Outcome analysis for patients with subarachnoid hemorrhage and vasospasm including endovascular treatment.

As a complication of subarachnoid hemorrhage (SAH), vasospasm substantially contributes to its morbidity and mortality. We aimed at analyzing predictors of outcome for these patients including the role of endovascular treatment (ET). Our database was screened for patients with SAH treated in our Neuro-ICU from 2009 to 2019. Clinical parameters including functional outcome (modified Rankin Scale, mRS of 0-2 or 3-6 at discharge and after a median follow-up of 18 months) and details about ET were gathered on 465 patients, 241 (52%) of whom experienced vasospasm. Descriptive analyses were performed to identify explanatory variables for the dichotomized mRS score. A logistic regression model was fitted on 241 patients with vasospasm including age, Hunt and Hess Score, extraventricular drainage (EVD), forced hypertension, ET and delayed cerebral ischemia (DCI). The model found a Hunt and Hess Score of 5 (OR = 0.043, p = 0.008), requirement of EVD (OR = 0.161, p < 0.001), forced hypertension (OR = 0.242, p = 0.001), ET (OR = 0.431, p = 0.043) and DCI (OR = 0.229, p < 0.001) to be negative predictors of outcome while age was not. Use of intraarterial nimodipine alone (OR = 0.778, p = 0.705) or including balloon angioplasty (OR = 0.894, p = 0.902) and number of ETs per patient (OR = 0.757, p = 0.416) were not significant in a separate model with otherwise identical variables. While DCI is clearly associated with poor outcome, the influence of ET on outcome remains inconclusive. Limited by their retrospective nature and an indication bias, these data encourage a randomized assessment of ET.

Prophylactic anticoagulation in patients with glioblastoma or brain metastases and atrial fibrillation: an increased risk for intracranial hemorrhage?

PURPOSE: Patients with glioblastoma (GBM) or brain metastases (MET) and atrial fibrillation (AF) might be at an increased risk of intracranial hemorrhage (ICH) due to anticoagulation (AC). Our aim was to assess this risk. METHODS: Our institution's database (from 2005 to 2017) was screened for patients with GBM or MET and AF with an indication for AC according to their CHA2DS2VASc stroke risk score (≥ 2). Required follow-up was at least 3 months. AC was either performed with heparins, phenprocoumon or non-Vitamin K antagonist oral anticoagulants. Applying the propensity score approach, patient cohorts (matched according to primary tumor, age, sex) were generated (GBM [or MET] with AF ± AC, GBM [or MET] without AF/AC, no GBM [or MET] but AF on AC). ICH was defined as clinical deterioration caused by new blood on imaging. A log rank test was performed to compare the risk for ICH between the three groups. RESULTS: In total, 104 patients were identified of which 49 with GBM (37% on AC) and 37 with MET (46% on AC) were successfully matched. Median follow up was 8.6 and 7.2 months, respectively. ICH occurred in 10.2% of GBM + AF and 12.2% GBM-AF, whereas 8% of patients with AF on AC suffered ICH (p = 0.076). 13.5% of patients with MET + AF had ICHs, in the controls it was 16% for MET-AF and 8% for AF on AC (p = 0.11). CONCLUSION: AC did not seem to influence the incidence of ICH in patients with glioblastoma or brain metastases within follow up of just under 9 months.

Tumor Infiltration in Enhancing and Non-Enhancing Parts of Glioblastoma: A Correlation with Histopathology.

PURPOSE: To correlate histopathologic findings from biopsy specimens with their corresponding location within enhancing areas, non-enhancing areas and necrotic areas on contrast enhanced T1-weighted MRI scans (cT1). MATERIALS AND METHODS: In 37 patients with newly diagnosed glioblastoma who underwent stereotactic biopsy, we obtained a correlation of 561 1mm3 biopsy specimens with their corresponding position on the intraoperative cT1 image at 1.5 Tesla. Biopsy points were categorized as enhancing (CE), non-enhancing (NE) or necrotic (NEC) on cT1 and tissue samples were categorized as "viable tumor cells", "blood" or "necrotic tissue (with or without cellular component)". Cell counting was done semi-automatically. RESULTS: NE had the highest content of tissue categorized as viable tumor cells (89% vs. 60% in CE and 30% NEC, respectively). Besides, the average cell density for NE (3764 ± 2893 cells/mm2) was comparable to CE (3506 ± 3116 cells/mm2), while NEC had a lower cell density with 2713 ± 3239 cells/mm2. If necrotic parts and bleeds were excluded, cell density in biopsies categorized as "viable tumor tissue" decreased from the center of the tumor (NEC, 5804 ± 3480 cells/mm2) to CE (4495 ± 3209 cells/mm2) and NE (4130 ± 2817 cells/mm2). DISCUSSION: The appearance of a glioblastoma on a cT1 image (circular enhancement, central necrosis, peritumoral edema) does not correspond to its diffuse histopathological composition. Cell density is elevated in both CE and NE parts. Hence, our study suggests that NE contains considerable amounts of infiltrative tumor with a high cellularity which might be considered in resection planning.

Downfield-NOE-suppressed amide-CEST-MRI at 7 Tesla provides a unique contrast in human glioblastoma.

PURPOSE: The chemical exchange saturation transfer (CEST) effect observed in brain tissue in vivo at the frequency offset 3.5 ppm downfield of water was assigned to amide protons of the protein backbone. Obeying a base-catalyzed exchange process such an amide-CEST effect would correlate with intracellular pH and protein concentration, correlations that are highly interesting for cancer diagnosis. However, recent experiments suggested that, besides the known aliphatic relayed-nuclear Overhauser effect (rNOE) upfield of water, an additional downfield rNOE is apparent in vivo resonating as well around +3.5 ppm. In this study, we present further evidence for the underlying downfield-rNOE signal, and we propose a first method that suppresses the downfield-rNOE contribution to the amide-CEST contrast. Thus, an isolated amide-CEST effect depending mainly on amide proton concentration and pH is generated. METHODS: The isolation of the exchange mediated amide proton effect was investigated in protein model-solutions and tissue lysates and successfully applied to in vivo CEST images of 11 glioblastoma patients. RESULTS: Comparison with gadolinium contrast enhancing longitudinal relaxation time-weighted images revealed that the downfield-rNOE-suppressed amide-CEST contrast forms a unique contrast that delineates tumor regions and show remarkable overlap with the gadolinium contrast enhancement. CONCLUSION: Thus, suppression of the downfield rNOE contribution might be the important step to yield the amide proton CEST contrast originally aimed at. Magn Reson Med 77:196-208, 2017. © 2016 Wiley Periodicals, Inc.

Radiogenomics of Glioblastoma: Machine Learning-based Classification of Molecular Characteristics by Using Multiparametric and Multiregional MR Imaging Features.

Purpose To evaluate the association of multiparametric and multiregional magnetic resonance (MR) imaging features with key molecular characteristics in patients with newly diagnosed glioblastoma. Materials and Methods Retrospective data evaluation was approved by the local ethics committee, and the requirement to obtain informed consent was waived. Preoperative MR imaging features were correlated with key molecular characteristics within a single-institution cohort of 152 patients with newly diagnosed glioblastoma. Preoperative MR imaging features (n = 31) included multiparametric (anatomic and diffusion-, perfusion-, and susceptibility-weighted images) and multiregional (contrast-enhancing regions and hyperintense regions at nonenhanced fluid-attenuated inversion recovery imaging) information with histogram quantification of tumor volumes, volume ratios, apparent diffusion coefficients, cerebral blood flow, cerebral blood volume, and intratumoral susceptibility signals. Molecular characteristics determined included global DNA methylation subgroups (eg, mesenchymal, RTK I "PGFRA," RTK II "classic"), MGMT promoter methylation status, and hallmark copy number variations (EGFR, PDGFRA, MDM4, and CDK4 amplification; PTEN, CDKN2A, NF1, and RB1 loss). Univariate analyses (voxel-lesion symptom mapping for tumor location, Wilcoxon test for all other MR imaging features) and machine learning models were applied to study the strength of association and discriminative value of MR imaging features for predicting underlying molecular characteristics. Results There was no tumor location predilection for any of the assessed molecular parameters (permutation-adjusted P > .05). Univariate imaging parameter associations were noted for EGFR amplification and CDKN2A loss, with both demonstrating increased Gaussian-normalized relative cerebral blood volume and Gaussian-normalized relative cerebral blood flow values (area under the receiver operating characteristics curve: 63%-69%, false discovery rate-adjusted P < .05). Subjecting all MR imaging features to machine learning-based classification enabled prediction of EGFR amplification status and the RTK II glioblastoma subgroup with a moderate, yet significantly greater, accuracy (63% for EGFR [P < .01], 61% for RTK II [P = .01]) than prediction by chance; prediction accuracy for all other molecular parameters was not significant. Conclusion The authors found associations between established MR imaging features and molecular characteristics, although not of sufficient strength to enable generation of machine learning classification models for reliable and clinically meaningful prediction of molecular characteristics in patients with glioblastoma. © RSNA, 2016 Online supplemental material is available for this article.

Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting.

OBJECTIVE: Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. MATERIALS AND METHODS: Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. RESULTS: There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman's ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman's ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. CONCLUSIONS: Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas.

Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma.

BACKGROUND: The purpose of this study was to determine the relevance of clinical data, apparent diffusion coefficient (ADC), and relative cerebral blood volume (rCBV) from dynamic susceptibility contrast (DSC) perfusion and the volume transfer constant (ktrans) from dynamic contrast-enhanced (DCE) perfusion for predicting overall survival (OS) and progression-free survival (PFS) in newly diagnosed treatment-naïve glioblastoma patients. METHODS: Preoperative MR scans including standardized contrast-enhanced T1 (cT1), T2 - fluid-attenuated inversion recovery (FLAIR), ADC, DSC, and DCE of 125 patients with subsequent histopathologically confirmed glioblastoma were performed on a 3 Tesla MRI scanner. ADC, DSC, and DCE parameters were analyzed in semiautomatically segmented tumor volumes on contrast-enhanced (CE) cT1 and hyperintense signal changes on T2 FLAIR (ED). Univariate and multivariable Cox regression analyses including age, sex, extent of resection (EOR), and KPS were performed to assess the influence of each parameter on OS and PFS. RESULTS: Univariate Cox regression analysis demonstrated a significant association of age, KPS, and EOR with PFS and age, KPS, EOR, lower ADC, and higher rCBV with OS. Multivariable analysis showed independent significance of male sex, KPS, EOR, and increased rCBVCE for PFS, and age, sex, KPS, and EOR for OS. CONCLUSIONS: MRI parameters help to predict OS in a univariate Cox regression analysis, and increased rCBVCE is associated with shorter PFS in the multivariable model. In summary, however, our findings suggest that the relevance of MRI parameters is outperformed by clinical parameters in a multivariable analysis, which limits their prognostic value for survival prediction at the time of initial diagnosis.

Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.

Purpose To evaluate whether radiomic feature-based magnetic resonance (MR) imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma with improved accuracy compared with that of established clinical and radiologic risk models. Materials and Methods Retrospective evaluation of data was approved by the local ethics committee and informed consent was waived. A total of 119 patients (allocated in a 2:1 ratio to a discovery [n = 79] or validation [n = 40] set) with newly diagnosed glioblastoma were subjected to radiomic feature extraction (12 190 features extracted, including first-order, volume, shape, and texture features) from the multiparametric (contrast material-enhanced T1-weighted and fluid-attenuated inversion-recovery imaging sequences) and multiregional (contrast-enhanced and unenhanced) tumor volumes. Radiomic features of patients in the discovery set were subjected to a supervised principal component (SPC) analysis to predict progression-free survival (PFS) and overall survival (OS) and were validated in the validation set. The performance of a Cox proportional hazards model with the SPC analysis predictor was assessed with C index and integrated Brier scores (IBS, lower scores indicating higher accuracy) and compared with Cox models based on clinical (age and Karnofsky performance score) and radiologic (Gaussian normalized relative cerebral blood volume and apparent diffusion coefficient) parameters. Results SPC analysis allowed stratification based on 11 features of patients in the discovery set into a low- or high-risk group for PFS (hazard ratio [HR], 2.43; P = .002) and OS (HR, 4.33; P < .001), and the results were validated successfully in the validation set for PFS (HR, 2.28; P = .032) and OS (HR, 3.45; P = .004). The performance of the SPC analysis (OS: IBS, 0.149; C index, 0.654; PFS: IBS, 0.138; C index, 0.611) was higher compared with that of the radiologic (OS: IBS, 0.175; C index, 0.603; PFS: IBS, 0.149; C index, 0.554) and clinical risk models (OS: IBS, 0.161, C index, 0.640; PFS: IBS, 0.139; C index, 0.599). The performance of the SPC analysis model was further improved when combined with clinical data (OS: IBS, 0.142; C index, 0.696; PFS: IBS, 0.132; C index, 0.637). Conclusion An 11-feature radiomic signature that allows prediction of survival and stratification of patients with newly diagnosed glioblastoma was identified, and improved performance compared with that of established clinical and radiologic risk models was demonstrated. (©) RSNA, 2016 Online supplemental material is available for this article.

Time-dependent parameter of perfusion imaging as independent predictor of clinical outcome in symptomatic carotid artery stenosis.

BACKGROUND: Carotid artery stenosis is a frequent cause of ischemic stroke. While any degree of stenosis can cause embolic stroke, a higher degree of stenosis can also cause hemodynamic infarction. The hemodynamic effect of a stenosis can be assessed via perfusion weighted MRI (PWI). Our aim was to investigate the ability of PWI-derived parameters such as TTP (time-to-peak) and T(max) (time to the peak of the residue curve) to predict outcome in patients with unilateral acute symptomatic internal carotid artery (sICA) stenosis. METHODS: Patients with unilateral acute sICA stenosis (≥50% according to NASCET), without intracranial stenosis or occlusion, who underwent PWI, were included. Clinical characteristics, volume of restricted diffusion, volume of prolonged TTP and T(max) were retrospectively analyzed and correlated with outcome represented by the modified Rankin Scale (mRS) score at discharge. TTP and T(max) volumes were dichotomized using a ROC curve analysis. Multivariate analysis was performed to determine which PWI-parameter was an independent predictor of outcome. RESULTS: Thirty-two patients were included. Degree of stenosis, volume of visually assessed TTP and volume of TTP ≥2 s did not distinguish patients with favorable (mRS 0-2) and unfavorable (mRS 3-6) outcome. In contrast, patients with unfavorable outcome had higher volumes of TTP ≥4 s (9.12 vs. 0.87 ml; p = 0.043), TTP ≥6 s (6.70 vs. 0.20 ml; p = 0.017), T(max) ≥4 s (25.27 vs. 0.00 ml; p = 0.043), T(max) ≥6 s (9.21 vs. 0.00 ml; p = 0.017), T(max) ≥8 s (6.86 vs. 0.00 ml; p = 0.011) and T(max) ≥10s (5.94 vs. 0.00 ml; p = 0.025) in univariate analysis. Multivariate logistic regression showed that NIHSS score on admission (Odds Ratio (OR) 0.466, confidence interval (CI) [0.224;0.971], p = 0.041), T(max) ≥8 s (OR 0.025, CI [0.001;0.898] p = 0.043) and TTP ≥6 s (OR 0.025, CI [0.001;0.898] p = 0.043) were independent predictors of clinical outcome. CONCLUSION: As they stood out in multivariate regression and are objective and reproducible parameters, PWI-derived volumes of T(max) ≥8 s and TTP ≥6 s might be superior to degree of stenosis and visually assessed TTP maps in predicting short term patient outcome. Future studies should assess if perfusion weighted imaging might guide the selection of patients for recanalization procedures.

Cortical vessel sign on susceptibility weighted imaging reveals clinically relevant hypoperfusion in internal carotid artery stenosis.

BACKGROUND AND PURPOSE: Internal carotid artery (ICA) stenosis can lead to cerebral hypoperfusion and is a common cause of stroke. As susceptibility weighted imaging (SWI) has been used for penumbra imaging in acute ischemic stroke, we aimed at analyzing hypoperfusion using SWI in patients with ICA stenosis. MATERIAL AND METHODS: Clinical characteristics, asymmetric cortical vessel sign (more and/or larger, hypointense asymmetric cortical vessels) on SWI, Doppler sonography results and diffusion weighted imaging (DWI) lesion volume were retrospectively analyzed in patients with ICA stenosis. In a subgroup of patients, volume of prolonged time to peak and volume of prolonged time to peak of the residue curve (Tmax) were measured as reference standard. Outcome was assessed as modified Rankin score at discharge. RESULTS: 104 patients were included. Median age was 72 and median degree of stenosis 70% according to NASCET. 13% had a asymmetric cortical vessel sign. These patients had a higher degree of stenosis (80% vs. 70%, p=0.004), were more often symptomatic (93% vs. 61%, p=0.020) and had higher DWI volume (7.3ml vs. 0.2ml, p=0.011). Specificity for the prediction of DWI lesions was 86%. Also, patients with asymmetric cortical vessel sign had lower rates of favorable outcome (mRS=0-2; 57% vs. 82%, p=0.033) and volumes of Tmax≥4s, ≥6s, ≥8s, ≥10s and TTP≥2s, ≥4s, ≥6s were significantly higher. In multivariate analysis, asymmetric cortical vessel sign was an independent negative predictor of favorable outcome (mRS 0-2; OR 0.184; CI [0.039; 0.875] p=0.033). CONCLUSION: In patients with ICA stenosis, asymmetric cortical vessel sign is a sign of clinically relevant hypoperfusion.

MR Perfusion-derived Hemodynamic Parametric Response Mapping of Bevacizumab Efficacy in Recurrent Glioblastoma.

PURPOSE: To better understand the effect of bevacizumab therapy on tumor blood flow and oxygenation status in patients with recurrent glioblastoma. MATERIALS AND METHODS: Retrospective data evaluation was approved by the local ethics committee of the University of Heidelberg (ethics approval number, S-320/2012), and informed consent was waived. A total of 71 patients who received a diagnosis of recurrent glioblastoma underwent conventional anatomic magnetic resonance (MR) imaging and dynamic susceptibility contrast material-enhanced MR imaging at baseline and at the first follow-up examination after initiation of bevacizumab therapy. Parametric response maps (PRMs) were created with multistep (nonlinear) registration of patients' post- to pretreatment images and voxel-wise subtraction between Gaussian-normalized relative cerebral blood volume (nrCBV) and Gaussian-normalized relative cerebral blood flow (nrCBF) maps. Intratumor voxels were stratified as being increased (PRM[+]) or decreased (PRM[-]) if they exceeded a threshold that represented the 95% confidence interval in the normal-appearing brain. Correlation with progression-free and overall survival was performed with Cox proportional hazards models. RESULTS: The risks for disease progression and death significantly increased with (a) higher baseline nrCBV (hazard ratio [HR] = 1.86, P < .01; HR = 1.52, P < .01) and nrCBF (HR = 1.78, P < .01; HR = 1.86, P < .01) values and (b) higher PRM(-) of nrCBV (HR = 1.03, P = .01; HR = 1.02, P = .03) and nrCBF (HR = 1.04, P < .01; HR = 1.03, P < .01), but not with higher PRM(+) of nrCBV and nrCBF, and not for the relative change in mean nrCBV and nrCBF, confirming the superiority of the PRM approach. The magnitude of PRM(-) for both nrCBV and nrCBF significantly increased for higher baseline values (P < .01). CONCLUSION: Pretreatment hemodynamic parameters are the principal determinant of response to bevacizumab therapy in patients with recurrent glioblastoma. Although the magnitude of PRM(-) is a function of the corresponding pretreatment parameter, the finding of higher PRM(-) and a lack of change in PRM(+) in nonresponders to bevacizumab therapy implies that tumors with a high degree of angiogenesis before bevacizumab therapy retain a higher level of angiogenesis during therapy, despite a greater antiangiogenic effect of bevacizumab, such that a reversal of the biologic behavior and relative prognosis of these tumors does not occur.

Gadolinium retention in the dentate nucleus and globus pallidus is dependent on the class of contrast agent.

PURPOSE: To compare changes in signal intensity (SI) ratios of the dentate nucleus (DN) and the globus pallidus (GP) to those of other structures on unenhanced T1-weighted magnetic resonance (MR) images between linear and macrocyclic gadolinium-based contrast agents (GBCAs). MATERIALS AND METHODS: The study was approved by the ethical committee of the University of Heidelberg (reference no. S-324/2014). Owing to the retrospective character of the study, the ethical committee did not require any written informed consent. Two groups of 50 patients who underwent at least six consecutive MR imaging examinations with the exclusive use of either a linear GBCA (gadopentetate dimeglumine) or a macrocyclic GBCA (gadoterate meglumine) were analyzed retrospectively. The difference in mean SI ratios of DN to pons and GP to thalamus on unenhanced T1-weighted images from the last and first examinations was calculated. One-sample and independent-sample t tests were used to assess the difference in SI ratios for both groups, and regression analysis was performed to account for potential confounders. RESULTS: The SI ratio difference in the linear group was greater than 0 (mean DN difference ± standard deviation, 0.0407 ± 0.0398 [P < .001]; GP, 0.0287 ± 0.0275 [P < .001]) and significantly larger (DN, P < .001 and standardized difference of 1.16; GP, P < .001 and standardized difference of 0.81) than that in the macrocyclic group, which did not differ from 0 (DN, 0.0016 ± 0.0266 [P = .680]; GP, 0.0031 ± 0.0354 [P = .538]). The SI ratio difference between the last and first examinations for the DN remained significantly different between the two groups in the regression analysis (P < .001). CONCLUSION: This study indicates that an SI increase in the DN and GP on T1-weighted images is caused by serial application of the linear GBCA gadopentetate dimeglumine but not by the macrocyclic GBCA gadoterate meglumine. Clinical implications of this observation remain unclear.

Relaxation-compensated CEST-MRI of the human brain at 7T: Unbiased insight into NOE and amide signal changes in human glioblastoma.

Endogenous chemical exchange saturation transfer (CEST) effects of protons resonating near to water protons are always diluted by competing effects such as direct water saturation and semi-solid magnetization transfer (MT). This leads to unwanted T2 and MT signal contributions that contaminate the observed CEST signal. Furthermore, all CEST effects appear to be scaled by the T1 relaxation time of the mediating water pool. As MT, T1 and T2 are also altered in tumor regions, a recently published correction algorithm yielding the apparent exchange-dependent relaxation AREX, is used to evaluate in vivo CEST effects. This study focuses on CEST effects of amides (3.5ppm) and Nuclear-Overhauser-mediated saturation transfer (NOE, -3.5ppm) that can be properly isolated at 7T. These were obtained in 10 glioblastoma patients, and this is the first comprehensive study where AREX is applied in human brain as well as in human glioblastoma. The correction of CEST effects alters the contrast significantly: after correction, the CEST effect of amides does not show significant contrast between contrast enhancing tumor regions and normal tissue, whereas NOE drops significantly in the tumor area. In addition, new features in the AREX contrasts are visible. This suggests that previous CEST approaches might not have shown pure CEST effects, but rather water relaxation shine-through effects. Our insights help to improve understanding of the CEST effect changes in tumors and correlations on a cellular and molecular level.

Nuclear Overhauser Enhancement imaging of glioblastoma at 7 Tesla: region specific correlation with apparent diffusion coefficient and histology.

OBJECTIVE: To explore the correlation between Nuclear Overhauser Enhancement (NOE)-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC) and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST) that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells. PATIENTS AND METHODS: For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym) at 3.3ppm, B1 = 0.7 µT). Contrast enhanced T1 (CE-T1), T2 and diffusion-weighted MRI (DWI) were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp). In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site. RESULTS: Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, p<0.05). Seven correlations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (p<0.05, n = 3). No trend towards a correlation between MTRasym and ADC was found in CE-T1 tumor (-0.310.05, n = 6). The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSppatient3 = 0.69 and rSppatient15 = 0.87, p<0.05), while the correlation of ADC and cellularity was heterogeneous (rSppatient3 = 0.545 (p = 0.067), rSppatient4 = -0.021 (p = 0.948), rSppatient15 = -0.755 (p = 0.005)). DISCUSSION: NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes cellularity more accurately than ADC, especially in the CE-T1 tumor region.

Relative cerebral blood volume is a potential predictive imaging biomarker of bevacizumab efficacy in recurrent glioblastoma.

BACKGROUND: To analyze the relevance of dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI) derived relative cerebral blood volume (rCBV) analysis for predicting response to bevacizumab (BEV) in patients with recurrent glioblastoma (rGB). METHODS: A total of 127 patients diagnosed with rGB receiving either bevacizumab (71 patients, BEV cohort) or alkylating chemotherapy (56 patients, non-BEV cohort) underwent conventional anatomic MRI and DSC-MRI at baseline and at first follow-up after treatment initiation. The mean rCBV of the contrast-enhancing tumor (cT1) as well as cT1 and fluid-attenuated inversion recovery (FLAIR) volumes at both time points were correlated with progression-free survival (PFS) and overall survival (OS) using Cox proportional hazard models, logistic regression, and the log-rank test. RESULTS: Baseline rCBV was associated with both PFS (hazard ratio [HR] = 1.3; P < .01) and OS (HR = 1.3; P < .01) in the BEV cohort and predicted 6-month PFS in 82% and 12-month OS in 79% of patients, whereas it was not associated with PFS (HR = 1.0; P = .70) or OS (HR = 1.0; P = .47) in the non-BEV cohort. Corresponding median OS and PFS rates in the BEV cohort for patients with rCBV-values less than 3.92 (optimal threshold from receiver operating characteristic [ROC] analysis of 12-month OS data) were 14.2 and 6.0 months, as compared to 6.6 and 2.8 months for patients with rCBV-values greater than 3.92 (P < .01, respectively). cT1 and FLAIR volumes at first follow-up were significant predictors of 6-month PFS and 12-month OS in the BEV cohort but not in the non-BEV cohort. Corresponding volumes at baseline were not significant in any cohort. CONCLUSIONS: Pretreatment rCBV is a potential predictive imaging biomarker in BEV-treated rGB but not alkylating chemotherapy-treated rGB, which is superior to volumetric analysis of conventional anatomic MRI and predicts 6-month PFS and 12-month OS in 80% of BEV-treated patients.

Quantification of tumor vessels in glioblastoma patients using time-of-flight angiography at 7 Tesla: a feasibility study.

PURPOSE: To analyze if tumor vessels can be visualized, segmented and quantified in glioblastoma patients with time of flight (ToF) angiography at 7 Tesla and multiscale vessel enhancement filtering. MATERIALS AND METHODS: Twelve patients with newly diagnosed glioblastoma were examined with ToF angiography (TR = 15 ms, TE = 4.8 ms, flip angle = 15°, FOV = 160 × 210 mm(2), voxel size: 0.31 × 0.31 × 0.40 mm(3)) on a whole-body 7 T MR system. A volume of interest (VOI) was placed within the border of the contrast enhancing part on T1-weighted images of the glioblastoma and a reference VOI was placed in the non-affected contralateral white matter. Automated segmentation and quantification of vessels within the two VOIs was achieved using multiscale vessel enhancement filtering in ImageJ. RESULTS: Tumor vessels were clearly visible in all patients. When comparing tumor and the reference VOI, total vessel surface (45.3 ± 13.9 mm(2) vs. 29.0 ± 21.0 mm(2) (p<0.035)) and number of branches (3.5 ± 1.8 vs. 1.0 ± 0.6 (p<0.001) per cubic centimeter were significantly higher, while mean vessel branch length was significantly lower (3.8 ± 1.5 mm vs 7.2 ± 2.8 mm (p<0.001)) in the tumor. DISCUSSION: ToF angiography at 7-Tesla MRI enables characterization and quantification of the internal vascular morphology of glioblastoma and may be used for the evaluation of therapy response within future studies.