Improved Leakage Correction for Single-Echo Dynamic Susceptibility Contrast Perfusion MRI Estimates of Relative Cerebral Blood Volume in High-Grade Gliomas by Accounting for Bidirectional Contrast Agent Exchange

Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma

BACKGROUND AND PURPOSE

Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in examination time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient-echo-EPI sequence for T2*-sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors.

MATERIALS AND METHODS

Twenty-four consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, resting-sate functional MRI (rs-fMRI), and neurocognitive assessment. Voxelwise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the preprocessing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs, Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and nonimpaired patients.

RESULTS

Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689 ± 0.118 (group/patient), 0.973/0.730 ± 0.124, and 0.935/0.665 ± 0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode (P = .97) or language networks (P = .30), but there was a difference in motor networks (P = .02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (sensitivity = 84.6%, specificity = 63.6%, receiver operating characteristic area under the curve (AUC) = 0.7762 ± 0.0954 (standard error), P = .0221) and performance was not significantly different from full rs-fMRI predictions (AUC = 0.8881 ± 0.0733 (standard error), P = .0013, P = .29 compared with pseudo-rs-fMRI).

CONCLUSIONS

DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI

OBJECTIVE

To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection.

MATERIALS AND METHODS

Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression).

RESULTS

In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%.

CONCLUSIONS

Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection.

CLINICAL RELEVANCE STATEMENT

Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture.

KEY POINTS

• Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.

Dynamic Susceptibility Contrast Perfusion, Part 2: Deployment With and Without Contrast Leakage Present

A thorough description of perfusion analysis and basic DSC MR acquisition concepts has been described in the companion article to this article, which the interested reader may also find useful. DSC MR imaging requires an MR imaging pulse sequence that is sensitive to magnetic susceptibility changes to register the contrast concentration changes when GBCA passes through the capillary bed. Any pulse sequence that has T2∗-weighting can be used to pick up these changes, provided that the sequence is fast enough to acquire an image of that slice of tissue at least every 1 to 2 second.

Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration

Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.

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

INTRODUCTION

The 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 METHODS

rCBV 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.

RESULTS

41 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.

DISCUSSION

We 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.

Multi-nuclear sodium, diffusion, and perfusion MRI in human gliomas

PURPOSE

There is limited knowledge about the associations between sodium and proton MRI measurements in brain tumors. The purpose of this study was to quantify intra- and intertumoral correlations between sodium, diffusion, and perfusion MRI in human gliomas.

METHODS

Twenty glioma patients were prospectively studied on a 3T MRI system with multinuclear capabilities. Three mutually exclusive tumor volumes of interest (VOIs) were segmented: contrast-enhancing tumor (CET), T2/FLAIR hyperintense non-enhancing tumor (NET), and necrosis. Median and voxel-wise associations between apparent diffusion coefficient (ADC), normalized relative cerebral blood volume (nrCBV), and normalized sodium measurements were quantified for each VOI.

RESULTS

Both relative sodium concentration and ADC were significantly higher in areas of necrosis compared to NET (P = 0.003 and P = 0.008, respectively) and CET (P = 0.02 and P = 0.02). Sodium concentration was higher in CET compared to NET (P = 0.04). Sodium and ADC were higher in treated compared to treatment-naïve gliomas within NET (P = 0.006 and P = 0.01, respectively), and ADC was elevated in CET (P = 0.03). Median ADC and sodium concentration were positively correlated across patients in NET (r = 0.77, P < 0.0001) and CET (r = 0.84, P < 0.0001), but not in areas of necrosis (r = 0.45, P = 0.12). Median nrCBV and sodium concentration were negatively correlated across patients in areas of NET (r=-0.63, P = 0.003). Similar associations were observed when examining voxel-wise correlations within VOIs.

CONCLUSION

Sodium MRI is positively correlated with proton diffusion MRI measurements in gliomas, likely reflecting extracellular water. Unique areas of multinuclear MRI contrast may be useful in future studies to understand the chemistry of the tumor microenvironment.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Evaluation of the Diagnostic Performance of F18-Fluorodeoxyglucose-Positron Emission Tomography, Dynamic Susceptibility Contrast Perfusion, and Apparent Diffusion Coefficient in Differentiation between Recurrence of a High-grade Glioma and Radiation Necrosis

Background

Differentiation between recurrence of brain tumor and radiation necrosis remains a challenge in current neuro-oncology practice despite recent advances in both radiological and nuclear medicine techniques.

Purpose

The purpose of this study was to compare the diagnostic performance of dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging, and F18-fluorodeoxyglucose-positron emission tomography (F18-FDG-PET) in the differentiation between the recurrence of a high-grade glioma and radiation necrosis.

Materials and Methods

Patients with a diagnosis of high-grade glioma (WHO Grades III and IV) who had undergone surgical resection of the tumor followed by radiotherapy with or without chemotherapy were included in the study. DSC perfusion, diffusion-weighted MRI, and PET scan were acquired on a hybrid PET/MRI scanner. For each lesion, early and delayed tumor-to-brain ratio (TBR), early and delayed maximum standardized uptake value (SUVmax), normalized ADC ratio, and normalized relative cerebral blood volume (rCBV) ratio were calculated and the pattern of lesional enhancement was noted. The diagnosis was finalized with either histopathological examination or the characteristics on follow-up imaging. The statistical analysis using the receiver operator characteristic curves was done to determine the diagnostic performance of DSC perfusion, 18-F FDG-PET, and ADC in differentiation between tumor recurrence and radiation necrosis.

Results

Fifty patients were included in the final analysis, 32 of them being men (64%). A cutoff value of early TBR >0.8 (sensitivity of 100% and specificity of 80%), delayed TBR >0.93 (sensitivity of 92.3% and specificity of 80%), early SUVmax >10.2 (sensitivity of 76.9% and specificity of 80%), delayed SUVmax >13.2 (sensitivity of 61.54% and specificity of 100%), normalized rCBV ratio >1.21 (sensitivity of 100% and specificity of 60%), normalized ADC ratio >1.66 (sensitivity of 38.5% and specificity of 80%), and Grade 3 enhancement (sensitivity of 100% and specificity of 60%) were found to differentiate recurrence from radiation necrosis. Early TBR had the highest accuracy (94.44%), while ADC ratio had the lowest accuracy (50%). A combination of early TBR (cutoff value of 0.8), late TBR (cutoff value of 0.93), and rCBV ratio (cutoff value of 1.21) showed a sensitivity of 100%, specificity of 92.3%, positive predictive value of 88.9%, negative predictive value of 93.7%, and an accuracy of 96.6% in discrimination between radiation necrosis and recurrence of tumor.

Conclusion

F18-FDG-PET and DSC perfusion can reliably differentiate tumor recurrence from radiation necrosis, with early TBR showing the highest accuracy. ADC demonstrates a low sensitivity, specificity, and accuracy in differentiating radiation necrosis from recurrence. A combination of early TBR, delayed TBR, and rCBV may be more useful in discrimination between radiation necrosis and recurrence of glioma, with this combination showing a better diagnostic performance than individual parameters or any other combination of parameters.

A multi-reader comparison of normal-appearing white matter normalization techniques for perfusion and diffusion MRI in brain tumors

PURPOSE

There remains no consensus normal-appearing white matter (NAWM) normalization method to compute normalized relative cerebral blood volume (nrCBV) and apparent diffusion coefficient (nADC) in brain tumors. This reader study explored nrCBV and nADC differences using different NAWM normalization methods.

METHODS

Thirty-five newly diagnosed glioma patients were studied. For each patient, two readers created four NAWM regions of interests: (1) a single plane in the centrum semiovale (CSOp), (2) 3 spheres in the centrum semiovale (CSOs), (3) a single plane in the slice of the tumor center (TUMp), and (4) 3 spheres in the slice of the tumor center (TUMs). Readers repeated NAWM segmentations 1 month later. Differences in nrCBV and nADC of the FLAIR hyperintense tumor, inter-/intra-reader variability, and time to segment NAWM were assessed. As a validation step, the diagnostic performance of each method for IDH-status prediction was evaluated.

RESULTS

Both readers obtained significantly different nrCBV (P < .001), nADC (P < .001), and time to segment NAWM (P < .001) between the four normalization methods. nrCBV and nADC were significantly different between CSO and TUM methods, but not between planar and spherical methods in the same NAWM region. Broadly, CSO methods were quicker than TUM methods, and spherical methods were quicker than planar methods. For all normalization techniques, inter-reader reproducibility and intra-reader repeatability were excellent (intraclass correlation coefficient > 0.9), and the IDH-status predictive performance remained similar.

CONCLUSION

The selected NAWM region significantly impacts nrCBV and nADC values. CSO methods, particularly CSOs, may be preferred because of time reduction, similar reader variability, and similar diagnostic performance compared to TUM methods.

Early volumetric, perfusion, and diffusion MRI changes after mutant isocitrate dehydrogenase (IDH) inhibitor treatment in IDH1-mutant gliomas

Background

Inhibition of the isocitrate dehydrogenase (IDH)-mutant enzyme is a novel therapeutic target in IDH-mutant gliomas. Imaging biomarkers of IDH inhibitor treatment efficacy in human IDH-mutant gliomas are largely unknown. This study investigated early volumetric, perfusion, and diffusion MRI changes in IDH1-mutant gliomas during IDH inhibitor treatment.

Methods

Twenty-nine IDH1-mutant glioma patients who received IDH inhibitor and obtained anatomical, perfusion, and diffusion MRI pretreatment at 3-6 weeks (n = 23) and/or 2-4 months (n = 14) of treatment were retrospectively studied. Normalized relative cerebral blood volume (nrCBV), apparent diffusion coefficient (ADC), and fluid-attenuated inversion recovery (FLAIR) hyperintensity volume were analyzed.

Results

After 3-6 weeks of treatment, nrCBV was significantly increased (P = .004; mean %change = 24.15%) but not FLAIR volume (P = .23; mean %change = 11.05%) or ADC (P = .52; mean %change = -1.77%). Associations between shorter progression-free survival (PFS) with posttreatment nrCBV > 1.55 (P = .05; median PFS, 240 vs 55 days) and increased FLAIR volume > 4 cm³ (P = .06; 227 vs 29 days) trended toward significance. After 2-4 months, nrCBV, FLAIR volume, and ADC were not significantly different from baseline, but an nrCBV increase > 0% (P = .002; 1121 vs 257 days), posttreatment nrCBV > 1.8 (P = .01; 1121 vs. 270 days), posttreatment ADC < 1.15 μm²/ms (P = .02; 421 vs 215 days), median nrCBV/ADC ratio increase > 0% (P = .02; 1121 vs 270 days), and FLAIR volume change > 4 cm³ (P = .03; 421 vs 226.5 days) were associated with shorter PFS.

Conclusions

Increased nrCBV at 3-6 weeks of treatment may reflect transient therapeutic and/or tumor growth changes, whereas nrCBV, ADC, and FLAIR volume changes occurring at 2-4 months of treatment may more accurately reflect antitumor response to IDH inhibition.

Paradoxical Association Between Relative Cerebral Blood Volume Dynamics Following Chemoradiation and Increased Progression-Free Survival in Newly Diagnosed IDH Wild-Type MGMT Promoter Methylated Glioblastoma With Measurable Disease

Background and Purpose

While relative cerebral blood volume (rCBV) may be diagnostic and prognostic for survival in glioblastoma (GBM), changes in rCBV during chemoradiation in the subset of newly diagnosed GBM with subtotal resection and the impact of MGMT promoter methylation status on survival have not been explored. This study aimed to investigate the association between rCBV response, MGMT methylation status, and progression-free (PFS) and overall survival (OS) in newly diagnosed GBM with measurable enhancing lesions.

Methods

1,153 newly diagnosed IDH wild-type GBM patients were screened and 53 patients (4.6%) had measurable post-surgical tumor (>1mL). rCBV was measured before and after patients underwent chemoradiation. Patients with a decrease in rCBV >10% were considered rCBV Responders, while patients with an increase or a decrease in rCBV <10% were considered rCBV Non-Responders. The association between change in enhancing tumor volume, change in rCBV, MGMT promotor methylation status, and PFS or OS were explored.

Results

A decrease in tumor volume following chemoradiation trended towards longer OS (p=0.12; median OS=26.8 vs. 16.3 months). Paradoxically, rCBV Non-Responders had a significantly improved PFS compared to Responders (p=0.047; median PFS=9.6 vs. 7.2 months). MGMT methylated rCBV Non-Responders exhibited a significantly longer PFS compared to MGMT unmethylated rCBV Non-Responders (p<0.001; median PFS=0.5 vs. 7.1 months), and MGMT methylated rCBV Non-Responders trended towards longer PFS compared to methylated rCBV Responders (p=0.089; median PFS=20.5 vs. 13.8 months).

Conclusions

This preliminary report demonstrates that in newly diagnosed IDH wild-type GBM with measurable enhancing disease after surgery (5% of patients), an enigmatic non-response in rCBV was associated with longer PFS, particularly in MGMT methylated patients.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Towards controlled drug delivery in brain tumors with microbubble-enhanced focused ultrasound

Brain tumors are particularly challenging malignancies, due to their location in a structurally and functionally distinct part of the human body - the central nervous system (CNS). The CNS is separated and protected by a unique system of brain and blood vessel cells which together prevent most bloodborne therapeutics from entering the brain tumor microenvironment (TME). Recently, great strides have been made through microbubble (MB) ultrasound contrast agents in conjunction with ultrasound energy to locally increase the permeability of brain vessels and modulate the brain TME. As we elaborate in this review, this physical method can effectively deliver a wide range of anticancer agents, including chemotherapeutics, antibodies, and nanoparticle drug conjugates across a range of preclinical brain tumors, including high grade glioma (glioblastoma), diffuse intrinsic pontine gliomas, and brain metastasis. Moreover, recent evidence suggests that this technology can promote the effective delivery of novel immunotherapeutic agents, including immune check-point inhibitors and chimeric antigen receptor T cells, among others. With early clinical studies demonstrating safety, and several Phase I/II trials testing the preclinical findings underway, this technology is making firm steps towards shaping the future treatments of primary and metastatic brain cancer. By elaborating on its key components, including ultrasound systems and MB technology, along with methods for closed-loop spatial and temporal control of MB activity, we highlight how this technology can be tuned to enable new, personalized treatment strategies for primary brain malignancies and brain metastases.

Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations

Alterations to the cerebral microcirculation have been recognized to play a crucial role in the development of neurodegenerative disorders. However, the exact role of the microvascular alterations in the pathophysiological mechanisms often remains poorly understood. The early detection of changes in microcirculation and cerebral blood flow (CBF) can be used to get a better understanding of underlying disease mechanisms. This could be an important step towards the development of new treatment approaches. Animal models allow for the study of the disease mechanism at several stages of development, before the onset of clinical symptoms, and the verification with invasive imaging techniques. Specifically, pre-clinical magnetic resonance imaging (MRI) is an important tool for the development and validation of MRI sequences under clinically relevant conditions. This article reviews MRI strategies providing indirect non-invasive measurements of microvascular changes in the rodent brain that can be used for early detection and characterization of neurodegenerative disorders. The perfusion MRI techniques: Dynamic Contrast Enhanced (DCE), Dynamic Susceptibility Contrast Enhanced (DSC) and Arterial Spin Labeling (ASL), will be discussed, followed by less established imaging strategies used to analyze the cerebral microcirculation: Intravoxel Incoherent Motion (IVIM), Vascular Space Occupancy (VASO), Steady-State Susceptibility Contrast (SSC), Vessel size imaging, SAGE-based DSC, Phase Contrast Flow (PC) Quantitative Susceptibility Mapping (QSM) and quantitative Blood-Oxygenation-Level-Dependent (qBOLD). We will emphasize the advantages and limitations of each strategy, in particular on applications for high-field MRI in the rodent's brain.

Effect of Applying Leakage Correction on rCBV Measurement Derived From DSC-MRI in Enhancing and Nonenhancing Glioma

Purpose

Relative cerebral blood volume (rCBV) is the most widely used parameter derived from DSC perfusion MR imaging for predicting brain tumor aggressiveness. However, accurate rCBV estimation is challenging in enhancing glioma, because of contrast agent extravasation through a disrupted blood-brain barrier (BBB), and even for nonenhancing glioma with an intact BBB, due to an elevated steady-state contrast agent concentration in the vasculature after first passage. In this study a thorough investigation of the effects of two different leakage correction algorithms on rCBV estimation for enhancing and nonenhancing tumors was conducted.

Methods

Two datasets were used retrospectively in this study: 1. A publicly available TCIA dataset (49 patients with 35 enhancing and 14 nonenhancing glioma); 2. A dataset acquired clinically at Erasmus MC (EMC, Rotterdam, NL) (47 patients with 20 enhancing and 27 nonenhancing glial brain lesions). The leakage correction algorithms investigated in this study were: a unidirectional model-based algorithm with flux of contrast agent from the intra- to the extravascular extracellular space (EES); and a bidirectional model-based algorithm additionally including flow from EES to the intravascular space.

Results

In enhancing glioma, the estimated average contrast-enhanced tumor rCBV significantly (Bonferroni corrected Wilcoxon Signed Rank Test, p < 0.05) decreased across the patients when applying unidirectional and bidirectional correction: 4.00 ± 2.11 (uncorrected), 3.19 ± 1.65 (unidirectional), and 2.91 ± 1.55 (bidirectional) in TCIA dataset and 2.51 ± 1.3 (uncorrected), 1.72 ± 0.84 (unidirectional), and 1.59 ± 0.9 (bidirectional) in EMC dataset. In nonenhancing glioma, a significant but smaller difference in observed rCBV was found after application of both correction methods used in this study: 1.42 ± 0.60 (uncorrected), 1.28 ± 0.46 (unidirectional), and 1.24 ± 0.37 (bidirectional) in TCIA dataset and 0.91 ± 0.49 (uncorrected), 0.77 ± 0.37 (unidirectional), and 0.67 ± 0.34 (bidirectional) in EMC dataset.

Conclusion

Both leakage correction algorithms were found to change rCBV estimation with BBB disruption in enhancing glioma, and to a lesser degree in nonenhancing glioma. Stronger effects were found for bidirectional leakage correction than for unidirectional leakage correction.

Inflow-based vascular-space-occupancy (iVASO) might potentially predict IDH mutation status and tumor grade in diffuse cerebral gliomas

PURPOSE

The aim of the study is to assess the diagnostic performance of inflow-based vascular-space-occupancy (iVASO) MR imaging for differentiating glioblastomas (grade IV, GBM) and lower-grade diffuse gliomas (grade II and III, LGG) and its potential to predict IDH mutation status.

METHODS

One hundred and two patients with diffuse cerebral glioma (56 males; median age, 43.5 years) underwent iVASO and dynamic susceptibility contrast (DSC) MR imaging. The iVASO-derived arteriolar cerebral blood volume (CBVa), relative CBVa (rCBVa), and the DSC-derived relative cerebral blood volume (rCBV) were obtained, and these measurements were compared between the GBM group (n = 43) and the LGG group (n = 59) and between the IDH-mutation group (n = 54) and the IDH-wild group (n = 48).

RESULTS

Significant correlation was observed between rCBV and CBVa (P < 0.001) or rCBVa (P < 0.001). Both CBVa (P < 0.001) and rCBVa (P < 0.001) were higher in the GBM group. Both CBVa (P < 0.001) and rCBVa (P < 0.001) were lower in the IDH-mutation group compared to the IDH-wild group. Receiver operating characteristic analyses showed the area under curve (AUC) of 0.95 with CBVa and 0.97 with rCBVa in differentiating GBM from LGG. The AUCs were 0.82 and 0.85 for CBVa and rCBVa in predicting IDH gene status, respectively, which were lower than that of rCBV (AUC = 0.90). Combined rCBV and rCBVa significantly improved the diagnostic performance (AUC = 0.95).

CONCLUSIONS

iVASO MR imaging has the potential to predict IDH mutation and grade in glioma.

Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network

BACKGROUND

The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI.

METHODS

Four hundred sixty-three patients with gliomas who underwent preoperative MRI were enrolled in the study. All the patients had immunohistopathologic diagnoses of either IDH-wildtype or IDH-mutant gliomas. Tumor subregions were segmented using a convolutional neural network followed by manual correction. DSC perfusion MRI was performed to obtain T2* susceptibility signal intensity-time curves from each subregion of the tumors: enhancing tumor, non-enhancing tumor, peritumoral edema, and whole tumor. These, with arterial input functions, were fed into a neural network as multidimensional inputs. A convolutional long short-term memory model with an attention mechanism was developed to predict IDH genotypes. Receiver operating characteristics analysis was performed to evaluate the model.

RESULTS

The IDH genotype predictions had an accuracy, sensitivity, and specificity of 92.8%, 92.6%, and 93.1%, respectively, in the validation set (area under the curve [AUC], 0.98; 95% confidence interval [CI], 0.969-0.991) and 91.7%, 92.1%, and 91.5%, respectively, in the test set (AUC, 0.95; 95% CI, 0.898-0.982). In temporal feature analysis, T2* susceptibility signal intensity-time curves obtained from DSC perfusion MRI with attention weights demonstrated high attention on the combination of the end of the pre-contrast baseline, up/downslopes of signal drops, and/or post-bolus plateaus for the curves used to predict IDH genotype.

CONCLUSIONS

We developed an explainable recurrent neural network model based on DSC perfusion MRI to predict IDH genotypes in gliomas.

Relative oxygen extraction fraction (rOEF) MR imaging reveals higher hypoxia in human epidermal growth factor receptor (EGFR) amplified compared with non-amplified gliomas

PURPOSE

Epidermal growth factor receptor (EGFR) amplification promotes gliomagenesis and is linked to lack of oxygen within the tumor microenvironment. Using hypoxia-sensitive spin-and-gradient echo echo-planar imaging and perfusion MRI, we investigated the influence of EGFR amplification on tissue oxygen availability and utilization in human gliomas.

METHODS

This study included 72 histologically confirmed EGFR-amplified and non-amplified glioma patients. Reversible transverse relaxation rate (R₂'), relative cerebral blood volume (rCBV), and relative oxygen extraction fraction (rOEF) were calculated for the contrast-enhancing and non-enhancing tumor regions. Using Student t test or Wilcoxon rank-sum test, median R₂', rCBV, and rOEF were compared between EGFR-amplified and non-amplified gliomas. ROC analysis was performed to assess the ability of imaging characteristics to discriminate EGFR amplification status. Overall survival (OS) was determined using univariate and multivariate cox models. Kaplan-Meier survival curves were plotted and compared using the log-rank test.

RESULTS

EGFR amplified gliomas exhibited significantly higher median R₂' and rOEF than non-amplified gliomas. ROC analysis suggested that R₂' (AUC = 0.7190; P = 0.0048) and rOEF (AUC = 0.6959; P = 0.0156) could separate EGFR status. Patients with EGFR-amplified gliomas had a significantly shorter OS than non-amplified patients. Univariate cox regression analysis determined both R₂' and rOEF significantly influence OS. No significant difference was observed in rCBV between patient cohorts nor was rCBV found to be an effective differentiator of EGFR status.

CONCLUSION

Imaging of tumor oxygen characteristics revealed EGFR-amplified gliomas to be more hypoxic and contribute to shorter patient survival than EGFR non-amplified gliomas.

Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas

Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI methodology has not been standardized, hindering its utilization for response assessment in multicenter trials. Recently, the DSC-MRI Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition issued an updated consensus DSC-MRI protocol compatible with the standardized brain tumor imaging protocol (BTIP) for high-grade gliomas that is increasingly used in the clinical setting and is the default MRI protocol for the National Clinical Trials Network. After reviewing the basis for controversy over DSC-MRI protocols, this paper provides evidence-based best practices for clinical DSC-MRI as determined by the Committee, including pulse sequence (gradient echo vs spin echo), BTIP-compliant contrast agent dosing (preload and bolus), flip angle (FA), echo time (TE), and post-processing leakage correction. In summary, full-dose preload, full-dose bolus dosing using intermediate (60°) FA and field strength-dependent TE (40-50 ms at 1.5 T, 20-35 ms at 3 T) provides overall best accuracy and precision for cerebral blood volume estimates. When single-dose contrast agent usage is desired, no-preload, full-dose bolus dosing using low FA (30°) and field strength-dependent TE provides excellent performance, with reduced contrast agent usage and elimination of potential systematic errors introduced by variations in preload dose and incubation time.

Diagnostic Value of Perfusion MR Imaging as a Potential Ancillary Test for Brain Death

OBJECTIVE

The purpose of this study is to determine the potential role of dynamic susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging in diagnosing brain death.

MATERIALS AND METHODS

The study population was composed of 61 subjects (the Glasgow Coma Scale [GCS] score was 3 for all subjects), and 26 subjects were assigned to the control group (GCS scores between 4 and 6). At least four regions of interest (ROIs) from different anatomical regions were measured, the mean transit time (MTT), cerebral blood flow (CBF), and signal intensity time-to-course graphic were calculated. A second neurological examination (including an apnea test) was accepted as the gold standard method for the diagnosis of brain death.

RESULTS

DSC-MR perfusion imaging diagnosed brain death with a specificity of 100% (61/61) and a sensitivity of 86.8% (53/61). A cut-off value of maximum 3.5% decrease in the signal intensity time-to-course graphic was calculated by the Youden's index and established for the to differentiate brain death from other conditions.

CONCLUSION

DSC-MR perfusion imaging is a promising tool that may be used as a reliable add-on confirmatory diagnostic test for the brain death.

Validation of combined use of DWI and percentage signal recovery-optimized protocol of DSC-MRI in differentiation of high-grade glioma, metastasis, and lymphoma

PURPOSE

With conventional MRI, it is often difficult to effectively differentiate between contrast-enhancing brain tumors, including primary central nervous system lymphoma (PCNSL), high-grade glioma (HGG), and metastasis. This study aimed to assess the discrimination ability of the parameters obtained from DWI and the percentage signal recovery- (PSR-) optimized protocol of DSC-MRI between these three tumor types at an initial step.

METHODS

DSC-MRI using a PSR-optimized protocol (TR/TE = 1500/30 ms, flip angle = 90°, no preload) and DWI of 99 solitary enhancing tumors (60 HGGs, 24 metastases, 15 PCNSLs) were retrospectively assessed before treatment. rCBV, PSR, ADC in the tumor core and rCBV, and ADC in peritumoral edema were measured. The differences were evaluated using one-way ANOVA, and the diagnostic performance was evaluated using ROC curve analysis.

RESULTS

PSR in the tumor core showed the best discriminating performance in differentiating these three tumor types with AUC values of 0.979 for PCNSL vs. others and 0.947 for HGG vs. metastasis. The ADC was only helpful in the tumor core and distinguishing PCNSLs from others (AUC = 0.897).

CONCLUSION

Different from CBV-optimized protocols (preload, intermediate FA), PSR derived from the PSR-optimized protocol seems to be the most important parameter in the differentiation of HGGs, metastases, and PCNSLs at initial diagnosis. This property makes PSR remarkable and carries the need for comprehensive DSC-MRI protocols, which provides PSR sensitivity and CBV accuracy together, such as the preload use of the PSR-optimized protocol before the CBV-optimized protocol.

Multiparametric MR-PET Imaging Predicts Pharmacokinetics and Clinical Response to GDC-0084 in Patients with Recurrent High-Grade Glioma

PURPOSE

GDC-0084 is an oral, brain-penetrant small-molecule inhibitor of PI3K and mTOR. Because these two targets alter tumor vascularity and metabolism, respectively, we hypothesized multiparametric MR-PET could be used to quantify the response, estimate pharmacokinetic (PK) parameters, and predict progression-free survival (PFS) in patients with recurrent malignant gliomas.

PATIENTS AND METHODS

Multiparametric advanced MR-PET imaging was performed to evaluate physiologic response in a first-in-man, multicenter, phase I, dose-escalation study of GDC-0084 (NCT01547546) in 47 patients with recurrent malignant glioma.

RESULTS

Measured maximum concentration (C _max) was associated with a decrease in enhancing tumor volume (P = 0.0287) and an increase in fractional anisotropy (FA; P = 0.0418). Posttreatment tumor volume, ¹⁸F-FDG uptake, K^trans, and relative cerebral blood volume (rCBV) were all correlated with C _max. A linear combination of change in ¹⁸F-FDG PET uptake, apparent diffusion coefficient (ADC), FA, K^trans, v_p, and rCBV was able to estimate both C _max (R² = 0.4113; P < 0.0001) and drug exposure (AUC; R² = 0.3481; P < 0.0001). Using this composite multiparametric MR-PET imaging response biomarker to predict PK, patients with an estimated C _max > 0.1 μmol/L and AUC > 1.25 μmol/L*hour demonstrated significantly longer PFS compared with patients with a lower estimated concentration and exposure (P = 0.0039 and P = 0.0296, respectively).

CONCLUSIONS

Results from this study suggest composite biomarkers created from multiparametric MR-PET imaging targeting metabolic and/or physiologic processes specific to the drug mechanism of action may be useful for subsequent evaluation of treatment efficacy for larger phase II-III studies.

Systematic assessment of multi-echo dynamic susceptibility contrast MRI using a digital reference object

PURPOSE

Brain tumor dynamic susceptibility contrast (DSC) MRI is adversely impacted by T₁ and T 2 ∗ contrast agent leakage effects that result in inaccurate hemodynamic metrics. While multi-echo acquisitions remove T₁ leakage effects, there is no consensus on the optimal set of acquisition parameters. Using a computational approach, we systematically evaluated a wide range of acquisition strategies to determine the optimal multi-echo DSC-MRI perfusion protocol.

METHODS

Using a population-based DSC-MRI digital reference object (DRO), we assessed the influence of preload dosing (no preload and full dose preload), field strength (1.5 and 3T), pulse sequence parameters (echo time, repetition time, and flip angle), and leakage correction on relative cerebral blood volume (rCBV) and flow (rCBF) accuracy. We also compared multi-echo DSC-MRI protocols with standard single-echo protocols.

RESULTS

Multi-echo DSC-MRI is highly consistent across all protocols, and multi-echo rCBV (with or without use of a preload dose) had higher accuracy than single-echo rCBV. Regression analysis showed that choice of repetition time and flip angle had minimal impact on multi-echo rCBV and rCBV, indicating the potential for significant flexibility in acquisition parameters. The echo time combination had minimal impact on rCBV, though longer echo times should be avoided, particularly at higher field strengths. Leakage correction improved rCBV accuracy in all cases. Multi-echo rCBF was less biased than single-echo rCBF, although rCBF accuracy was reduced overall relative to rCBV.

CONCLUSIONS

Multi-echo acquisitions were more robust than single-echo, essentially decoupling both repetition time and flip angle from rCBV accuracy. Multi-echo acquisitions obviate the need for preload dosing, although leakage correction to remove residual T 2 ∗ leakage effects remains compulsory for high rCBV accuracy.

Longitudinal, leakage corrected and uncorrected rCBV during the first-line treatment of glioblastoma: a prospective study

PURPOSE

Dynamic susceptibility contrast (DSC) MR-perfusion is becoming a standard of care for the monitoring of glioblastoma. Yet, technical standards are lacking and measurements without leakage correction are still common. Also, data on leakage corrected measurements during stable disease is scarce. In this study we hypothesized that basic leakage correction would significantly enhance data quality during stable disease and improve progress detection. We furthermore investigated whether longitudinal data could increase diagnostic performance.

METHODS

Patients with histologically proven glioblastoma undergoing first-line therapy were prospectively recruited. We conducted DSC perfusion measurements without prebolus administration in 6-week intervals from the end of radiotherapy until progression. Maximum relative cerebral volume values (rCBV_max) with and without leakage correction were calculated using Philips IntelliSpace®.

RESULTS

We recruited 16 patients and conducted 82 MRI scans with a mean follow up of 7.2 month. During stable disease, corrected rCBV_max was significantly more stable than uncorrected rCBV_max. Detection of progression with a rCBV_max cutoff was better for corrected (specificity 86%) than for uncorrected rCBV_max (specificity 41%). Interestingly, the increase of corrected rCBV_max upon progression also had a good diagnostic performance with a combination of both cutoffs delivering the best result (sensitivity/specificity 89%/93%).

CONCLUSION

Corrected rCBV_max supports the imaging finding of a stable disease and large increases during longitudinal observation support the diagnosis of tumor progression. rCBV values without prebolus or leakage correction are not reliable to monitor glioblastomas. Further studies to investigate the value of longitudinal rCBV dynamics for the differentiation of real tumor progression from pseudoprogression are warranted.

Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast-based MRI in rectal cancer

BACKGROUND

Dynamic contrast-based MRI and intravoxel incoherent motion imaging (IVIM) MRI are both methods showing promise as diagnostic and prognostic tools in rectal cancer. Both methods aim at measuring perfusion-related parameters, but the relationship between them is unclear.

PURPOSE

To investigate the relationship between perfusion- and permeability-related parameters obtained by IVIM-MRI, T₁ -weighted dynamic contrast-enhanced (DCE)-MRI and T₂ *-weighted dynamic susceptibility contrast (DSC)-MRI.

STUDY TYPE

Prospective.

SUBJECTS

In all, 94 patients with histologically confirmed rectal cancer.

FIELD STRENGTH/SEQUENCE

Subjects underwent pretreatment 1.5T clinical procedure MRI, and in addition a study-specific diffusion-weighted sequence (b = 0, 25, 50, 100, 500, 1000, 1300 s/mm² ) and a multiecho dynamic contrast-based echo-planer imaging sequence.

ASSESSMENT

Median tumor values were obtained from IVIM (perfusion fraction [f], pseudodiffusion [D*], diffusion [D]), from the extended Tofts model applied to DCE data (K^trans , k_ep , v_p , v_e ) and from model free deconvolution of DSC (blood flow [BF] and area under curve). A subgroup of the excised tumors underwent immunohistochemistry with quantification of microvessel density and vessel size.

STATISTICAL TEST

Spearman's rank correlation test.

RESULTS

D* was correlated with BF (r_s = 0.47, P < 0.001), and f was negatively correlated with k_ep (r_s = -0.31, P = 0.002). BF was correlated with K^trans (r_s = 0.29, P = 0.004), but this correlation varied extensively when separating tumors into groups of low (r_s = 0.62, P < 0.001) and high (r_s = -0.06, P = 0.68) BF. K^trans was negatively correlated with vessel size (r_s = -0.82, P = 0.004) in the subgroup of tumors with high BF.

DATA CONCLUSION

We found an association between D* from IVIM and BF estimated from DSC-MRI. The relationship between IVIM and DCE-MRI was less clear. Comparing parameters from DSC-MRI and DCE-MRI highlights the importance of the underlying biology for the interpretation of these parameters.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1114-1124.

Optimization of Acquisition and Analysis Methods for Clinical Dynamic Susceptibility Contrast MRI Using a Population-Based Digital Reference Object

BACKGROUND AND PURPOSE

The accuracy of DSC-MR imaging CBV maps in glioblastoma depends on acquisition and analysis protocols. Multisite protocol heterogeneity has challenged standardization initiatives due to the difficulties of in vivo validation. This study sought to compare the accuracy of routinely used protocols using a digital reference object.

MATERIALS AND METHODS

The digital reference object consisted of approximately 10,000 simulated voxels recapitulating typical signal heterogeneity encountered in vivo. The influence of acquisition and postprocessing methods on CBV reliability was evaluated across 6912 parameter combinations, including contrast agent dosing schemes, pulse sequence parameters, field strengths, and postprocessing methods. Accuracy and precision were assessed using the concordance correlation coefficient and coefficient of variation.

RESULTS

Across all parameter space, the optimal protocol included full-dose contrast agent preload and bolus, intermediate (60°) flip angle, 30-ms TE, and postprocessing with a leakage-correction algorithm (concordance correlation coefficient = 0.97, coefficient of variation = 6.6%). Protocols with no preload or fractional dose preload and bolus using these acquisition parameters were generally less robust. However, a protocol with no preload, full-dose bolus, and low (30°) flip angle performed very well (concordance correlation coefficient = 0.93, coefficient of variation = 8.7% at 1.5T and concordance correlation coefficient = 0.92, coefficient of variation = 8.2% at 3T).

CONCLUSIONS

Schemes with full-dose preload and bolus maximize CBV accuracy and reduce variability, which could enable smaller sample sizes and more reliable detection of CBV changes in clinical trials. When a lower total contrast agent dose is desired, use of a low flip angle, no preload, and full-dose bolus protocol may provide an attractive alternative.

Simultaneous perfusion and permeability assessments using multiband multi-echo EPI (M2-EPI) in brain tumors

PURPOSE

To study a multiband multi-echo EPI (M2-EPI) sequence for dynamic susceptibility contrast (DSC) perfusion imaging with leakage correction and vascular permeability measurements, and to evaluate the benefits of increased temporal resolution provided by this acquisition strategy on the accuracy of perfusion and permeability estimations.

METHODS

A novel M2-EPI sequence was developed, and a pharmacokinetic model accounting for contrast agent extravasation was used to produce perfusion maps and additional vascular permeability maps. The advantage of M2-EPI for DSC perfusion imaging was demonstrated in vivo in 5 patients with brain tumors, and numerical simulations were performed to evaluate the advantage of improved temporal resolution afforded by the technique.

RESULTS

In contrast to underestimations of cerebral blood volume (CBV) in tumors using the single-echo acquisition strategy, M2-EPI provided more plausible estimates of CBV. A quantitative evaluation showed higher estimated values of CBV and mean transit time in tumor tissues using M2-EPI (CBV: 3.08 ± 0.78 mL/100 g versus 1.56 ± 1.38 mL/100 g [P = .006]; mean transit time: 4.94 ± 1.17 seconds versus 1.83 ± 2.06 seconds [P = 0.033]). Numerical simulations showed that higher temporal resolution provided by M2-EPI was associated with more accurate estimates of cerebral blood flow, CBV, and permeability parameters.

CONCLUSION

The novel M2-EPI acquisition strategy for DSC imaging facilitates leakage-corrected perfusion measurements with additional permeability assessments and more accurate estimates of perfusion/permeability parameters, and may be used as a quantitative tool for the diagnosis, prognosis, and treatment monitoring of brain tumors.

Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI

In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T₁, T₂ and T₂^∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T₁, T₂ and T₂^∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.

Detection of immune responses after immunotherapy in glioblastoma using PET and MRI

Contrast-enhanced MRI is typically used to follow treatment response and progression in patients with glioblastoma (GBM). However, differentiating tumor progression from pseudoprogression remains a clinical dilemma largely unmitigated by current advances in imaging techniques. Noninvasive imaging techniques capable of distinguishing these two conditions could play an important role in the clinical management of patients with GBM and other brain malignancies. We hypothesized that PET probes for deoxycytidine kinase (dCK) could be used to differentiate immune inflammatory responses from other sources of contrast-enhancement on MRI. Orthotopic malignant gliomas were established in syngeneic immunocompetent mice and then treated with dendritic cell (DC) vaccination and/or PD-1 mAb blockade. Mice were then imaged with [18F]-FAC PET/CT and MRI with i.v. contrast. The ratio of contrast enhancement on MRI to normalized PET probe uptake, which we term the immunotherapeutic response index, delineated specific regions of immune inflammatory activity. On postmortem examination, FACS-based enumeration of intracranial tumor-infiltrating lymphocytes directly correlated with quantitative [18F]-FAC PET probe uptake. Three patients with GBM undergoing treatment with tumor lysate-pulsed DC vaccination and PD-1 mAb blockade were also imaged before and after therapy using MRI and a clinical PET probe for dCK. Unlike in mice, [18F]-FAC is rapidly catabolized in humans; thus, we used another dCK PET probe, [18F]-clofarabine ([18F]-CFA), that may be more clinically relevant. Enhanced [18F]-CFA PET probe accumulation was identified in tumor and secondary lymphoid organs after immunotherapy. Our findings identify a noninvasive modality capable of imaging the host antitumor immune response against intracranial tumors.

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T₁ and T₂* changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials.

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II-III diffuse gliomas

The value of perfusion and diffusion-weighted MRI in differentiating histological subtypes according to the 2007 WHO glioma classification scheme (i.e. astrocytoma vs. oligodendroglioma) and genetic subtypes according to the 2016 WHO reclassification (e.g. 1p/19q co-deletion and IDH1 mutation status) in WHO grade II and III diffuse gliomas remains controversial. In the current study, we describe unique perfusion and diffusion MR signatures between histological and genetic glioma subtypes. Sixty-five patients with 2007 histological designations (astrocytomas and oligodendrogliomas), 1p/19q status (+ = intact/- = co-deleted), and IDH1 mutation status (MUT/WT) were included in this study. In all patients, median relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were estimated within T2 hyperintense lesions. Bootstrap hypothesis testing was used to compare subpopulations of gliomas, separated by WHO grade and 2007 or 2016 glioma classification schemes. A multivariable logistic regression model was also used to differentiate between 1p19q⁺ and 1p19q^- WHO II-III gliomas. Neither rCBV nor ADC differed significantly between histological subtypes of pure astrocytomas and pure oligodendrogliomas. ADC was significantly different between molecular subtypes (p = 0.0016), particularly between IDH^WT and IDH^MUT/1p19q⁺ (p = 0.0013). IDH^MUT/1p19q⁺ grade III gliomas had higher median ADC; IDH^WT grade III gliomas had higher rCBV with lower ADC; and IDH^MUT/1p19q^- had intermediate rCBV and ADC values, similar to their grade II counterparts. A multivariable logistic regression model was able to differentiate between IDH^WT and IDH^MUT WHO II and III gliomas with an AUC of 0.84 (p < 0.0001, 74% sensitivity, 79% specificity). Within IDH^MUT WHO II-III gliomas, a separate multivariable logistic regression model was able to differentiate between 1p19q⁺ and 1p19q^- WHO II-III gliomas with an AUC of 0.80 (p = 0.0015, 64% sensitivity, 82% specificity). ADC better differentiated between genetic subtypes of gliomas according to the 2016 WHO guidelines compared to the classification scheme outlined in the 2007 WHO guidelines based on histological features of the tissue. Results suggest a combination of rCBV, ADC, T2 hyperintense volume, and presence of contrast enhancement together may aid in non-invasively identifying genetic subtypes of diffuse gliomas.

Effects of MRI Protocol Parameters, Preload Injection Dose, Fractionation Strategies, and Leakage Correction Algorithms on the Fidelity of Dynamic-Susceptibility Contrast MRI Estimates of Relative Cerebral Blood Volume in Gliomas

BACKGROUND AND PURPOSE

DSC perfusion MR imaging assumes that the contrast agent remains intravascular; thus, disruptions in the blood-brain barrier common in brain tumors can lead to errors in the estimation of relative CBV. Acquisition strategies, including the choice of flip angle, TE, TR, and preload dose and incubation time, along with post hoc leakage-correction algorithms, have been proposed as means for combating these leakage effects. In the current study, we used DSC-MR imaging simulations to examine the influence of these various acquisition parameters and leakage-correction strategies on the faithful estimation of CBV.

MATERIALS AND METHODS

DSC-MR imaging simulations were performed in 250 tumors with perfusion characteristics randomly generated from the distributions of real tumor population data, and comparison of leakage-corrected CBV was performed with a theoretic curve with no permeability. Optimal strategies were determined by protocol with the lowest mean error.

RESULTS

The following acquisition strategies (flip angle/TE/TR and contrast dose allocation for preload and bolus) produced high CBV fidelity, as measured by the percentage difference from a hypothetic tumor with no leakage: 1) 35°/35 ms/1.5 seconds with no preload and full dose for DSC-MR imaging, 2) 35°/25 ms/1.5 seconds with ¼ dose preload and ¾ dose bolus, 3) 60°/35 ms/2.0 seconds with ½ dose preload and ½ dose bolus, and 4) 60°/35 ms/1.0 second with 1 dose preload and 1 dose bolus.

CONCLUSIONS

Results suggest that a variety of strategies can yield similarly high fidelity in CBV estimation, namely those that balance T1- and T2*-relaxation effects due to contrast agent extravasation.

Reliable estimation of microvascular flow patterns in patients with disrupted blood-brain barrier using dynamic susceptibility contrast MRI

PURPOSE

To present and quantify the performance of a method to compute tissue hemodynamic parameters from dynamic susceptibility contrast (DSC) MRI data in brain tissue with possible nonintact blood-brain barrier.

THEORY AND MATERIALS AND METHODS

We propose a Bayesian scheme to obtain perfusion metrics, including capillary transit-time heterogeneity (CTH), from DSC-MRI data in the presence of contrast agent extravasation. Initial performance assessment is performed through simulations. Next, we assessed possible over- or under correction for tracer extravasation in two patients receiving contrast agent preloading and two patients not receiving preloading. Perfusion metrics for N = 60 patients diagnosed with either grade III (N = 14) or grade IV gliomas (N = 46) were analyzed across tissue types to evaluate the ability to distinguish regions with different hemodynamic patterns. Finally, N = 4 patient cases undergoing anti-angiogenic treatment are evaluated qualitatively for treatment effects. All patient data were acquired at 3.0 Tesla.

RESULTS

The simulation studies showed good robustness against low signal-to-noise ratios, exemplified with Pearson correlations of R = 0.833 (mean transit time) and R = 0.738 (CTH) at signal-to-noise ratio = 20. Region-of-interest analysis of the N = 60 glioma patients showed that cerebral blood volume (CBV) significantly separated enhancing core from edema (grade IV: P < 10^-8 , grade III: P < 0.05) and enhancing core from normal appearing ipsilateral white matter (NAWM) (grade IV: P < 10^-8 , grade III: P < 0.05). The microvascular parameters were particularly good in separating edematous tissue from NAWM tissue in grade IV gliomas (P < 0.001). Finally, CTH separated grade III and grade IV core tissue (P < 0.05).

CONCLUSION

We have demonstrated robustness of the proposed Bayesian algorithm against experimental noise and demonstrated complementary value in microvascular parameters to the CBV parameter in separating tissue types in gliomas.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:537-549.