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Feasibility of intravoxel incoherent motion in the assessment of tumor microvasculature and blood-brain barrier integrity: a case-based evaluation of gliomas
Abstract
Objective
To evaluate the feasibility of intravoxel incoherent motion (IVIM) in assessing blood–brain barrier (BBB) integrity and microvasculature in tumoral tissue of glioma patients.Methods
Images from 8 high-grade and 4 low-grade glioma patients were acquired on a 3 T MRI scanner. Acquisition protocol included pre- and post-contrast T1- and T2-weighted imaging, FLAIR, dynamic susceptibility contrast (DSC), and susceptibility-weighted imaging (SWI). In addition, IVIM was acquired with 15 b-values and fitted under the non-negative least square (NNLS) model to output the diffusion (D) and pseudo-diffusion (D*) coefficients, perfusion fraction (f), and f times D* (fD*) maps.ResultsIVIM perfusion-related maps were sensitive to (1) blood flow and perfusion alterations within the microvasculature of brain tumors, in agreement with intra-tumoral susceptibility signal (ITSS); (2) enhancing areas of BBB breakdown in agreement with DSC maps as well as areas of BBB abnormality that was not detected on DSC maps; (3) enhancing perfusion changes within edemas; (4) detecting early foci of increased perfusion within low-grade gliomas.Conclusion
The results suggest IVIM may be a promising approach to delineate tumor extension and progression in size, and to predict histological grade, which are clinically relevant information that characterize tumors and guide therapeutic decisions in patients with glioma.
... Parkinson's disease ( Szturm et al., 2021), and to assess gliomas ( Paschoal et al., 2022;Raja et al., 2016). We have also used ACID to investigate spinal cord white matter following spinal cord injury ( Büeler et al., 2024;David et al., 2019David et al., , 2021David et al., , 2022Grabher et al., 2016;Huber et al., 2018;Seif et al., 2020;Vallotton et al., 2021). ...
Diffusion MRI (dMRI) has become a crucial imaging technique in the field of neuroscience, with a growing number of clinical applications. Although most studies still focus on the brain, there is a growing interest in utilizing dMRI to investigate the healthy or injured spinal cord. The past decade has also seen the development of biophysical models that link MR-based diffusion measures to underlying microscopic tissue characteristics, which necessitates validation through ex vivo dMRI measurements. Building upon 13 years of research and development, we present an open-source, MATLAB-based academic software toolkit dubbed ACID: A Comprehensive Toolbox for Image Processing and Modeling of Brain, Spinal Cord, and Ex Vivo Diffusion MRI Data. ACID is an extension to the Statistical Parametric Mapping (SPM) software, designed to process and model dMRI data of the brain, spinal cord, and ex vivo specimens by incorporating state-of-the-art artifact correction tools, diffusion and kurtosis tensor imaging, and biophysical models that enable the estimation of microstructural properties in white matter. Additionally, the software includes an array of linear and nonlinear fitting algorithms for accurate diffusion parameter estimation. By adhering to the Brain Imaging Data Structure (BIDS) data organization principles, ACID facilitates standardized analysis, ensures compatibility with other BIDS-compliant software, and aligns with the growing availability of large databases utilizing the BIDS format. Furthermore, being integrated into the popular SPM framework, ACID benefits from a wide range of segmentation, spatial processing, and statistical analysis tools as well as a large and growing number of SPM extensions. As such, this comprehensive toolbox covers the entire processing chain from raw DICOM data to group-level statistics, all within a single software package.
... Accordingly, fD* is often considered a flow-related parameter, considered more related to cerebral blood flow (CBF) than f or D* alone (Yao et al., 2016). Due to the relative ease with which IVIM data can be acquired non-invasively and without contrast, IVIM has garnered widespread attention in various neurological pathologies such as malignant tumors (Paschoal et al., 2022) and cerebrovascular disease (Paschoal et al., 2018). IVIM has also been used to investigate perfusion-related phenomena outside the brain in organs such as the liver (Li et al., 2017). ...
Abstract
Purpose: Intravoxel incoherent motion (IVIM) is a quantitative magnetic resonance imaging (MRI) method used to quantify perfusion properties of tissue non-invasively without contrast. However, clinical applications are limited by unreliable parameter estimates, particularly for the perfusion fraction (f) and pseudodiffusion coefficient (D*). This study aims to develop a high-fidelity reconstruction for reliable estimation of IVIM parameters. The proposed method is versatile and amenable to various acquisition schemes and fitting methods.
Methods: To address current challenges with IVIM, we adapted several advanced reconstruction techniques. We used a low-rank approximation of IVIM images and temporal subspace modeling to constrain the magnetization dynamics of the bi-exponential diffusion signal decay. In addition, motion-induced phase variations were corrected between diffusion directions and b-values, facilitating the use of high SNR real-valued diffusion data. The proposed method was evaluated in simulations and in vivo brain acquisitions in six healthy subjects and six individuals with a history of SARS-CoV-2 infection and compared with the conventionally reconstructed magnitude data. Following reconstruction, IVIM parameters were estimated voxel-wise.
Results: Our proposed method reduced noise contamination in simulations, resulting in a 60%, 58.9%, and 83.9% reduction in the NRMSE for D, f, and D*, respectively, compared to the conventional reconstruction. In vivo, anisotropic properties of D, f, and D* were preserved with the proposed method, highlighting microvascular differences in gray matter between individuals with a history of COVID-19 and those without (p = 0.0210), which wasn't observed with the conventional reconstruction.
Conclusion: The proposed method yielded a more reliable estimation of IVIM parameters with less noise than the conventional reconstruction. Further, the proposed method preserved anisotropic properties of IVIM parameter estimates and demonstrated differences in microvascular perfusion in COVID-affected subjects, which weren't observed with conventional reconstruction methods.
Keywords: Diffusion MRI; Intravoxel incoherent motion; Quantitative mri; SARS-CoV-2 Infection; Subspace modeling; low-rank modeling.
... ACID has been used in a variety of clinical and neuroscience research, e.g., in dMRI studies assessing cerebral changes in patients with multiple sclerosis (Deppe et al., 2016a(Deppe et al., , 2016bDossi et al., 2018;Kugler & Deppe, 2018) and Parkinson's disease (Szturm et al., 2021), and to assess gliomas (Paschoal et al., 2022;Raja et al., 2016). ACID has also been used to investigate spinal cord white matter following spinal cord injury (David et al., 2019(David et al., , 2022Grabher et al., 2016;Huber et al., 2018;Seif et al., 2020;Vallotton et al., 2021). ...
Diffusion MRI (dMRI) has become a crucial imaging technique within the field of neuroscience and has an increasing number of clinical applications. Although most studies still focus on the brain, there is a growing interest in utilizing dMRI to investigate the healthy or injured spinal cord. The past decade has also seen the development of biophysical models that link MR-based diffusion measures to underlying microscopic tissue characteristics. Building upon 13 years of research and development, we present an open-source, MATLAB-based academic software toolkit dubbed ACID: A Comprehensive Toolbox for Image Processing and Modeling of Brain, Spinal Cord, and Post-mortem Diffusion MRI Data. ACID is designed to process and model dMRI data of the brain, spinal cord, and post-mortem specimens by incorporating state-of-the-art artifact correction tools, diffusion and kurtosis tensor imaging, and biophysical models that enable the estimation of microstructural properties in white matter. Additionally, the software includes an array of linear and non-linear fitting algorithms for accurate diffusion parameter estimation. By adhering to the Brain Imaging Data Structure (BIDS) data organization principles, ACID facilitates standardized analysis, ensures compatibility with other BIDS-compliant software, and aligns with the growing availability of large databases utilizing the BIDS format. Furthermore, ACID seamlessly integrates into the popular Statistical Parametric Mapping (SPM) framework, benefitting from a wide range of established segmentation, spatial processing, and statistical analysis tools as well as a large and growing number of SPM extensions. As such, this comprehensive toolbox covers the entire processing chain from raw DICOM data to group-level statistics, all within a single software package.
Glioma characterized by high morbidity and mortality, is one of the most common brain tumors. The application of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in differentiating glioma grading and IDH1 mutation status were poorly investigated. 78 glioma patients confirmed by pathological and imaging methods were enrolled. Glioma patients were measured using IVIM-DWI, then related parameters such as cerebral blood flow (CBF), perfusion fraction (f), pseudo diffusivity (D*), and true diffusivity (D), were derived. Receiver operating characteristic (ROC) curves were made to calculate specificity and sensitivity. The values of CBF1, CBF3, D*1, rCBF1-2, rCBF3-2, and age in group high-grade gliomas (HGG) were significantly higher than that of in group low-grade gliomas (LGG). The values of CBF1, CBF3, rCBF1-2, rCBF3-2, D*1, and age in group IDH1
mut
were significantly lower than that of in group IDH1
wt
. The levels of D1 and f1 were remarkably higher in the group IDH1
mut
than group IDH1
wt
. rCBF1-2 had a remarkably positive correlation with CBF1 (r=0.852, p<0.001). f1 showed a markedly negative correlation with CBF1 (r= -0.306, p=0.007). IVIM-DWI presented efficacy in differentiating glioma grading and IDH1 mutation status.
Background
Effect of isocitr ate dehydrogenase 1 ( IDH1 ) mutation in neovascularization might be linked with tissue perfusion in gliomas. At present, the need of injection of contrast agent and the increasing scanning time limit the application of perfusion techniques. We used a simplified intravoxel incoherent motion (IVIM)-derived perfusion fraction ( SPF ) calculated from diffusion-weighted imaging (DWI) using only three b-values to quantitatively assess IDH1 -linked tissue perfusion changes in WHO grade II-III gliomas (LGGs). Additionally, by comparing accuracy with dynamic contrast-enhanced (DCE) and full IVIM MRI, we tried to find the optimal imaging markers to predict IDH1 mutation status.
Patients and methods
Thirty patients were prospectively examined using DCE and multi-b-value DWI. All parameters were compared between the IDH1 mutant and wild-type LGGs using the Mann–Whitney U test, including the DCE MRI-derived K trans , v e and v p , the conventional apparen t diffusion coefficient ( ADC 0,1000 ), IVIM-de rived perfusion fraction ( f ), diffusion coefficient ( D ) and pseudo-diffusion coefficient ( D* ), SPF . We evaluated the diagnostic performance by receive r operating characteristic (ROC) analysis.
Results
Significant differences were detected between WHO grade II-III gliomas for all perfusion and diffusion parameters ( P < 0.05). When compared to IDH1 mutant LGGs, IDH1 wild-type LGGs exhibited significantly higher perfusion metrics ( P < 0.05) and lower diffusion metrics ( P < 0.05). Among all parameters, SPF showed a higher diagnostic performance (area under the curve 0.861), with 94.4% sensitivity and 75% specificity.
Conclusions
DWI, DCE and IVIM MRI may noninvasively help discriminate IDH1 mutation statuses in LGGs. Specifically, simplified DWI-derived SPF showed a superior diagnostic performance.
Purpose
This study aims to incorporate informative histogram indicator analyses and advanced multimodal MRI parameters to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs) and to explore the features associated with patients’ survival.
Patients and methods
A total of 120 patients with pathologically confirmed LGGs or HGGs receiving conventional and advanced MRI such as three-dimensional arterial spin labeling (3D-ASL), intravoxel incoherent motion-diffusion weighted imaging (IVIM-DWI), and dynamic contrast-enhanced MRI (DCE-MRI) were included. The mean and histogram indicators from advanced MRI were calculated from the entire tumor. The efficacies of a single indicator or multiple parameters were tested in distinguishing HGGs from LGGs and predicting patients’ survival. Receiver operating characteristic (ROC) curve and multivariable stepwise logistic regression were used to evaluate the diagnostic efficacies. Leave-one-out cross-validation was further used to validate the accuracy of the parameter sets in glioma grading. Log-rank test using the Kaplan–Meier curve was utilized to predict patients’ survival.
Results
Overall, parameters from DCE-MRI performed better than those from 3D-ASL or IVIM-DWI in both glioma grading and survival prediction. The histogram metrics of Ve were demonstrated to have higher accuracies (the accuracies for Extended Tofts_Vemean and Extended Tofts_Vemedian were 68.33% and 71.67%, respectively, while those for the Incremental_Vemean and Incremental_Ve75th were 68.33% and 72.50%, respectively) in grading LGGs from HGGs. The combination of Tofts_Ve histogram metrics was the one with the highest accuracy (81.67%) and area under ROC curve (AUC = 0.840). On the other hand, Patlak_Ktrans95th (AUC = 0.9265) and Extended Tofts_Ve95th (AUC = 0.9154) performed better than their corresponding means (Patlak_Ktransmean: AUC = 0.9118 and Extended Tofts_Vemean: AUC = 0.9044) in predicting patients’ overall survival (OS) at 18-month follow-up.
Conclusion
DCE-MRI-derived histogram features from the entire tumor were promising metrics for glioma grading and OS prediction. Combining single modal histogram features improved glioma grading.
Trial registration
NCT 02622620.
Purpose
To quantitate gadolinium deposits in gliomas and adjacent normal brain specimens, and to evaluate their association with tumor contrast enhancement and the type of gadolinium-based contrast agent (GBCA) used.
Methods
A total of 69 patients with primary glioma who underwent contrast-enhanced magnetic resonance imaging (MRI) prior to surgery were included in this retrospective study. Gadolinium was measured from histologically viable tumor, normal brain, and necrosis within the sample, when available, using inductively coupled plasma mass spectrometry (ICP-MS). Tumor contrast enhancement was categorized as none, minimal, or noticeable. Differences in gadolinium deposits by contrast enhancement and GBCA type were assessed.
Results
Seven patients received linear GBCA and 62 macrocyclic, respectively. At the time of surgery, gadolinium deposits were detected in 39 out of 69 (57%) tumor samples, 8 out of 13 (62%) normal brain, and 12 out of 14 (86%) necrotic specimens. Gadolinium was detected in both enhancing and non-enhancing tumors, but was greatest in gliomas with noticeable enhancement (p = 0.02). Administration of linear agents gadodiamide and gadopentetate dimeglumine resulted in significantly higher tumor gadolinium relative to macrocyclic gadoterate meglumine (p < 0.01 and p < 0.05, respectively). Normal brain and necrosis also showed higher gadolinium after exposure to linear gadodiamide (both p < 0.05). In multivariate regression, GBCA type (linear/macrocyclic) was the most powerful predictor of tumor gadolinium retention (p < 0.001).
Conclusion
Gadolinium can be detected in both enhancing and non-enhancing gliomas, neighboring normal brain, and necrosis. Gadolinium retention is higher after exposure to linear GBCAs compared with the macrocyclic gadoterate meglumine.
Background:
Differentiation of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) is an important clinical problem because treatment strategies vary greatly. This study was performed to investigate the potential diagnostic value of incoherent intravoxel motion imaging (IVIM) to distinguish HGG from LGG by meta-analysis.
Methods:
A computerized search of the literature was performed using the free-access PubMed database, Web of Science, and Chinese biomedical database, and relevant articles until September 18, 2018 that used IVIM to distinguish HGG from LGG were included. All analyses were performed using Review Manager 5.3 and Stata. Mean difference (MD) at 95% confidence interval (CI) of the apparent diffusion coefficient (ADC), diffusion coefficient value (D), perfusion fraction value (f), and perfusion coefficient value (D*) were summarized.
Results:
Nine studies were used for general data pooling. In the tumor parenchyma (TP) regions, subgroup analysis revealed D* in HGG is higher than in LGG (MD = 1.19, P = .002), and D in HGG is lower than in LGG (MD = -1.06, P = .001). However, no significant difference in f (MD = 0.89, P = .056) was detected between HGG and LGG. In the white matter regions, HGG had higher D* (MD = 0.76, P = .04) compared with LGG, while no marked differences between the D value (P = .07) and f (P = .09) values.
Conclusion:
The present meta-analysis shows that the ADC, D, and D* values derived from IVIM may be useful in differentiating HGG from LGG. Considering the small sample of this study, we need to be cautious when interpreting the results of this study. Other prospective and large-sample randomized controlled trials were needed to establish the value of IVIM in differentiating HGG from LGG.
The regulation of aberrant glucose metabolism in diabetes associated-kidney fibrosis is not well known. In this study we found the suppression of SIRT3 protein level in diabetic kidney, displays responsibility in fibrogenic programming associated with aberrant glycolysis and such abnormal glycolysis is the therapeutic target in diabetes associated-kidney fibrosis. When analyzing different strains of streptozotocin-induced diabetic mice model (fibrotic model: CD-1, less fibrotic model: C57Bl6), we found SIRT3 suppression was associated with kidney fibrosis in fibrotic CD-1; further SIRT3 suppression by systemic administration of SIRT3 siRNA in the diabetic mice, showed profound fibrogenic phenotype in the kidney. Such suppression in SIRT3 was associated with the induction of transforming growth factor-β (TGF-β)/smad signaling, higher level of HIF1α accumulation and PKM2 dimer formation; these alterations subsequently led to abnormal glycolysis and linked abnormal mesenchymal transformations in vivo and in vitro. Inhibition of such aberrant glycolysis suppressed fibrogenic programming and restored SIRT3 level as well. Such aberrant glycolysis was confirmed in the KK/Ta-Ins2Akita mouse, the mouse model of progressive diabetic kidney disease. These data demonstrate that SIRT3 deficiency promotes abnormal glycolysis which is responsible for the fibrogenic pathway in diabetic kidney. Restoration of SIRT3 could be an alternative strategy in combating diabetes associated-kidney fibrosis via inhibition of aberrant glycolysis.
Intravoxel Incoherent Motion (IVIM) is a recently rediscovered noninvasive magnetic resonance imaging (MRI) method based on diffusion-weighted imaging. It enables the separation of the intravoxel signal into diffusion due to Brownian motion and perfusion-related contributions and provides important information on microperfusion in the tissue and therefore it is a promising tool for applications in neurological and neurovascular diseases. This review focuses on the basic principles and outputs of IVIM and details it major applications in the brain, such as stroke, tumor, and cerebral small vessel disease. A bi-exponential model that considers two different compartments, namely capillaries, and medium-sized vessels, has been frequently used for the description of the IVIM signal and may be important in those clinical applications cited before. Moreover, the combination of IVIM and arterial spin labeling MRI enables the estimation of water permeability across the blood-brain barrier (BBB), suggesting a potential imaging biomarker for disrupted-BBB diseases.
Intravoxel Incoherent Motion (IVIM) refers to translational movements which within a given voxel and during the measurement time present a distribution of speeds in orientation and/or amplitude. The IVIM concept has been used to estimate perfusion in tissues as blood flow in randomly oriented capillaries mimics a pseudo-diffusion process. IVIM-based perfusion MRI, which does not require contrast agents, has gained momentum recently, especially in the field oncology. In this introductory review the basic concepts, models, technical requirements and limitations inherent to IVIM-based perfusion MRI are outlined, as well as new, non-perfusion applications of IVIM MRI, such as virtual MR Elastography.
The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor. For the first time, the WHO classification of CNS tumors uses molecular parameters in addition to histology to define many tumor entities, thus formulating a concept for how CNS tumor diagnoses should be structured in the molecular era. As such, the 2016 CNS WHO presents major restructuring of the diffuse gliomas, medulloblastomas and other embryonal tumors, and incorporates new entities that are defined by both histology and molecular features, including glioblastoma, IDH-wildtype and glioblastoma, IDH-mutant; diffuse midline glioma, H3 K27M-mutant; RELA fusion-positive ependymoma; medulloblastoma, WNT-activated and medulloblastoma, SHH-activated; and embryonal tumour with multilayered rosettes, C19MC-altered. The 2016 edition has added newly recognized neoplasms, and has deleted some entities, variants and patterns that no longer have diagnostic and/or biological relevance. Other notable changes include the addition of brain invasion as a criterion for atypical meningioma and the introduction of a soft tissue-type grading system for the now combined entity of solitary fibrous tumor / hemangiopericytoma-a departure from the manner by which other CNS tumors are graded. Overall, it is hoped that the 2016 CNS WHO will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.
Astrocytes, members of the glial family, interact through the exchange of soluble factors
or by directly contacting neurons and other brain cells, such as microglia and endothelial
cells. Astrocytic projections interact with vessels and act as additional elements of the
Blood Brain Barrier (BBB). By mechanisms not fully understood, astrocytes can undergo
oncogenic transformation and give rise to gliomas. The tumors take advantage of the BBB
to ensure survival and continuous growth. A glioma can develop into a very aggressive
tumor, the glioblastoma (GBM), characterized by a highly heterogeneous cell population
(including tumor stem cells), extensive proliferation and migration. Nevertheless, gliomas
can also give rise to slow growing tumors and in both cases, the afflux of blood, via BBB
is crucial. Glioma cells migrate to different regions of the brain guided by the extension of
blood vessels, colonizing the healthy adjacent tissue. In the clinical context, GBM can
lead to tumor-derived seizures, which represent a challenge to patients and clinicians,
since drugs used for its treatment must be able to cross the BBB. Uncontrolled and fast
growth also leads to the disruption of the chimeric and fragile vessels in the tumor mass
resulting in peritumoral edema. Although hormonal therapy is currently used to control
the edema, it is not always efficient. In this review we comment the points cited above,
considering the importance of the BBB and the concerns that arise when this barrier is
affected.
Diffusion weighted magnetic resonance imaging is a key investigation technique in modern neuroscience. In clinical settings, diffusion weighted imaging (DWI) and its extension to diffusion tensor imaging (DTI) is usually performed applying the technique of echo-planar imaging (EPI). EPI is the commonly available ultrafast acquisition technique for single-shot acquisition with spatial encoding in a Cartesian system. A drawback of these sequences is their high sensitivity against small perturbations of the magnetic field, caused, e.g., by differences in magnetic susceptibility of soft tissue, bone, and air. The resulting magnetic field inhomogeneities thus cause geometrical distortions and intensity modulations in diffusion weighted images. This complicates the fusion with anatomical T1-or T2-weighted MR images obtained with conventional spin-or gradient echo images and negligible distortion. In order to limit the degradation of diffusion weighted MR data we present here a variational approach based on a reference scan pair with reversed polarity of the phase-and frequency encoding gradients and hence reversed distortion. The key novelty is a tailored nonlinear regularization functional to obtain smooth and diffeomorphic transformations. We incorporate the physical distortion model into a variational image registration framework and derive an accurate and fast correction algorithm. We evaluate the applicability of our approach to distorted DTI brain scans of six healthy volunteers. For all datasets, the automatic correction algorithm considerably reduced the image degradation. We show that after correction, fusion with T1-or T2-weighted images can be obtained by a simple rigid registration. Furthermore, we demonstrate the improvement due to the novel regularization scheme. Most importantly, we show that it provides meaningful, i.e., diffeomorphic geometric transformations, independent of the actual choice of the regularization parameters.
Molecular diffusion and microcirculation in the capillary network result in a distribution of phases in a single voxel in the presence of magnetic field gradients. This distribution produces a spin-echo attenuation. The authors have developed a magnetic resonance (MR) method to image such intravoxel incoherent motions (IVIMs) by using appropriate gradient pulses. Images were generated at 0.5 T in a high-resolution, multisection mode. Diffusion coefficients measured on images of water and acetone phantoms were consistent with published values. Images obtained in the neurologic area from healthy subjects and patients were analyzed in terms of an apparent diffusion coefficient (ADC) incorporating the effect of all IVIMs. Differences were found between various normal and pathologic tissues. The ADC of in vivo water differed from the diffusion coefficient of pure water. Results were assessed in relation to water compartmentation in biologic tissues (restricted diffusion) and tissue perfusion. Nonuniform slow flow of cerebrospinal fluid appeared as a useful feature on IVIM images. Observation of these motions may significantly extend the diagnostic capabilities of MR imaging.
Glioblastoma (GBM) has explosive biologic properties with rapid clinical progression leading to death. Its distinguishing pathologic features, necrosis with surrounding pseudopalisades and microvascular hyperplasia, are believed to be instrumental to its accelerated growth. Microvascular hyperplasia arises in response to the secretion of proangiogenic factors by hypoxic pseudopalisades and allows for peripheral neoplastic expansion. Mechanisms underlying necrosis and hypoxia remain obscure, but vaso-occlusive and prothrombotic contributions could be substantial. Recent investigations on the origin of pseudopalisades suggest that this morphologic phenomenon is created by a tumor cell population actively migrating away from a central hypoxic region and that, in at least a significant subset, hypoxia-induced migration appears due to vaso-occlusion caused by intravascular thrombosis. Both vascular endothelial growth factor induced vascular permeability to plasma coagulation factors and the increased neoplastic expression of tissue factor likely contribute to a prothrombotic state favoring intravascular thrombosis. In addition to prothrombotic mechanisms, vaso-occlusion could also result from angiopoietin-2-mediated endothelial cell apoptosis and vascular regression, which follows neoplastic co-option of native vessels in animal models of gliomas. Vaso-occlusive and prothrombotic mechanisms in GBM could readily explain the presence of pseudopalisades and coagulative necrosis in tissue sections, the emergence of central contrast enhancement and its rapid peripheral expansion on neuroimaging, and the dramatic shift to an accelerated rate of clinical progression. Since the hypoxic induction of angiogenesis appears to support further neoplastic growth, therapeutic targeting of the underlying vascular pathology and thrombosis could provide a new means to prolong time to progression.
Background:
Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and three-dimensional arterial spin labeling (3D-ASL) have been applied to brain tumors; however, the relationship between their parameters and the Ki-67 labeling index (Ki-67 LI) for the grading of gliomas have yet to be investigated.
Purpose:
The aim of this study is to compare multiple parameters obtained from IVIM-DWI and 3D-ASL with the Ki-67 LI when grading gliomas.
Material and methods:
Fifty-two patients with pathologically confirmed gliomas had undergone magnetic resonance imaging (MRI), including IVIM-DWI and 3D-ASL imaging. Mann-Whitney U tests were conducted and receiver operating characteristic (ROC) curves were generated to determine parameters for distinguishing high-grade gliomas (HGGs) from low-grade gliomas (LGGs). These parameters included the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), cerebral blood flow (CBF), and their relative values (rADC, rD, rD*, rf, and rCBF). Spearman correlation analysis was used to assess the correlations of the parameters of MRI with the Ki-67 LI.
Results:
The rADC, rD, and rf were significantly lower in HGGs than in LGGs (P < 0.005 for all). The rD had a significantly greater area under the ROC curve than that of the other parameters in the differentiation of HGGs from LGGs (P < 0.05). Both the rD and rf were moderately negatively correlated with the Ki-67 LI.
Conclusion:
Both the rD and rf can be used for the quantitative prediction of the Ki-67 LI. Among the extracted parameters, the rD had the significantly greatest diagnostic efficacy.
More than two decades of functional magnetic resonance imaging (fMRI) of the human brain have succeeded to identify, with a growing level of precision, the neural basis of multiple cognitive skills within various domains (perception, sensorimotor processes, language, emotion and social cognition …). Progress has been made in the comprehension of the functional organization of localized brain areas. However, the long time required for fMRI acquisition limits the number of experimental conditions performed in a single individual. As a consequence, distinct brain localizations have mostly been studied in separate groups of participants, and their functional relationships at the individual level remain poorly understood. To address this issue, we report here preliminary results on a database of fMRI data acquired on 78 individuals who each performed a total of 29 experimental conditions, grouped in 4 cross-domains functional localizers. This protocol has been designed to efficiently isolate, in a single session, the brain activity associated with language, numerical representation, social perception and reasoning, premotor and visuomotor representations. Analyses are reported at the group and at the individual level, to establish the ability of our protocol to selectively capture distinct regions of interest in a very short time. Test-retest reliability was assessed in a subset of participants. The activity evoked by the different contrasts of the protocol is located in distinct brain networks that, individually, largely replicate previous findings and, taken together, cover a large proportion of the cortical surface. We provide detailed analyses of a subset of regions of relevance: the left frontal, left temporal and middle frontal cortices. These preliminary analyses highlight how combining such a large set of functional contrasts may contribute to establish a finer-grained brain atlas of cognitive functions, especially in regions of high functional overlap. Detailed structural images (structural connectivity, micro-structures, axonal diameter) acquired in the same individuals in the context of the ARCHI database provide a promising situation to explore functional/structural interdependence. Additionally, this protocol might also be used as a way to establish individual neurofunctional signatures in large cohorts.
Background:
The application of conventional magnetic resonance imaging (MRI) in glioma grading is limited and non-specific.
Purpose:
To investigate the application values of MRI, texture analysis (TA) of dynamic contrast-enhanced MRI (DCE-MRI) and intratumoral susceptibility signal (ITSS) on susceptibility weighted imaging (SWI), alone and in combination, for glioma grading.
Material and methods:
Fifty-two patients with pathologically confirmed gliomas who underwent DCE-MRI and SWI were enrolled in this retrospective study. Conventional MRIs were evaluated by the VASARI scoring system. TA of DCE-MRI-derived parameters and the degree of ITSS were compared between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). The diagnostic ability of each parameter and their combination for glioma grading were analyzed.
Results:
Significant statistical differences in VASARI features were observed between LGGs and HGGs ( P < 0.05), of which the enhancement quality had the highest area under the curve (AUC) (0.873) with 93.3% sensitivity and 80% specificity. The TA of DCE-MRI derived parameters were significantly different between LGGs and HGGs ( P < 0.05), of which the uniformity of Ktrans had the highest AUC (0.917) with 93.3% sensitivity and 90% specificity. The degree of ITSS was significantly different between LGGs and HGGs ( P < 0.001). The AUC of the ITSS was 0.925 with 93.3% sensitivity and 90% specificity. The best discriminative power was obtained from a combination of enhancement quality, Ktrans- uniformity, and ITSS, resulting in 96.7% sensitivity, 100.0% specificity, and AUC of 0.993.
Conclusion:
Combining conventional MRI, TA of DCE-MRI, and ITSS on SWI may help to improve the differentiation between LGGs and HGGs.
Susceptibility-weighted imaging (SWI) provides invaluable insight into glioma pathophysiology and internal tumoral architecture. The physical contribution of intratumoral susceptibility signal (ITSS) may correspond to intralesional hemorrhage, calcification, or tumoral neovascularity. In this review, we present emerging evidence of ITSS for assessment of intratumoral calcification, grading of glioma, and factors influencing the pattern of ITSS in glioblastoma. SWI phase imaging assists in identification of intratumoral calcification that aids in narrowing the differential diagnosis. Development of intratumoral calcification posttreatment of glioma serves as an imaging marker of positive therapy response. Grading of tumors with ITSS using information attributed to microhemorrhage and neovascularity in SWI correlates with MR perfusion parameters and histologic grading of glioma and enriches preoperative prognosis. Quantitative susceptibility mapping may provide a means to discriminate subtle calcifications and hemorrhage in tumor imaging. Recent data suggest ITSS patterns in glioblastoma vary depending on tumoral volume and sublocation and correlate with degree of intratumoral necrosis and neovascularity. Increasingly, there is a recognized role of obtaining contrast-enhanced SWI (CE-SWI) for assessment of tumoral margin in high-grade glioma. Significant higher concentration of gadolinium accumulates at the border of the tumoral invasion zone as seen on the SWI sequence; this results from contrast-induced phase shift that clearly delineates the tumor margin. Lastly, absence of ITSS may aid in differentiation between high-grade glioma and primary CNS lymphoma, which typically shows absence of ITSS. We conclude that SWI and CE-SWI are indispensable tools for diagnosis, preoperative grading, posttherapy surveillance, and assessment of glioma.
Purpose:
To determine the utility of intravoxel incoherent motion (IVIM) imaging in grading gliomas and compare IVIM perfusion metrics with arterial spin labeling (ASL)-derived cerebral blood flow (CBF).
Materials and methods:
Fifty-two patients with pathologically confirmed gliomas underwent IVIM and ASL imaging at 3.0T. IVIM perfusion-related diffusivity (D*), perfusion fraction (f), product of f and D*(f×D*), true diffusivity (D), and apparent diffusion coefficient (ADC) were obtained to distinguish glioma grades. The CBF derived from pseudocontinuous ASL within the solid tumor was compared and correlated with IVIM perfusion metrics for grading of gliomas. Values were also normalized to the contralateral normal-appearing white matter. Receiver-operating characteristic was performed to determine diagnostic efficiency. The reliability was estimated with intraclass coefficient, coefficient of variance, and Bland-Altman plots.
Results:
IVIM perfusion metrics and CBF were significantly higher in the high-grade than the low-grade gliomas (P < 0.001), ADC and D were significantly lower in the high-grade than the low-grade gliomas (P < 0.001). f×D* differed significantly between grades II through IV (P < 0.05 for all). The other metrics showed significant difference between grade II and grade III (P < 0.05 for all). Area under the curve (AUC) was largest for f×D* in distinguishing high-grade from low-grade gliomas (AUC = 0.979, P < 0.001) and between grade II and grade III (AUC = 0.957, P < 0.001). f×D* improved diagnostic performance of CBF in grading gliomas and showed strong correlation with CBF (r = 0.696, P < 0.001).
Conclusion:
IVIM-derived metrics are promising biomarkers in preoperative grading gliomas. IVIM imaging may be an additive method to ASL and ADC for evaluating tumor perfusion and diffusion. J. Magn. Reson. Imaging 2016.
This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade-offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo-continuous labeling, background suppression, a segmented three-dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.
To evaluate the feasibility of intravoxel incoherent motion (IVIM) perfusion measurements in the brain with currently available imaging systems.
We acquired high in-plane resolution (1.2 × 1.2 mm(2) ) diffusion-weighted images with 16 different values of b ranging from 0 to 900 s/mm(2) , in three orthogonal directions, on 3T systems with a 32-multichannel receiver head coil. IVIM perfusion maps were extracted by fitting a double exponential model of signal amplitude decay. Regions of interest were drawn in pathological and control regions, where IVIM perfusion parameters were compared to the corresponding dynamic susceptibility contrast (DSC) parameters.
Hyperperfusion was found in the nonnecrotic or cystic part of two histologically proven glioblastoma multiforme and in two histologically proven glioma WHO grade III, as well as in a brain metastasis of lung adenocarcinoma, in a large meningioma, and in a case of ictal hyperperfusion. A monoexponential decay was found in a territory of acute ischemia, as well as in the necrotic part of a glioblastoma. The IVIM perfusion fraction f correlated well with DSC CBV.
Our initial report suggests that high-resolution brain perfusion imaging is feasible with IVIM in the current clinical setting.J. Magn. Reson. Imaging 2013. © 2013 Wiley Periodicals, Inc.
Background and purpose:
Intravoxel incoherent motion MRI has been proposed as an alternative method to measure brain perfusion. Our aim was to evaluate the utility of intravoxel incoherent motion perfusion parameters (the perfusion fraction, the pseudodiffusion coefficient, and the flow-related parameter) to differentiate high- and low-grade brain gliomas.
Materials and methods:
The intravoxel incoherent motion perfusion parameters were assessed in 21 brain gliomas (16 high-grade, 5 low-grade). Images were acquired by using a Stejskal-Tanner diffusion pulse sequence, with 16 values of b (0-900 s/mm(2)) in 3 orthogonal directions on 3T systems equipped with 32 multichannel receiver head coils. The intravoxel incoherent motion perfusion parameters were derived by fitting the intravoxel incoherent motion biexponential model. Regions of interest were drawn in regions of maximum intravoxel incoherent motion perfusion fraction and contralateral control regions. Statistical significance was assessed by using the Student t test. In addition, regions of interest were drawn around all whole tumors and were evaluated with the help of histograms.
Results:
In the regions of maximum perfusion fraction, perfusion fraction was significantly higher in the high-grade group (0.127 ± 0.031) than in the low-grade group (0.084 ± 0.016, P < .001) and in the contralateral control region (0.061 ± 0.011, P < .001). No statistically significant difference was observed for the pseudodiffusion coefficient. The perfusion fraction correlated moderately with dynamic susceptibility contrast relative CBV (r = 0.59). The histograms of the perfusion fraction showed a "heavy-tailed" distribution for high-grade but not low-grade gliomas.
Conclusions:
The intravoxel incoherent motion perfusion fraction is helpful for differentiating high- from low-grade brain gliomas.
The purpose of this study was to evaluate the feasibility of intravoxel incoherent motion (IVIM) imaging and its value in differentiating the histologic grade among human gliomas.
The IVIM model generated parametric images for apparent diffusion coefficient ADC, slow diffusion coefficient D (or D slow), fast diffusion coefficient D* (or D fast), and fractional perfusion-related volume f in 22 patients with gliomas (WHO grade II-IV) using monopolar Stejskal-Tanner diffusion-weighted imaging (DWI) scheme and 14 b values ranging from 0 s/mm(2) to a maximum of 1,300 s/mm(2). A region-of-interest analysis on the tumor as well as in the white matter was conducted. The parameter values were tested for significant differences. The repeatability of the measurements was tested by coefficient of variation and Bland-Altman plots.
D, D*, and f in the high-grade gliomas demonstrated significant differences compared to the healthy white matter. D* and f showed a significant difference between low- and high-grade gliomas. D tended to be slightly lower in the WHO grade II compared to WHO grade III-IV tumors. f and D* demonstrated higher coefficients of variation than the ADC and D in tumor. The Bland-Altman plots demonstrated satisfactory results without any outliers outside the mean ± 1.96 standard deviation.
The IVIM-fitted post-processing of DWI-signal decay in human gliomas could show significantly different values of fractional perfusion-related volume and fast diffusion coefficient between low- and high-grade tumors, which might enable a noninvasive WHO grading in vivo.
Diffusion tensor imaging is often performed by acquiring a series of diffusion-weighted spin-echo echo-planar images with different direction diffusion gradients. A problem of echo-planar images is the geometrical distortions that obtain near junctions between tissues of differing magnetic susceptibility. This results in distorted diffusion-tensor maps. To resolve this we suggest acquiring two images for each diffusion gradient; one with bottom-up and one with top-down traversal of k-space in the phase-encode direction. This achieves the simultaneous goals of providing information on the underlying displacement field and intensity maps with adequate spatial sampling density even in distorted areas. The resulting DT maps exhibit considerably higher geometric fidelity, as assessed by comparison to an image volume acquired using a conventional 3D MR technique.
Measurement of tissue perfusion is important for the functional assessment of organs in vivo. Here we report the use of 1H NMR imaging to generate perfusion maps in the rat brain at 4.7 T. Blood water flowing to the brain is saturated in the neck region with a sliceselective saturation imaging sequence, creating an endogenous tracer in the form of proximally saturated spins. Because proton T1 times are relatively long, particularly at high field strengths, saturated spins exchange with bulk water in the brain and a steady state is created where the regional concentration of saturated spins is determined by the regional blood flow and regional T1. Distal saturation applied equidistantly outside the brain serves as a control for effects of the saturation pulses. Average cerebral blood flow in normocapnic rat brain under halothane anesthesia was determined to be 105 ± 16 cc. 100 g−1. min−1 (mean ± SEM, n = 3), in good agreement with values reported in the literature, and was sensitive to increases in arterial pCO2. This technique allows regional perfusion maps to be measured noninvasively, with the resolution of 1H MRI, and should be readily applicable to human studies. © 1992 Academic Press, Inc.
Perfusion provides oxygen and nutrients to tissues and is closely tied to tissue function while disorders of perfusion are major sources of medical morbidity and mortality. It has been almost two decades since the use of arterial spin labeling (ASL) for noninvasive perfusion imaging was first reported. While initial ASL magnetic resonance imaging (MRI) studies focused primarily on technological development and validation, a number of robust ASL implementations have emerged, and ASL MRI is now also available commercially on several platforms. As a result, basic science and clinical applications of ASL MRI have begun to proliferate. Although ASL MRI can be carried out in any organ, most studies to date have focused on the brain. This review covers selected research and clinical applications of ASL MRI in the brain to illustrate its potential in both neuroscience research and clinical care.
FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford. For this NeuroImage special issue on "20 years of fMRI" we have been asked to write about the history, developments and current status of FSL. We also include some descriptions of parts of FSL that are not well covered in the existing literature. We hope that some of this content might be of interest to users of FSL, and also maybe to new research groups considering creating, releasing and supporting new software packages for brain image analysis.
Dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) data analysis requires the knowledge of the arterial input function (AIF) to quantify the cerebral blood flow (CBF), volume (CBV) and the mean transit time (MTT). AIF can be obtained either manually or using automatic algorithms. We present a method to derive the AIF on the middle cerebral artery (MCA). The algorithm draws a region of interest (ROI) where the MCA is located. Then, it uses a recursive cluster analysis on the ROI to select the arterial voxels. The algorithm had been compared on simulated data to literature state of art automatic algorithms and on clinical data to the manual procedure. On in silico data, our method allows to reconstruct the true AIF and it is less affected by partial volume effect bias than the other methods. In clinical data, automatic AIF provides CBF and MTT maps with a greater contrast level compared to manual AIF ones. Therefore, AIF obtained with the proposed method improves the estimate reliability and provides a quantitatively reliable physiological picture.
Eddy-current (EC) and motion effects in diffusion-tensor imaging (DTI) bias the estimation of quantitative diffusion indices, such as the fractional anisotropy. Both effects can be retrospectively corrected by registering the strongly distorted diffusion-weighted images to less-distorted T2-weighted images acquired without diffusion weighting. Two different affine spatial transformations are usually employed for this correction: slicewise and whole-brain transformations. However, a relation between estimated transformation parameters and EC distortions has not been established yet for the latter approach. In this study, a novel diffusion-gradient-direction-independent estimation of the EC field is proposed based solely on affine whole-brain registration parameters. Using this model, it is demonstrated that a more distinct evaluation of the whole-brain EC effects is possible if the through-plane distortion was considered in addition to the well-known in-plane distortions. Moreover, a comparison of different whole-brain registrations relative to a slicewise approach is performed, in terms of the relative tensor error. Our findings suggest that for appropriate intersubject comparison of DTI data, a whole-brain registration containing nine affine parameters provides comparable performance (between 0 and 3%) to slicewise methods and can be performed in a fraction of the time.
An accurate characterization of tissue residue function R(t) in bolus-tracking magnetic resonance imaging is of crucial importance to quantify cerebral hemodynamics. R(t) estimation requires to solve a deconvolution problem. The most popular deconvolution method is singular value decomposition (SVD). However, SVD is known to bear some limitations, e.g., R(t) profiles exhibit nonphysiological oscillations and take on negative values. In addition, SVD estimates are biased in presence of bolus delay and dispersion. Recently, other deconvolution methods have been proposed, in particular block-circulant SVD (cSVD) and Tikhonov regularization (TIKH). Here we propose a new method based on nonlinear stochastic regularization (NSR). NSR is tested on simulated data and compared with SVD, cSVD, and TIKH in presence and absence of bolus dispersion. A clinical case in one patient has also been considered. NSR is shown to perform better than SVD, cSVD, and TIKH in reconstructing both the peak and the residue function, in particular when bolus dispersion is considered. In addition, differently from SVD, cSVD, and TIKH, NSR always provides positive and smooth R(t).
The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).
To differentiate glioma grade based on blood flow measured using continuous arterial spin labeled (CASL) perfusion MRI, implemented at 3 Tesla for improved signal-to-noise ratio (SNR) and spin labeling effect.
CASL perfusion images were obtained preoperatively in 26 patients with brain neoplasms (19 high-grade gliomas (HGGs; WHO grades 3 and 4) and seven low-grade gliomas (LGGs; WHO grades 1 and 2)). The mean and maximum tumor blood flow (TBF and TBFmax) were calculated in the neoplasm, including surrounding infiltrating tumor vs. edema. Measures normalized to global CBF (nTBF and nTBFmax) were also obtained.
Normalized measures of TBFmax provided the best distinction between HGG and LGG groups (Wilcoxon rank sum test, P = 0.01). Seventeen of 19 HGGs showed nTBFmax > 1.0, and 15 of 19 showed nTBFmax > 1.3. Four of seven LGGs showed nTBFmax < 1.0, and six of seven showed nTBFmax < 1.3. Absolute TBFmax also differed significantly between the HGG and LGG groups (P = 0.04). TBFmax in 11 of 17 HGGs was >50 mL/100 g/min (mean +/- SD = 94.9 +/- 71.7 mL/100 g/min). All but one LGGs showed TBFmax < or = 50 mL/100 g/min (mean +/- SD = 42.8 +/- 22.0 mL/100 g/min).
CASL perfusion MRI provides a quantitative, noninvasive alternative to dynamic susceptibility contrast perfusion MR methods for evaluating gliomas.
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What can we see with IVIM MRI? Neuroimage