Measuring blood volume and vascular transfer constant from dynamic, T(2)*-weighted contrast-enhanced MRI

Synthetic interpolated DSA for radiation exposure reduction via gamma variate contrast flow modeling: a retrospective cohort study

BACKGROUND

Digital subtraction angiography (DSA) yields high cumulative radiation dosages (RD) delivered to patients. We present a temporal interpolation of low frame rate angiograms as a method to reduce cumulative RDs.

METHODS

Patients undergoing interventional evaluation and treatment of cerebrovascular vasospasm following subarachnoid hemorrhage were retrospectively identified. DSAs containing pre- and post-intervention runs capturing the full arterial, capillary, and venous phases with at least 16 frames each were selected. Frame rate reduction (FRR) of the original DSAs was performed to 50%, 66%, and 75% of the original frame rate. Missing frames were regenerated by sampling a gamma variate model (GVM) fit to the contrast response curves to the reduced data. A formal reader study was performed to assess the diagnostic accuracy of the "synthetic" studies (sDSA) compared to the original DSA.

RESULTS

Thirty-eight studies met inclusion criteria (average RD 1,361.9 mGy). Seven were excluded for differing views, magnifications, or motion. GVMs fit to 50%, 66%, and 75% FRR studies demonstrated average voxel errors of 2.0 ± 2.5% (mean ± standard deviation), 6.5 ± 1.5%, and 27 ± 2%, respectively for anteroposterior projections, 2.0 ± 2.2%, 15.0 ± 3.1%, and 14.8 ± 13.0% for lateral projections, respectively. Reconstructions took 0.51 s/study. Reader studies demonstrated an average rating of 12.8 (95% CI 12.3-13.3) for 75% FRR, 12.7 (12.2-13.2) for 66% FRR and 12.0 (11.5-12.5) for 50% FRR using Subjective Image Grading Scale. Kendall's coefficient of concordance resulted in W = 0.506.

CONCLUSION

FRR by 75% combined with GVM reconstruction does not compromise diagnostic quality for the assessment of cerebral vasculature.

RELEVANCE STATEMENT

Using this novel algorithm, it is possible to reduce the frame rate of DSA by as much as 75%, with a proportional reduction in radiation exposure, without degrading imaging quality.

KEY POINTS

• DSA delivers some of the highest doses of radiation to patients. • Frame rate reduction (FRR) was combined with bolus tracking to interpolate intermediate frames. • This technique provided a 75% FRR with preservation of diagnostic utility as graded by a formal reader study for cerebral angiography performed for the evaluation of cerebral vasospasm. • This approach can be applied to other types of angiography studies.

Vascular contributions to Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by progressive neurodegeneration and cognitive decline. Understanding the pathophysiology underlying AD is paramount for the management of individuals at risk of and suffering from AD. The vascular hypothesis stipulates a relationship between cardiovascular disease and AD-related changes although the nature of this relationship remains unknown. In this review, we discuss several potential pathological pathways of vascular involvement in AD that have been described including dysregulation of neurovascular coupling, disruption of the blood brain barrier, and reduced clearance of metabolite waste such as beta-amyloid, a toxic peptide considered the hallmark of AD. We will also discuss the two-hit hypothesis which proposes a 2-step positive feedback loop in which microvascular insults precede the accumulation of Aß and are thought to be at the origin of the disease development. At neuroimaging, signs of vascular dysfunction such as chronic cerebral hypoperfusion have been demonstrated, appearing early in AD, even before cognitive decline and alteration of traditional biomarkers. Cerebral small vessel disease such as cerebral amyloid angiopathy, characterized by the aggregation of Aß in the vessel wall, is highly prevalent in vascular dementia and AD patients. Current data is unclear whether cardiovascular disease causes, precipitates, amplifies, precedes, or simply coincides with AD. Targeted imaging tools to quantitatively evaluate the intracranial vasculature and longitudinal studies in individuals at risk for or in the early stages of the AD continuum could be critical in disentangling this complex relationship between vascular disease and AD.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

A comprehensive evaluation and impact of normalization of generalized tracer kinetic model parameters to characterize blood-brain-barrier permeability in normal-appearing and tumor tissue regions of patients with glioma

RATIONALE AND OBJECTIVES

To comprehensively evaluate robustness and variations of DCE-MRI derived generalized-tracer-kinetic-model (GTKM) parameters in healthy and tumor tissues and impact of normalization in mitigating these variations on application to glioma.

MATERIALS (PATIENTS) AND METHODS

A retrospective study included pre-operative 31 high-grade-glioma(HGG), 22 low-grade-glioma(LGG) and 33 follow-up data from 10 patients a prospective study with 4 HGG subjects. Voxel-wise GTKM was fitted to DCE-MRI data to estimate K^trans, v_e, v_b. Simulations were used to evaluate noise sensitivity. Variation of parameters with-respect-to arterial-input-function (AIF) variation and data length were studied. Normalization of parameters with-respect-to mean values in gray-matter (GM) and white-matter (WM) regions (GM-Type-2, WM-Type-2) and mean curves (GM-Type-1, WM-Type-1) were also evaluated. Co-efficient-of-variation(CoV), relative-percentage-error (RPE), Box-Whisker plots, bar graphs and t-test were used for comparison.

RESULTS

GTKM was fitted well in all tissue regions. K^trans and v_e in contrast-enhancing (CE) has shown improved noise sensitivity in longer data. v_b was reliable in all tissues. Mean AIF and C(t) peaks showed ~38% and ~35% variations. During simulation, normalizations have mitigated variations due to changes in AIF amplitude in K^trans and v_b.. v_e was less sensitive to normalizations. CoV of K^trans and v_b has reduced ~70% after GM-Type-1 normalization and ~80% after GM-Type-2 normalization, respectively. GM-Type-1 (p = 0.003) and GM-Type-2 (p = 0.006) normalizations have significantly improved differentiation of HGG and LGG using K^trans.

CONCLUSION

K^trans and v_b can be reliably estimated in normal-appearing brain tissues and can be used for normalization of corresponding parameters in tumor tissues for mitigating inter-subject variability due to errors in AIF. Normalized K^trans and v_b provided improved differentiation of HGG and LGG.

Development of a spiral spin- and gradient-echo (spiral-SAGE) approach for improved multi-parametric dynamic contrast neuroimaging

PURPOSE

The purpose of this study was to develop a spiral-based combined spin- and gradient-echo (spiral-SAGE) method for simultaneous dynamic contrast-enhanced (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI).

METHODS

Using this sequence, we obtained gradient-echo TEs of 1.69 and 26 ms, a SE TE of 87.72 ms, with a TR of 1663 ms. Using an iterative SENSE reconstruction followed by deblurring, spiral-induced image artifacts were minimized. Healthy volunteer images are shown to demonstrate image quality using the optimized reconstruction, as well as for comparison with EPI-based SAGE. A bioreactor phantom was used to compare dynamic-contrast time courses with both spiral-SAGE and EPI-SAGE. A proof-of-concept cohort of patients with brain tumors shows the range of hemodynamic maps available using spiral-SAGE.

RESULTS

Comparison of spiral-SAGE images with conventional EPI-SAGE images illustrates substantial reductions of image distortion and artifactual image intensity variations. Bioreactor phantom data show similar dynamic contrast time courses between standard EPI-SAGE and spiral-SAGE for the second and third echoes, whereas first-echo data show improvements in quantifying T₁ changes with shorter echo times. In a cohort of patients with brain tumors, spiral-SAGE-based perfusion and permeability maps are shown with comparison with the standard single-echo EPI perfusion map.

CONCLUSION

Spiral-SAGE provides a substantial improvement for the assessment of perfusion and permeability by mitigating artifacts typically encountered with EPI and by providing a shorter echo time for improved characterization of permeability. Spiral-SAGE enables quantification of perfusion, permeability, and vessel architectural parameters, as demonstrated in brain tumors.

A dynamic simulation framework for CT perfusion in stroke assessment built from first principles

PURPOSE

Physicians utilize cerebral perfusion maps (e.g., cerebral blood flow, cerebral blood volume, transit time) to prescribe the plan of care for stroke patients. Variability in scanning techniques and post-processing software can result in differences between these perfusion maps. To determine which techniques are acceptable for clinical care, it is important to validate the accuracy and reproducibility of the perfusion maps. Validation using clinical data is challenging due to the lack of a gold standard to assess cerebral perfusion and the impracticality of scanning patients multiple times with different scanning techniques. In contrast, simulated data from a realistic digital phantom of the cerebral perfusion in acute stroke patients would enable studies to optimize and validate the scanning and post-processing techniques.

METHODS

We describe a complete framework to simulate CT perfusion studies for stroke assessment. We begin by expanding the XCAT brain phantom to enable spatially varying contrast agent dynamics and incorporate a realistic model of the dynamics in the cerebral vasculature derived from first principles. A dynamic CT simulator utilizes the time-concentration curves to define the contrast agent concentration in the object at each time point and generates CT perfusion images compatible with commercially available post-processing software. We also generate ground truth perfusion maps to which the maps generated by post-processing software can be compared.

RESULTS

We demonstrate a dynamic CT perfusion study of a simulated patient with an ischemic stroke and the resulting perfusion maps generated by post-processing software. We include a visual comparison between the computer-generated perfusion maps and the ground truth perfusion maps. The framework is highly tunable; users can modify the perfusion properties (e.g., occlusion location, CBF, CBV, and MTT), scanner specifications (e.g., focal spot size and detector configuration), scanning protocol (e.g., kVp and mAs), and reconstruction parameters (e.g., slice thickness and reconstruction filter).

CONCLUSIONS

This framework provides realistic test data with the underlying ground truth that enables a robust assessment of CT perfusion techniques and post-processing methods for stroke assessment.

Regional Lung Perfusion Analysis in Experimental ARDS by Electrical Impedance and Computed Tomography

Electrical impedance tomography is clinically used to trace ventilation related changes in electrical conductivity of lung tissue. Estimating regional pulmonary perfusion using electrical impedance tomography is still a matter of research. To support clinical decision making, reliable bedside information of pulmonary perfusion is needed. We introduce a method to robustly detect pulmonary perfusion based on indicator-enhanced electrical impedance tomography and validate it by dynamic multidetector computed tomography in two experimental models of acute respiratory distress syndrome. The acute injury was induced in a sublobar segment of the right lung by saline lavage or endotoxin instillation in eight anesthetized mechanically ventilated pigs. For electrical impedance tomography measurements, a conductive bolus (10% saline solution) was injected into the right ventricle during breath hold. Electrical impedance tomography perfusion images were reconstructed by linear and normalized Gauss-Newton reconstruction on a finite element mesh with subsequent element-wise signal and feature analysis. An iodinated contrast agent was used to compute pulmonary blood flow via dynamic multidetector computed tomography. Spatial perfusion was estimated based on first-pass indicator dilution for both electrical impedance and multidetector computed tomography and compared by Pearson correlation and Bland-Altman analysis. Strong correlation was found in dorsoventral (r = 0.92) and in right-to-left directions (r = 0.85) with good limits of agreement of 8.74% in eight lung segments. With a robust electrical impedance tomography perfusion estimation method, we found strong agreement between multidetector computed and electrical impedance tomography perfusion in healthy and regionally injured lungs and demonstrated feasibility of electrical impedance tomography perfusion imaging.

Comparative evaluation of cerebral gliomas using rCBV measurements during sequential acquisition of T1-perfusion and T2*-perfusion MRI

Objective

To assess the inter-technique agreement of relative cerebral blood volume (rCBV) measurements obtained using T1- and T2*-perfusion MRI on 3T scanner in glioma patients.

Methods

A total of 49 adult patients with gliomas underwent both on T1- and T2*-perfusion in the same scanning session, and rCBV maps were estimated using both methods. For the quantitative analysis; Two independent observers recorded the rCBV values from the tumor as well as contralateral brain tissue from both T1- and T2*-perfusion. Inter-observer and inter-technique rCBV measurement agreement were determined by using 95% Bland-Altman limits of agreement and intra-class correlation coefficient (ICC) statistics.

Results

Qualitative analysis of the conventional and perfusion images showed that 16/49 (32.65%) tumors showed high susceptibility, and in these patients T2*-perfusion maps were suboptimal. Bland-Altman plots revealed an agreement between two independent observers recorded rCBV values for both T1- and T2*-perfusion. The ICC demonstrated strong agreement between rCBV values recorded by two observers for both T2* (ICC = 0.96, p = 0.040) and T1 (ICC = 0.97, p = 0.026) perfusion and similarly, good agreement was noted between rCBV estimated using two methods (ICC = 0.74, P<0.001). ROC analysis showed that rCBV estimated using T1- and T2*-perfusion methods were able to discriminate between grade-III and grade-IV tumors with AUC of 0.723 and 0.767 respectively. Comparison of AUC values of two ROC curves did not show any significant difference.

Conclusions

In the current study, T1- and T2*-perfusion showed similar diagnostic performance for discrimination of grade III and grade IV gliomas; however, T1-perfusion was found to be better for the evaluation of tumors with intratumoral hemorrhage, postoperative recurrent tumors, and lesions near skull base. We conclude that T1-perfusion MRI with a single dose of contrast could be used as an alternative to T2*-perfusion to overcome the issues associated with this technique in brain tumors for reliable perfusion quantification.

Mapping water exchange across the blood-brain barrier using 3D diffusion-prepared arterial spin labeled perfusion MRI

PURPOSE

To present a novel MR pulse sequence and modeling algorithm to quantify the water exchange rate (k_w ) across the blood-brain barrier (BBB) without contrast, and to evaluate its clinical utility in a cohort of elderly subjects at risk of cerebral small vessel disease (SVD).

METHODS

A diffusion preparation module with spoiling of non-Carr-Purcell-Meiboom-Gill signals was integrated with pseudo-continuous arterial spin labeling (pCASL) and 3D gradient and spin echo (GRASE) readout. The tissue/capillary fraction of the arterial spin labeling (ASL) signal was separated by appropriate diffusion weighting (b = 50 s/mm² ). k_w was quantified using a single-pass approximation (SPA) model with total generalized variation (TGV) regularization. Nineteen elderly subjects were recruited and underwent 2 MRIs to evaluate the reproducibility of the proposed technique. Correlation analysis was performed between k_w and vascular risk factors, Clinical Dementia Rating (CDR) scale, neurocognitive assessments, and white matter hyperintensity (WMH).

RESULTS

The capillary/tissue fraction of ASL signal can be reliably differentiated with the diffusion weighting of b = 50 s/mm² , given ~100-fold difference between the (pseudo-)diffusion coefficients of the 2 compartments. Good reproducibility of k_w measurements (intraclass correlation coefficient = 0.75) was achieved. Average k_w was 105.0 ± 20.6, 109.6 ± 18.9, and 94.1 ± 19.6 min^-1 for whole brain, gray and white matter. k_w was increased by 28.2%/19.5% in subjects with diabetes/hypercholesterolemia. Significant correlations between k_w and vascular risk factors, CDR, executive/memory function, and the Fazekas scale of WMH were observed.

CONCLUSION

A diffusion prepared 3D GRASE pCASL sequence with TGV regularized SPA modeling was proposed to measure BBB water permeability noninvasively with good reproducibility. k_w may serve as an imaging marker of cerebral SVD and associated cognitive impairment.

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

BACKGROUND AND PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

MRI measurements of Blood-Brain Barrier function in dementia: A review of recent studies

Blood-brain barrier (BBB) separates the systemic circulation and the brain, regulating transport of most molecules to protect the brain microenvironment. Multiple structural and functional components preserve the integrity of the BBB. Several imaging modalities are available to study disruption of the BBB. However, the subtle changes in BBB leakage that occurs in vascular cognitive impairment and Alzheimer's disease have been less well studied. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is the most widely adopted non-invasive imaging technique for evaluating BBB breakdown. It is used as a significant marker for a wide variety of diseases with large permeability leaks, such as brain tumors and multiple sclerosis, to more subtle disruption in chronic vascular disease and dementia. DCE-MRI analysis of BBB includes both model-free parameters and quantitative parameters using pharmacokinetic modelling. We review MRI studies of BBB breakdown in dementia. The challenges in measuring subtle BBB changes and the state of the art techniques are initially examined. Subsequently, a systematic review comparing methodologies from recent in-vivo MRI studies is presented. Various factors related to subtle BBB permeability measurement such as DCE-MRI acquisition parameters, arterial input assessment, T1 mapping and data analysis methods are reviewed with the focus on finding the optimal technique. Finally, the reported BBB permeability values in dementia are compared across different studies and across various brain regions. We conclude that reliable measurement of low-level BBB permeability across sites remains a difficult problem and a standardization of the methodology for both data acquisition and quantitative analysis is required. This article is part of the Special Issue entitled 'Cerebral Ischemia'.

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

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

DCE MRI reveals early decreased and later increased placenta perfusion after a stress challenge during pregnancy in a mouse model

OBJECTIVES

Stress during pregnancy is known to have negative effects on fetal outcome. The purpose of this exploratory study was to examine placental perfusion alterations after stress challenge during pregnancy in a mouse model.

MATERIAL AND METHODS

Seven Tesla MRI was performed on pregnant mice at embrionic day (ED) 14.5 and 16.5. Twenty dams were exposed to an established acoustic stress challenge model while twenty non-exposed dams served as controls. Placental perfusion was analyzed in dynamic contrast-enhanced (DCE) MRI using the steepest slope model. The two functional placental compartments, the highly vascularized labyrinth and the endocrine junctional zone, were assessed separately.

RESULTS

Statistical analysis revealed decreased perfusion levels in the stress group at ED 14.5 compared to controls in both placenta compartments. On ED 16.5, the perfusion level increased significantly in the stress group while placenta perfusion in controls remained similar or even slightly decreased leading to an overall increased perfusion in the stress group on ED 16.5 compared to controls.

CONCLUSION

MR imaging allows noninvasive placenta perfusion assessment in this fetal stress mimicking animal model. In this exploratory study, we demonstrated that stress challenge during pregnancy leads to an initial reduction followed by an increase of placenta perfusion.

Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading

BACKGROUND AND OBJECTIVE

To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (K^trans) for glioma grading and to explore the diagnostic performance of the histogram analysis of K^trans and blood plasma volume (v_p).

METHODS

We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of K^trans and v_p, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades.

RESULTS

Histogram parameters of K^trans and v_p showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean K^trans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of K^trans and v_p.

CONCLUSIONS

Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor K^trans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.

Quantitative analysis of permeability for glioma grading using dynamic contrast-enhanced magnetic resonance imaging

The objective of the present study was to quantitatively analyze the permeability of tumor entity and peritumor edema in glioma grading, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In the present retrospective study, 80 patients underwent T1-weighted DCE-MRI examination at 3.0 T and the pathological results (including astrocytoma and oligodendroglioma) were obtained between January 2012 and June 2015. All cases were surgically validated as grade I–IV gliomas. The original DCE-MRI data were analyzed using dual compartment modified Tofts model. The forward volume transfer constant (K^trans), backflux rate (k_ep) and fractional volume (v_e) were calculated with the region of interest selected on the highest permeability area of the tumor entity and peritumor edema. Analysis of variance with the Bonferroni correction was used to compare the values of K^trans, k_ep, and v_e of the tumor entity and peritumor edema in different glioma grades. The results of the present study revealed that the K^trans, k_ep, and v_e values in each stage were associated with the pathological grading (r=0.951, 0.804 and 0.766, respectively). There were significant differences identified between different tumor grades in K^trans, k_ep, with the exception being between grades II and III in k_ep. In addition, there was a significant difference revealed between grade I/II and grade III/IV in v_e. Receiver operator characteristics curve analysis was used to evaluate the diagnosis accuracies of permeability parameters. K^trans was demonstrated to exhibit the highest sensitivity and specificity for evaluating the tumor grade. With the threshold values of 0.160, 0.420 and 0.935 in K^trans on tumor, glioma grades I vs. II, II vs III and III vs. IV may be differentiated with sensitivities of 0.900, 0.950 and 0.950, and specificities of 0.950, 0.950 and 0.850, respectively. Furthermore, associations were observed between the K^trans, k_ep and v_e values of peritumor edema and the pathological grading in glioma (K^trans r=0.438, P<0.001; K_ep r=0.385, P<0.001; V_e r=0.397, P<0.001, respectively). K^trans values in peritumoral edema revealed significant differences between low-grade and high-grade glioma. The sensitivity and specificity for K^trans of peritumor edema were 0.975 and 0.950, with a threshold value of 0.007. Therefore, the DCE-MRI parameters of K^trans of tumor entity and peritumor edema in gliomas may be used to accurately differentiate glioma grades.

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

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

Bayesian Quantification of Contrast-Enhanced Ultrasound Images With Adaptive Inclusion of an Irreversible Component

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity and it can be particularly useful in early detection and grading of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. However, in some cases the heterogeneity of the kinetics can be such that even the Gamma model does not properly describe the curve, with a high number of outliers. In this work we apply to CEUS data the single compartment recirculation model (SCR) which takes explicitly into account the trapping of the microbubbles contrast agent by adding to the single Gamma-variate model its integral. The SCR model, originally proposed for dynamic-susceptibility magnetic resonance imaging, is solved here at pixel level within a Bayesian framework using Variational Bayes (VB). We also include the automatic relevant determination (ARD) algorithm to automatically infer the model complexity (SCR vs. Gamma model) from the data. We demonstrate that the inclusion of trapping best describes the CEUS patterns in 50% of the pixels, with the other 50% best fitted by a single Gamma. Such results highlight the necessity of the use ARD, to automatically exclude the irreversible component where not supported by the data. VB with ARD returns precise estimates in the majority of the kinetics (88% of total percentage of pixels) in a limited computational time (on average, 3.6 min per subject). Moreover, the impact of the additional trapping component has been evaluated for the differentiation of rheumatoid and non-rheumatoid patients, by means of a support vector machine classifier with backward feature selection. The results show that the trapping parameter is always present in the selected feature set, and improves the classification.

Validation of Blood Volume Fraction Quantification with 3D Gradient Echo Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Porcine Skeletal Muscle

The purpose of this study was to assess the accuracy of fractional blood volume (v_b) estimates in low-perfused and low-vascularized tissue using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The results of different MRI methods were compared with histology to evaluate the accuracy of these methods under clinical conditions. v_b was estimated by DCE-MRI using a 3D gradient echo sequence with k-space undersampling in five muscle groups in the hind leg of 9 female pigs. Two gadolinium-based contrast agents (CA) were used: a rapidly extravasating, extracellular, gadolinium-based, low-molecular-weight contrast agent (LMCA, gadoterate meglumine) and an extracellular, gadolinium-based, albumin-binding, slowly extravasating blood pool contrast agent (BPCA, gadofosveset trisodium). LMCA data were evaluated using the extended Tofts model (ETM) and the two-compartment exchange model (2CXM). The images acquired with administration of the BPCA were used to evaluate the accuracy of v_b estimation with a bolus deconvolution technique (BD) and a method we call equilibrium MRI (EqMRI). The latter calculates the ratio of the magnitude of the relaxation rate change in the tissue curve at an approximate equilibrium state to the height of the same area of the arterial input function (AIF). Immunohistochemical staining with isolectin was used to label endothelium. A light microscope was used to estimate the fractional vascular area by relating the vascular region to the total tissue region (immunohistochemical vessel staining, IHVS). In addition, the percentage fraction of vascular volume was determined by multiplying the microvascular density (MVD) with the average estimated capillary lumen, π(d2)2, where d = 8μm is the assumed capillary diameter (microvascular density estimation, MVDE). Except for ETM values, highly significant correlations were found between most of the MRI methods investigated. In the cranial thigh, for example, the v_b medians (interquartile range, IQRs) of IHVS, MVDE, BD, EqMRI, 2CXM and ETM were v_b = 0.7(0.3)%, 1.1(0.4)%, 1.1(0.4)%, 1.4(0.3)%, 1.2(1.8)% and 0.1(0.2)%, respectively. Variances, expressed by the difference between third and first quartiles (IQR) were highest for the 2CXM for all muscle groups. High correlations between the values in four muscle groups—medial, cranial, lateral thigh and lower leg - estimated with MRI and histology were found between BD and EqMRI, MVDE and 2CXM and IHVS and ETM. Except for the ETM, no significant differences between the v_b medians of all MRI methods were revealed with the Wilcoxon rank sum test. The same holds for all muscle regions using the 2CXM and MVDE. Except for cranial thigh muscle, no significant difference was found between EqMRI and MVDE. And except for the cranial thigh and the lower leg muscle, there was also no significant difference between the v_b medians of BD and MVDE. Overall, there was good v_b agreement between histology and the BPCA MRI methods and the 2CXM LMCA approach with the exception of the ETM method. Although LMCA models have the advantage of providing excellent curve fits and can in principle determine more physiological parameters than BPCA methods, they yield more inaccurate results.

Permeability Imaging as a Biomarker of Leptomeningeal Collateral Flow in Patients with Intracranial Arterial Stenosis

Different methods of angiography are of great clinical utility; however, it still remains unstandardized as which method would be suitable to determine cerebral collateral circulation. Here we compared digital subtraction angiography (DSA), computer tomography angiography (CTA) and dynamic contrast-enhanced T1-weighted imaging magnetic resonance imaging (MRI) findings in seven patients with severe intracranial arterial stenosis, and determine whether volume transfer constant (K(trans)) maps of permeability imaging could be used as the biomarkers of cerebral collateral circulation. We retrospectively reviewed seven adult patients with severe intracranial arterial stenosis or occlusion with a complete parenchymal and vascular imaging work-up. DSA, CTA source imaging (CTA-SI), arterial spin labeling (ASL), and K(trans) maps were used to assess their collateral flow. Cohen's Kappa coefficient was calculated to test the consistency of their collateral scores. A reasonable agreement was found between DSA and K(trans) maps (Kappa = 0.502, P < 0.001) when all 15 regional vascular sites were included, and a better agreement found after exclusion of perforating artery territories (N = 10 sites, Kappa = 0.766, P < 0.001). The agreement between CTA-SI and DSA was moderate on all 15 sites (Kappa = 0.413, P < 0.001) and 10 sites (Kappa = 0.329, P < 0.001). The agreement between ASL and DSA was least favorable, no matter for all 15 sites (Kappa = 0.270, P < 0.001) or 10 sites (Kappa = 0.205, P = 0.002). K(trans) maps are useful and promising for leptomeningeal collateral assessment, when compared to CTA-SI or ASL. Further studies are requited for verify its validity in a large registry of patients.

Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation

Relative cerebral blood volume (rCBV) is a magnetic resonance imaging biomarker that is used to differentiate progression from pseudoprogression in patients with glioblastoma multiforme, the most common primary brain tumor. However, calculated rCBV depends considerably on the software used. Automating all steps required for rCBV calculation is important, as user interaction can lead to increased variability and possible inaccuracies in clinical decision-making. Here, we present an automated tool for computing rCBV from dynamic susceptibility contrast-magnetic resonance imaging that includes leakage correction. The entrance and exit bolus time points are automatically calculated using wavelet-based detection. The proposed tool is compared with 3 Food and Drug Administration-approved software packages, 1 automatic and 2 requiring user interaction, on a data set of 43 patients. We also evaluate manual and automated white matter (WM) selection for normalization of the cerebral blood volume maps. Our system showed good agreement with 2 of the 3 software packages. The intraclass correlation coefficient for all comparisons between the same software operated by different people was >0.880, except for FuncTool when operated by user 1 versus user 2. Little variability in agreement between software tools was observed when using different WM selection techniques. Our algorithm for automatic rCBV calculation with leakage correction and automated WM selection agrees well with 2 out of the 3 FDA-approved software packages.

Spiral Perfusion Imaging With Consecutive Echoes (SPICE™) for the Simultaneous Mapping of DSC- and DCE-MRI Parameters in Brain Tumor Patients: Theory and Initial Feasibility

Dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) are the perfusion imaging techniques most frequently used to probe the angiogenic character of brain neoplasms. With these methods, T₁- and T₂/T₂*-weighted imaging sequences are used to image the distribution of gadolinium (Gd)-based contrast agents. However, it is well known that Gd exhibits combined T₁, T₂, and T₂* shortening effects in tissue, and therefore, the results of both DCE- and DSC-MRI can be confounded by these opposing effects. In particular, residual susceptibility effects compete with T₁ shortening, which can confound DCE-MRI parameters, whereas dipolar T₁ and T₂ leakage and residual susceptibility effects can confound DSC-MRI parameters. We introduce here a novel perfusion imaging acquisition and postprocessing method termed Spiral Perfusion Imaging with Consecutive Echoes (SPICE) that can be used to simultaneously acquire DCE- and DSC-MRI data, which requires only a single dose of the Gd contrast agent, does not require the collection of a precontrast T₁ map for DCE-MRI processing, and eliminates the confounding contrast agent effects due to contrast extravasation. A detailed mathematical description of SPICE is provided here along with a demonstration of its utility in patients with high-grade glioma.

Assessment of a simplified spin and gradient echo (sSAGE) approach for human brain tumor perfusion imaging

The goal of this study was to validate a simplified spin- and gradient-echo (sSAGE) approach to obtain T₁-corrected dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) data in a clinical brain tumor population. A five-echo SAGE sequence was used to acquire DSC-MRI data (n=8 patients, 3 primary glioma, and 5 brain metastases). The ΔR₂^⁎ and ΔR₂ time series obtained from a nonlinear fit of all echoes (SAGE) were compared to ΔR₂^⁎ and ΔR₂ time series obtained analytically (sSAGE) using three echoes (two GEs and one SE). Through the use of multiple echoes, both methods removed T₁ leakage effects from the ΔR₂^⁎ and ΔR₂ time series, and the sSAGE ΔR₂^⁎ and ΔR₂ time series were highly correlated with those from SAGE, with average correlations of 0.9. The resulting hemodynamic parameters included GE and SE cerebral blood volume (CBV), cerebral blood flow (CBF), mean vessel diameter (mVD), volume transfer constant (K^trans), and volume fraction of the extravascular extracellular space (v_e). For each metric, there was good correlation (>0.86) between sSAGE and SAGE, with no significant differences. The sSAGE method provides T₁-corrected GE and SE DSC-MRI parameters in an efficient and clinically feasible manner.

The Role of Dynamic Contrast-Enhanced MR in Evaluating Level III Collateral Circulation in a Rat Model of Acute Ischemic Stroke

The study aimed to investigate the correlations between parameters of permeability magnetic resonance (MR) and the intensity of vasculature in the focal ischemic cortex of a rat model of middle cerebral artery occlusion. In the present study, sham operation or ischemic-reperfusion with tissue plasminogen activator (tPA) thrombolysis were performed in rats. Cranial MR scans and brain tissue samples were obtained from all animals. Brain slices were stained for immunohistological analyses with confocal fluorescence microscopy, and the intensities of microvessels and capillaries were calculated. Consistency between collateral circulation imaging classification and pathological vascular density was analyzed. We found that the K ^trans value and capillary intensity have the similar trends of declining and increasing, according to different time points, if compared with the sham operation group (P < 0.05). Permeability parameters have better correlations with capillary intensity, and K ^trans value had the best correlation at 4.5 h (kappa = 0.764, P < 0.001), while injection area under curve (IAUC) at 7 days (kappa = 0.725, P < 0.001). Susceptibility-weighted imaging (SWI) exhibited better correlation with microvessel intensity at both 3 days (kappa = 0.715, P < 0.001) and 7 days (kappa = 0.719, P < 0.001). In conclusion, the permeability parameters, such as IAUC and K ^trans map, can quantitatively assess capillary intensity, which may indicate angiogenesis categorized as level III collateral circulation after ischemic stroke.

Validation of a T1 and T2* leakage correction method based on multiecho dynamic susceptibility contrast MRI using MION as a reference standard

PURPOSE

A combined biophysical- and pharmacokinetic-based method is proposed to separate, quantify, and correct for both T1 and T2* leakage effects using dual-echo dynamic susceptibility contrast (DSC) acquisitions to provide more accurate hemodynamic measures, as validated by a reference intravascular contrast agent (CA).

THEORY AND METHODS

Dual-echo DSC-MRI data were acquired in two rodent glioma models. The T1 leakage effects were removed and also quantified to subsequently correct for the remaining T2* leakage effects. Pharmacokinetic, biophysical, and combined biophysical and pharmacokinetic models were used to obtain corrected cerebral blood volume (CBV) and cerebral blood flow (CBF), and these were compared with CBV and CBF from an intravascular CA.

RESULTS

T1 -corrected CBV was significantly overestimated compared with MION CBV, while T1 + T2*-correction yielded CBV values closer to the reference values. The pharmacokinetic and simplified biophysical methods showed similar results and underestimated CBV in tumors exhibiting strong T2* leakage effects. The combined method was effective for correcting T1 and T2* leakage effects across tumor types.

CONCLUSION

Correcting for both T1 and T2* leakage effects yielded more accurate measures of CBV. The combined correction method yields more reliable CBV measures than either correction method alone, but for certain brain tumor types (e.g., gliomas), the simplified biophysical method may provide a robust and computationally efficient alternative. Magn Reson Med 76:613-625, 2016. © 2015 Wiley Periodicals, Inc.

Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma

BACKGROUND AND PURPOSE

Relative cerebral blood volume, as measured by T2*-weighted dynamic susceptibility-weighted contrast-enhanced MRI, represents the most robust and widely used perfusion MR imaging metric in neuro-oncology. Our aim was to determine whether differences in modeling implementation will impact the correction of leakage effects (from blood-brain barrier disruption) and the accuracy of relative CBV calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced MR imaging at 3T field strength.

MATERIALS AND METHODS

This study included 52 patients with glioma undergoing DSC MR imaging. Thirty-six patients underwent both non-preload dose- and preload dose-corrected DSC acquisitions, with 16 patients undergoing preload dose-corrected acquisitions only. For each acquisition, we generated 2 sets of relative CBV metrics by using 2 separate, widely published, FDA-approved commercial software packages: IB Neuro and nordicICE. We calculated 4 relative CBV metrics within tumor volumes: mean relative CBV, mode relative CBV, percentage of voxels with relative CBV > 1.75, and percentage of voxels with relative CBV > 1.0 (fractional tumor burden). We determined Pearson (r) and Spearman (ρ) correlations between non-preload dose- and preload dose-corrected metrics. In a subset of patients with recurrent glioblastoma (n = 25), we determined receiver operating characteristic area under the curve for fractional tumor burden accuracy to predict the tissue diagnosis of tumor recurrence versus posttreatment effect. We also determined correlations between rCBV and microvessel area from stereotactic biopsies (n = 29) in 12 patients.

RESULTS

With IB Neuro, relative CBV metrics correlated highly between non-preload dose- and preload dose-corrected conditions for fractional tumor burden (r = 0.96, ρ = 0.94), percentage > 1.75 (r = 0.93, ρ = 0.91), mean (r = 0.87, ρ = 0.86), and mode (r = 0.78, ρ = 0.76). These correlations dropped substantially with nordicICE. With fractional tumor burden, IB Neuro was more accurate than nordicICE in diagnosing tumor versus posttreatment effect (area under the curve = 0.85 versus 0.67) (P < .01). The highest relative CBV-microvessel area correlations required preload dose and IB Neuro (r = 0.64, ρ = 0.58, P = .001).

CONCLUSIONS

Different implementations of perfusion MR imaging software modeling can impact the accuracy of leakage correction, relative CBV calculation, and correlations with histologic benchmarks.

Prognostic Value of Dynamic Susceptibility Contrast-Enhanced and Diffusion-Weighted MR Imaging in Patients with Glioblastomas

BACKGROUND AND PURPOSE

Prediction of survival in patients with glioblastomas is important for individualized treatment planning. This study aimed to assess the prognostic utility of presurgical dynamic susceptibility contrast and diffusion-weighted imaging for overall survival in patients with glioblastoma.

MATERIALS AND METHODS

MR imaging data from pathologically proved glioblastomas between June 2006 to December 2013 in 58 patients (mean age, 62.7 years; age range, 22-89 years) were included in this retrospective study. Patients were divided into long survival (≥15 months) and short survival (<15 months) groups, depending on overall survival time. Patients underwent dynamic susceptibility contrast perfusion and DWI before surgery and were treated with chemotherapy and radiation therapy. The maximum relative cerebral blood volume and minimum mean diffusivity values were measured from the enhancing part of the tumor.

RESULTS

Maximum relative cerebral blood volume values in patients with short survival were significantly higher compared with those who demonstrated long survival (P < .05). No significant difference was observed in the minimum mean diffusivity between short and long survivors. Receiver operator curve analysis demonstrated that a maximum relative cerebral blood volume cutoff value of 5.79 differentiated patients with low and high survival with an area under the curve of 0.93, sensitivity of 0.89, and specificity of 0.90 (P < .001), while a minimum mean diffusivity cutoff value of 8.35 × 10(-4)mm(2)/s had an area under the curve of 0.55, sensitivity of 0.71, and specificity of 0.47 (P > .05) in separating the 2 groups.

CONCLUSIONS

Maximum relative cerebral blood volume may be used as a prognostic marker of overall survival in patients with glioblastomas.

Novel Magnetic Resonance Imaging Techniques in Brain Tumors

Magnetic resonance imaging is a powerful, noninvasive imaging technique with exquisite sensitivity to soft tissue composition. Magnetic resonance imaging is primary tool for brain tumor diagnosis, evaluation of drug response assessment, and clinical monitoring of the patient during the course of their disease. The flexibility of magnetic resonance imaging pulse sequence design allows for a variety of image contrasts to be acquired, including information about magnetic resonance-specific tissue characteristics, molecular dynamics, microstructural organization, vascular composition, and biochemical status. The current review highlights recent advancements and novel approaches in MR characterization of brain tumors.

Diagnosis of brain tumors using dynamic contrast-enhanced perfusion imaging with a short acquisition time

This study sought to determine the diagnostic utility of perfusion parameters derived from dynamic contrast-enhanced (DCE) perfusion MRI with a short acquisition time (approximately 3.5 min) in patients with glioma, brain metastasis, and primary CNS lymphoma (PCNSL).

Twenty-six patients with 29 lesions (4 low-grade glioma, 13 high-grade glioma, 7 metastasis, and 5 PCNSL) underwent DCE-MRI in a 3 T scanner. A ROI was placed on the hotspot of each tumor in maps for volume transfer contrast K^trans, extravascular extracellular volume V_e, and fractional plasma volume V_p. We analyzed differences in parameters between tumors using the Mann–Whitney U test. We calculated sensitivity and specificity using receiver operating characteristics analysis.

Mean K^trans values of LGG, HGG, metastasis and PCNSL were 0.034, 0.31, 0.38, 0.44, respectively. Mean Ve values of each tumors was 0.036, 0.57, 0.47, 0.96, and mean Vp value of each tumors was 0.070, 0.086, 0.26, 0.17, respectively. Compared with other tumor types, low-grade glioma showed lower K^trans (P < 0.01, sensitivity = 88%, specificity = 100%) and lower V_e (P < 0.01, sensitivity = 96%, specificity = 100%). PCNSL showed higher V_e (P < 0.01, sensitivity = 100%, specificity = 88%), but the other perfusion parameters overlapped with those of different histology.

Kinetic parameters derived from DCE-MRI with short acquisition time provide useful information for the differential diagnosis of brain tumors.

Which combination of MR imaging modalities is best for predicting recurrent glioblastoma? Study of diagnostic accuracy and reproducibility

PURPOSE

To compare the added value of dynamic contrast material-enhanced ( CE contrast enhanced ) ( DCE dynamic CE ) magnetic resonance (MR) imaging with that of dynamic susceptibility CE contrast enhanced ( DSC dynamic susceptibility CE ) MR imaging with the combination of CE contrast enhanced T1-weighted imaging and diffusion-weighted ( DW diffusion weighted ) imaging for predicting recurrent glioblastoma.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board, with the requirement for informed patient consent waived. CE contrast enhanced T1-weighted images, DW diffusion weighted images, DSC dynamic susceptibility CE MR images, and DCE dynamic CE MR images in 169 patients with pathologically or clinicoradiologically diagnosed recurrent glioblastoma (n = 87) or radiation necrosis (n = 82) were retrospectively reviewed. Histogram cutoffs of quantitative parametric values were calculated from DW diffusion weighted images, DSC dynamic susceptibility CE MR images, and DCE dynamic CE MR images. Area under the receiver operating characteristic curve ( Az area under the ROC curve ) and interreader agreement were assessed.

RESULTS

For predicting recurrent glioblastoma, adding DCE dynamic CE MR imaging to the combination of CE contrast enhanced T1-weighted imaging and DW diffusion weighted imaging significantly improved Az area under the ROC curve from 0.84 to 0.96 for reader 1 and from 0.81 to 0.97 for reader 2, respectively. Adding DSC dynamic susceptibility CE MR imaging also significantly improved Az area under the ROC curve (0.95 for reader 1 and 0.93 for reader 2). However, there was no significant difference in Az between the combination of CE contrast enhanced T1-weighted imaging, DW diffusion weighted imaging, and DSC dynamic susceptibility CE MR imaging and the combination of CE contrast enhanced T1-weighted imaging, DW diffusion weighted imaging, and DCE dynamic CE MR imaging for both readers. The interreader agreement was highest for the combination of CE contrast enhanced T1-weighted imaging, DW diffusion weighted imaging, and DCE dynamic CE MR imaging (κ = 0.78) and lowest for CE contrast enhanced T1-weighted imaging and DW diffusion weighted imaging (κ = 0.65).

CONCLUSION

Adding perfusion MR imaging to the combination of CE contrast enhanced T1-weighted imaging and DW diffusion weighted imaging significantly improves the prediction of recurrent glioblastoma; however, selection of perfusion MR method does not affect the diagnostic performance.

GRE T2∗-weighted MRI: principles and clinical applications

The sequence of a multiecho gradient recalled echo (GRE) T2*-weighted imaging (T2*WI) is a relatively new magnetic resonance imaging (MRI) technique. In contrast to T2 relaxation, which acquires a spin echo signal, T2* relaxation acquires a gradient echo signal. The sequence of a GRE T2*WI requires high uniformity of the magnetic field. GRE T2*WI can detect the smallest changes in uniformity in the magnetic field and can improve the rate of small lesion detection. In addition, the T2* value can indirectly reflect changes in tissue biochemical components. Moreover, it can be used for the early diagnosis and quantitative diagnosis of some diseases. This paper reviews the principles and clinical applications as well as the advantages and disadvantages of GRE T2*WI.

Imaging of cerebrovascular pathology in animal models of Alzheimer's disease

In Alzheimer's disease (AD), vascular pathology may interact with neurodegeneration and thus aggravate cognitive decline. As the relationship between these two processes is poorly understood, research has been increasingly focused on understanding the link between cerebrovascular alterations and AD. This has at last been spurred by the engineering of transgenic animals, which display pathological features of AD and develop cerebral amyloid angiopathy to various degrees. Transgenic models are versatile for investigating the role of amyloid deposition and vascular dysfunction, and for evaluating novel therapeutic concepts. In addition, research has benefited from the development of novel imaging techniques, which are capable of characterizing vascular pathology in vivo. They provide vascular structural read-outs and have the ability to assess the functional consequences of vascular dysfunction as well as to visualize and monitor the molecular processes underlying these pathological alterations. This article focusses on recent in vivo small animal imaging studies addressing vascular aspects related to AD. With the technical advances of imaging modalities such as magnetic resonance, nuclear and microscopic imaging, molecular, functional and structural information related to vascular pathology can now be visualized in vivo in small rodents. Imaging vascular and parenchymal amyloid-β (Aβ) deposition as well as Aβ transport pathways have been shown to be useful to characterize their dynamics and to elucidate their role in the development of cerebral amyloid angiopathy and AD. Structural and functional imaging read-outs have been employed to describe the deleterious affects of Aβ on vessel morphology, hemodynamics and vascular integrity. More recent imaging studies have also addressed how inflammatory processes partake in the pathogenesis of the disease. Moreover, imaging can be pivotal in the search for novel therapies targeting the vasculature.

Simultaneous assessment of vessel size index, relative blood volume, and vessel permeability in a mouse brain tumor model using a combined spin echo gradient echo echo-planar imaging sequence and viable tumor analysis

PURPOSE

Combining multiple imaging biomarkers in one magnetic resonance imaging (MRI) session would be beneficial to gain more data pertaining to tumor vasculature under therapy. Therefore, simultaneous measurement of perfusion, permeability, and vessel size imaging (VSI) using a gradient echo spin echo (GE-SE) sequence with injection of a clinically approved gadolinium (Gd)-based contrast agent was assessed in an orthotopic glioma model.

MATERIALS AND METHODS

A combined spin echo gradient echo echo-planar imaging sequence was implemented using a single contrast agent Gd diethylenetriaminepentaacetic acid (Gd-DTPA). This sequence was tested in a mouse brain tumor model (U87_MG), also under treatment with an antiangiogenic agent (bevacizumab). T2 maps and the apparent diffusion coefficient (ADC) were used to differentiate regions of cell death and viable tumor tissue.

RESULTS

In viable tumor tissue regional blood volume was 5.7 ± 0.6% in controls and 5.2 ± 0.3% in treated mice. Vessel size was 18.1 ± 2.4 μm in controls and 12.8 ± 2.0 μm in treated mice, which correlated with results from immunohistochemistry. Permeability (K(trans) ) was close to zero in treated viable tumor tissue and 0.062 ± 0.024 min(-1) in controls.

CONCLUSION

Our MRI method allows simultaneous assessment of several physiological and morphological parameters and extraction of MRI biomarkers for vasculature. These could be used for treatment monitoring of novel therapeutic agents such as antiangiogenic drugs.

Classic models for dynamic contrast-enhanced MRI

Dynamic contrast-enhanced MRI (DCE-MRI) is a functional MRI method where T1 -weighted MR images are acquired dynamically after bolus injection of a contrast agent. The data can be interpreted in terms of physiological tissue characteristics by applying the principles of tracer-kinetic modelling. In the brain, DCE-MRI enables measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), blood-brain barrier (BBB) permeability-surface area product (PS) and the volume of the interstitium (ve ). These parameters can be combined to form others such as the volume-transfer constant K(trans) , the extraction fraction E and the contrast-agent mean transit times through the intra- and extravascular spaces. A first generation of tracer-kinetic models for DCE-MRI was developed in the early 1990s and has become a standard in many applications. Subsequent improvements in DCE-MRI data quality have driven the development of a second generation of more complex models. They are increasingly used, but it is not always clear how they relate to the models of the first generation or to the model-free deconvolution methods for tissues with intact BBB. This lack of understanding is leading to increasing confusion on when to use which model and how to interpret the parameters. The purpose of this review is to clarify the relation between models of the first and second generations and between model-based and model-free methods. All quantities are defined using a generic terminology to ensure the widest possible scope and to reveal the link between applications in the brain and in other organs.

Measurements of tumor vascular leakiness using DCE in brain tumors: clinical applications

Various imaging techniques have been employed to evaluate blood-brain-barrier leakiness in brain tumors, as higher tumor vascular leakiness is known to be associated with higher grade and malignant potential of the tumor, and hence can help provide additional diagnostic and prognostic information. These imaging techniques range from routine post-contrast T1 -weighted images that highlight degree of contrast enhancement to absolute measurement of quantitative metrics of vascular leakiness employing complex pharmacokinetic modeling. The purpose of this article is to discuss the clinical applications of available imaging techniques, and in particular dynamic contrast-enhanced T1 -weighted MR imaging (DCE-MRI), to evaluate tumor vascular leakiness.

Quantitative MR perfusion parameters related to survival time in high-grade gliomas

OBJECTIVES

To evaluate the quantitative parameters obtained from dynamic MR T2*-weighted images as predictors of survival taking into consideration the biasing effects of other survival-related covariates.

METHODS

Thirty-nine patients (60 ± 14 years; survival 267 ± 191 days) with high-grade gliomas (8 grade III, 31 grade IV) were retrospectively included in the study. Additional data incorporated Karnofsky performance scale, tumour resection extension after surgery and type of treatment. Dynamic T2*-weighted MRI was acquired before treatment. Tumour curves were extracted for each voxel, and several quantitative parameters were obtained from the whole tumour volume and the 10 % maximum values. Additional image covariates included the presence of necrosis, single or multiple lesions, and tumour and oedema volumes. The relationship between quantitative parameters and survival was assessed using clusterisation techniques and the log-rank method. Cox regression analysis was used to evaluate each parameter's predictive value.

RESULTS

Only the mean of the 10 % maximum values of the transfer coefficient showed an independent relationship with patient survival (log-rank chi-squared test <0.001, Cox regression P = 0.015), with higher values corresponding to lower survival rates.

CONCLUSIONS

High maximum transfer coefficient values show an independent statistical relationship with low survival in high-grade glioma patients. This imaging biomarker can be used as a predictor of prognosis.

[Perfusion magnetic resonance imaging for high grade astrocytomas: Can cerebral blood volume, peak height, and percentage of signal intensity recovery distinguish between progression and pseudoprogression?]

OBJECTIVES

To study the usefulness of common MRI perfusion parameters for identifying pseudoprogression in high grade astrocytomas.

MATERIAL AND METHODS

This retrospective case-control study compared the relative cerebral blood volume (rCBV), the relative percentage of signal intensity recovery (rPSR), and the relative peak height (rPH) recorded in a sample of 17 cases of anaplastic astrocytomas and gliomas considered to be undergoing pseudoprogression by biopsy or follow-up with those recorded in a sample of histologically similar tumors that were treated and considered to be undergoing progression by histologic study or follow-up. We evaluated the accuracy of these parameters and the correlations among them. Statistical significance was set at P<.05.

RESULTS

The rCBV, rPSR, and rPH were significantly different between the two groups (P=.001). The cutoff values rPH=1.37, rCBV=0.9, and rPSR=99% yielded sensitivity (S)=88% and specificity (Sp)=82.2% for rPH, S=100% and Sp=100% for rCBV, and S=100% and Sp=70.6% for rPSR, respectively. We found negative correlations between rPRS and rPH (-0.76) and between rPRS and rCBV (-0.81) and a high positive correlation between rPH and rCBV (0.87).

CONCLUSION

The variables rPH and rCBV were useful for differentiating between pseudoprogression and true progression in our sample. The variable rPRS was also very sensitive, although the overlap in the values between samples make it less useful a priori.

Effects of microvascular permeability changes on contrast-enhanced T1 and pharmacokinetic MR imagings after ischemia

BACKGROUND AND PURPOSE

Brain enhancement on contrast-enhanced T1-weighted imaging (CET1-WI) after ischemic stroke is generally accepted as an indicator of the blood-brain barrier disruption. However, this phenomenon usually starts to become visible at the subacute phase. The purpose of this study was to evaluate the time-course profiles of K(trans), cerebral blood volume (vp), and CET1-WI with early detection of blood-brain barrier changes on K(trans) maps and their role for prediction of subsequent hemorrhagic transformation in acute middle cerebral arterial infarct.

METHODS

Twenty-six patients with acute middle cerebral arterial stroke and early spontaneous reperfusion, whose MR images were obtained at predetermined stroke stages, were included. T2*-based MR perfusion-weighted images were acquired using the first-pass pharmacokinetic model to derive K(trans) and vp. Parenchymal enhancement observed on maps of K(trans), vp, and CET1-WI at each stage was compared. Association among these measurements and hemorrhagic transformation was analyzed.

RESULTS

K(trans) map showed significantly higher parenchymal enhancement in ischemic parenchyma as compared with that of vp map and CET1-WI at early stroke stages (P<0.05). The increased K(trans) at acute stage was not associated with parenchymal enhancement in CET1-WI at the same stage. Parenchymal enhancement in CET1-WI started to occur at the late subacute stage and tended to be luxury reperfusion-dependent. Patients with hemorrhagic transformation showed higher mean K(trans) values as compared with patients without hemorrhagic transformation (P=0.02).

CONCLUSIONS

Postischemic brain enhancement on routine CET1-WI seems to be closely related to the luxury reperfusion at the late subacute stage and is not dependent on microvascular permeability changes at the acute stage.

Longitudinal MRI evaluation of intracranial development and vascular characteristics of breast cancer brain metastases in a mouse model

Longitudinal MRI was applied to monitor intracranial initiation and development of brain metastases and assess tumor vascular volume and permeability in a mouse model of breast cancer brain metastases. Using a 9.4T system, high resolution anatomic MRI and dynamic susceptibility contrast (DSC) perfusion MRI were acquired at different time points after an intracardiac injection of brain-tropic breast cancer MDA-MB231BR-EGFP cells. Three weeks post injection, multifocal brain metastases were first observed with hyperintensity on T₂-weighted images, but isointensity on T₁-weighted post contrast images, indicating that blood-tumor-barrier (BTB) at early stage of brain metastases was impermeable. Follow-up MRI revealed intracranial tumor growth and increased number of metastases that distributed throughout the whole brain. At the last scan on week 5, T₁-weighted post contrast images detected BTB disruption in 160 (34%) of a total of 464 brain metastases. Enhancement in some of the metastases was only seen in partial regions of the tumor, suggesting intratumoral heterogeneity of BTB disruption. DSC MRI measurements of relative cerebral blood volume (rCBV) showed that rCBV of brain metastases was significantly lower (mean  = 0.89±0.03) than that of contralateral normal brain (mean  = 1.00±0.03; p<0.005). Intriguingly, longitudinal measurements revealed that rCBV of individual metastases at early stage was similar to, but became significantly lower than that of contralateral normal brain with tumor growth (p<0.05). The rCBV data were concordant with histological analysis of microvascular density (MVD). Moreover, comprehensive analysis suggested no significant correlation among tumor size, rCBV and BTB permeability. In conclusion, longitudinal MRI provides non-invasive in vivo assessments of spatial and temporal development of brain metastases and their vascular volume and permeability. The characteristic rCBV of brain metastases may have a diagnostic value.