rCBV Maps Research Articles

Multi-Site Benchmark Study for Standardized Relative Cerebral Blood Volume in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol.

A national consensus recommendation for the collection of DSC (dynamic susceptibility contrast) MRI perfusion data, used to create maps of relative cerebral blood volume (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce inter-site variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multi-site study was to determine rCBV in untreated brain metastases in comparison to glioblastoma and normal appearing brain using the national consensus protocol. Subjects from three sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a mid-range flip angle, GRE-EPI acquisition and the administration of both a pre-load and 2nd DSC-MRI dose of 0.1 mmol/kg GBCA. Quantitative maps of standardized rCBV (sRCBV) were generated and enhancing lesion ROIs determined from post-contrast T1-weighted images alone or calibrated difference maps, termed delta T1 (dT1) maps. Mean sRCBV for metastases were compared to normal appearing white matter (NAWM) and glioblastoma (GBM) from a previous study. Comparisons were performed using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney nonparametric test for unpaired comparisons. 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (n=1), melanoma (n=5), gastrointestinal (GI) (n=3) and genitourinary (GU) (n=9) were included in comparison to GBM (n=31). The mean sRCBV of all metastases (1.83+/-1.05) were significantly lower (p=0.0009) than mean sRCBV for GBM (2.67±1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (n=1), melanoma (n=5), gastrointestinal (GI) (n=3) and genitourinary (GU) (n=9) were included in comparison to GBM (n=31). The mean sRCBV of all metastases (1.83+/-1.05) were significantly lower (p=0.0009) than mean sRCBV for GBM (2.67+1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. dT1=delta T1; GBCA=gadolinium-based contrast agent; NAWM=normal appearing white matter; normalized relative cerebral blood volume=nRCBV; relative cerebral blood volume=rCBV; standardized relative cerebral blood volume=sRCBV.

E.2 Proof of concept for liquid biopsy: positive correlation between extracellular vesicles shed by high grade gliomas and volume of hypervascular tumour tissue on MRI

Background: High grade gliomas (HGGs) shed extracellular vesicles (EVs) into the bloodstream. EV-derived RNA (EV-RNA) can be detected in plasma, making it a potential biomarker for HGG recurrence after treatment. We sought to establish a baseline relationship between EV-RNA in plasma and hypervascular HGG tissue on MRI. Methods: Eight patients with a new diagnosis of HGG had measurements of plasma EV-RNA and contemporaneous dynamic susceptibility contrast (DSC) MRI. Patient-specific median signal intensity of corpus callosum (mSI-CC) was determined from 10 measurements on the relative cerebral blood volume (rCBV) map. Tumour tissue with signal intensity &gt; mSI-CC and &gt; 2x, &gt; 3x, &gt; 4x and &gt; 5x mSI-CC was segmented on the rCBV map. EV-RNA plasma concentration was correlated with tissue volumes. Results: Pearson correlation showed a significant positive relationship between EV-RNA plasma concentration and tissue volume with signal intensity &gt; mSI-CC (r(6) = 0.899, p = 0.002). No significant relationship could be detected for progressively smaller tissue volumes with signal intensity &gt; 2x, &gt; 3x, &gt; 4x and &gt; 5x mSI-CC. Conclusions: EV-RNA plasma concentration correlates strongly with the total volume of hypervascular HGG tissue on DSC MRI at baseline and merits further evaluation as a biomarker of tumour behaviour in longitudinal imaging studies.

Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma

IntroductionThe purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients. Material and MethodsrCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient. Results41 patients (18 females; median age = 59 years; range 21–77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85. DiscussionWe demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved.

Intravoxel incoherent motion for differentiating residual/recurrent tumor from post-treatment change in patients with high-grade glioma.

To investigate the diagnostic value of f derived from IVIM technique and to correlate it with rCBV derived from DSC for the differentiation of residual/recurrent tumor from post-treatment change in patients with high-grade glioma. Patients who underwent MR imaging with IVIM and DSC studies for evaluation of high-grade glioma after standard treatment were enrolled in this retrospective study. For qualitative analysis, the f and rCBV maps were interpreted as hypoperfused or hyperperfused in each parameter. Quantitative analysis was performed using ROI analysis in f and rCBV parameters. The lesions were divided into residual/recurrent tumor and post-treatment change groups. Nineteen patients with high-grade glioma were included. In qualitative analysis, the f-map shows higher sensitivity (100.0%) than rCBV map (92.3%), while the rCBV map shows higher specificity (100.0%) than the f-map (83.3%). In quantitative analysis, the optimal cutoff values of 1.19 for f and 1.06 for rCBV are shown to provide high diagnostic value with high sensitivity (91.7%) for both parameters but slightly higher specificity of rCBV (85.7%) than f (71.4%). The correlation between f and rCBV was good with ICC of 0.810. The f value measured by IVIM technique, non-contrast perfusion technique, has high diagnostic performance and potential to be an alternative method to CBV measured by DSC for differentiation between residual/recurrent tumor and post-treatment change in patients with high-grade glioma.

Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma.

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol. The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV < 1.0), tumor with moderate angiogenesis (1.0 < sRCBV < 1.75), and tumor with high angiogenesis (sRCBV > 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold. The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%). The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time.

Early Differentiation of Pseudoprogression for Recurrent Glioblastoma in STERIMGLI Trial Using Multimodal MRI Radiomics Signature

<h3>Purpose/Objective(s)</h3> Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in adults. Local relapse of GBM is constant and leads to death. STERIMGLI trial (NCT02866747) evaluates the efficacy of combined stereotactic radiotherapy with Durvalumab as salvage treatment for patients with recurrent GBM. However, immunotherapy leads to morphological pseudoprogression (PP) images. Interestingly, patients in phase I who presented a PP had a prolonged local control. Up to date, no early imaging biomarkers are able to predict which patients will present a PP and potentially respond to the combined treatment. The study aims at identifying early predictive imaging biomarkers to characterize PP from true progression. <h3>Materials/Methods</h3> 26 patients from STERIMGLI phase I/IIa with longitudinal multi-parametric MRI follow-up (morphological MRI modalities, diffusion, perfusion) were included. BraTS Toolkit was used for image preprocessing and first automatic segmentation of tumor subregions (<i>Piram et al. EANO 2021</i>) named here after labels enhanced tumor (ET) and flair edema (ED). Segmentations were reviewed by a radiation oncologist and neuroradiologist, and MRIs were classified as PP or true progression (TP). First order radiomic features were extracted with open-source software in FLAIR, ADC map, rCBV map for ED label and T1, T1c, ADC, rCBV for ET label. Extracted features were compared at baseline, first event and variation (∆) between baseline and first event, in TP and PP groups, for tumor (ET, ED) and contralateral healthy tissue (control ET, control ED). <h3>Results</h3> On baseline FLAIR, kurtosis in ED label predicts PP (K< 2.52) and TP (K> 2.52) outcome (p= 0.0047). Sensitivity and specificity were respectively 76% and 89% in our study group. In ET label, ∆volume (p=0.0055), ∆entropy on 3 modalities T1 (p=0.0142), T1c (p= 0.0253) and ADC map (p= 0.001) showed significant differences between TP and PP groups on univariate analysis, whereas no difference was observed in healthy tissue. A combined score of those 4 features, was able to differentiate patients in two groups: low risk of TP versus high risk of TP and discriminate between TP and PP with 87% sensitivity and 88% specificity. Odd ratio between the 2 groups is 19.50 [2.2; 173.5]. <h3>Conclusion</h3> Radiomics analysis was able to identify a predictive feature of PP on baseline FLAIR MRI and a diagnostic combined score was able to discriminate between TP and PP, from variation between first significant volume increase and baseline MRI, in patients treated with combined stereotactic radiotherapy with Durvalumab for recurrent GBM. However, these results have to be confirmed on a larger cohort (on-going STERIMGLI phase IIb will provide a validation cohort)

Radiotherapy Target Volume Definition in Newly Diagnosed High-Grade Glioma Using 18F-FET PET Imaging and Multiparametric MRI: An Inter Observer Agreement Study.

Background: The aim of this prospective monocentric study was to assess the inter-observer agreement for tumor volume delineations by multiparametric MRI and 18-F-FET-PET/CT in newly diagnosed, untreated high-grade glioma (HGG) patients. Methods: Thirty patients HGG underwent O-(2-[18F]-fluoroethyl)-l-tyrosine(18F-FET) positron emission tomography (PET), and multiparametric MRI with computation of rCBV map and K2 map. Three nuclear physicians and three radiologists with different levels of experience delineated the 18-F-FET-PET/CT and 6 MRI sequences, respectively. Spatial similarity (Dice and Jaccard: DSC and JSC) and overlap (Overlap: OV) coefficients were calculated between the readers for each sequence. Results: DSC, JSC, and OV were high for 18F-FET PET/CT, T1-GD, and T2-FLAIR (>0.67). The Spearman correlation coefficient between readers was ≥0.6 for these sequences. Cross-comparison of similarity and overlap parameters showed significant differences for DSC and JSC between 18F-FET PET/CT and T2-FLAIR and for JSC between 18F-FET PET/CT and T1-GD with higher values for 18F-FET PET/CT. No significant difference was found between T1-GD and T2-FLAIR. rCBV, K2, b1000, and ADC showed correlation coefficients between readers <0.6. Conclusion: The interobserver agreements for tumor volume delineations were high for 18-F-FET-PET/CT, T1-GD, and T2-FLAIR. The DWI (b1000, ADC), rCBV, and K2-based sequences, as performed, did not seem sufficiently reproducible to be used in daily practice.

Diagnostic Accuracy of Arterial Spin Labeling in Comparison With Dynamic Susceptibility Contrast-Enhanced Perfusion for Brain Tumor Surveillance at 3T MRI.

PurposeWe aimed to compare arterial spin labeling (ASL) with dynamic susceptibility contrast (DSC) enhanced perfusion MRI for the surveillance of primary and metastatic brain tumors at 3T, both in terms of lesion perfusion metrics and diagnostic accuracy.MethodsIn this retrospective study, we included 115 patients, who underwent both ASL and DSC perfusion in the same 3T MRI scanning session between 1 January and 31 December 2019. ASL-derived cerebral blood flow (CBF) maps and DSC-derived relative cerebral blood volume (rCBV) maps, both uncorrected and corrected for leakage, were created with commercially available software. Lesions were identified as T2-/T2-FLAIR hyperintensity with or without contrast enhancement. Measurements were done by placing a region of interest in the visually determined area of highest perfusion, copying to the contralateral normal appearing white matter (NAWM), and then propagating to the other perfusion maps. Pearson’s correlation coefficients were calculated between the CBF and rCBV ratios of tumor versus NAWM. Accuracy for diagnosing tumor progression was calculated as the area under the receiver operating characteristics (ROC) curve (AUC) for the ASL-CBF and leakage corrected DSC-rCBV ratios.ResultsWe identified 178 lesions, 119 with and 59 without contrast enhancement. Correlation coefficients between ASL-derived CBF versus DSC-derived rCBV ratios were 0.60–0.67 without and 0.72–0.78 with leakage correction in all lesions (n = 178); these were 0.65–0.80 in enhancing glioma (n = 80), 0.58–0.73 in non-enhancing glioma, and 0.14–0.40 in enhancing metastasis (n = 31). No significant correlation was found in enhancing (n = 8) or non-enhancing (n = 7) lymphomas. The areas under the ROC curves (AUCs) for all patients were similar for ASL and DSC (0.73–0.78), and were higher for enhancing glioma (AUC = 0.78–0.80) than for non-enhancing glioma (AUC = 0.56–0.62). In brain metastasis, the AUC was lower for ASL-derived CBF (AUC = 0.72) than for DSC-derived rCBV ratios (AUC = 0.87–0.93).ConclusionWe found that ASL and DSC have more or less the same diagnostic accuracy. Our findings suggest that ASL can be used as an alternative to DSC to measure perfusion in enhancing and non-enhancing gliomas and brain metastasis at 3T. For lymphoma, this should be further investigated in a larger population.

Simultaneous Mapping of Vasculature, Hypoxia, and Proliferation Using Dynamic Susceptibility Contrast MRI, 18F-FMISO PET, and 18F-FLT PET in Relation to Contrast Enhancement in Newly Diagnosed Glioblastoma.

Conventional MRI plays a key role in the management of patients with high-grade glioma, but multiparametric MRI and PET tracers could provide further information to better characterize tumor metabolism and heterogeneity by identifying regions having a high risk of recurrence. In this study, we focused on proliferation, hypervascularization, and hypoxia, all factors considered indicative of poor prognosis. They were assessed by measuring uptake of 18F-3'-deoxy-3'-18F-fluorothymidine (18F-FLT), relative cerebral blood volume (rCBV) maps, and uptake of 18F-fluoromisonidazole (18F-FMISO), respectively. For each modality, the volumes and high-uptake subvolumes (hot spots) were semiautomatically segmented and compared with the contrast enhancement (CE) volume on T1-weighted gadolinium-enhanced (T1w-Gd) images, commonly used in the management of patients with glioblastoma. Methods: Dynamic susceptibility contrast-enhanced MRI (31 patients), 18F-FLT PET (20 patients), or 18F-FMISO PET (20 patients), for a total of 31 patients, was performed on preoperative glioblastoma patients. Volumes and hot spots were segmented on SUV maps for 18F-FLT PET (using the fuzzy locally adaptive bayesian algorithm) and 18F-FMISO PET (using a mean contralateral image + 3.3 SDs) and on rCBV maps (using a mean contralateral image + 1.96 SDs) for dynamic susceptibility contrast-enhanced MRI and overlaid on T1w-Gd images. For each modality, the percentages of the peripheral volumes and the peripheral hot spots outside the CE volume were calculated. Results: All tumors showed highly proliferated, hypervascularized, and hypoxic regions. The images also showed pronounced heterogeneity of both tracers regarding their uptake and rCBV maps, within each individual patient. Overlaid volumes on T1w-Gd images showed that some proliferative, hypervascularized, and hypoxic regions extended beyond the CE volume but with marked differences between patients. The ranges of peripheral volume outside the CE volume were 1.6%-155.5%, 1.5%-89.5%, and 3.1%-78.0% for 18F-FLT, rCBV, and 18F-FMISO, respectively. All patients had hyperproliferative hot spots outside the CE volume, whereas hypervascularized and hypoxic hot spots were detected mainly within the enhancing region. Conclusion: Spatial analysis of multiparametric maps with segmented volumes and hot spots provides valuable information to optimize the management and treatment of patients with glioblastoma.

Deep Learning Can Differentiate IDH-Mutant from IDH-Wild GBM.

Isocitrate dehydrogenase (IDH) mutant and wildtype glioblastoma multiforme (GBM) often show overlapping features on magnetic resonance imaging (MRI), representing a diagnostic challenge. Deep learning showed promising results for IDH identification in mixed low/high grade glioma populations; however, a GBM-specific model is still lacking in the literature. Our aim was to develop a GBM-tailored deep-learning model for IDH prediction by applying convoluted neural networks (CNN) on multiparametric MRI. We selected 100 adult patients with pathologically demonstrated WHO grade IV gliomas and IDH testing. MRI sequences included: MPRAGE, T1, T2, FLAIR, rCBV and ADC. The model consisted of a 4-block 2D CNN, applied to each MRI sequence. Probability of IDH mutation was obtained from the last dense layer of a softmax activation function. Model performance was evaluated in the test cohort considering categorical cross-entropy loss (CCEL) and accuracy. Calculated performance was: rCBV (accuracy 83%, CCEL 0.64), T1 (accuracy 77%, CCEL 1.4), FLAIR (accuracy 77%, CCEL 1.98), T2 (accuracy 67%, CCEL 2.41), MPRAGE (accuracy 66%, CCEL 2.55). Lower performance was achieved on ADC maps. We present a GBM-specific deep-learning model for IDH mutation prediction, with a maximal accuracy of 83% on rCBV maps. Highest predictivity achieved on perfusion images possibly reflects the known link between IDH and neoangiogenesis through the hypoxia inducible factor.

Simultaneous multi-slice spin- and gradient-echo dynamic susceptibility-contrast perfusion-weighted MRI of gliomas.

Although combined spin- and gradient-echo (SAGE) dynamic susceptibility-contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T1 -shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi-band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR2 *(t) and ΔR2 (t) curves were derived to calculate dynamic signal-to-noise ratio (dSNR), ΔR2 *- and ΔR2 -based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal-appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal-appearing gray matter were not statistically significant between the two protocols. ΔR2 *- and ΔR2 -rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors.

Synthetic generation of DSC-MRI-derived relative CBV maps from DCE MRI of brain tumors.

Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. Pearson correlation analysis showed that both the tumor rCBV and tumor-to-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.

Assessment of Cerebral Vasodilatory Capacity as Part of Catheter-Based Cerebral Angiography.

Cerebral vasodilatory capacity assessment for risk stratification in patients with extracranial arterial stenosis or occlusion may be useful. We describe a new method that assesses cerebral vasodilatory capacity as part of catheter-based cerebral angiography. We prospectively assessed regional cerebral blood volume (rCBV) in the arterial distribution of interest using a controlled contrast injection in the common carotid or the subclavian arteries. rCBV maps were created using a predefined algorithm based on contrast distribution in the venous phase (voxel size: .466 mm3 ). rCBV maps were acquired again after selective administration of intra-arterial nicardipine (2.0 mg) distal to the stenosis. Two independent observers graded the change in rCBV in 10 predefined anatomical regions within the tributaries of the artery of interest (0 = reduction, 1 = no change, 2 = increase) and total rCBV change scores were summated. Twenty-five patients with internal carotid artery stenosis (n = 18; 0-90% in severity) or extracranial vertebral artery stenosis (n = 7; 0-100% in severity) were assessed. There was an increase in rCBV in a tributary of the artery of interest in 18 of 25 after intra-arterial nicardipine (mean score: 11.98; range 0-19.5). There was no change or decrease in rCBV in 7 of 25 patients. The mean rCBV change score was similar in patients with an assessment of internal carotid artery or vertebral artery distributions (12.2 ± 5.3; 11.4 ± 2.5; P = .68). Selective vasodilatory response to intra-arterial nicardipine in the affected arterial distribution during catheter-based cerebral angiography may provide new data for risk stratification.

Abstract WP22: A New Technique for the Assessment of Cerebral Vasodilatory Capacity as Part of Catheter-Based Cerebral Angiography

Background: Cerebral vasodilatory capacity assessment for risk stratification in patients with extracranial arterial stenosis or occlusion may be useful. We describe a new method that assesses cerebral vasodilatory capacity as part of catheter-based cerebral angiography. Methods: We prospectively assessed regional cerebral blood volume (rCBV) in the arterial distribution of interest using a controlled contrast injection in the common carotid or the subclavian arteries. rCBV maps were created using a predefined algorithm based on contrast distribution in the venous phase (voxel size 0.466 mm 3 ). rCBV maps were acquired again after selective administration of intra-arterial nicardipine (2.5 mg) distal to the stenosis. Two independent observers graded the change in rCBV in 10 predefined anatomical regions within the tributaries of the artery of interest (0=reduction, 1=no change, 2=increase) and total rCBV change scores were summated. The rCBV score values were averaged between the two observers for each patient. Mean arterial pressure was monitored at baseline and at 1 minute intervals post nicardipine administration for 5 minutes. Results: Twenty-five patients with internal carotid artery stenosis (n=18; 0%-90% in severity) or extracranial vertebral artery stenosis (n=7; 0%-100% in severity) were assessed. There was an increase in rCBV in a tributary of the artery of interest in 18 of 25 after intra-arterial nicardipine (mean score 11.98; range 0-19.5). There was no change or decrease in rCBV in 7 of 25 patients. The mean rCBV change score was similar in patients with assessment of internal carotid artery or vertebral artery distributions (12.2 ± 5.3; 11.4 ± 2.5; p=0.68 by ANOVA). There was an average (±SD) reduction of mean arterial pressure of 14mmHg ± 7.5 after intra-arterial nicardipine. There was no correlation between the magnitude of mean arterial pressure reduction post nicardipine (regression coefficient -0.13; p=0.38) or between the severity of stenosis (regression coefficient -0.04; p=0.29) and rCBV change scores. Conclusions: We describe a new technique for selective assessment of cerebral vasodilatory response in the affected arterial distribution during catheter-based cerebral angiography.

A New Technique for the Assessment of Cerebral Vasodilatory Capacity as Part of Catheter-Based Cerebral Angiography

Previous studies have demonstrated the value of cerebral vasodilatory capacity assessment for risk stratification in patients with extracranial arterial stenosis or occlusion. We describe a new method that assesses cerebral vasodilatory capacity as part of catheter-based cerebral angiography. We assessed regional cerebral blood volume (rCBV) in the arterial distribution of interest using a controlled contrast injection through a diagnostic catheter placed in the common carotid or the subclavian artery. rCBV maps were created using predefined algorithm based on contrast distribution in the venous phase (voxel size 0.466 mm3) into high, intermediate, low, and no detectable rCBV regions. rCBV maps were acquired again after the administration of intra-arterial nicardipine (1.5-2.5 mg), and percentage increases of the area of various grades of rCBV were calculated. Three patients with internal carotid artery stenosis (32% - 64% in severity) and 1 patient with extracranial vertebral artery stenosis (46% in severity) were assessed. There was a variable but consistent increase in the area of high rCBV in the ipsilateral hemisphere in 3 patients with internal carotid artery flow (5.5%-24.5%) and the cerebellum (9.6%) in 1 patient with vertebral artery flow assessments. The increase in high rCBV was most prominent in the patient who received 2.5 mg (24.5%) and least prominent in a patient who received 1.5 mg (5.5%) of intra-arterial nicardipine. There was a concurrent reduction in areas of intermediate and low rCBV (shift) in 3 patients, and there was an increase in all areas of rCBV grades (addition) in 1 patient. Selective assessment of cerebral vasodilatory response in the affected arterial distribution is feasible during catheter-based cerebral angiography.

Visual inspection of MR relative cerebral blood volume maps has limited value for distinguishing progression from pseudoprogression in glioblastoma multiforme patients.

We examined whether visual interpretation of relative cerebral blood volume (rCBV) color maps made with dynamic susceptibility-weighted perfusion MRI can reliably distinguish progressive disease (PD) from pseudoprogression (PsPD) in glioblastoma patients during treatment with temozolomide chemoradiation. Magnetic resonance (MR) perfusion-weighted images were evaluated based on visual inspection of rCBV maps. Sensitivity and specificity were calculated to assess if rCBV can reliably differentiate between PD and PsPD, during standard chemoradiation therapy. Evaluation of dynamic susceptibility-weighted contrast-enhanced perfusion MRI by visual interpretation of rCBV maps did not differentiate PD from PsPD (sensitivity = 72%; specificity = 23%). Furthermore, the interpretation of the rCBV maps had no prognostic value regarding survival. Qualitative rCBV-based dynamic susceptibility-weighted contrast-enhanced perfusion MRI does not reliably differentiate PD from PsPD, and is not prognostic for survival in glioblastoma multiforme patients during treatment with temozolomide chemoradiation.

FMISO-PET-derived brain oxygen tension maps: application to glioblastoma and less aggressive gliomas

Quantitative imaging modalities for the analysis of hypoxia in brain tumors are lacking. The objective of this study was to generate absolute maps of tissue ptO2 from [18F]-FMISO images in glioblastoma and less aggressive glioma patients in order to quantitatively assess tumor hypoxia. An ancillary objective was to compare estimated ptO2 values to other biomarkers: perfusion weighted imaging (PWI) and tumor metabolism obtained from 1H-MR mono-voxel spectroscopy (MRS). Ten patients with glioblastoma (GBM) and three patients with less aggressive glioma (nGBM) were enrolled. All patients had [18F]-FMISO and multiparametric MRI (anatomic, PWI, MRS) scans. A non-linear regression was performed to generate ptO2 maps based on normal appearing gray (NAGM) and white matter (NAWM) for each patient. As expected, a marked [18F]-FMISO uptake was observed in GBM patients. The ptO2 based on patient specific calculations was notably low in this group (4.8 ± 1.9 mmHg, p < 0.001) compared to all other groups (nGBM, NAGM and NAWM). The rCBV was increased in GBM (1.4 ± 0.2 when compared to nGBM tumors 0.8 ± 0.4). Lactate (and lipid) concentration increased in GBM (27.8 ± 13.8%) relative to nGBM (p < 0.01). Linear, nonlinear and ROC curve analyses between ptO2 maps, PWI-derived rCBV maps and MRS-derived lipid and lactate concentration strengthens the robustness of our approaches.

Assessment of tumor hypoxia in BEV resistant GBM using FMISO 18F-PET and MRI.

2045 Background: Glioblastoma (GBM) is the most common malignant brain tumor in adults, and is characterized by poor survival and marked resistance to treatment. Hypoxic volume is directly correlated with poor outcome in GBM, with structural and functional tumor vasculature changes regarded as a primary driver of tumor hypoxia. As part of an ongoing clinical trial with a hypoxia activated prodrug, we sought to explore the correlation between abnormal tumor vasculature and hypoxia in bevacizumab (BEV) resistant GBM. Methods: MRI and 18F-FMISO PET scans were acquired at study entry. The MRI protocols include standard anatomical sequences as well as Dynamic Susceptibility Contrast (DSC/perfusion) imaging. Enhancing tumor ROIs were determined from Delta T1 maps, non-enhancing tumor ROIs were obtained from FLAIR images, ratio between enhancing and non-enhancing volumes were calculated, values from standardized rCBV maps were extracted from corresponding enhancing ROIs. Decay correction was applied to18F-FMISO images and converted to SUV units. After registration to MR images, cerebellar regions were used as surrogates for blood activity. The FMISO images were then normalized to generate tissue to blood ratio (TB). A threshold of TB &gt; 1.2 was used in discriminating the hypoxia volume (HV). Correlation between parameters was assessed using Pearson correlation. Results: 7 patients from University of Texas Health Science center and 7 patients from Dana-Farber Cancer Institute had evaluable MR and PET imaging. We compared MRI parameters (enhancing and non-enhancing tumor volumes, srCBV) with hypoxia (HV and maxSUV). There was a positive correlation between HV and enhancing volume (R = 0.732, p = 0.0029) as well as between HV and ratio (R = 0.644, p = 0.013. The correlation between other pairs were not statistically significant (HV vs srCBV: p = 0.862, T1 vs maxSUV p = 0.492, srCBV vs maxSUV: p = 0.393, ratio vs maxSUV = 0.178). Conclusions: The hypoxic volume following bevacizumab failure correlates with both the volume of enhancement and the fraction of enhancement within the mass. The clinical implications of this is being assessed in an ongoing phase 2 study. Clinical trial information: NCT02342379.

12. Analysis of the impact of rCBV map threshold to predict tumor recurrence in high-grade gliomas

Introduction Patients suffering from high-grade gliomas currently have a median survival time of 14 months despite treatment. Our purpose was to investigate whether MR perfusion and relative Cerebral Blood Volume (rCBV) maps could help to predict tumor recurrence areas and improve treatment outcome. This study investigates the impact of rCBV map thresholds on the ability of MR perfusion to predict tumor recurrence. Methods This retrospective study included 17 patients suffering from high grade gliomas who received standard chemo-radiation (30 × 2 Gy/fraction, Temodal). Subjects underwent pre-treatment CT, gadolinium-enhanced T1-weighted, T2 FLAIR acquisitions and a DSC-MR scan. rCBV maps were calculated with GE READE View Advantage Workstation and normalized to the contralateral normal white matter perfusion. The PLANET software (DOSIsoft) was used to register MR images to the CT. A senior radiologist and a senior radiotherapist delineated conventionally GTV on anatomical MR images. PTV were defined by a physicist. Thresholds t of 1.5–2.5 were applied to the normalized rCBV maps to define hyper-perfused volumes ( V perf , t ) . Follow-up anatomical MR images were used to localize recurrence areas (GTV′). Correlations between all volumes were analyzed using six indexes. I 1 , t was the percentage of V perf , t not included in the GTV. I 2 , t , I 3 and I4 were respectively the percentages of GTV′ included in V perf , t , GTV, and PTV. I 5 , t was the percentage of V perf , t included in GTV′. I 6 , t was the percentage of V perf , t not included in the GTV which was predictive of tumor recurrence outside GTV. Results Index evolution when t rises is slow and no obvious break in slope suggests an optimal threshold. Whatever t (1) I 1 , t is higher than 20% for 14 patients, suggesting that V perf , t and GTV as defined using anatomical images are distinct volumes (2) I 2 , t shows that the proportion of relapse volumes characterized by high rCBV is between 2% and 63% (3) I 5 , t indicates that hyper-perfused areas will not necessary lead to relapse ( 1 % I 5 , t 98 % ) (4) I 6 , t is lower than 5% for 8 patients and greater than 40% for 5 patients: perfusion may help to predict relapse outside GTV in about half of the cases. Based on I 3 value analysis, two groups can be distinguished: The first (9 patients) shows a high overlap between GTV and GTV′( I 3 > 80 % ) while this overlap is moderate in the second ( 30 % I 3 50 % ). I 4 is almost always equal to 100%: recurrence occurs inside the PTV. Conclusions Recurrence areas are always located in the PTV: an improvement of treatment planning will consist in defining boost areas rather than modifying the GTV. The impact of the threshold used to define hyper-perfused area is low. Although 17 cases only were studied, our results suggest that MR perfusion is neither specific nor sensible enough for defining by itself recurrence (hence potential boost) areas. Multi-modality imaging such as PET-MR might help identify tissues with a high risk of recurrence.

Interobserver variability in the radiological assessment of magnetic resonance imaging (MRI) including perfusion MRI in glioblastoma multiforme.

Conventional magnetic resonance imaging (MRI) has limited value for differentiation of true tumor progression and pseudoprogression in treated glioblastoma multiforme (GBM). Perfusion weighted imaging (PWI) may be helpful in the differentiation of these two phenomena. Here interobserver variability in routine radiological evaluation of GBM patients is assessed using MRI, including PWI. Three experienced neuroradiologists evaluated MR scans of 28 GBM patients during temozolomide chemoradiotherapy at three time points: preoperative (MR1) and postoperative (MR2) MR scan and the follow-up MR scan after three cycles of adjuvant temozolomide (MR3). Tumor size was measured both on T1 post-contrast and T2 weighted images according to the Response Assessment in Neuro-Oncology criteria. PW images of MR3 were evaluated by visual inspection of relative cerebral blood volume (rCBV) color maps and by quantitative rCBV measurements of enhancing areas with highest rCBV. Image interpretability of PW images was also scored. Finally, the neuroradiologists gave a conclusion on tumor status, based on the interpretation of both T1 and T2 weighted images (MR1, MR2 and MR3) in combination with PWI (MR3). Interobserver agreement on visual interpretation of rCBV maps was good (κ = 0.63) but poor on quantitative rCBV measurements and on interpretability of perfusion images (intraclass correlation coefficient 0.37 and κ = 0.23, respectively). Interobserver agreement on the overall conclusion of tumor status was moderate (κ = 0.48). Interobserver agreement on the visual interpretation of PWI color maps was good. However, overall interpretation of MR scans (using both conventional and PW images) showed considerable interobserver variability. Therefore, caution should be applied when interpreting MRI results during chemoradiation therapy.