Dynamic Susceptibility Contrast Perfusion MRI Research Articles

Pseudo-resting-state functional MRI derived from dynamic susceptibility contrast perfusion MRI can predict cognitive impairment in glioma.

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 exam 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. N=24 consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, rs-fMRI, and neurocognitive assessment. Voxel-wise 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 pre-processing 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 non-impaired patients. 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=0.97) or language networks (P=0.30), but there was a difference in motor networks (P=0.02). 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%, ROC AUC=0.7762±0.0954 (SE), P=0.0221) and performance was not significantly different than full rs-fMRI predictions (AUC=0.8881±0.0733 (SE), P=0.0013, P=0.29 compared to pseudo-rs-fMRI). 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.ABBREVIATIONS: AUC = Area under curve; BOLD = Blood oxygenation level dependent; FC = Functional connectivity; MNI = Montreal Neurological Institute; ROC = Receiver operating characteristic; Rs-fMRI = Resting-state functional MRI.

SPINNED: Simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast MRI perfusion data.

To propose the simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast (DSC) MRI (SPINNED) as an alternative for more robust and accurate deconvolution compared to existing methods. The SPINNED method was developed by generating synthetic tissue residue functions and arterial input functions through mathematical simulations and by using them to create synthetic DSC MRI time series. The SPINNED model was trained using these simulated data to learn the underlying physical relation (deconvolution) between the DSC-MRI time series and the arterial input functions. The accuracy and robustness of the proposed SPINNED method were assessed by comparing it with two common deconvolution methods in DSC MRI data analysis, circulant singular value decomposition, and Volterra singular value decomposition, using both simulation data and real patient data. The proposed SPINNED method was more accurate than the conventional methods across all SNR levels and showed better robustness against noise in both simulation and real patient data. The SPINNED method also showed much faster processing speed than the conventional methods. These results support that the proposed SPINNED method can be a good alternative to the existing methods for resolving the deconvolution problem in DSC MRI. The proposed method does not require any separate ground-truth measurement for training and offers additional benefits of quick processing time and coverage of diverse clinical scenarios. Consequently, it will contribute to more reliable, accurate, and rapid diagnoses in clinical applications compared with the previous methods including those based on supervised learning.

Challenges, Limitations and Pitfalls of PET and Advanced MRI in Patients with Brain Tumors - A Report of the PET/RANO Group.

Brain tumor diagnostics have significantly evolved with the use of PET and advanced MRI techniques. In addition to anatomical MRI, these modalities may provide valuable information for several clinical applications such as differential diagnosis, delineation of tumor extent, prognostication, differentiation between tumor relapse and treatment-related changes, and the evaluation of response to anticancer therapy. In particular, joint recommendations of the RANO group, the EANO, and major European and American Nuclear Medicine societies highlighted that the additional clinical value of radiolabeled amino acids compared to anatomical MRI alone is outstanding and that its widespread clinical use should be supported. For advanced MRI and its steadily increasing use in clinical practice, the Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition provided more recently an updated acquisition protocol for the widely used dynamic susceptibility contrast perfusion MRI. Besides amino acid PET and perfusion MRI, other PET tracers and advanced MRI techniques (e.g., MR spectroscopy) are of considerable clinical interest and are increasingly integrated into everyday clinical practice. Nevertheless, these modalities have shortcomings which should be considered in clinical routine. This comprehensive review provides an overview of potential challenges, limitations and pitfalls associated with PET imaging and advanced MRI techniques in patients with gliomas or brain metastases. Despite these issues, PET imaging and advanced MRI techniques continue to play an indispensable role in brain tumor management. Acknowledging and mitigating these challenges through interdisciplinary collaboration, standardized protocols, and continuous innovation will further enhance the utility of these modalities in guiding optimal patient care.

Reproducibility of rCBV in glioblastomas using T2*-weighted perfusion MRI: an evaluation of sampling, normalization, and experience.

The reproducibility of relative cerebral blood volume (rCBV) measurements among readers with different levels of experience is a concern. This study aimed to investigate the inter-reader reproducibility of rCBV measurement of glioblastomas using the hotspot method in dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) with various strategies. In this institutional review board-approved single-center study, 30 patients with glioblastoma were retrospectively evaluated with DSC-MRI at a 3.0 Tesla scanner. Three groups of reviewers, including neuroradiologists, general radiologists, and radiology residents, calculated the rCBV based on the number of regions of interest (ROIs) and reference areas. For statistical analysis of feature reproducibility, the intraclass correlation coefficient (ICC) and Bland-Altman plots were used. Analyses were made among individuals, reader groups, reader-group pooling, and a population that contained all of them. For individuals, the highest inter-reader reproducibility was observed between neuroradiologists [ICC: 0.527; 95% confidence interval (CI): 0.21-0.74] and between residents (ICC: 0.513; 95% CI: 0.20-0.73). There was poor reproducibility in the analyses of individuals with different levels of experience (ICC range: 0.296-0.335) and in reader-wise and group-wise pooling (ICC range: 0.296-0.335 and 0.397-0.427, respectively). However, an increase in ICC values was observed when five ROIs were used. In an analysis of all strategies, the ICC for the centrum semiovale was significantly higher than that for contralateral white matter (P < 0.001). The inter-reader reproducibility of rCBV measurement was poor to moderate regardless of whether it was calculated by neuroradiologists, general radiologists, or residents, which may indicate the need for automated methods. Choosing five ROIs and using the centrum semiovale as a reference area may increase reliability for all users.

Probing the glioma microvasculature: a case series of the comparison between perfusion MRI and intraoperative high-frame-rate ultrafast Doppler ultrasound

BackgroundWe aimed to describe the microvascular features of three types of adult-type diffuse glioma by comparing dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) with intraoperative high-frame-rate ultrafast Doppler ultrasound.MethodsCase series of seven patients with primary brain tumours underwent both DSC perfusion MRI and intra-operative high-frame-rate ultrafast Doppler ultrasound. From the ultrasound images, three-dimensional vessel segmentation was obtained of the tumour vascular bed. Relative cerebral blood volume (rCBV) maps were generated with leakage correction and normalised to the contralateral normal-appearing white matter. From tumour histograms, median, mean, and maximum rCBV ratios were extracted.ResultsLow-grade gliomas (LGGs) showed lower perfusion than high-grade gliomas (HGGs), as expected. Within the LGG subgroup, oligodendroglioma showed higher perfusion than astrocytoma. In HGG, the median rCBV ratio for glioblastoma was 3.1 while astrocytoma grade 4 showed low perfusion with a median rCBV of 1.2. On the high-frame-rate ultrafast Doppler ultrasound images, all tumours showed a range of rich and organised vascular networks with visually apparent abnormal vessels, even in LGG.ConclusionsThis unique case series revealed in vivo insights about the microvascular architecture in both LGGs and HGGs. Ultrafast Doppler ultrasound revealed rich vascularisation, also in tumours with low perfusion at DSC MRI. These findings warrant further investigations using advanced MRI postprocessing, in particular for characterising adult-type diffuse glioma.Relevance statementOur findings challenge the current assumption behind the estimation of relative cerebral blood volume that the distribution of blood vessels in a voxel is random.Key points• Ultrafast Doppler ultrasound revealed rich vascularity irrespective of perfusion dynamic susceptibility contrast MRI state.• Rich and organised vascularisation was also observed even in low-grade glioma.• These findings challenge the assumptions for cerebral blood volume estimation with MRI.Graphical

Low rCBV values in glioblastoma tumor progression under chemoradiotherapy.

After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence. Inclusion criteria were (1) age > 18years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software. Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time. Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.

Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol.

Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying biology remains ambiguous. Standard (clinical) tissue sampling fails to capture the full heterogeneity of the disease. Biopsies are required to obtain a pathological diagnosis and are predominantly taken from the tumor core, which often has different traits to the surrounding invasive tumor that typically leads to recurrent disease. One approach to solving this issue is to characterize the spatial heterogeneity of molecular, genetic, and cellular features of glioma through the intraoperative collection of multiple image-localized biopsy samples paired with multi-parametric MRIs. We have adopted this approach and are currently actively enrolling patients for our 'Image-Based Mapping of Brain Tumors' study. Patients are eligible for this research study (IRB #16-002424) if they are 18 years or older and undergoing surgical intervention for a brain lesion. Once identified, candidate patients receive dynamic susceptibility contrast (DSC) perfusion MRI and diffusion tensor imaging (DTI), in addition to standard sequences (T1, T1Gd, T2, T2-FLAIR) at their presurgical scan. During surgery, sample anatomical locations are tracked using neuronavigation. The collected specimens from this research study are used to capture the intra-tumoral heterogeneity across brain tumors including quantification of genetic aberrations through whole-exome and RNA sequencing as well as other tissue analysis techniques. To date, these data (made available through a public portal) have been used to generate, test, and validate predictive regional maps of the spatial distribution of tumor cell density and/or treatment-related key genetic marker status to identify biopsy and/or treatment targets based on insight from the entire tumor makeup. This type of methodology, when delivered within clinically feasible time frames, has the potential to further inform medical decision-making by improving surgical intervention, radiation, and targeted drug therapy for patients with glioma.

NIMG-09. APPLICATION OF FRACTIONAL TUMOR BURDEN MAPPING TO MONITOR GLIOBLASTOMA PROGRESSION IN THE PHASE 1 TRIAL OF GALLIUM MALTOLATE

Abstract BACKGROUND To address the need for improved glioblastoma (GBM) therapeutics, a Phase 1 trial of gallium maltolate (GaM) for recurrent GBM is ongoing. GaM targets GBM iron metabolism, representing a novel therapeutic mechanism to treat GBM. Monitoring GBM progression is typically accomplished by standard MRI protocols. However, distinguishing progression from treatment effect is often difficult using standard MRI alone; this is especially true for experimental therapeutics. Fractional tumor burden (FTB) mapping incorporates dynamic susceptibility contrast perfusion MRI to generate spatial and quantifiable tumor likelihood estimates. Here, we present three cases from the Phase I trial of GaM to illustrate application of FTB mapping in the clinical trial setting. METHODS Patients enrolled in the GaM trial receive pre-trial baseline imaging and subsequent imaging at 8-week intervals. For each imaging timepoint, an FTB map was created from tissue-validated thresholds of standardized relative cerebral blood volume (sRCBV) in areas of enhancement as determined by pre/post T1 subtraction. RESULTS Case #1 illustrates low FTB-determined tumor probability in a patient with minimal disease who did not progress while on trial for &amp;gt; 33 weeks. Case #2 shows an increase in tumor probability concurrent with radiographic and pathology-confirmed progression soon after initiating GaM. Case #3 demonstrates an increase in tumor probability soon after GaM initiation which preceded an increase in volume by &amp;gt; 10 weeks; GBM progression was confirmed by pathology. CONCLUSIONS The presented cases illustrate the utility of FTB mapping for monitoring GBM progression in the setting of GaM treatment. FTB maps could predict disease progression before standard MRI in some patients. Our experience implicates FTB mapping as an important imaging tool in future GBM clinical trials. The cases add to previous reports that FTB is useful in distinguishing progression from treatment effect with standard treatment regimens.

NIMG-12. SPATIALLY MAPPING TREATMENT-EFFECT IN RECURRENT GLIOMA WITH PHYSIOLOGIC MRI AND DEEP LEARNING

Abstract INTRODUCTION Discriminating between glioma tumor recurrence (rTumor) and treatment-induced effects (TxE) from chemo and radiotherapy using MRI is an ongoing challenge in neuro-oncology. Although deep learning has been used to characterize suspicious lesions, these models typically do not account for lesions that are comprised of mixtures of rTumor and TxE components. We hypothesize that using an approach that includes using tissue samples with known location on MRI, incorporating perfusion-weighted and diffusion-weighted with anatomical MRI, self-supervised pretraining, and a novel ensembling strategy will improve performance and attain spatial maps of rTumor and TxE for determining subsequent treatment. METHODS Using 218 pathology confirmed tissue samples with coordinates on multi-parametric MRI from 111 patients with suspected tumor progression, we developed a deep learning approach to spatially map intratumoral regions of rTumor and TxE. Our model leveraged 10mm isotropic cubes centered on the tissue sample coordinates that includes Diffusion-Weighted and Dynamic Susceptibility-Contrast Perfusion MRI and large amounts of pathologically unlabeled data from the lesion in self-supervised pretraining. The multiple networks of the ensemble were generated through repeated constrained cross validation (RC-CV) which enabled unique repetitions of training with more variation in class proportions. RESULTS Our best classifier performed with a RC-CV/test AUROC of 0.85/0.81 and was able to generate maps of tumor probability as well as ensenble variance and uncertainty. Ensemble variance was significantly higher in prediction failures of rTumor (P=.006) and epistemic uncertainty was significantly higher (P=.002) in prediction failures of TxE in training. Test Performance dropped by 14.7% when removing self-supervised pretraining, 21.3% when removing physiological imaging contrasts, and 1.2% when ensembling across standard 4-fold CV. CONCLUSION The AUROC of .81 supports the feasibility of discriminating between TxE and rTumor within a single lesion non-invasively. Physiologic MRI, pretraining on pathology unlabeled data, and ensembling networks, improve performance and help characterize model failures.

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

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

Vascular differences between IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 at imaging and transcriptomic levels.

Global agreement in central nervous system (CNS) tumor classification is essential for predicting patient prognosis and determining the correct course of treatment, as well as for stratifying patients for clinical trials at international level. The last update by the World Health Organization of CNS tumor classification and grading in 2021 considered, for the first time, IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 as different tumors. Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 occur early and, importantly, contribute to gliomagenesis. IDH mutation produces a metabolic reprogramming of tumor cells, thus affecting the processes of hypoxia and vascularity, resulting in a clear advantage for those patients who present with IDH-mutated astrocytomas. Despite the clinical relevance of IDH mutation, current protocols do not include full sequencing for every patient. Alternative biomarkers could be useful and complementary to obtain a more reliable classification. In this sense, magnetic resonance imaging (MRI)-perfusion biomarkers, such as relative cerebral blood volume and flow, could be useful from the moment of presurgery, without incurring additional financial costs or requiring extra effort. The main purpose of this work is to analyze the vascular and hemodynamic differences between IDH-wildtype glioblastoma and IDH-mutant astrocytoma. To achieve this, we evaluate and validate the association between dynamic susceptibility contrast-MRI perfusion biomarkers and IDH mutation status. In addition, to gain a deeper understanding of the vascular differences in astrocytomas depending on the IDH mutation, we analyze the transcriptomic bases of the vascular differences.

Diagnostic Value of Dynamic Contrast-Enhanced (DCE), Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) Perfusion MRI for Differentiation of High-Grade and Low-Grade Gliomas

Objective: To evaluate dynamic contrast-enhanced (DCE), dynamic susceptibility contrast (DSC), and arterial spin labeling (ASL)-derived perfusion magnetic resonance imaging (MRI) parameters as a non-invasive technique for differentiating between high-grade gliomas (HGGs) and low-grade gliomas (LGGs), and to determine the diagnostic value of each parameter. Materials and Methods: Twenty-four patients with histopathologically confirmed HGGs or LGGs underwent DCE-, DSC-, and ASL-magnetic resonance perfusion (MRP). Retrospective qualitative and quantitative assessment of MRP-derived parameters, including DCE-Ktrans, DCE-Ve, DCE-Vp, DSC-rCBV, DSC-rCBF, and ASL-rCBF were performed, and the diagnostic value of each parameter was determined using ROC analysis. Results: Of the 24 patients enrolled in the present study, which included 10 LGGs and 14 HGGs, DCE-derived Vp showed the best diagnostic performance for differentiating between HGGs and LGGs (AUC 0.833, cutoff &gt;0.0002 mL/100 g, p=0.018, 100% sensitivity, 28.6% specificity), followed by DCE-derived Ktrans (AUC 0.75, cutoff &gt;0.024 min⁻¹, p=0.011, 58.3% sensitivity, 100% specificity) and DSC-derived normalized rCBV (AUC 0.75, p=0.021, cutoff &gt;1.15, 100% sensitivity, 37.5% specificity). The ASL-derived normalized rCBF showed no statistically significant difference between HGGs and LGGs (AUC 0.457, p=0.757). Conclusion: DCE-derived Vp, DCE-derived Ktrans, and DSC-derived rCBV are helpful perfusion MRI parameters for differentiating HGGs and LGGs, with DCE-derived Vp showing the best diagnostic performance in the present study. Keywords: DCE; DSL; ASL; Perfusion MR; Glioma

Large-scale transient peri-ictal perfusion magnetic resonance imaging abnormalities detected by quantitative image analysis.

Epileptic seizures require a rapid and safe diagnosis to minimize the time from onset to adequate treatment. Some epileptic seizures can be diagnosed clinically with the respective expertise. For more subtle seizures, imaging is mandatory to rule out treatable structural lesions and potentially life-threatening conditions. MRI perfusion abnormalities associated with epileptic seizures have been reported in CT and MRI studies. However, the interpretation of transient peri-ictal MRI abnormalities is routinely based on qualitative visual analysis and therefore reader dependent. In this retrospective study, we investigated the diagnostic yield of visual analysis of perfusion MRI during ictal and postictal states based on comparative expert ratings in 51 patients. We further propose an automated semi-quantitative method for perfusion analysis to determine perfusion abnormalities observed during ictal and postictal MRI using dynamic susceptibility contrast MRI, which we validated on a subcohort of 27 patients. The semi-quantitative method provides a parcellation of 3D T1-weighted images into 32 standardized cortical regions of interests and subcortical grey matter structures based on a recently proposed method, direct cortical thickness estimation using deep learning-based anatomy segmentation and cortex parcellation for brain anatomy segmentation. Standard perfusion maps from a Food and Drug Administration-approved image analysis tool (Olea Sphere 3.0) were co-registered and investigated for region-wise differences between ictal and postictal states. These results were compared against the visual analysis of two readers experienced in functional image analysis in epilepsy. In the ictal group, cortical hyperperfusion was present in 17/18 patients (94% sensitivity), whereas in the postictal cohort, cortical hypoperfusion was present only in 9/33 (27%) patients while 24/33 (73%) showed normal perfusion. The (semi-)quantitative dynamic susceptibility contrast MRI perfusion analysis indicated increased thalamic perfusion in the ictal cohort and hypoperfusion in the postictal cohort. Visual ratings between expert readers performed well on the patient level, but visual rating agreement was low for analysis of subregions of the brain. The asymmetry of the automated image analysis correlated significantly with the visual consensus ratings of both readers. We conclude that expert analysis of dynamic susceptibility contrast MRI effectively discriminates ictal versus postictal perfusion patterns. Automated perfusion evaluation revealed favourable interpretability and correlated well with the classification of the visual ratings. It may therefore be employed for high-throughput, large-scale perfusion analysis in extended cohorts, especially for research questions with limited expert rater capacity.

Utility of dynamic susceptibility contrast MRI for differentiation between paragangliomas and meningiomas in the cerebellopontine angle and jugular foramen region

PurposeDifferentiation of paragangliomas and meningiomas can be a challenge. This study aimed to assess the utility of dynamic susceptibility contrast perfusion MRI (DSC-MRI) to distinguish paragangliomas from meningiomas. MethodsThis retrospective study included 40 patients with paragangliomas and meningiomas in the cerebellopontine angle and jugular foramen region between March 2015 and February 2022 in a single institution. Pretreatment DSC-MRI and conventional MRI were performed in all cases. Normalized relative cerebral blood volume (nrCBV), relative cerebral blood flow (nrCBF), relative mean transit time (nrMTT), and time to peak (nTTP) as well as conventional MRI features were compared between the 2 tumor types and between meningioma subtypes as appropriate. Receiver operating characteristic curve and multivariate logistic regression analysis were performed. ResultsTwenty-eight meningiomas including 8 WHO grade II meningiomas (12 males, 16 females; median age 55 years) and 12 paragangliomas (5 males, 7 females; median age 35 years) were included in this study. Paragangliomas had a higher rate of cystic/necrotic changes (10/12 vs 10/28; P = 0.014), a higher rate of internal flow voids (9/12 vs 8/28; P = 0.013), higher nrCBV (median 9.78 vs 6.64; P = 0.04), and shorter nTTP (median 0.78 vs 1.06; P < 0.001) than meningiomas. There was no difference in conventional imaging features and DSC-MRI parameters between meningioma subtypes. nTTP was identified as the most significant parameter for the 2 tumor types in the multivariate logistic regression analysis (P = 0.009). ConclusionsIn this small retrospective study, DSC-MRI perfusion differences were observed between paragangliomas and meningiomas, but not between grade I and II meningiomas.

Longitudinal evaluation of the functional connectivity changes in the secondary somatosensory cortex (S2) of the monkey brain during acute stroke

BackgroundSomatosensory deficits are frequently seen in acute stroke patients and may recover over time and affect functional outcome. However, the underlying mechanism of function recovery remains poorly understood. In the present study, progressive function alteration of the secondary somatosensory cortex (S2) and its relationship with regional perfusion and neurological outcome were examined using a monkey model of stroke. Methods and materialsRhesus monkeys (n = 4) were induced with permanent middle cerebral artery occlusion (pMCAo). Resting-state functional MRI, dynamic susceptibility contrast perfusion MRI, diffusion-weighted, T1 and T2 weighted images were collected before surgery and at 4–6, 48, and 96 h post stroke on a 3T scanner. Progressive changes of relative functional connectivity (FC), cerebral blood flow (CBF), and CBF/Tmax (Time to Maximum) of affected S2 regions were evaluated. Neurological deficits were assessed using the Spetzler approach. ResultsIschemic lesion was evidently seen in the MCA territory including S2 in each monkey. Relative FC of injured S2 regions decreased substantially following stroke. Spetzler scores dropped substantially at 24 h post stroke but slightly recovered from Day 2 to Day 4. Relative FC progressively increased from 6 to 48 and 96 h post stroke and correlated significantly with relative CBFand CBF/Tmax changes. ConclusionThe present study revealed the progressive alteration of function connectivity in S2 during acute stroke. The preliminary results suggested the function recovery might start couple days post occlusion and collateral circulation might play a key role in the recovery of somatosensory function after stroke insult. The relative function connectivity in S2 may provide additional information for prediction of functional outcome in stroke patients.

NIMG-44. DSC-MRI FRACTIONAL TUMOR BURDEN VOLUME PREDICTS OVERALL SURVIVAL IN UNMETHYLATED NEWLY DIAGNOSED HIGH GRADE GLIOMA

Abstract OBJECTIVE Image maps of Fractional Tumor Burden (FTB), derived from dynamic susceptibility contrast (DSC) perfusion MRI, provide clinically meaningful information for glioma treatment management. The goal of this study was to determine if presurgical FTB is predictive of overall survival (OS) in high-grade glioma (HGG) classified according to WHO 2016 criteria. METHODS Standardized relative cerebral blood volume (sRCBV) maps were created and co-registered with T1+C images using Horos (Version 4.0.0) and Imaging Biometrics software (Version 21.05) (Elm Grove, WI). Enhancing tumor volumes were determined from calibrated pre/post T1 difference (dT1) maps. Tissue-validated sRCBV thresholds were used to create FTB class maps within enhancing lesion with red regions (sRCBV &amp;gt; 1.556) indicating a high probability of vascular tumor, blue regions (sRCBV&amp;lt; 1.0) indicating avascular (non-tumor) tissue and yellow representing tissue with a lower probability of vascular tumor. FTB volume fractions (FTBv) for all vascular tumor (sRCBV &amp;gt;1.0) or the most vascular tumor (sRCBV &amp;gt; 1.566) were determined. Subjects were separated by MGMT methylation status. GraphPad Prism statistical software (Version 9.3.1) was used for Kaplan Meier survival analysis at 12 and 24 months with patients stratified by median FTBv. RESULTS Forty-one subjects (23 males, 18 females) with a median age of 59.45 years were included. Median 12-month and overall survival of unmethylated groups stratified by FTBv (rCBV &amp;gt; 1.0) of 8.33cc was 10.69 and 15.35 months (p=.0453; p=.0317). Unmethylated subjects stratified with FTBv (rCBV &amp;gt; 1.566) of 7.13cc had a median survival of 10.69 and 15.20 with short- and long-term survival distinguished at 12 months (p=0.0033), 24 months (p=0.0002) and overall (p=0.0002). No significant difference in survival was found between the methylated subgroups with FTBv (rCBV &amp;gt; 1.0) or FTBv (rCBV &amp;gt; 1.566) stratified analyses. CONCLUSION These results demonstrate that pre-surgical FTBv is predictive of OS in newly diagnosed unmethylated high-grade glioma.

NIMG-90. DIFFERENTIATION OF INTRACRANIAL SOLITARY FIBROUS TUMOR AND MENINGIOMA ON CONVENTIONAL, DIFFUSION-WEIGHTED, AND DYNAMIC SUSCEPTIBILITY CONTRAST PERFUSION MRI

Abstract BACKGROUND AND PURPOSE To evaluate the differences in the imaging findings of intracranial solitary fibrous tumor (SFT) and meningioma on dynamic susceptibility contrast (DSC) perfusion MRI, apparent diffusion coefficient (ADC), and conventional sequences. METHODS Between January 2016 and April 2022, the study enrolled 14 (median, 46 years [range, 25–74]; six females; seven with DSC-MRI) and 27 patients (median, 53 years [21–83]; 23 females; all with DSC-MRI) with pathologically proven SFT and meningioma, respectively. The normalized relative cerebral blood volume and flow (nrCBV and nrCBF), percentage signal recovery (PSR), normalized mean ADC (nADCmean), and conventional imaging features, including T1-weighted hyperintensity, were evaluated and statistically compared using Bonferonni correction. RESULTS PSR was significantly lower in SFT compared with that in meningioma (median, 22.5 [range, 6.4–48.8] vs. 70.1 [range, 18.6–104.2], p&amp;lt; 0.001). The majority of SFT showed mainly T1-weighted hyperintensities compared to the gray matter, while only one meningioma showed the finding (8/14 [57.1%] vs. 1/27 [3.7%], p&amp;lt; 0.001). No significant difference was observed in nrCBV, nrCBF, or nADCmean. CONCLUSIONS PFS was significantly lower in intracranial SFT compared with that in meningioma, indicating the difference in capillary permeability between the tumors. Comparing the hyperintensity on T1WI of the solid components with that of the cerebral cortex was a simple and useful characteristic to differentiate SFT from meningioma.

Intracranial paragangliomas versus schwannomas: Role of dynamic susceptibility contrast perfusion and diffusion MRI.

Background and PurposeDifferentiating paragangliomas from schwannomas and distinguishing sporadic from neurofibromatosis type 2 (NF 2)‐related schwannomas is challenging but clinically important. This study aimed to assess the utility of dynamic susceptibility contrast perfusion MRI (DSC‐MRI) and diffusion‐weighted imaging (DWI) in discriminating infratentorial extra‐axial schwannomas from paragangliomas and NF2‐related schwannomas.MethodsThis retrospective study included 41 patients diagnosed with paragangliomas, sporadic schwannomas, and NF2‐related schwannomas in the infratentorial extra‐axial space between April 2013 and August 2021. All cases had pretreatment DSC‐MRI and DWI. Normalized mean apparent diffusion coefficient (nADCmean), normalized relative cerebral blood volume (nrCBV), and normalized relative cerebral blood flow (nrCBF) were compared between paragangliomas and schwannomas and between sporadic and NF2‐related schwannomas as appropriate.ResultsnrCBV and nrCBF were significantly higher in paragangliomas than in sporadic/NF2‐related schwannomas (nrCBV: median 11.5 vs. 1.14/3.74; p < .001 and .004, nrCBF: median 7.43 vs. 1.13/2.85; p < .001 and .007, respectively), while nADCmean were not. The corresponding diagnostic performances were area under the curves (AUCs) of .99/.92 and 1.0/.90 with cutoffs of 2.56/4.22 and 1.94/3.36, respectively. nADCmean were lower, and nrCBV and nrCBF were higher in NF2‐related than in sporadic schwannomas (nADCmean: median 1.23 vs. 1.58, nrCBV: median 3.74 vs. 1.14, nrCBF: median 2.85 vs. 1.13; all p < .001), and the corresponding diagnostic performances were AUCs of .93, .91, and .95 with cutoffs of 1.37, 2.63, and 2.48, respectively.ConclusionsDSC‐MRI and DWI both can aid in differentiating paragangliomas from schwannomas and sporadic from NF2‐related schwannomas.

Salvage multiple burr hole surgery in patients with Moyamoya disease: efficacy evaluation using probabilistic independent component analysis of dynamic susceptibility contrast perfusion MRI

Multiple burr hole surgery is considered to be an option for achieving indirect revascularization in patients with ischemic Moyamoya disease (MMD). We aimed to investigate the efficacy of stand-alone multiple burr hole surgery for salvage revascularization in patients with MMD by assessing the hemodynamic changes via normalized time-to-peak (nTTP) analysis and independent component analysis (ICA) of preoperative and postoperative dynamic susceptibility contrast (DSC) perfusion MRI data. The DSC perfusion MRI data of 25 hemispheres from 21 patients with MMD, who underwent multiple burr hole surgery for salvage revascularization due to persistent or recurrent symptoms after primary revascularization with modified encephaloduroarteriosynangiosis (mEDAS), were analyzed. The nTTP, which was measured using the region of interests covering the entire surgical hemisphere, was compared between the preoperative and postoperative images. ICA was used to compare the relative arterial and venous components of the surgical hemispheres between the respective preoperative and postoperative images. The median postoperative nTTP (1.80s) was significantly shorter than the median preoperative nTTP (4.10s) (P < 0.001). The postoperative relative arterial component of the surgical hemisphere (median: 0.04) was significantly higher than the preoperative relative arterial component (median: - 0.02, P < 0.001). In contrast, the postoperative relative venous component of the surgical hemisphere (median: - 0.05) was significantly lower than the preoperative value (median: 0.05, P < 0.001). The improvement in cerebral perfusion parameters observed on postoperative DSC perfusion MRI demonstrated that stand-alone multiple burr hole surgery could be a favorable salvage revascularization technique after mEDAS failure in patients with ischemic MMD.

Diagnostic performance of DSC perfusion MRI to distinguish tumor progression and treatment-related changes: a systematic review and meta-analysis.

BackgroundIn patients with high-grade glioma (HGG), true disease progression and treatment-related changes often appear similar on magnetic resonance imaging (MRI), making it challenging to evaluate therapeutic response. Dynamic susceptibility contrast (DSC) MRI has been extensively studied to differentiate between disease progression and treatment-related changes. This systematic review evaluated and synthesized the evidence for using DSC MRI to distinguish true progression from treatment-related changes.MethodsWe searched Ovid MEDLINE and the Ovid MEDLINE in-process file (January 2005–October 2019) and the reference lists. Studies on test performance of DSC MRI using relative cerebral blood volume in HGG patients were included. One investigator abstracted data, and a second investigator confirmed them; two investigators independently assessed study quality. Meta-analyses were conducted to quantitatively synthesize area under the receiver operating curve (AUROC), sensitivity, and specificity.ResultsWe screened 1177 citations and included 28 studies with 638 patients with true tumor progression, and 430 patients with treatment-related changes. Nineteen studies reported AUROC and the combined AUROC is 0.85 (95% CI, 0.81–0.90). All studies contributed data for sensitivity and specificity, and the pooled sensitivity and specificity are 0.84 (95% CI, 0.80–0.88), and 0.78 (95% CI, 0.72–0.83). Extensive subgroup analyses based on study, treatment, and imaging characteristics generally showed similar results.ConclusionsThere is moderate strength of evidence that relative cerebral blood volume obtained from DSC imaging demonstrated “excellent” ability to discriminate true tumor progression from treatment-related changes, with robust sensitivity and specificity.