal recessive Noonan syndrome. LZTR1 is also a driver gene in non syndromal glioblastoma. We report a 26-year-old patient with typical Noonan syndrome, and the dominantly transmitted c.850C > T (p.(Arg284Cys)) variant in LZTR1. An oligoastrocytoma was diagnosed in the patient at the age of 22 years; recurrence of the tumor occurred at age 26, as a ganglioblastoma. The patient had been transiently treated with growth hormone between ages 15 and 17. Considering the implication of LZTR1 in sporadic tumors of the nervous system, we hypothesize that gliomas are a possible complication of LZTR1-related Noonan syndrome. This report also supports a possible link between occurrence of a cerebral tumor in Noonan syndrome and a previous treatment with growth hormone.
METHODS:BACKGROUND:Susceptibility weighted imaging (SWI) provides vascular information and plays an important role in improving the diagnostic accuracy of preoperative glioma grading. Intratumoral susceptibility signal intensities (ITSS) obtained from SWI has been used in glioma grading. However, the current method for estimation of ITSS is semiquantitative, manual count-dependent, and includes hemorrhage as well as vasculature. PURPOSE:To develop a quantitative approach that calculates the vasculature volume within tumors by filtering out the hemorrhage from ITSS using R2 * values and connected component analysis-based segmentation algorithm; to evaluate the accuracy of the proposed ITSS vasculature volume (IVV) for differentiating various grades of glioma; and compare it with reported semiquantitative ITSS approach. STUDY TYPE:Retrospective. SUBJECTS:Histopathologically confirmed 41 grade IV, 19 grade III, and 15 grade II glioma patients.Field Strength/Sequence: SWI (four echoes: 5.6, 11.8, 18, 24.2 msec) along with conventional MRI sequences (T2 -weighted, T1 -weighted, 3D-fluid-attenuated inversion recovery [FLAIR], and diffusion-weighted imaging [DWI]) at 3.0T. ASSESSMENT:R2 * relaxation maps were calculated from multiecho SWI. The R2 * cutoff value for hemorrhage ITSS was determined. A segmentation algorithm was designed, based on this R2 * hemorrhage combined with connected component shape analysis, to quantify the IVV from all slices containing tumor by filtering out hemorrhages. Semiquantitative ITSS scoring as well as total ITSS volume (TIV) including hemorrhages were also calculated. STATISTICAL TESTS:One-way analysis of variance (ANOVA) and Tukey-Kramer post-hoc tests were performed to see the difference among the three grades of the tumor (II, III, and IV) in terms of semiquantitative ITSS scoring, TIV, and IVV. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the three methods individually in discriminating between grades of glioma. RESULTS:One-way ANOVA showed that only the proposed IVV significantly differentiated different grades of gliomas having visible ITSS. ROC analysis showed that IVV provided the highest AUC for the discrimination of grade II vs. III (0.93), grade III vs. IV (0.98), and grade II vs. IV glioma (0.94). IVV also provided the highest sensitivity and specificity for differentiating grade II vs. III (87.44, 98.41), grade III vs. IV (97.15, 94.12), and grade II vs. IV (98.72, 92.31). DATA CONCLUSION:The proposed quantitative method segregates hemorrhage from tumor vasculature. It scores above the existing semiquantitative method in terms of ITSS estimation and grading accuracy. LEVEL OF EVIDENCE:4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:225-233.