Cerebral perivascular spaces as predictors of dementia risk and accelerated brain atrophy

Cerebral small vessel disease, an important risk factor for dementia, lacks robust, in vivo measurement methods. Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. We developed a novel, robust algorithm to automatically assess PVS count and size on MRI, and investigated their relationship with dementia risk and brain atrophy. We analyzed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1±9.7 years-old, 56.6% women). Fewer PVS and larger PVS diameter at baseline were associated with higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers were significantly different in non-demented individuals who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants less likely to develop dementia based on our PVS markers enhanced the power of the trial. These novel radiographic cerebrovascular markers may improve risk-stratification of individuals, potentially reducing cost and increasing throughput of clinical trials to combat dementia.

Arterial Spin-Labeling and DSC Perfusion Metrics Improve Agreement in Neuroradiologists' Clinical Interpretations of Posttreatment High-Grade Glioma Surveillance MR Imaging-An Institutional Experience

BACKGROUND AND PURPOSE

MR perfusion has shown value in the evaluation of posttreatment high-grade gliomas, but few studies have shown its impact on the consistency and confidence of neuroradiologists' interpretation in routine clinical practice. We evaluated the impact of adding MR perfusion metrics to conventional contrast-enhanced MR imaging in posttreatment high-grade glioma surveillance imaging.

MATERIALS AND METHODS

This retrospective study included 45 adults with high-grade gliomas who had posttreatment perfusion MR imaging. Four neuroradiologists assigned Brain Tumor Reporting and Data System scores for each examination on the basis of the interpretation of contrast-enhanced MR imaging and then after the addition of arterial spin-labeling-CBF, DSC-relative CBV, and DSC-fractional tumor burden. Interrater agreement and rater agreement with a multidisciplinary consensus group were assessed with κ statistics. Raters used a 5-point Likert scale to report confidence scores. The frequency of clinically meaningful score changes resulting from the addition of each perfusion metric was determined.

RESULTS

Interrater agreement was moderate for contrast-enhanced MR imaging alone (κ = 0.63) and higher with perfusion metrics (arterial spin-labeling-CBF, κ = 0.67; DSC-relative CBV, κ = 0.66; DSC-fractional tumor burden, κ = 0.70). Agreement between raters and consensus was highest with DSC-fractional tumor burden (κ = 0.66-0.80). Confidence scores were highest with DSC-fractional tumor burden. Across all raters, the addition of perfusion resulted in clinically meaningful interpretation changes in 2%-20% of patients compared with contrast-enhanced MR imaging alone.

CONCLUSIONS

Adding perfusion to contrast-enhanced MR imaging improved interrater agreement, rater agreement with consensus, and rater confidence in the interpretation of posttreatment high-grade glioma MR imaging, with the highest agreement and confidence scores seen with DSC-fractional tumor burden. Perfusion MR imaging also resulted in interpretation changes that could change therapeutic management in up to 20% of patients.

Detecting High-Dose Methotrexate-Induced Brain Changes in Pediatric and Young Adult Cancer Survivors Using [18F]FDG PET/MRI: A Pilot Study

Significant improvements in treatments for children with cancer have resulted in a growing population of childhood cancer survivors who may face long-term adverse outcomes. Here, we aimed to diagnose high-dose methotrexate-induced brain injury on [18F]FDG PET/MRI and correlate the results with cognitive impairment identified by neurocognitive testing in pediatric cancer survivors. Methods: In this prospective, single-center pilot study, 10 children and young adults with sarcoma (n = 5), lymphoma (n = 4), or leukemia (n = 1) underwent dedicated brain [18F]FDG PET/MRI and a 2-h expert neuropsychologic evaluation on the same day, including the Wechsler Abbreviated Scale of Intelligence, second edition, for intellectual functioning; Delis-Kaplan Executive Function System (DKEFS) for executive functioning; and Wide Range Assessment of Memory and Learning, second edition (WRAML), for verbal and visual memory. Using PMOD software, we measured the SUVmean, cortical thickness, mean cerebral blood flow (CBFmean), and mean apparent diffusion coefficient of 3 different cortical regions (prefrontal cortex, cingulate gyrus, and hippocampus) that are routinely involved during the above-specified neurocognitive testing. Standardized scores of different measures were converted to z scores. Pairs of multivariable regression models (one for z scores < 0 and one for z scores > 0) were fitted for each brain region, imaging measure, and test score. Heteroscedasticity regression models were used to account for heterogeneity in variances between brain regions and to adjust for clustering within patients. Results: The regression analysis showed a significant correlation between the SUVmean of the prefrontal cortex and cingulum and DKEFS-sequential tracking (DKEFS-TM4) z scores (P = 0.003 and P = 0.012, respectively). The SUVmean of the hippocampus did not correlate with DKEFS-TM4 z scores (P = 0.111). The SUVmean for any evaluated brain regions did not correlate significantly with WRAML-visual memory (WRAML-VIS) z scores. CBFmean showed a positive correlation with SUVmean (r = 0.56, P = 0.01). The CBFmean of the cingulum, hippocampus, and prefrontal cortex correlated significantly with DKEFS-TM4 (all P < 0.001). In addition, the hippocampal CBFmean correlated significantly with negative WRAML-VIS z scores (P = 0.003). Conclusion: High-dose methotrexate-induced brain injury can manifest as a reduction in glucose metabolism and blood flow in specific brain areas, which can be detected with [18F]FDG PET/MRI. The SUVmean and CBFmean of the prefrontal cortex and cingulum can serve as quantitative measures for detecting executive functioning problems. Hippocampal CBFmean could also be useful for monitoring memory problems.

Emergence of Boltzmann Subspaces in Open Quantum Systems Far from Equilibrium

Single molecule junctions are important examples of complex out-of-equilibrium many-body quantum systems. We identify a nontrivial clustering of steady state populations into distinctive subspaces with Boltzmann-like statistics, which persist far from equilibrium. Such Boltzmann subspaces significantly reduce the information needed to describe the steady state, enabling modeling of high-dimensional systems that are otherwise beyond the reach of current computations. The emergence of Boltzmann subspaces is demonstrated analytically and numerically for fermionic transport systems of increasing complexity.

Tumor treating fields increases blood-brain barrier permeability and relative cerebral blood volume in patients with glioblastoma

BACKGROUND AND OBJECTIVE

200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans.

METHODS

Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results.

RESULTS

Among 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only.

CONCLUSION

Using pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.

A rare non-gadolinium enhancing sarcoma brain metastasis with microenvironment dominated by tumor-associated macrophages

Brain metastases occur in 1% of sarcoma cases and are associated with a median overall survival of 6 months. We report a rare case of a brain metastasis with unique radiologic and histopathologic features in a patient with low grade fibromyxoid sarcoma (LGFMS) previously treated with immune checkpoint inhibitor (ICI) therapy. The lone metastasis progressed in the midbrain tegmentum over 15 months as a non-enhancing, T2-hyperintense lesion with peripheral diffusion restriction, mimicking a demyelinating lesion. Histopathology of the lesion at autopsy revealed a rich infiltrate of tumor-associated macrophages (TAMs) with highest density at the leading edge of the metastasis, whereas there was a paucity of lymphocytes, suggestive of an immunologically cold environment. Given the important immunosuppressive and tumor-promoting functions of TAMs in gliomas and carcinoma/melanoma brain metastases, this unusual case provides an interesting example of a dense TAM infiltrate in a much rarer sarcoma brain metastasis.

Brain Tumor Imaging: Review of Conventional and Advanced Techniques

Approaches to central nervous system (CNS) tumor classification and evaluation have undergone multiple iterations over the past few decades, in large part due to our growing understanding of the influence of genetics on tumor behavior and our refinement of brain tumor imaging techniques. Computed tomography and magnetic resonance imaging (MRI) both play a critical role in the diagnosis and monitoring of brain tumors, although MRI has become especially important due to its superior soft tissue resolution. The purpose of this article will be to briefly review the fundamentals of conventional and advanced techniques used in brain tumor imaging. We will also highlight the applications of these imaging tools in the context of commonly encountered tumors based on the most recently updated 2021 World Health Organization (WHO) classification of CNS tumors framework.

Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas

Objective

This study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2-4) from 3 different centers.

Methods

To quantify the DSC perfusion signal two different mathematical modeling methods were used (Gamma fitting, leakage correction algorithms) considering the assumptions about the compartments contributing in the blood flow between the extra- and intra vascular space.

Results

The Mean slope of increase (MSI) and the K1 parameter of the bidirectional exchange model exhibited the highest performance with (ACC 74.3% AUROC 74.2%) and (ACC 75% AUROC 70.5%) respectively.

Conclusion

The proposed framework on DSC-MRI radiogenomics in gliomas has the potential of becoming a reliable diagnostic support tool exploiting the mathematical modeling of the DSC signal to characterize IDH mutation status through a more reproducible and standardized signal analysis scheme for facilitating clinical translation.

2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data

Introduction

Management of patients with brain metastases is often based on manual lesion detection and segmentation by an expert reader. This is a time- and labor-intensive process, and to that end, this work proposes an end-to-end deep learning segmentation network for a varying number of available MRI available sequences.

Methods

We adapt and evaluate a 2.5D and a 3D convolution neural network trained and tested on a retrospective multinational study from two independent centers, in addition, nnU-Net was adapted as a comparative benchmark. Segmentation and detection performance was evaluated by: (1) the dice similarity coefficient, (2) a per-metastases and the average detection sensitivity, and (3) the number of false positives.

Results

The 2.5D and 3D models achieved similar results, albeit the 2.5D model had better detection rate, whereas the 3D model had fewer false positive predictions, and nnU-Net had fewest false positives, but with the lowest detection rate. On MRI data from center 1, the 2.5D, 3D, and nnU-Net detected 79%, 71%, and 65% of all metastases; had an average per patient sensitivity of 0.88, 0.84, and 0.76; and had on average 6.2, 3.2, and 1.7 false positive predictions per patient, respectively. For center 2, the 2.5D, 3D, and nnU-Net detected 88%, 86%, and 78% of all metastases; had an average per patient sensitivity of 0.92, 0.91, and 0.85; and had on average 1.0, 0.4, and 0.1 false positive predictions per patient, respectively.

Discussion/Conclusion

Our results show that deep learning can yield highly accurate segmentations of brain metastases with few false positives in multinational data, but the accuracy degrades for metastases with an area smaller than 0.4 cm².

Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging

Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.

Deep learning-based brain tumor segmentation on limited sequences of magnetic resonance imaging

2054

Background: Deep learning algorithms trained to segment brain tumors from magnetic resonance imaging (MRI) perform well in ideal conditions supplied by curated datasets. An example is the MICCAI BraTS 2018 dataset, which provides a set of four MRI sequences (T1, T1 post-gadolinium contrast-enhanced, T2, FLAIR) on 285 samples, along with ground truth segmentations annotated by experts. In real-world settings, however, it is not uncommon for patients to undergo MRI with a limited number of image sequence acquisitions. We examined the effect of restricting the imaging sequence set when training a deep learning model for brain tumor segmentation. Our goal was to identify a limited subset that still achieved acceptably high performance. Methods: In our experiments, we used the convolutional neural network-based U-Net architecture. Instead of the standard BraTS task, we focused on sub-segmenting specific areas of brain tumors: the active, enhancing tumor (AT) and the tumor core (TC; AT plus the cystic/necrotic core). We trained the architecture on 285 samples of the BraTS 2018 dataset using one or both of two sequences: T1 contrast-enhanced (T1CE) and FLAIR. Using each training model, we predicted segmentation masks given a volumetric MR image of a brain tumor on 66 samples in the held-out validation dataset. We submitted the predicted segmentations to the Center for Biomedical Image Computing and Analytics (CBICA) imaging portal for evaluation, which reports prediction accuracy by returning dice scores on each prediction. Results: As shown in the Table, the U-Net model using T1CE alone yielded high performances, with median dice scores of 0.84461 and 0.88267, when segmenting AT and TC, respectively. On the other hand, using FLAIR alone generated lower performances on the same tasks of segmenting the AT (0.25996) and the TC regions (0.51153). Combining T1CE and FLAIR provided no additional performance improvement compared with T1CE used as a standalone sequence. Conclusions: We achieved high performances in two brain tumor sub-segmentation tasks using a limited number of MRI sequences in training a deep-learning algorithm. T1CE alone produced high performances on both TC and AT segmentations. Given the ubiquity of the T1CE sequence, the ability to achieve high performance tumor segmentations in the face of limited image sequence availability is critical when applying our algorithm in real-world clinical or research settings. [Table: see text]

Retinal artery and vein occlusion in calciphylaxis

Purpose

To report a case of branch retinal artery occlusion (BRAO) followed by branch retinal vein occlusion (BRVO) and paracentral acute middle maculopathy (PAMM) in a patient with confirmed calciphylaxis.

Observations

A 52-year-old female with a history of BRAO in the right eye one-year prior presented with decreased vision and a new inferotemporal scotoma. Computed tomography angiography of the head and neck demonstrated vascular calcifications at the origin of both ophthalmic arteries, which were otherwise poorly visualized. Ophthalmic examination demonstrated retinal whitening superiorly with intraretinal hemorrhages inferiorly. Optical coherence tomography (OCT) demonstrated middle retinal hyperreflectivity and a mild epiretinal membrane. Fluorescein angiography (FFA) demonstrated delayed perfusion of superior retinal arcade. On further questioning, patient was found to have a history of IgA nephropathy with end-stage renal disease, secondary hyperparathyroidism and calciphylaxis. Calciphylaxis is a systemic disease, characterized by high levels of calcium and progressive calcification of the vascular medial layer leading to ischemia. Anterior ischemic optic neuropathy (AION) and crystalline retinopathy have been reported as ocular manifestations of calciphylaxis, however, there are very few reports on ophthalmic manifestations of calciphylaxis.

Conclusion and importance

Clinical manifestations of calciphylaxis are variable and a detailed clinical history is important to suspect calciphylaxis. Calciphylaxis should be considered in the differential diagnosis of BRAO, BRVO, PAMM or any ophthalmic vascular manifestation in patients with end-stage renal disease.

DSC Perfusion MRI-Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery

BACKGROUND AND PURPOSE

Differentiation between tumor and radiation necrosis in patients with brain metastases treated with stereotactic radiosurgery is challenging. We hypothesized that MR perfusion and metabolic metrics can differentiate radiation necrosis from progressive tumor in this setting.

MATERIALS AND METHODS

We retrospectively evaluated MRIs comprising DSC, dynamic contrast-enhanced, and arterial spin-labeling perfusion imaging in subjects with brain metastases previously treated with stereotactic radiosurgery. For each lesion, we obtained the mean normalized and standardized relative CBV and fractional tumor burden, volume transfer constant, and normalized maximum CBF, as well as the maximum standardized uptake value in a subset of subjects who underwent FDG-PET. Relative CBV thresholds of 1 and 1.75 were used to define low and high fractional tumor burden.

RESULTS

Thirty subjects with 37 lesions (20 radiation necrosis, 17 tumor) were included. Compared with radiation necrosis, tumor had increased mean normalized and standardized relative CBV (P = .002) and high fractional tumor burden (normalized, P = .005; standardized, P = .003) and decreased low fractional tumor burden (normalized, P = .03; standardized, P = .01). The area under the curve showed that relative CBV (normalized = 0.80; standardized = 0.79) and high fractional tumor burden (normalized = 0.77; standardized = 0.78) performed the best to discriminate tumor and radiation necrosis. For tumor prediction, the normalized relative CBV cutoff of ≥1.75 yielded a sensitivity of 76.5% and specificity of 70.0%, while the standardized cutoff of ≥1.75 yielded a sensitivity of 41.2% and specificity of 95.0%. No significance was found with the volume transfer constant, normalized CBF, and standardized uptake value.

CONCLUSIONS

Increased relative CBV and high fractional tumor burden (defined by a threshold relative CBV of ≥1.75) best differentiated tumor from radiation necrosis in subjects with brain metastases treated with stereotactic radiosurgery. Performance of normalized and standardized approaches was similar.

How to stop using gadolinium chelates for magnetic resonance imaging: clinical-translational experiences with ferumoxytol

Gadolinium chelates have been used as standard contrast agents for clinical MRI for several decades. However, several investigators recently reported that rare Earth metals such as gadolinium are deposited in the brain for months or years. This is particularly concerning for children, whose developing brain is more vulnerable to exogenous toxins compared to adults. Therefore, a search is under way for alternative MR imaging biomarkers. The United States Food and Drug Administration (FDA)-approved iron supplement ferumoxytol can solve this unmet clinical need: ferumoxytol consists of iron oxide nanoparticles that can be detected with MRI and provide significant T1- and T2-signal enhancement of vessels and soft tissues. Several investigators including our research group have started to use ferumoxytol off-label as a new contrast agent for MRI. This article reviews the existing literature on the biodistribution of ferumoxytol in children and compares the diagnostic accuracy of ferumoxytol- and gadolinium-chelate-enhanced MRI. Iron oxide nanoparticles represent a promising new class of contrast agents for pediatric MRI that can be metabolized and are not deposited in the brain.

MRI pulse sequence integration for deep-learning-based brain metastases segmentation

PURPOSE

Magnetic resonance (MR) imaging is an essential diagnostic tool in clinical medicine. Recently, a variety of deep-learning methods have been applied to segmentation tasks in medical images, with promising results for computer-aided diagnosis. For MR images, effectively integrating different pulse sequences is important to optimize performance. However, the best way to integrate different pulse sequences remains unclear. In addition, networks trained with a certain subset of pulse sequences as input are unable to perform when given a subset of those pulse sequences. In this study, we evaluate multiple architectural features and characterize their effects in the task of metastasis segmentation while creating a method to robustly train a network to be able to work given any strict subset of the pulse sequences available during training.

METHODS

We use a 2.5D DeepLabv3 segmentation network to segment metastases lesions on brain MR's with four pulse sequence inputs. To study how we can best integrate MR pulse sequences for this task, we consider (1) different pulse sequence integration schemas, combining our features at early, middle, and late points within a deep network, (2) different modes of weight sharing for parallel network branches, and (3) a novel integration level dropout layer, which will allow the networks to be robust to performing inference on input with only a subset of pulse sequences available at the training.

RESULTS

We find that levels of integration and modes of weight sharing that favor low variance work best in our regime of small amounts of training data (n = 100). By adding an input-level dropout layer, we could preserve the overall performance of these networks while allowing for inference on inputs with missing pulse sequences. We illustrate not only the generalizability of the network but also the utility of this robustness when applying the trained model to data from a different center, which does not use the same pulse sequences. Finally, we apply network visualization methods to better understand which input features are most important for network performance.

CONCLUSIONS

Together, these results provide a framework for building networks with enhanced robustness to missing data while maintaining comparable performance in medical imaging applications.

Multicenter DSC-MRI-Based Radiomics Predict IDH Mutation in Gliomas

Simple Summary

Significant efforts have been put toward developing MRI-based radiogenomics for IDH status subtyping predictions; however, in the vast majority of these approaches, the external validation sets are absent. Another limitation in current studies is the lack of explainability in radiomics models, which hampers clinical trust and translation. Motivated by these challenges, we proposed a multicenter DSC–MRI-based radiomics study based on an independent exploratory set, which was externally validated on two independent cohorts, for IDH mutation status prediction. Our results demonstrated that DSC–MRI radiogenomics in gliomas, coupled with dynamic-based image standardization techniques, hold the potential to provide (a) increased predictive performance by offering models that generalize well, (b) reasoning behind the IDH mutation status predictions, and (c) interpretability of the radiomics features’ impacts in model performance.

Abstract

To address the current lack of dynamic susceptibility contrast magnetic resonance imaging (DSC–MRI)-based radiomics to predict isocitrate dehydrogenase (IDH) mutations in gliomas, we present a multicenter study that featured an independent exploratory set for radiomics model development and external validation using two independent cohorts. The maximum performance of the IDH mutation status prediction on the validation set had an accuracy of 0.544 (Cohen’s kappa: 0.145, F1-score: 0.415, area under the curve-AUC: 0.639, sensitivity: 0.733, specificity: 0.491), which significantly improved to an accuracy of 0.706 (Cohen’s kappa: 0.282, F1-score: 0.474, AUC: 0.667, sensitivity: 0.6, specificity: 0.736) when dynamic-based standardization of the images was performed prior to the radiomics. Model explainability using local interpretable model-agnostic explanations (LIME) and Shapley additive explanations (SHAP) revealed potential intuitive correlations between the IDH–wildtype increased heterogeneity and the texture complexity. These results strengthened our hypothesis that DSC–MRI radiogenomics in gliomas hold the potential to provide increased predictive performance from models that generalize well and provide understandable patterns between IDH mutation status and the extracted features toward enabling the clinical translation of radiogenomics in neuro-oncology.

EGFR-targeted intraoperative fluorescence imaging detects high-grade glioma with panitumumab-IRDye800 in a phase 1 clinical trial

Rationale: First-line therapy for high-grade gliomas (HGGs) includes maximal safe surgical resection. The extent of resection predicts overall survival, but current neuroimaging approaches lack tumor specificity. The epidermal growth factor receptor (EGFR) is a highly expressed HGG biomarker. We evaluated the safety and feasibility of an anti-EGFR antibody, panitumuab-IRDye800, at subtherapeutic doses as an imaging agent for HGG. Methods: Eleven patients with contrast-enhancing HGGs were systemically infused with panitumumab-IRDye800 at a low (50 mg) or high (100 mg) dose 1-5 days before surgery. Near-infrared fluorescence imaging was performed intraoperatively and ex vivo, to identify the optimal tumor-to-background ratio by comparing mean fluorescence intensities of tumor and histologically uninvolved tissue. Fluorescence was correlated with preoperative T1 contrast, tumor size, EGFR expression and other biomarkers. Results: No adverse events were attributed to panitumumab-IRDye800. Tumor fragments as small as 5 mg could be detected ex vivo and detection threshold was dose dependent. In tissue sections, panitumumab-IRDye800 was highly sensitive (95%) and specific (96%) for pathology confirmed tumor containing tissue. Cellular delivery of panitumumab-IRDye800 was correlated to EGFR overexpression and compromised blood-brain barrier in HGG, while normal brain tissue showed minimal fluorescence. Intraoperative fluorescence improved optical contrast in tumor tissue within and beyond the T1 contrast-enhancing margin, with contrast-to-noise ratios of 9.5 ± 2.1 and 3.6 ± 1.1, respectively. Conclusions: Panitumumab-IRDye800 provided excellent tumor contrast and was safe at both doses. Smaller fragments of tumor could be detected at the 100 mg dose and thus more suitable for intraoperative imaging.

Clinical Review of Computed Tomography and MR Perfusion Imaging in Neuro-Oncology

Neuroimaging plays an essential role in the initial diagnosis and continued surveillance of intracranial neoplasms. The advent of perfusion techniques with computed tomography and MR imaging have proven useful in neuro-oncology, offering enhanced approaches for tumor grading, guiding stereotactic biopsies, and monitoring treatment efficacy. Perfusion imaging can help to identify treatment-related processes, such as radiation necrosis, pseudoprogression, and pseudoregression, and can help to inform treatment-related decision making. Perfusion imaging is useful to differentiate between tumor types and between tumor and nonneoplastic conditions. This article reviews the clinical relevance and implications of perfusion imaging in neuro-oncology and highlights promising perfusion biomarkers.

Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study

The purpose of this study was to assess the clinical value of a deep learning (DL) model for automatic detection and segmentation of brain metastases, in which a neural network is trained on four distinct MRI sequences using an input-level dropout layer, thus simulating the scenario of missing MRI sequences by training on the full set and all possible subsets of the input data. This retrospective, multicenter study, evaluated 165 patients with brain metastases. The proposed input-level dropout (ILD) model was trained on multisequence MRI from 100 patients and validated/tested on 10/55 patients, in which the test set was missing one of the four MRI sequences used for training. The segmentation results were compared with the performance of a state-of-the-art DeepLab V3 model. The MR sequences in the training set included pre-gadolinium and post-gadolinium (Gd) T1-weighted 3D fast spin echo, post-Gd T1-weighted inversion recovery (IR) prepped fast spoiled gradient echo, and 3D fluid attenuated inversion recovery (FLAIR), whereas the test set did not include the IR prepped image-series. The ground truth segmentations were established by experienced neuroradiologists. The results were evaluated using precision, recall, Intersection over union (IoU)-score and Dice score, and receiver operating characteristics (ROC) curve statistics, while the Wilcoxon rank sum test was used to compare the performance of the two neural networks. The area under the ROC curve (AUC), averaged across all test cases, was 0.989 ± 0.029 for the ILD-model and 0.989 ± 0.023 for the DeepLab V3 model (p = 0.62). The ILD-model showed a significantly higher Dice score (0.795 ± 0.104 vs. 0.774 ± 0.104, p = 0.017), and IoU-score (0.561 ± 0.225 vs. 0.492 ± 0.186, p < 0.001) compared to the DeepLab V3 model, and a significantly lower average false positive rate of 3.6/patient vs. 7.0/patient (p < 0.001) using a 10 mm3 lesion-size limit. The ILD-model, trained on all possible combinations of four MRI sequences, may facilitate accurate detection and segmentation of brain metastases on a multicenter basis, even when the test cohort is missing input MRI sequences.

Management of brain tumors presenting in pregnancy: a case series and systematic review

Patients who present with brain tumors during pregnancy require unique imaging and neurosurgical, obstetrical, and anesthetic considerations. Here, we review the literature and discuss the management of patients who present with brain tumors during pregnancy. Between 2009 and 2019, 9 patients were diagnosed at our institution with brain tumors during pregnancy. Clinical information was extracted from the electronic medical records. The median age at presentation was 29 years (range, 25-38 years). The most common symptoms at presentation included headache (n=5), visual changes (n=4), hemiparesis (n=3), and seizures (n=3). The median gestational age at presentation was 20.5 weeks (range, 11-37 weeks). Of note, 8 patients (89%) delivered healthy newborns, and 1 patient terminated her pregnancy. In addition, 5 patients (56%) required neurosurgical procedures during pregnancy (gestational ages, 14-37 weeks) because of disease progression (n=2) or neurologic instability (n=3). There was 1 episode of postneurosurgery morbidity (pulmonary embolism [PE]) and no surgical maternal mortality. The median length of follow-up was 15 months (range, 6-45 months). In cases demonstrating unstable or progressive neurosurgical status past the point of fetal viability, neurosurgical intervention should be considered. The physiological and pharmacodynamic changes of pregnancy substantially affect anesthetic management. Pregnancy termination should be discussed and offered to the patient when aggressive disease necessitates immediate treatment and the fetal gestational age remains previable, although neurologically stable patients may be able to continue the pregnancy to term. Ultimately, pregnant patients with brain tumors require an individualized approach to their care under the guidance of a multidisciplinary team.

Critical illness-associated cerebral microbleeds in severe COVID-19 infection

Neurologic complications of COVID-19 infection have been recently described and include dizziness, headache, loss of taste and smell, stroke, and encephalopathy. Brain MRI in these patients have revealed various findings including ischemia, hemorrhage, inflammation, and demyelination. In this article, we report a case of critical illness-associated cerebral microbleeds identified on MRI in a patient with severe COVID-19 infection and discuss the potential etiologies of these neuroimaging findings.

Cerebrospinal Fluid Metals and the Association with Cerebral Small Vessel Disease

BACKGROUND

Brain metal homeostasis is essential for brain health, and deregulation can result in oxidative stress on the brain parenchyma.

OBJECTIVE

Our objective in this study was to focus on two hemorrhagic MRI manifestations of small vessel disease [cerebral microbleeds (CMBs) and cortical superficial siderosis (cSS)] and associations with cerebrospinal fluid (CSF) iron levels. In addition, we aimed to analyze CSF biomarkers for dementia and associations with CSF metal levels.

METHODS

This is a cross-sectional study of 196 patients who underwent memory clinic investigation, including brain MRI. CSF was collected and analyzed for metals, amyloid-β (Aβ) 42, total tau (T-tau), and phosphorylated tau (P-tau), and CSF/serum albumin ratios. Statistical analyses were performed using generalized linear models.

RESULTS

No significant difference was found between CSF metal levels across diagnostic groups. Higher iron and copper levels were associated with higher CSF levels of Aβ42, T-tau, P-tau, and CSF/serum albumin ratios (p < 0.05). Zinc was associated with higher CSF/serum albumin ratios. There was no significant association between CMBs or cSS and CSF iron levels. An increase in CSF iron with the number of CMBs was seen in APOEɛ4 carriers.

CONCLUSION

CSF iron levels are elevated with cerebral microbleeds in APOEɛ4 carriers, with no other association seen with hemorrhagic markers of small vessel disease. The association of elevated CSF iron and copper with tau could represent findings of increased neurodegeneration in these patients.

Utility of a Quantitative Approach Using Diffusion Tensor Imaging for Prognostication Regarding Motor and Functional Outcomes in Patients With Surgically Resected Deep Intracranial Cavernous Malformations

BACKGROUND

Resection of deep intracranial cavernous malformations (CMs) is associated with a higher risk of neurological deterioration and uncertainty regarding clinical outcomes.

OBJECTIVE

To examine diffusion tractography imaging (DTI) data evaluating the corticospinal tract (CST) in relation to motor and functional outcomes in patients with surgically resected deep CMs.

METHODS

Perilesional CST was characterized as disrupted, displaced, or normal. Mean fractional anisotropy (FA) values were obtained for whole ipsilateral CST and in 3 regions: subcortical (proximal), perilesional, and distally. Mean FA values in anatomically equivalent regions in the contralateral CST were obtained. Clinical and radiological data were collected independently. Multivariable regression analysis was used for statistical analysis.

RESULTS

A total of 18 patients [brainstem (15) and thalamus/basal ganglia (3); median follow-up: 270 d] were identified over 2 yr. The CST was identified preoperatively as disrupted (6), displaced (8), and normal (4). Five of 6 patients with disruption had weakness. Higher preoperative mean FA values for distal ipsilateral CST segment were associated with better preoperative lower (P < .001), upper limb (P = .004), postoperative lower (P = .005), and upper limb (P < .001) motor examination. Preoperative mean FA values for distal ipsilateral CST segment (P = .001) and contralateral perilesional CST segment (P < .001) were negatively associated with postoperative modified Rankin scale scores.

CONCLUSION

Lower preoperative mean FA values for overall and defined CST segments corresponded to worse patient pre- and postoperative motor examination and/or functional status. FA value for the distal ipsilateral CST segment has prognostic potential with respect to clinical outcomes.

Simultaneous time of flight-MRA and T2* imaging for cerebrovascular MRI

PURPOSE

3D multi-echo gradient-recalled echo (ME-GRE) can simultaneously generate time-of-flight magnetic resonance angiography (pTOF) in addition to T2*-based susceptibility-weighted images (SWI). We assessed the clinical performance of pTOF generated from a 3D ME-GRE acquisition compared with conventional TOF-MRA (cTOF).

METHODS

Eighty consecutive children were retrospectively identified who obtained 3D ME-GRE alongside cTOF. Two blinded readers independently assessed pTOF derived from 3D ME-GRE and compared them with cTOF. A 5-point Likert scale was used to rank lesion conspicuity and to assess for diagnostic confidence.

RESULTS

Across 80 pediatric neurovascular pathologies, a similar number of lesions were reported on pTOF and cTOF (43-40%, respectively, p > 0.05). Rating of lesion conspicuity was higher with cTOF (4.5 ± 1.0) as compared with pTOF (4.0 ± 0.7), but this was not significantly different (p = 0.06). Diagnostic confidence was rated higher with cTOF (4.8 ± 0.5) than that of pTOF (3.7 ± 0.6; p < 0.001). Overall, the inter-rater agreement between two readers for lesion count on pTOF was classified as almost perfect (κ = 0.98, 96% CI 0.8-1.0).

CONCLUSIONS

In this study, TOF-MRA simultaneously generated in addition to SWI from 3D MR-GRE can serve as a diagnostic adjunct, particularly for proximal vessel disease and when conventional TOF-MRA images are absent.

Brain Iron Assessment after Ferumoxytol-enhanced MRI in Children and Young Adults with Arteriovenous Malformations: A Case-Control Study

Background Iron oxide nanoparticles are an alternative contrast agent for MRI. Gadolinium deposition has raised safety concerns, but it is unknown whether ferumoxytol administration also deposits in the brain. Purpose To investigate whether there are signal intensity changes in the brain at multiecho gradient imaging following ferumoxytol exposure in children and young adults. Materials and Methods This retrospective case-control study included children and young adults, matched for age and sex, with brain arteriovenous malformations who received at least one dose of ferumoxytol from January 2014 to January 2018. In participants who underwent at least two brain MRI examinations (subgroup), the first and last available examinations were analyzed. Regions of interests were placed around deep gray structures on quantitative susceptibility mapping and R2* images. Mean susceptibility and R2* values of regions of interests were recorded. Measurements were assessed by linear regression analyses: a between-group comparison of ferumoxytol-exposed and unexposed participants and a within-group (subgroup) comparison before and after exposure. Results Seventeen participants (mean age ± standard deviation, 13 years ± 5; nine male) were in the ferumoxytol-exposed (case) group, 21 (mean age, 14 years ± 5; 11 male) were in the control group, and nine (mean age, 12 years ± 6; four male) were in the subgroup. The mean number of ferumoxytol administrations was 2 ± 1 (range, one to four). Mean susceptibility (in parts per million [ppm]) and R2* (in inverse seconds [sec^-1]) values of the dentate (case participants: 0.06 ppm ± 0.04 and 23.87 sec^-1 ± 4.13; control participants: 0.02 ppm ± 0.03 and 21.7 sec^-1 ± 5.26), substantia nigrae (case participants: 0.08 ppm ± 0.06 and 27.46 sec^-1 ± 5.58; control participants: 0.04 ppm ± 0.05 and 24.96 sec^-1 ± 5.3), globus pallidi (case participants: 0.14 ppm ± 0.05 and 30.75 sec^-1 ± 5.14; control participants: 0.08 ppm ± 0.07 and 28.82 sec^-1 ± 6.62), putamina (case participants: 0.03 ppm ± 0.02 and 20.63 sec^-1 ± 2.44; control participants: 0.02 ppm ± 0.02 and 19.65 sec^-1 ± 3.6), caudate (case participants: -0.1 ppm ± 0.04 and 18.21 sec^-1 ± 3.1; control participants: -0.06 ppm ± 0.05 and 18.83 sec^-1 ± 3.32), and thalami (case participants: 0 ppm ± 0.03 and 16.49 sec^-1 ± 3.6; control participants: 0.02 ppm ± 0.02 and 18.38 sec^-1 ± 2.09) did not differ between groups (susceptibility, P = .21; R2*, P = .24). For the subgroup, the mean interval between the first and last ferumoxytol administration was 14 months ± 8 (range, 1-25 months). Mean susceptibility and R2* values of the dentate (first MRI: 0.06 ppm ± 0.05 and 25.78 sec^-1 ± 5.9; last MRI: 0.06 ppm ± 0.02 and 25.55 sec^-1 ± 4.71), substantia nigrae (first MRI: 0.06 ppm ± 0.06 and 28.26 sec^-1 ± 9.56; last MRI: 0.07 ppm ± 0.06 and 25.65 sec^-1 ± 6.37), globus pallidi (first MRI: 0.13 ppm ± 0.07 and 27.53 sec^-1 ± 8.88; last MRI: 0.14 ppm ± 0.06 and 29.78 sec^-1 ± 6.54), putamina (first MRI: 0.03 ppm ± 0.03 and 19.78 sec^-1 ± 3.51; last MRI: 0.03 ppm ± 0.02 and 19.73 sec^-1 ± 3.01), caudate (first MRI: -0.09 ppm ± 0.05 and 21.38 sec^-1 ± 4.72; last MRI: -0.1 ppm ± 0.05 and 18.75 sec^-1 ± 2.68), and thalami (first MRI: 0.01 ppm ± 0.02 and 17.65 sec^-1 ± 5.16; last MRI: 0 ppm ± 0.02 and 15.32 sec^-1 ± 2.49) did not differ between the first and last MRI examinations (susceptibility, P = .95; R2*, P = .54). Conclusion No overall significant differences were found in susceptibility and R2* values of deep gray structures to suggest retained iron in the brain between ferumoxytol-exposed and unexposed children and young adults with arteriovenous malformations and in those exposed to ferumoxytol over time. © RSNA, 2020.

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study

BACKGROUND AND PURPOSE

Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor detection and tumor pathology classification.

MATERIALS AND METHODS

The study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons (n = 122), medulloblastoma (n = 272), pilocytic astrocytoma (n = 135), and ependymoma (n = 88). There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRIs as input to detect the presence of tumor and predict tumor class. Deep learning model performance was compared against that of 4 radiologists.

RESULTS

Model tumor detection accuracy exceeded an AUROC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F₁ score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate. Tumor type classification accuracy and F₁ score were higher than those of 2 of the 4 radiologists.

CONCLUSIONS

We present a multi-institutional deep learning model for pediatric posterior fossa tumor detection and classification with the potential to augment and improve the accuracy of radiologic diagnosis.

Variable Refocusing Flip Angle Single-Shot Imaging for Sedation-Free Fast Brain MRI

BACKGROUND AND PURPOSE

Conventional single-shot FSE commonly used for fast MRI may be suboptimal for brain evaluation due to poor image contrast, SNR, or image blurring. We investigated the clinical performance of variable refocusing flip angle single-shot FSE, a variation of single-shot FSE with lower radiofrequency energy deposition and potentially faster acquisition time, as an alternative approach to fast brain MR imaging.

MATERIALS AND METHODS

We retrospectively compared half-Fourier single-shot FSE with half- and full-Fourier variable refocusing flip angle single-shot FSE in 30 children. Three readers reviewed images for motion artifacts, image sharpness at the brain-fluid interface, and image sharpness/tissue contrast at gray-white differentiation on a modified 5-point Likert scale. Two readers also evaluated full-Fourier variable refocusing flip angle single-shot FSE against T2-FSE for brain lesion detectability in 38 children.

RESULTS

Variable refocusing flip angle single-shot FSE sequences showed more motion artifacts (P < .001). Variable refocusing flip angle single-shot FSE sequences scored higher regarding image sharpness at brain-fluid interfaces (P < .001) and gray-white differentiation (P < .001). Acquisition times for half- and full-Fourier variable refocusing flip angle single-shot FSE were faster than for single-shot FSE (P < .001) with a 53% and 47% reduction, respectively. Intermodality agreement between full-Fourier variable refocusing flip angle single-shot FSE and T2-FSE findings was near-perfect (κ = 0.90, κ = 0.95), with an 8% discordance rate for ground truth lesion detection.

CONCLUSIONS

Variable refocusing flip angle single-shot FSE achieved 2× faster scan times than single-shot FSE with improved image sharpness at brain-fluid interfaces and gray-white differentiation. Such improvements are likely attributed to a combination of improved contrast, spatial resolution, SNR, and reduced T2-decay associated with blurring. While variable refocusing flip angle single-shot FSE may be a useful alternative to single-shot FSE and, potentially, T2-FSE when faster scan times are desired, motion artifacts were more common in variable refocusing flip angle single-shot FSE, and, thus, they remain an important consideration before clinical implementation.

Brain iron deposition after Ferumoxytol-enhanced MRI: A study of Porcine Brains

Recent evidence of gadolinium deposition in the brain has raised safety concerns. Iron oxide nanoparticles are re-emerging as promising alternative MR contrast agents, because the iron core can be metabolized. However, long-term follow up studies of the brain after intravenous iron oxide administration have not been reported thus far. In this study, we investigated, if intravenously administered ferumoxytol nanoparticles are deposited in porcine brains.

Methods: In an animal care and use committee-approved prospective case-control study, ten Göttingen minipigs received either intravenous ferumoxytol injections at a dose of 5 mg Fe/kg (n=4) or remained untreated (n=6). Nine to twelve months later, pigs were sacrificed and the brains of all pigs underwent ex vivo MRI at 7T with T2 and T2*-weighted sequences. MRI scans were evaluated by measuring R2* values (R2*=1000/T2*) of the bilateral caudate nucleus, lentiform nucleus, thalamus, dentate nucleus, and choroid plexus. Pig brains were sectioned and stained with Prussian blue and evaluated for iron deposition using a semiquantitative scoring system. Data of ferumoxytol exposed and unexposed groups were compared with an unpaired t-test and a Mann-Whitney U test.

Results: T2 and T2* signal of the different brain regions was not visually different between ferumoxytol exposed and unexposed controls. There were no significant differences in R2* values of the different brain regions in the ferumoxytol exposed group compared to controls (p>0.05). Prussian blue stains of the same brain regions, scored according to a semiquantitative score, were not significantly different either between the ferumoxytol exposed group and unexposed controls (p>0.05).

Conclusions: Our study shows that intravenous ferumoxytol doses of 5-10 mg Fe/kg do not lead to iron deposition in the brain of pigs. We suggest iron oxide nanoparticles as a promising alternative for gadolinium-enhanced MRI.

Phase I study of BPM31510 and vitamin K in patients with high grade glioma recurrent after a bevacizumab-containing regimen

2543

Background: BPM31510 is an ubidecarenone-lipid conjugate nanodispersion in clinical development for advanced malignancies, including high grade glioma (HGG). BPM31510’s anti-cancer effect is mediated by induction of mitochondrial superoxide and activation of cell death in glioblastoma models. Herein, we present preliminary pharmaco-kinetic and dynamic data, and survival from a phase I study of BPM31510 + Vitamin K in HGG with progression after bevacizumab (BEV). Methods: This was an open-label phase I study of BPM31510 continuous infusion with Vitamin K (10mg IM qweek) using a mTPI design, starting at 110mg/kg 2X/week, allowing 2 dose escalations & 1 de-escalation. Patients had received ChemoRT and were in recurrence after BEV. Results: Of 12 patients treated with BPM31510, 9 completed the 28-day DLT period. 2 patients came off study for progressive disease; 1 patient after asymptomatic hemorrhage into tumor bed (G1). 10 patients had primary GB, 2 had AA. Median age was 54.5yo (27-67) and KPS 70 (60-90). On Day 1 of BPM31510, a dose dependent increase in Cmax was observed; Tmax values were similar for all doses. AUC was linear with dose escalation. For all doses, Day 4 Cmax values were higher compared to Day 1. In contrast there was variable decrease in Tmax (table). Of evaluable patients, 4 patients received the highest dose 171mg/kg, where a single patient experienced DLT: G3 AST & ALT. The most common grade 1/2 AEs were elevated AST, rash, and fatigue, each occurring in 4 patients. The mOS for 9 eligible/evaluable patients was 128 days (95% CI: 48-209) while PFS was 34 days (95% CI of mean 8.9). Two patients are currently alive >12 months. Conclusions: BPM31510 + vitamin K demonstrated a safe profile to maximum dose of 171mg/kg twice/week with potential therapeutic utility in treatment-refractory HGG patients. Multi-omic molecular profiles characterizing AE and response to be reported from the study will be investigated for next phase of clinical development. Clinical trial information: NCT03020602 . [Table: see text]

Ballistic transport and quantum unfurling in molecular junctions via minimal representations of quantum master equations

Quantum furling and unfurling are inelastic transitions between localized and delocalized electronic states. We predict scenarios where these processes govern charge transport through donor-bridge-acceptor molecular junctions. Like in the case of ballistic transport, the resulting currents are nearly independent of the molecular bridge length. However, currents involving quantum furling and unfurling processes can be controlled by the coupling to vibrations in the intra-molecular and the extra-molecular environment, which can be experimentally tuned. Our study is based on rate equations for exchange of energy (bosons) and particles (fermions) between the molecular bridge and its environment. An efficient algorithm is introduced for a compact representation of the relevant rate equations, which utilizes the redundancies in the rate matrix and the sparsity of the creation and annihilation operators in the molecular Fock space.

Advanced Imaging of Brain Metastases: From Augmenting Visualization and Improving Diagnosis to Evaluating Treatment Response

Early detection of brain metastases and differentiation from other neuropathologies is crucial. Although biopsy is often required for definitive diagnosis, imaging can provide useful information. After treatment commences, imaging is also performed to assess the efficacy of treatment. Contrast-enhanced magnetic resonance imaging (MRI) is the traditional imaging method for the evaluation of brain metastases, as it provides information about lesion size, morphology, and macroscopic properties. Newer MRI sequences have been developed to increase the conspicuity of detecting enhancing metastases. Other advanced MRI techniques, that have the capability to probe beyond the anatomic structure, are available to characterize micro-structures, cellularity, physiology, perfusion, and metabolism. Artificial intelligence provides powerful computational tools for detection, segmentation, classification, prediction, and prognosis. We highlight and review a few advanced MRI techniques for the assessment of brain metastases-specifically for (1) diagnosis, including differentiating between malignancy types and (2) evaluation of treatment response, including the differentiation between radiation necrosis and disease progression.

Altered cerebral perfusion in children with Langerhans cell histiocytosis after chemotherapy

BACKGROUND AND PURPOSE

Children with Langerhans cell histiocytosis (LCH) may develop a wide array of neurological symptoms, but associated cerebral physiologic changes are poorly understood. We examined cerebral hemodynamic properties of pediatric LCH using arterial spin-labeling (ASL) perfusion magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A retrospective study was performed in 23 children with biopsy-proven LCH. Analysis was performed on routine brain MRI obtained before or after therapy. Region of interest (ROI) methodology was used to determine ASL cerebral blood flow (CBF) (mL/100 g/min) in the following bilateral regions: angular gyrus, anterior prefrontal cortex, orbitofrontal cortex, dorsal anterior cingulate cortex, and hippocampus. Quantile (median) regression was performed for each ROI location. CBF patterns were compared between pre- and posttreatment LCH patients as well as with age-matched healthy controls.

RESULTS

Significantly reduced CBF was seen in posttreatment children with LCH compared to age-matched controls in angular gyrus (P = .046), anterior prefrontal cortex (P = .039), and dorsal anterior cingulate cortex (P = .023). Further analysis revealed dominant perfusion abnormalities in the right hemisphere. No significant perfusion differences were observed in the hippocampus or orbitofrontal cortex.

CONCLUSION

Perfusion in specific cerebral regions may be consistently reduced in children with LCH, and may represent effects of underlying disease physiology and/or sequelae of chemotherapy. Studies that combine a formal cognitive assessment and hemodynamic data may further provide insight into perfusion deficits associated with the disease and the potential neurotoxic effects in children treated by chemotherapy.

Utilization of Novel High-Resolution, MRI-Based Vascular Imaging Modality for Preoperative Stereoelectroencephalography Planning in Children: A Technical Note

INTRODUCTION

Stereoelectroencephalography (SEEG) is a powerful intracranial diagnostic tool that requires accurate imaging for proper electrode trajectory planning to ensure efficacy and maximize patient safety. Computed tomography (CT) angiography and digital subtraction angiography are commonly used, but recent developments in magnetic resonance angiography allow for high-resolution vascular visualization without added risks of radiation. We report on the accuracy of electrode placement under robotic assistance planning utilizing a novel high-resolution magnetic resonance imaging (MRI)-based imaging modality.

METHODS

Sixteen pediatric patients between February 2014 and October 2017 underwent SEEG exploration for epileptogenic zone localization. A gadolinium-enhanced 3D T1-weighted spoiled gradient recalled echo sequence with minimum echo time and repetition time was applied for background parenchymal suppression and vascular enhancement. Electrode placement accuracy was determined by analyzing postoperative CT scans laid over preoperative virtual electrode trajectory paths. Entry point, target point, and closest vessel intersection were measured.

RESULTS

For any intersection along the trajectory path, 57 intersected vessels were measured. The mean diameter of an intersected vessel was 1.0343 ± 0.1721 mm, and 21.05% of intersections involved superficial vessels. There were 157 overall intersection + near-miss events. The mean diameter for an involved vessel was 1.0236 ± 0.0928 mm, and superficial vessels were involved in 20.13%. Looking only at final electrode target, 3 intersection events were observed. The mean diameter of an intersected vessel was 1.0125 ± 0.2227 mm. For intersection + near-miss events, 24 were measured. An involved vessel's mean diameter was 1.1028 ± 0.2634 mm. For non-entry point intersections, 45 intersected vessels were measured. The mean diameter for intersected vessels was 0.9526 ± 0.0689 mm. For non-entry point intersections + near misses, 126 events were observed. The mean diameter for involved vessels was 0.9826 ± 0.1008 mm.

CONCLUSION

We believe this novel sequence allows better identification of superficial and deeper subcortical vessels compared to conventional T1-weighted gadolinium-enhanced MRI.

The effects of repetitive transcranial magnetic stimulation in older adults with mild cognitive impairment: a protocol for a randomized, controlled three-arm trial

BACKGROUND

Mild Cognitive Impairment (MCI) carries a high risk of progression to Alzheimer's disease (AD) dementia. Previous clinical trials testing whether cholinesterase inhibitors can slow the rate of progression from MCI to AD dementia have yielded disappointing results. However, recent studies of the effects of repetitive transcranial magnetic stimulation (rTMS) in AD have demonstrated improvements in cognitive function. Because few rTMS trials have been conducted in MCI, we designed a trial to test the short-term efficacy of rTMS in MCI. Yet, in both MCI and AD, we know little about what site of stimulation would be ideal for improving cognitive function. Therefore, two cortical sites will be investigated in this trial: (1) the dorsolateral prefrontal cortex (DLPFC), which has been well studied for treatment of major depressive disorder; and (2) the lateral parietal cortex (LPC), a novel site with connectivity to AD-relevant limbic regions.

METHODS/DESIGN

In this single-site trial, we plan to enroll 99 participants with single or multi-domain amnestic MCI. We will randomize participants to one of three groups: (1) Active DLPFC rTMS; (2) Active LPC rTMS; and (3) Sham rTMS (evenly split between DLPFC and LPC locations). After completing 20 bilateral rTMS treatment sessions, participants will be followed for 6 months to test short-term efficacy and track durability of effects. The primary efficacy measure is the California Verbal Learning Test-II (CVLT-II), assessed 1 week after intervention. Secondary analyses will examine effects of rTMS on other cognitive measures, symptoms of depression, and brain function with respect to the site of stimulation. Finally, selected biomarkers will be analyzed to explore predictors of response and mechanisms of action.

DISCUSSION

The primary aim of this trial is to test the short-term efficacy of rTMS in MCI. Additionally, the project will provide information on the durability of cognitive effects and potentially distinct effects of stimulating DLPFC versus LPC regions. Future efforts would be directed toward better understanding therapeutic mechanisms and optimizing rTMS for treatment of MCI. Ultimately, if rTMS can be utilized to slow the rate of progression to AD dementia, this will be a significant advancement in the field.

TRIAL REGISTRATION

Clinical Trials NCT03331796. Registered 6 November 2017, https://clinicaltrials.gov/ct2/show/NCT03331796. All items from the World Health Organization Trial Registration Data Set are listed in Appendix A.

PROTOCOL VERSION

This report is based on version 1, approved by the DSMB on 30 November, 2017 and amended on 14 August, 2018 and 19 September, 2019.

Patient-specific 3-dimensionally printed models for neurosurgical planning and education

OBJECTIVE

Advances in 3-dimensional (3D) printing technology permit the rapid creation of detailed anatomical models. Integration of this technology into neurosurgical practice is still in its nascence, however. One potential application is to create models depicting neurosurgical pathology. The goal of this study was to assess the clinical value of patient-specific 3D printed models for neurosurgical planning and education.

METHODS

The authors created life-sized, patient-specific models for 4 preoperative cases. Three of the cases involved adults (2 patients with petroclival meningioma and 1 with trigeminal neuralgia) and the remaining case involved a pediatric patient with craniopharyngioma. Models were derived from routine clinical imaging sequences and manufactured using commercially available software and hardware.

RESULTS

Life-sized, 3D printed models depicting bony, vascular, and neural pathology relevant to each case were successfully manufactured. A variety of commercially available software and hardware were used to create and print each model from radiological sequences. The models for the adult cases were printed in separate pieces, which had to be painted by hand, and could be disassembled for detailed study, while the model for the pediatric case was printed as a single piece in separate-colored resins and could not be disassembled for study. Two of the models were used for patient education, and all were used for presurgical planning by the surgeon.

CONCLUSIONS

Patient-specific 3D printed models are useful to neurosurgical practice. They may be used as a visualization aid for surgeons and patients, or for education of trainees.

Macrophage Exclusion after Radiation Therapy (MERT): A First in Human Phase I/II Trial using a CXCR4 Inhibitor in Glioblastoma

PURPOSE

Preclinical studies have demonstrated that postirradiation tumor revascularization is dependent on a stromal cell-derived factor-1 (SDF-1)/C-X-C chemokine receptor type 4 (CXCR4)-driven process in which myeloid cells are recruited from bone marrow. Blocking this axis results in survival improvement in preclinical models of solid tumors, including glioblastoma (GBM). We conducted a phase I/II study to determine the safety and efficacy of Macrophage Exclusion after Radiation Therapy (MERT) using the reversible CXCR4 inhibitor plerixafor in patients with newly diagnosed glioblastoma.

PATIENTS AND METHODS

We enrolled nine patients in the phase I study and an additional 20 patients in phase II using a modified toxicity probability interval (mTPI) design. Plerixafor was continuously infused intravenously via a peripherally inserted central catheter (PICC) line for 4 consecutive weeks beginning at day 35 of conventional treatment with concurrent chemoradiation. Blood serum samples were obtained for pharmacokinetic analysis. Additional studies included relative cerebral blood volume (rCBV) analysis using MRI and histopathology analysis of recurrent tumors.

RESULTS

Plerixafor was well tolerated with no drug-attributable grade 3 toxicities observed. At the maximum dose of 400 μg/kg/day, biomarker analysis found suprathreshold plerixafor serum levels and an increase in plasma SDF-1 levels. Median overall survival was 21.3 months [95% confidence interval (CI), 15.9-NA] with a progression-free survival of 14.5 months (95% CI, 11.9-NA). MRI and histopathology support the mechanism of action to inhibit postirradiation tumor revascularization.

CONCLUSIONS

Infusion of the CXCR4 inhibitor plerixafor was well tolerated as an adjunct to standard chemoirradiation in patients with newly diagnosed GBM and improves local control of tumor recurrences.

ACTR-59. A PHASE 1 STUDY OF BPM31510 PLUS VITAMIN K IN SUBJECTS WITH HIGH-GRADE GLIOMA THAT HAS RECURRED ON A BEVACIZUMAB-CONTAINING REGIMEN

BACKGROUND

High-grade gliomas (HGG) are characterized by dysregulated metabolism, utilizing glycolysis for energy production to support unrestricted growth. BPM 31510, an ubidecarenone (coenzyme Q10) containing lipid nanodispersion, causes a switch in cancer energy sourcing from glycolysis towards mitochondrial oxidative phosphorylation in vitro, reversing the Warburg effect and suggesting potential as an anti-tumor agent. The current study is a phase I study of BPM31510 + vitamin K in GB with tumor growth after bevacizumab (BEV).

METHODS

This is an open-label phase I study of BPM31510 continuous infusion with weekly vitamin K (10mg IM) in HGG patients using an mTPI design, starting at 110mg/kg, allowing for a single dose de-escalation and 2 dose-escalations. Patients had received first-line ChemoRadiation and were in recurrence following a BEV containing regimen.

RESULTS

9 eligible and evaluable patients completed the 28 day DLT period. 8 patients had primary GB, 1 had anaplastic astrocytoma with confirmed pathologic transformation to GB. Median age was 55 years (27–67) and median KPS 70 (60–90) at enrollment. 4 patients were treated at the highest dose 171mg/kg, where there was a single DLT: Grade 3 AST & ALT. The most common grade 1–2 AEs possibly, probably or definitely related to drug were elevated AST, rash, and fatigue, each occurring in 3 patients. Median OS for 9 eligible/evaluable patients was 128 days (95% CI: 48–209) while PFS was 34 days (CI of mean 8.9). 3 patients are currently alive; 2 patients have survived >1 year. PK/PD data are being processed and will be presented.

CONCLUSION

This study confirms that BPM 31510 + vitamin K is safe and feasible in treatment-refractory HGG patients. Though this study demonstrates safety at 171mg/kg, the proposed dose for future studies in GB, based on additional pre-clinical and non-GB clinical data is 88mg/kg.

Nodular Leptomeningeal Disease-A Distinct Pattern of Recurrence After Postresection Stereotactic Radiosurgery for Brain Metastases: A Multi-institutional Study of Interobserver Reliability

PURPOSE

For brain metastases, surgical resection with postoperative stereotactic radiosurgery is an emerging standard of care. Postoperative cavity stereotactic radiosurgery is associated with a specific, underrecognized pattern of intracranial recurrence, herein termed nodular leptomeningeal disease (nLMD), which is distinct from classical leptomeningeal disease. We hypothesized that there is poor consensus regarding the definition of LMD, and that a formal, self-guided training module will improve interrater reliability (IRR) and validity in diagnosing LMD.

METHODS AND MATERIALS

Twenty-two physicians at 16 institutions, including 15 physicians with central nervous system expertise, completed a 2-phase survey that included magnetic resonance imaging and treatment information for 30 patients. In the "pretraining" phase, physicians labeled cases using 3 patterns of recurrence commonly reported in prospective studies: local recurrence (LR), distant parenchymal recurrence (DR), and LMD. After a self-directed training module, participating physicians completed the "posttraining" phase and relabeled the 30 cases using the 4 following labels: LR, DR, classical leptomeningeal disease, and nLMD.

RESULTS

IRR increased 34% after training (Fleiss' Kappa K = 0.41 to K = 0.55, P < .001). IRR increased most among non-central nervous system specialists (+58%, P < .001). Before training, IRR was lowest for LMD (K = 0.33). After training, IRR increased across all recurrence subgroups and increased most for LMD (+67%). After training, ≥27% of cases initially labeled LR or DR were later recognized as nLMD.

CONCLUSIONS

This study highlights the large degree of inconsistency among clinicians in recognizing nLMD. Our findings demonstrate that a brief self-guided training module distinguishing nLMD can significantly improve IRR across all patterns of recurrence, and particularly in nLMD. To optimize outcomes reporting, prospective trials in brain metastases should incorporate central imaging review and investigator training.

Perfusion MRI-Based Fractional Tumor Burden Differentiates between Tumor and Treatment Effect in Recurrent Glioblastomas and Informs Clinical Decision-Making

BACKGROUND AND PURPOSE

Fractional tumor burden better correlates with histologic tumor volume fraction in treated glioblastoma than other perfusion metrics such as relative CBV. We defined fractional tumor burden classes with low and high blood volume to distinguish tumor from treatment effect and to determine whether fractional tumor burden can inform treatment-related decision-making.

MATERIALS AND METHODS

Forty-seven patients with high-grade gliomas (primarily glioblastoma) with recurrent contrast-enhancing lesions on DSC-MR imaging were retrospectively evaluated after surgical sampling. Histopathologic examination defined treatment effect versus tumor. Normalized relative CBV thresholds of 1.0 and 1.75 were used to define low, intermediate, and high fractional tumor burden classes in each histopathologically defined group. Performance was assessed with an area under the receiver operating characteristic curve. Consensus agreement among physician raters reporting hypothetic changes in treatment-related decisions based on fractional tumor burden was compared with actual real-time treatment decisions.

RESULTS

Mean lower fractional tumor burden, high fractional tumor burden, and relative CBV of the contrast-enhancing volume were significantly different between treatment effect and tumor (P = .002, P < .001, and P < .001), with tumor having significantly higher fractional tumor burden and relative CBV and lower fractional tumor burden. No significance was found with intermediate fractional tumor burden. Performance of the area under the receiver operating characteristic curve was the following: high fractional tumor burden, 0.85; low fractional tumor burden, 0.7; and relative CBV, 0.81. In comparing treatment decisions, there were disagreements in 7% of tumor and 44% of treatment effect cases; in the latter, all disagreements were in cases with scattered atypical cells.

CONCLUSIONS

High fractional tumor burden and low fractional tumor burden define fractions of the contrast-enhancing lesion volume with high and low blood volume, respectively, and can differentiate treatment effect from tumor in recurrent glioblastomas. Fractional tumor burden maps can also help to inform clinical decision-making.

Ferumoxytol-enhanced MRI for surveillance of pediatric cerebral arteriovenous malformations

OBJECTIVE

Children with intracranial arteriovenous malformations (AVMs) undergo digital DSA for lesion surveillance following their initial diagnosis. However, DSA carries risks of radiation exposure, particularly for the growing pediatric brain and over lifetime. The authors evaluated whether MRI enhanced with a blood pool ferumoxytol (Fe) contrast agent (Fe-MRI) can be used for surveillance of residual or recurrent AVMs.

METHODS

A retrospective cohort was assembled of children with an established AVM diagnosis who underwent surveillance by both DSA and 3-T Fe-MRI from 2014 to 2016. Two neuroradiologists blinded to the DSA results independently assessed Fe-enhanced T1-weighted spoiled gradient recalled acquisition in steady state (Fe-SPGR) scans and, if available, arterial spin labeling (ASL) perfusion scans for residual or recurrent AVMs. Diagnostic confidence was examined using a Likert scale. Sensitivity, specificity, and intermodality reliability were determined using DSA studies as the gold standard. Radiation exposure related to DSA was calculated as total dose area product (TDAP) and effective dose.

RESULTS

Fifteen patients were included in this study (mean age 10 years, range 3-15 years). The mean time between the first surveillance DSA and Fe-MRI studies was 17 days (SD 47). Intermodality agreement was excellent between Fe-SPGR and DSA (κ = 1.00) but poor between ASL and DSA (κ = 0.53; 95% CI 0.18-0.89). The sensitivity and specificity for detecting residual AVMs using Fe-SPGR were 100% and 100%, and using ASL they were 72% and 100%, respectively. Radiologists reported overall high diagnostic confidence using Fe-SPGR. On average, patients received two surveillance DSA studies over the study period, which on average equated to a TDAP of 117.2 Gy×cm2 (95% CI 77.2-157.4 Gy×cm2) and an effective dose of 7.8 mSv (95% CI 4.4-8.8 mSv).

CONCLUSIONS

Fe-MRI performed similarly to DSA for the surveillance of residual AVMs. Future multicenter studies could further investigate the efficacy of Fe-MRI as a noninvasive alternative to DSA for monitoring AVMs in children.

Physiological motion of the optic chiasm and its impact on stereotactic radiosurgery dose

OBJECTIVE

Avoidance of radiation-induced optic neuropathy (RION) from stereotactic radiosurgery (SRS) requires precise anatomical localization; however, no prior studies have characterized the physiologic motion of the optic chiasm. We measured the extent of chiasm motion and its impact on SRS dose.

METHODS

In this cross-sectional study, serial MRI was performed in multiple planes in 11 human subjects without optic pathway abnormalities to determine chiasm motion across time. Subsequently, the measured displacement was applied to the hypothetical chiasm dose received in 11 patients treated with SRS to a perichiasmatic lesion.

RESULTS

On sagittal images, the average anteroposterior chiasm displacement was 0.51 mm [95% confidence interval (CI) 0.27 - 0.75 mm], and the average superior-inferior displacement was 0.48 mm (95% CI 0.22 - 0.74 mm). On coronal images, the average superior-inferior displacement was 0.42 mm (95% CI 0.13 - 0.71 mm), and the average lateral displacement was 0.75 mm (95% CI 0.42 - 1.08 mm). In 11 patients who underwent SRS to a perichiasmatic lesion, the average displacements increased the maximum chiasm dose (Dmax) by a mean of 14 % (range 6-23 %; p < 0.001).

CONCLUSION

Average motion of the optic chiasm was approximately 0.50-0.75 mm, which increased chiasm Dmax by a mean of 14%. In the occasional patient with higher-than-average chiasm motion in a region of steep dose gradient, the increase in chiasm Dmax and risk of RION could be even larger. Similarly, previously reported chiasm dose constraints may underestimate the true dose received during radiosurgery.

ADVANCES IN KNOWLEDGE

To limit the risk of RION, clinicians may consider adding a 0.50-0.75 mm expansion to the chiasm avoidance structure.

Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI

BACKGROUND

Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multisequence 3D imaging.

PURPOSE

To demonstrate automated detection and segmentation of brain metastases on multisequence MRI using a deep-learning approach based on a fully convolution neural network (CNN).

STUDY TYPE

Retrospective.

POPULATION

In all, 156 patients with brain metastases from several primary cancers were included.

FIELD STRENGTH

1.5T and 3T. [Correction added on May 24, 2019, after first online publication: In the preceding sentence, the first field strength listed was corrected.] SEQUENCE: Pretherapy MR images included pre- and postgadolinium T₁ -weighted 3D fast spin echo (CUBE), postgadolinium T₁ -weighted 3D axial IR-prepped FSPGR (BRAVO), and 3D CUBE fluid attenuated inversion recovery (FLAIR).

ASSESSMENT

The ground truth was established by manual delineation by two experienced neuroradiologists. CNN training/development was performed using 100 and 5 patients, respectively, with a 2.5D network based on a GoogLeNet architecture. The results were evaluated in 51 patients, equally separated into those with few (1-3), multiple (4-10), and many (>10) lesions.

STATISTICAL TESTS

Network performance was evaluated using precision, recall, Dice/F1 score, and receiver operating characteristic (ROC) curve statistics. For an optimal probability threshold, detection and segmentation performance was assessed on a per-metastasis basis. The Wilcoxon rank sum test was used to test the differences between patient subgroups.

RESULTS

The area under the ROC curve (AUC), averaged across all patients, was 0.98 ± 0.04. The AUC in the subgroups was 0.99 ± 0.01, 0.97 ± 0.05, and 0.97 ± 0.03 for patients having 1-3, 4-10, and >10 metastases, respectively. Using an average optimal probability threshold determined by the development set, precision, recall, and Dice score were 0.79 ± 0.20, 0.53 ± 0.22, and 0.79 ± 0.12, respectively. At the same probability threshold, the network showed an average false-positive rate of 8.3/patient (no lesion-size limit) and 3.4/patient (10 mm³ lesion size limit).

DATA CONCLUSION

A deep-learning approach using multisequence MRI can automatically detect and segment brain metastases with high accuracy.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:175-182.

MR Imaging-Based Radiomic Signatures of Distinct Molecular Subgroups of Medulloblastoma

BACKGROUND AND PURPOSE

Distinct molecular subgroups of pediatric medulloblastoma confer important differences in prognosis and therapy. Currently, tissue sampling is the only method to obtain information for classification. Our goal was to develop and validate radiomic and machine learning approaches for predicting molecular subgroups of pediatric medulloblastoma.

MATERIALS AND METHODS

In this multi-institutional retrospective study, we evaluated MR imaging datasets of 109 pediatric patients with medulloblastoma from 3 children's hospitals from January 2001 to January 2014. A computational framework was developed to extract MR imaging-based radiomic features from tumor segmentations, and we tested 2 predictive models: a double 10-fold cross-validation using a combined dataset consisting of all 3 patient cohorts and a 3-dataset cross-validation, in which training was performed on 2 cohorts and testing was performed on the third independent cohort. We used the Wilcoxon rank sum test for feature selection with assessment of area under the receiver operating characteristic curve to evaluate model performance.

RESULTS

Of 590 MR imaging-derived radiomic features, including intensity-based histograms, tumor edge-sharpness, Gabor features, and local area integral invariant features, extracted from imaging-derived tumor segmentations, tumor edge-sharpness was most useful for predicting sonic hedgehog and group 4 tumors. Receiver operating characteristic analysis revealed superior performance of the double 10-fold cross-validation model for predicting sonic hedgehog, group 3, and group 4 tumors when using combined T1- and T2-weighted images (area under the curve = 0.79, 0.70, and 0.83, respectively). With the independent 3-dataset cross-validation strategy, select radiomic features were predictive of sonic hedgehog (area under the curve = 0.70-0.73) and group 4 (area under the curve = 0.76-0.80) medulloblastoma.

CONCLUSIONS

This study provides proof-of-concept results for the application of radiomic and machine learning approaches to a multi-institutional dataset for the prediction of medulloblastoma subgroups.

Quantification of Macrophages in High-Grade Gliomas by Using Ferumoxytol-enhanced MRI: A Pilot Study

Purpose To investigate ferumoxytol-enhanced MRI as a noninvasive imaging biomarker of macrophages in adults with high-grade gliomas. Materials and Methods In this prospective study, adults with high-grade gliomas were enrolled between July 2015 and July 2017. Each participant was administered intravenous ferumoxytol (5 mg/kg) and underwent 3.0-T MRI 24 hours later. Two sites in each tumor were selected for intraoperative sampling on the basis of the degree of ferumoxytol-induced signal change. Susceptibility and the relaxation rates R2* (1/T2*) and R2 (1/T2) were obtained by region-of-interest analysis by using the respective postprocessed maps. Each sample was stained with Prussian blue, CD68, CD163, and glial fibrillary acidic protein. Pearson correlation and linear mixed models were performed to assess the relationship between imaging measurements and number of 400× magnification high-power fields with iron-containing macrophages. Results Ten adults (four male participants [mean age, 65 years ± 9 {standard deviation}; age range, 57-74 years] and six female participants [mean age, 53 years ± 12 years; age range, 32-65 years]; mean age of all participants, 58 years ± 12 [age range, 32-74 years]) with high-grade gliomas were included. Significant positive correlations were found between susceptibility, R2*, and R2' and the number of high-power fields with CD163-positive (r range, 0.64-0.71; P < .01) and CD68-positive (r range, 0.55-0.57; P value range, .01-.02) iron-containing macrophages. No significant correlation was found between R2 and CD163-positive (r = 0.33; P = .16) and CD68-positive (r = 0.24; P = .32) iron-containing macrophages. Similar significance results were obtained with linear mixed models. At histopathologic analysis, iron particles were found only in macrophages; none was found in glial fibrillary acidic protein-positive tumor cells. Conclusion MRI measurements of susceptibility, R2*, and R2' (R2* - R2) obtained after ferumoxytol administration correlate with iron-containing macrophage concentration, and this shows their potential as quantitative imaging markers of macrophages in malignant gliomas. © RSNA, 2018 Online supplemental material is available for this article.