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The dynamic susceptibility contrast (DSC) MRI measures of relative cerebral blood volume (rCBV) play a central role in monitoring therapeutic response and disease progression in patients with gliomas. Previous investigations have demonstrated promise of using rCBV in classifying tumor grade, elucidating tumor viability after therapy, and differentiating pseudoprogression and pseudoresponse. However, the quantification and reproducibility of rCBV measurements across patients, devices, and software remain a critical barrier to routine or clinical trial use of longitudinal DSC MRI in patients with gliomas. To address this limitation, the RSNA DSC MRI Biomarker Committee of the Quantitative Imaging Biomarkers Alliance developed a Profile that defines statistics-based claims for the precision of longitudinal measurements. Although rCBV is the clinical marker of interest, the Profile focused on the reproducibility of the measured quantitative imaging biomarker, which is the area under the contrast agent concentration-time curve (AUC) normalized by the mean value of normal-appearing contralateral white matter tissue (tissue-normalized AUC values). Based on previous reports of within-subject coefficient of variation (wCV) in the tissue-normalized AUC values for enhancing gliomas (wCV = 0.31), an increase of 182% or more with respect to the baseline tissue-normalized AUC value indicates that an increase has occurred with 95% confidence. In contrast, a decrease of 64% or more with respect to baseline suggests that a decrease has occurred with 95% confidence. Similarly, an increase of 399% or more in the tissue-normalized AUC values in normal brain gray matter tissue (wCV = 0.40) suggests that an increase has occurred with 95% confidence, whereas a decrease of 80% or more with respect to baseline suggests that a decrease has occurred with 95% confidence. This article provides the rationale for these claims and the compliance activities needed to achieve these claims. Potential updates to incorporate new data based on advances in technology and clinical care in the Profile are also discussed., (© RSNA, 2024 See also the editorial by Peters in this issue.)

Objective. We aim to develop a Multi-modal Fusion and Feature Enhancement U-Net (MFFE U-Net) coupling with stem cell niche proximity estimation to improve voxel-wise Glioblastoma (GBM) recurrence prediction. Approach. 57 patients with pre- and post-surgery magnetic resonance (MR) scans were retrospectively solicited from 4 databases. Post-surgery MR scans included two months before the clinical diagnosis of recurrence and the day of the radiologicaly confirmed recurrence. The recurrences were manually annotated on the T1ce. The high-risk recurrence region was first determined. Then, a sparse multi-modal feature fusion U-Net was developed. The 50 patients from 3 databases were divided into 70% training, 10% validation, and 20% testing. 7 patients from the 4th institution were used as external testing with transfer learning. Model performance was evaluated by recall, precision, F1-score, and Hausdorff Distance at the 95% percentile (HD95). The proposed MFFE U-Net was compared to the support vector machine (SVM) model and two state-of-the-art neural networks. An ablation study was performed. Main results. The MFFE U-Net achieved a precision of 0.79 ± 0.08, a recall of 0.85 ± 0.11, and an F1-score of 0.82 ± 0.09. Statistically significant improvement was observed when comparing MFFE U-Net with proximity estimation couple SVM (SVM PE ), mU-Net, and Deeplabv3. The HD95 was 2.75 ± 0.44 mm and 3.91 ± 0.83 mm for the 10 patients used in the model construction and 7 patients used for external testing, respectively. The ablation test showed that all five MR sequences contributed to the performance of the final model, with T1ce contributing the most. Convergence analysis, time efficiency analysis, and visualization of the intermediate results further discovered the characteristics of the proposed method. Significance . We present an advanced MFFE learning framework, MFFE U-Net, for effective voxel-wise GBM recurrence prediction. MFFE U-Net performs significantly better than the state-of-the-art networks and can potentially guide early RT intervention of the disease recurrence., (© 2024 Institute of Physics and Engineering in Medicine.)

Contrast transport models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Conte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Cushing's disease manifests as symptoms of glucocorticoid excess secondary to the increased secretion of corticotropin by a corticotroph adenoma in the pituitary gland. Unfortunately, magnetic resonance imaging (MRI) performed at conventional clinical field strengths of 1.5 or 3 Tesla has limited sensitivity for the detection of these pituitary tumors, and radiologic uncertainty often necessitates more invasive workup to confirm diagnosis and guide resection. It has been postulated that higher static magnetic field strengths may increase the adenoma detection rate and thus the utility of MRI for this clinical application. In this report, we describe our initial experience using ultra-high field 7 Tesla (7 T) MRI in patients with suspected Cushing's disease and negative or equivocal imaging at conventional field strengths. We performed contrast-enhanced 7 T pituitary MRI in 10 patients with up to three different T1-weighted sequences and correlated the imaging abnormalities identified with results of histologic evaluation in patients who subsequently underwent resection. We found that 7 T MRI enabled the identification of previously undetected areas of focal pituitary hypoenhancement in 9 patients (90%), of which 7 corresponded histologically to corticotroph adenomas. These early findings suggest an important adjunctive role for ultra-high field MR imaging in the noninvasive clinical workup of suspected Cushing's disease.

Blood-brain barrier (BBB) dysfunction has been implicated in ischemic risk following aneurysmal subarachnoid hemorrhage (aSAH), but never directly imaged. We prospectively examined whether post-bleed day 4 dynamic contrast-enhanced magnetic resonance (DCE-MR) BBB permeability imaging could predict development of delayed cerebral ischemia (DCI). Global MR-derived BBB permeability ( K trans ) was significantly higher in aSAH patients who subsequently developed DCI (five patients; 2.28 ± 0.09 × 10 -3 min -1 ) compared to those who experienced radiographic vasospasm only (three patients; 1.85 ± 0.12 × 10 -3 min -1 ; p < 0.05), or no vasospasm/ischemia (eight patients; 1.74 ± 0.07 × 10 -3 min -1 ; p < 0.01). K trans  > 2 × 10 -3 min -1 predicted development of DCI (AUC = 0.98, 95% CI: 0.93-1). Global BBB dysfunction following aSAH is detectable with DCE-MR and predictive of ischemic risk.

Background: Lymphomatosis cerebri (LC) is a rare variant of primary central nervous system lymphoma (PCNSL), characterized by diffuse infiltration without the formation of a discrete mass. The diagnosis of LC is a challenge because the imaging findings are atypical for lymphoma. The purpose of present study is to investigate MRI characteristics and clinical features of LC and potentially facilitate an early and accurate diagnosis of this often-missed disease., Methods: Seven patients (average 44 years, 19-58 years) with LC proved basing on MRI and histology were retrospectively reviewed the clinical data and cerebral MR imaging findings., Results: The common presenting symptoms were cognitive decline, behavioral disturbance, gait disturbance. All patients had both deep and lobar lesion distribution, and two of them had infratentorial involvement. Lack of contrast enhancement and subtle patchy enhanced pattern were observed in two and three patients, respectively. The remaining two patients presented multiple patchy enhancement. Most of the lesions were slightly hyperintense to normal brain on DWI as well as hyperintense on ADC maps. Three patients presented a pattern of marked decrease of NAA/Cr, increase of Cho/Cr, and two of the three cases showed increased Lip/Cr and Lac/Cr on MRS., Conclusions: We conclude that diffuse bilateral lesions especially in deep and lobar region including white and gray matter, without enhancement or with patchy enhancement, marked decrease of NAA/Cr and increase of Cho/Cr, and increased Lip/Cr and Lac/Cr are suggestive of LC. Prompt recognition of these imaging patterns may lead to early diagnosis of LC and brain biopsy with improved prognosis.

Dynamic susceptibility contrast (DSC) MR imaging, a perfusion-weighted MR imaging technique typically used in neuro-oncologic applications for estimating the relative cerebral blood volume within brain tumors, has demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response of gliomas. This review highlights recent developments using DSC-MR imaging and emphasizes the need for technical standardization and validation in prospective studies in order for this technique to become incorporated into standard-of-care imaging for patients with brain tumors., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints., Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm(3), FOV 22 × 22 × 4.2 cm(3), and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm(3), and broader coverage 22 × 22 × 19 cm(3). Temporal resolution was 5 s for both protocols. Time-resolved images and blood-brain barrier permeability maps were qualitatively evaluated by two radiologists., Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans., Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients., (© The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes., Method: An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects., Summary: The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Introduction: The specific goal of this study was to determine whether the inclusion of MRS had a measureable and positive impact on the accuracy of pre-surgical MR examinations of untreated pediatric brain tumors over that of MRI alone in clinical practice., Methods: Final imaging reports of 120 pediatric patients with newly detected brain tumors who underwent combined MRI/MRS examinations were retrospectively reviewed. Final pathology was available in all cases. Group A comprised 60 subjects studied between June 2001 and January 2005, when MRS was considered exploratory and radiologists utilized only conventional MRI to arrive at a diagnosis. For group B, comprising 60 subjects studied between January 2005 and March 2008, the radiologists utilized information from both MRI and MRS. Furthermore, radiologists revisited group A (blind review, time lapse >4 years) to determine whether the additional information from MRS would have altered their interpretation., Results: Sixty-three percent of patients in group A were diagnosed correctly, whereas in 10% the report was partially correct with the final tumor type mentioned (but not mentioned as most likely tumor), while in 27% of cases the reports were wrong. For group B, the diagnoses were correct in 87%, partially correct in 5%, and incorrect in 8% of the cases, which is a significant improvement (p < 0.005). Re-review of combined MRI and MRS of group A resulted 87% correct, 7% partially correct, and 7% incorrect diagnoses, which is a significant improvement over the original diagnoses (p < 0.05)., Conclusion: Adding MRS to conventional MRI significantly improved diagnostic accuracy in preoperative pediatric patients with untreated brain tumors.

This review covers important topics relating to the imaging evaluation of glioblastoma multiforme after therapy. An overview of the Macdonald and Response Assessment in Neuro-Oncology criteria as well as important questions and limitations regarding their use are provided. Pseudoprogression and pseudoresponse as well as the use of advanced magnetic resonance imaging techniques such as perfusion, diffusion, and spectroscopy in the evaluation of the posttherapeutic brain are also reviewed.

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is used to track the first pass of an exogenous, paramagnetic, nondiffusible contrast agent through brain tissue, and has emerged as a powerful tool in the characterization of brain tumor hemodynamics. DSC-MRI parameters can be helpful in many aspects, including tumor grading, prediction of treatment response, likelihood of malignant transformation, discrimination between tumor recurrence and radiation necrosis, and differentiation between true early progression and pseudoprogression. This review aims to provide a conceptual overview of the underlying principles of DSC-MRI of the brain for clinical neuroradiologists, scientists, or students wishing to improve their understanding of the technical aspects, pitfalls, and controversies of DSC perfusion MRI of the brain. Future consensus on image acquisition parameters and postprocessing of DSC-MRI will most likely allow this technique to be evaluated and used in high-quality multicenter studies and ultimately help guide clinical care., (© 2014 Wiley Periodicals, Inc.)

Gliomas comprise 80% of primary brain neoplasms, with glioblastoma multiforme being the most commonly diagnosed glioma. The annual incidence is 5.26 per 100,000, or 17,000 newly diagnosed cases per year in the United States. The incidence increases with age, peaking between the 6th and 8th decades. Gliomas are more common among Caucasians and occur more often in men. They can be associated with certain rare hereditary syndromes including Cowden, Turcot, Li-Fraumeni, neurofibromatosis type 1 and type 2, tuberous sclerosis, and familial schwannomatosis. Known risk factors include a history of ionizing radiation, family history of glioma, and certain genetic susceptibility variants that are weakly associated with glioma. Preventative measures have not been shown to decrease the risk of later development. In addition, screening tests are unwarranted since early diagnosis and treatment have not been shown to improve outcome., (Copyright © 2014. Published by Elsevier Inc.)

The quantitative, multiparametric assessment of brain lesions requires coregistering different parameters derived from MRI sequences. This will be followed by analysis of the voxel values of the ROI within the sequences and calculated parametric maps, and deriving multiparametric models to classify imaging data. There is a need for an intuitive, automated quantitative processing framework that is generalized and adaptable to different clinical and research questions. As such flexible frameworks have not been previously described, we proceeded to construct a quantitative post-processing framework with commonly available software components. Matlab was chosen as the programming/integration environment, and SPM was chosen as the coregistration component. Matlab routines were created to extract and concatenate the coregistration transforms, take the coregistered MRI sequences as inputs to the process, allow specification of the ROI, and store the voxel values to the database for statistical analysis. The functionality of the framework was validated using brain tumor MRI cases. The implementation of this quantitative post-processing framework enables intuitive creation of multiple parameters for each voxel, facilitating near real-time in-depth voxel-wise analysis. Our initial empirical evaluation of the framework is an increased usage of analysis requiring post-processing and increased number of simultaneous research activities by clinicians and researchers with non-technical backgrounds. We show that common software components can be utilized to implement an intuitive real-time quantitative post-processing framework, resulting in improved scalability and increased adoption of post-processing needed to answer important diagnostic questions.

Objective: This article addresses questions that radiologists frequently ask when planning, performing, processing, and interpreting MRI perfusion studies in CNS imaging., Conclusion: Perfusion MRI is a promising tool in assessing stroke, brain tumors, and neurodegenerative diseases. Most of the impediments that have limited the use of per-fusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols.

Although conventional contrast-enhanced MR imaging remains the standard-of-care imaging method in the posttreatment evaluation of gliomas, recent developments in therapeutic options such as chemoradiation and antiangiogenic agents have caused the neuro-oncology community to rethink traditional imaging criteria. This article highlights the latest recommendations. These recommendations should be viewed as works in progress. As more is learned about the pathophysiology of glioma treatment response, quantitative imaging biomarkers will be validated within this context. There will likely be further refinements to glioma response criteria, although the lack of technical standardization in image acquisition, postprocessing, and interpretation also need to be addressed., (Copyright © 2013 Elsevier Inc. All rights reserved.)

This article focuses on advanced magnetic resonance (MR) imaging techniques and how they can be used to help diagnose a specific tumor, suggest tumor grade and prognosis, follow tumor progression, evaluate tumor extension, suggest the ideal site for biopsy, and assess therapeutic response. Advanced MR imaging techniques may also help to distinguish between lesions that simulate brain tumors on conventional MR imaging studies., (Copyright © 2013. Published by Elsevier Inc.)

Neurocysticercosis (NCC) is an infection of the central nervous system by the Taenia solium larvae, and is the most common cause of acquired epilepsy in endemic regions. The natural history of parenchymal NCC lesions can be divided into 4 stages with unique imaging and clinical features. Evaluation of cysticerci is challenging on conventional magnetic resonance (MR) imaging and computed tomography, and is significantly improved with MR cysternography techniques. Differentiation of NCC lesions from metastatic disease and pyogenic abscesses can be improved with advanced MR imaging including (1)H nuclear MR spectroscopy, diffusion-weighted imaging, and MR perfusion imaging., (Copyright © 2012 Elsevier Inc. All rights reserved.)

This article presents an overview of advanced magnetic resonance (MR) imaging techniques using contrast media in neuroimaging, focusing on T2*-weighted dynamic susceptibility contrast MR imaging and T1-weighted dynamic contrast-enhanced MR imaging. Image acquisition and data processing methods and their clinical application in brain tumors, stroke, dementia, and multiple sclerosis are discussed., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Identification of abnormalities in the contralateral hemisphere in patients with hemimegalencephaly is critical in their management. In this report, we present a 5-day-old neonate with hemimegalencephaly who demonstrated an enlarged ipsilateral cerebral hemisphere and diffuse volume loss in the contralateral hemisphere on conventional MR imaging sequences. The ipsilateral frontal white matter demonstrated relatively increased NAA, fractional anistropy, and cerebral blood volume values compared to published normative data. In addition, the white matter of the contralateral hemisphere demonstrated elevated lactate and increased mean diffusivity compared to published normative data, supporting the abnormal conventional MR findings. Advanced MR neuroimaging techniques may help further confirm and characterize abnormalities in the smaller contralateral hemisphere in neonatal hemimegalencephaly.

Objective: The objective of our study was to evaluate the changes in quantitative diffusion tensor (DT) metrics and normalized T2-signal intensity (nT2-SI) values of normal-appearing cortical gray matter (CGM) and deep gray matter (DGM) in patients with multiple sclerosis (MS)., Methods: Fifty patients with MS and 25 patients with no MS matched on sex/age were selected as controls. Conventional magnetic resonance imaging and DT imaging were performed. Fractional anisotropy (FA)/mean diffusivity (MD) and nT2-SI values of CGM and DGM were measured. Analyses of variance between the 2 groups were analyzed; Pearson correlations between DT metrics and nT2-SI values and brain parenchymal fraction (BPF) and T2 lesion volumes (LVs) were used., Results: Patients with MS showed larger MD/smaller FA values in the CGM region compared with controls (P < 0.05). However, MD/FA values were not statistically significant in the DGM between MS and healthy control group. In DGM of MS patients, a significant decrease of nT2-SI values were observed when compared with controls (P < 0.05), but nT2-SI values in the CGM of MS patients showed no significant decrease. In CGM, only MD values of frontal lobes in MS patients were significantly (negatively) correlated with BPF(right: P = 0.009, left: P = 0.036) or T2 LVs (right: P = 0.002, left: P = 0.047). Normalized T2-SI values in all DGM regions of MS patients were significantly correlated with BPF (r = 0.282-0.504, P < 0.05) except for the left thalamus and bilateral red nucleus. There was no correlation between nT2-SI in all DGM regions and T2 LVs of MS patients., Conclusion: In CGM, the change in quantitative DT metrics of MS patients and the association with BPF and T2 LVs suggest the existence of microstructural destruction corresponding to inflammation, demyelination, or wallerian degeneration, but the changes in CGM were independent of the concomitant changes in BPF and T2 lesion. In DGM, a decrease of nT2-SI in MS patients and the correlation of nT2-SI values with BPF (brain atrophy) suggest excessive iron deposition related to chronic destruction. Our investigation indicates the possibility of different mechanism of pathological change in CGM and DGM.

Purpose: To evaluate retrospectively quantitative diffusion tensor imaging (DTI) values of hyperintense lesions on nonenhanced T1-weighted magnetic resonance (MR) images in patients with multiple sclerosis (MS) to elucidate the degree of demyelination or remyelination associated with T1 hyperintense lesions and study their relationship to MR markers of tissue damage (brain atrophy)., Materials and Methods: Institutional review board approval was obtained; informed consent was waived for this HIPAA-compliant study, including 76 patients with MS and 20 healthy control subjects without evidence of MS clinically or on imaging. T1 lesions were compared with normal white matter on nonenhanced images and judged to be hyperintense. Quantitative DTI metrics of T1 hyperintense lesions were examined, and the relationship between DTI parameters and brain atrophy were investigated in this study., Results: At least one T1 hyperintense lesion was found in 16 patients (total, 28 lesions). Hyperintense lesions on T1-weighted imaging (T1WI) had lower mean diffusion (MD) than others signal intensity lesions on T1WI but higher MD than normal white matter (F = 3.931; P < 0.001); Fractional anisotropy (FA; F = 3.24; P < 0.001) and volume ratio (VR; F = 1.664; P < 0.001) were higher in hyperintense lesions on T1WI than hypointense/isointense lesions on T1WI, but were lower than normal-appearing white matter (NAWM) and normal white matter in controls. There was correlation between FA and VR (r = 0.678; P < 0.001) and inverse correlation between FA and MD (r = -0.437; P = 0.02), MD and VR (r = -0.423; P 0.025) for T1 hyperintense lesion. The MD values of T1 hyperintense lesions (r = -0.304; P < 0.001) and the VR values of T1 hyperintense lesions (r = 0.096; P = 0.042) were significantly (negative) correlated with Brain parenchymal fraction (BPF; higher BPF score); the FA values of T1 hyperintense lesions (r = -0.111; P = 0.018), the MD values of T1 hyperintense lesions (r = 0.379; P < 0.001) and the VR values of T1 hyperintense lesions (r = -0.142; P = 0.003) were significantly correlated with third ventricular width (lower width). However, the FA value of T1 hyperintense lesions was not significantly associated with BPF(r = 0.083; P = 0.08)., Conclusion: The quantitative DTI values of T1 hyperintense MS plaques were between hypo-/isointense lesions and NAWM or normal white matter, and correlated with BPF and third ventricular width. Our results supports the notion that axonal remyelination may be the reason for T1 hyperintense lesions., ((c) 2010 Wiley-Liss, Inc.)

PurposeTo develop an MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) technique for simultaneous quantification of permeability and leakage-insensitive perfusion with a single-dose contrast injection.MethodsMT-DICE builds on a saturation-recovery prepared multi-echo fast low-angle shot sequence. The k-space is randomly sampled for 7.6 min, with single-dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole-brain coverage, a saturation-recovery time dimension, and a TE dimension for dynamic T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ quantification, respectively, and a contrast dynamics dimension for capturing contrast kinetics. The derived pixel-wise T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ time series are converted into contrast concentration-time curves for calculation of kinetic metrics. The technique was assessed for its agreement with reference methods in T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ measurements in eight healthy subjects and, in three of them, inter-session repeatability of permeability and leakage-insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors.ResultsMT-DICE T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter ). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range.ConclusionBased on dynamic T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ mapping, MT-DICE allows for simultaneous quantification of permeability and leakage-insensitive perfusion metrics with a single-dose contrast injection.

PurposeTo provide early and localized glioblastoma (GBM) recurrence prediction, we introduce a novel postsurgery multiparametric magnetic resonance-based support vector machine (SVM) method coupling with stem cell niche (SCN) proximity estimation.Methods and materialsThis study used postsurgery magnetic resonance imaging (MRI) scans from 50 patients with recurrent GBM, obtained approximately 2 months before clinically diagnosed recurrence. The main prediction pipeline consisted of a proximity-based estimator to identify regions with high risk of recurrence (HRRs) and an SVM classifier to provide voxelwise prediction in HRRs. The HRRs were estimated using the weighted sum of inverse distances to 2 possible origins of recurrence-the SCN and the tumor cavity. Subsequently, multiparametric voxels (from T1, T1 contrast-enhanced, fluid-attenuated inversion recovery, T2, and apparent diffusion coefficient) within the HRR were grouped into recurrent (warped from the clinical diagnosis) and nonrecurrent subregions and fed into the proximity estimation-coupled SVM classifier (SVMPE). The cohort was randomly divided into 40% and 60% for training and testing, respectively. The trained SVMPE was then extrapolated to an earlier time point for earlier recurrence prediction. As an exploratory analysis, the SVMPE predictive cluster sizes and the image intensities from the 5 magnetic resonance sequences were compared across time to assess the progressive subclinical traces.ResultsOn 2-month prerecurrence MRI scans from 30 test cohort patients, the SVMPE classifier achieved a recall of 0.80, a precision of 0.69, an F1-score of 0.73, and a mean boundary distance of 7.49 mm. Exploratory analysis at early time points showed spatially consistent but significantly smaller subclinical clusters and significantly increased T1 contrast-enhanced and apparent diffusion coefficient values over time.ConclusionsWe demonstrated a novel voxelwise early prediction method, SVMPE, for GBM recurrence based on clinical follow-up MR scans. The SVMPE is promising in localizing subclinical traces of recurrence 2 months ahead of clinical diagnosis and may be used to guide more effective personalized early salvage therapy.

Blood-brain barrier (BBB) dysfunction has been implicated in ischemic risk following aneurysmal subarachnoid hemorrhage (aSAH), but never directly imaged. We prospectively examined whether post-bleed day 4 dynamic contrast-enhanced magnetic resonance (DCE-MR) BBB permeability imaging could predict development of delayed cerebral ischemia (DCI). Global MR-derived BBB permeability ( Ktrans) was significantly higher in aSAH patients who subsequently developed DCI (five patients; 2.28 ± 0.09 × 10-3 min-1) compared to those who experienced radiographic vasospasm only (three patients; 1.85 ± 0.12 × 10-3 min-1; p  2 × 10-3 min-1 predicted development of DCI (AUC = 0.98, 95% CI: 0.93-1). Global BBB dysfunction following aSAH is detectable with DCE-MR and predictive of ischemic risk.

Introduction: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle (“low-FA”) with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle (“intermediate-FA”) and modelbased leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson’s, Spearman’s and intraclass correlation coefficients (ICC). Results: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/ P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload. [ABSTRACT FROM AUTHOR]

With the development of HER2-directed therapies, identifying non-invasive imaging biomarkers of HER2 expression in breast cancer brain metastases has become increasingly important. The purpose of this study was to investigate whether relative cerebral blood volume (rCBV) from dynamic susceptibility contrast-enhanced (DSC) perfusion MR could help identify the HER2 status of breast cancer brain metastases. With IRB approval for this HIPAA-compliant cross-sectional study and a waiver of informed consent, we queried our institution's electronic medical record to derive a cohort of 14 histologically proven breast cancer brain metastases with preoperative DSC perfusion MR and HER2 analyses of the resected/biopsied brain specimens from 2011-2021. The rCBV of the lesions was measured and compared using Mann-Whitney tests. Receiver operating characteristic analyses were performed to evaluate the performance of rCBV in identifying HER2 status. The study cohort was comprised of 14 women with a mean age of 56 years (range: 32-81 years) with a total of 14 distinct lesions. The rCBV of HER2-positive breast cancer brain metastases was significantly greater than the rCBV of HER2-negative lesions (8.02 vs 3.97, U=48.00, p =0.001). rCBV differentiated HER2-positive lesions from HER2-negative lesions with an area under the curve of 0.98 (standard error=0.032, p <0.001). The accuracy-maximizing rCBV threshold (4.8) was associated with an accuracy of 93% (13/14), a sensitivity of 100% (7/7), and a specificity of 86% (6/7). rCBV may assist in identifying the HER2 status of breast cancer brain metastases, if validated in a large prospective trial. [ABSTRACT FROM AUTHOR]

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121. [ABSTRACT FROM AUTHOR]

Background and purpose: Brain tumors in the corticospinal tract (CST) region are more likely to cause motor dysfunction. The aim of this study is to evaluate the effect of gliomas located in the CST region on motor function with diffusion tensor imaging (DTI) preoperatively. Materials and methods: Forty-five patients with histopathologically confirmed gliomas were included in this pilot study, in all cases (low-grade n = 13, high-grade n = 32) CST but not the motor cortex were involved by the tumor. DTI image were acquired and the posterior limb of the internal capsule fractional anisotropy (FA) and relative FA (rFA = affected FA/contralateral FA) were measured. Injury of the CST from tumor was divided into three grades (grade 1: displacement, grade 2: displacement and infiltration, grade 3: displacement and disruption). The fiber density index (FDi) and relative FDi (rFDi = affected FDi/contralateral FDi) of the injured and contralateral CST were measured. The correlations between muscle strength and the CST injury grade and the rFA, affected FDi, rFDi values were calculated using Spearman rank correlation analysis. rFA and rFDi values of muscle strength groups (MMT2-5) were compared with one-way analysis of variance (ANOVA). The difference of muscle strength between low- and high-grade glioma groups were analysed with the Mann-Whitney U-test. Results: Muscle strength was negatively correlated with the injury grade of the CST (r = -0.840, P<0.001). Muscle strength was positively correlated with rFA, FDi and rFDi (correlation coefficients (r) were 0.615, 0.643 and 0.567 for rFA, FDi and rFDi, respectively). The rFA values between grades (2&3, 2&4, 2&5, 3&5, 4&5) of muscle strength were significantly different (P<0.05), the rFDi values between grades (2&4, 2&5, 3&4, 3&5) of muscle strength were significantly different (P<0.05), while the rFA and rFDi values in the remaining groups of muscle strength grades showed no significant differences(P>0.05). Conclusions: Preoperative DTI and diffusion tensor tractography may quantify the injury degrees of CST and the extent of motor dysfunction in patients with brain glioma. [ABSTRACT FROM AUTHOR]

Central neurocytomas comprise nearly half of adult intraventricular neoplasms. The median age of onset is 34 years. It is typically a low-grade neoplasm (World Health Organization grade II), although some cases of malignant neurocytomas have been described. We present a rare case of an atypical central neurocytoma with craniospinal dissemination, including both imaging and pathologic findings. [ABSTRACT FROM AUTHOR]

The management of pituitary apoplexy, caused by acute hemorrhage and/or infarction of a pituitary adenoma, is debated. To analyze clinical characteristics of patients undergoing endoscopic endonasal approaches (EEAs) for pituitary apoplexy. A retrospective review of patients at our institution from 2012 to 2018 undergoing EEA for pituitary apoplexy diagnosed clinically and with imaging/pathologic findings. Analysis included demographics, symptoms, neuroendocrine deficits, neuroimaging, complications, symptom resolution, and follow-up details. Fifty patients (mean age, 53 years) were included. Preoperative symptoms included headache (86%), vision loss (62%), and cranial nerve paresis (40%). Mean tumor diameter was 2.7 cm and extrasellar extension was observed in 96% of tumors. Twenty-eight tumors were hemorrhagic (76%), 24 were necrotic (65%), and 13 (35%) had both features. Magnetic resonance imaging showed gross total resection in 58% of patients. Headache and vision loss improved in 87% and 86% of presenting patients. Cranial nerve paresis resolved in 72% of patients, partially improved in 11%, and remained unchanged in 17%. There were no deaths or carotid artery injuries. Surgical complications included postoperative cerebrospinal fluid leak (n = 4, 8%), epistaxis (n = 2, 4%), postoperative abscess (n = 1, 2%), and transient postoperative vision loss requiring reoperation (n = 1, 4%). Endocrinopathies improved in 21% of patients and panhypopituitarism persisted in 48% and developed in 6% of patients. Mean follow-up time was 26 months; 2 patients experienced recurrence. EEA for pituitary apoplexy is effective in rapidly improving headache and visual symptoms. Although neuro-ophthalmic deficits often improve over time, panhypopituitarism persists in most patients after surgical resection. [ABSTRACT FROM AUTHOR]

Cystic sellar masses (CSMs) pose diagnostic and therapeutic challenges associated with subtotal cyst wall resection, cerebrospinal fluid (CSF) leak repair, and disease recurrence. Current magnetic resonance imaging (MRI) interpretation often cannot reliably differentiate CSMs, mandating adaptable intraoperative strategies. We reviewed our diagnostic and therapeutic experience after endoscopic endonasal approaches (EEAs) for CSMs. A retrospective record review of patients with CSM managed via EEA at the University of Southern California from 2011 to 2018 was conducted. Patient demographics, preoperative characteristics, surgical details, pathologic findings, and postoperative outcomes were assessed. Analysis included 47 patients (mean age, 43.2 years); of these, 78.7% were women. Preoperative symptoms included headache (76.6%) and vision loss (42.6%). Histologically verified sellar pathology included 27 Rathke cleft cysts (RCCs) (57.4%), 17 cystic pituitary adenomas (CPAs) (36.2%), 2 arachnoid cysts (4.3%), and 1 xanthogranuloma (2.1%). Twelve patients (70.6%) with CPAs underwent complete resection and 5 (29.4%) underwent subtotal resection. All 27 patients with RCC and 2 patients with arachnoid cyst underwent complete fenestration and drainage. One xanthogranuloma was completely resected. There were 14 intraoperative (29.8%) and 4 postoperative CSF leaks (8.5%). Headaches, vision, and endocrinopathy improved in 69.2%, 80.0%, and 33.3% of patients with CPA and 73.9%, 71.4%, and 40.9% of patients with RCC, respectively. There were 2 RCC recurrences and 1 CPA recurrence over the follow-up period. Surgeons must prepare for versatile management strategies of CSMs based on pretest probability associated with MRI and intraoperative findings. Outcomes after EEA for CSMs show low complication profiles and excellent rates of headache and visual improvement, albeit lower rates of endocrine normalization. [ABSTRACT FROM AUTHOR]