Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities

Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy

Personalised drug delivery enables a tailored treatment plan for each patient compared to conventional drug delivery, where a generic strategy is commonly employed. It can not only achieve precise treatment to improve effectiveness but also reduce the risk of adverse effects to improve patients' quality of life. Drug delivery involves multiple interconnected physiological and physicochemical processes, which span a wide range of time and length scales. How to consider the impact of individual differences on these processes becomes critical. Multiphysics models are an open system that allows well-controlled studies on the individual and combined effects of influencing factors on drug delivery outcomes while accommodating the patient-specific in vivo environment, which is not economically feasible through experimental means. Extensive modelling frameworks have been developed to reveal the underlying mechanisms of drug delivery and optimise effective delivery plans. This review provides an overview of currently available models, their integration with advanced medical imaging modalities, and code packages for personalised drug delivery. The potential to incorporate new technologies (i.e., machine learning) in this field is also addressed for development.

Exploring neurodegenerative disorders using advanced magnetic resonance imaging of the glymphatic system

The glymphatic system, a macroscopic waste clearance system in the brain, is crucial for maintaining neural health. It facilitates the exchange of cerebrospinal and interstitial fluid, aiding the clearance of soluble proteins and metabolites and distributing essential nutrients and signaling molecules. Emerging evidence suggests a link between glymphatic dysfunction and the pathogenesis of neurodegenerative disorders, including Alzheimer's, Parkinson's, and Huntington's disease. These disorders are characterized by the accumulation and propagation of misfolded or mutant proteins, a process in which the glymphatic system is likely involved. Impaired glymphatic clearance could lead to the buildup of these toxic proteins, contributing to neurodegeneration. Understanding the glymphatic system's role in these disorders could provide insights into their pathophysiology and pave the way for new therapeutic strategies. Pharmacological enhancement of glymphatic clearance could reduce the burden of toxic proteins and slow disease progression. Neuroimaging techniques, particularly MRI-based methods, have emerged as promising tools for studying the glymphatic system in vivo. These techniques allow for the visualization of glymphatic flow, providing insights into its function under healthy and pathological conditions. This narrative review highlights current MRI-based methodologies, such as motion-sensitizing pulsed field gradient (PFG) based methods, as well as dynamic gadolinium-based and glucose-enhanced methodologies currently used in the study of neurodegenerative disorders.

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review

This AJR Expert Panel Narrative explores the current status of advanced MRI and PET techniques for the post-therapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from post-treatment effects include DWI and diffusion tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced MRI, and arterial spin labeling; MR spectroscopy including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after HGG treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The article concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

Comparison of computed tomography perfusion and magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging in canine brain

Brain perfusion allows for the evaluation of cerebral hemodynamics, particularly in brain infarcts and tumors. Computed tomography (CT) perfusion (CTP) provides reliable data; however, it has a limited scan field of view and radiation exposure. Magnetic resonance (MR) perfusion provides detailed imaging of small structures and a wide scan field of view. However, no study has compared CTP and MR perfusion and assessed the correlation between the perfusion parameters measured using CTP and MR perfusion. The aim of the present study was to assess the correlation and agreement of the cerebral perfusion derived from dynamic susceptibility contrast (DSC)-MRI and CTP in dogs. In this crossover design study, the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time, and time to peak were measured in the temporal cerebral cortex, caudate nucleus, thalamus, piriform lobe, and hippocampus using CTP and DSC-MRI in six healthy beagle dogs and a dog with a pituitary tumor. On the color map of healthy beagles, blood vessels and the perivascular brain parenchyma appeared as red-green, indicating high perfusion, and the areas distant from the vessels appeared as green-blue, indicating low perfusion levels in CTP and DSC-MRI. CTP parameters were highest in the piriform lobe (CBF = 121.11 ± 12.78 mL/100 g/min and CBV = 8.70 ± 2.04 mL/100 g) and lowest in the thalamus (CBF = 63.75 ± 25.24 mL/100 g/min and CBV = 4.02 ± 0.55 mL/100 g). DSC-MRI parameters were also highest in the piriform lobe (CBF = 102.31 ± 14.73 mL/100 g/min and CBV = 3.17 ± 1.23 mL/100 g) and lowest in the thalamus (CBF = 37.73 ± 25.11 mL/100 g/min and CBV = 0.81 ± 0.44 mL/100 g) although there was no statistical correlation in the quantitative perfusion parameters between CTP and DSC-MRI. In a dog with a pituitary tumor, the color map of the tumor appeared as a red scale, indicating high perfusion and higher CBF and CBV on CTP (149 mL/100 g and 20 mL/100 g/min) and on DSC-MRI (116.3 mL/100 g and 15.32 mL/100 g/min) compared to those measured in healthy dogs. These findings indicate that DSC-MRI and CTP maps exhibit comparability and interchangeability in the assessment of canine brain perfusion.

Mapping cerebral perfusion in mice under various anesthesia levels using highly sensitive BOLD MRI with transient hypoxia

Cerebral perfusion is critical for the early detection of neurological diseases and for effectively monitoring disease progression and treatment responses. Mouse models are widely used in brain research, often under anesthesia, which can affect vascular physiology. However, the impact of anesthesia on regional cerebral blood volume and flow in mice has not been thoroughly investigated. In this study, we have developed a whole-brain perfusion MRI approach by using a 5-second nitrogen gas stimulus under inhalational anesthetics to induce transient BOLD dynamic susceptibility contrast (DSC). This method proved to be highly sensitive, repeatable within each imaging session, and across four weekly sessions. Relative cerebral blood volumes measured by BOLD DSC agree well with those by contrast agents. Quantitative cerebral blood volume and flow metrics were successfully measured in mice under dexmedetomidine and various isoflurane doses using both total vasculature-sensitive gradient-echo and microvasculature-sensitive spin-echo BOLD MRI. Dexmedetomidine reduces cerebral perfusion, while isoflurane increases cerebral perfusion in a dose-dependent manner.

DSC MRI in the human brain using deoxyhemoglobin and gadolinium-Simulations and validations at 3T

INTRODUCTION

Dynamic susceptibility contrast (DSC) MRI allows clinicians to determine perfusion parameters in the brain, such as cerebral blood flow, cerebral blood volume, and mean transit time. To enable quantification, susceptibility changes can be induced using gadolinium (Gd) or deoxyhemoglobin (dOHb), the latter just recently introduced as a contrast agent in DSC. Previous investigations found that experimental parameters and analysis choices, such as the susceptibility amplitude and partial volume, affect perfusion quantification. However, the accuracy and precision of DSC MRI has not been systematically investigated, particularly in the lower susceptibility range.

METHODS

In this study, we compared perfusion values determined using Gd with values determined using a contrast agent with a lower susceptibility-dOHb-under different physiological conditions, such as varying the baseline blood oxygenation and/or magnitude of hypoxic bolus, by utilizing numerical simulations and conducting experiments on healthy subjects at 3T. The simulation framework we developed for DSC incorporates MRI signal contributions from intravascular and extravascular proton spins in arterial, venous, and cerebral tissue voxels. This framework allowed us to model the MRI signal in response to both Gd and dOHb.

RESULTS AND DISCUSSION

We found, both in the experimental results and simulations, that a reduced intravascular volume of the selected arterial voxel, reduced baseline oxygen saturation, greater susceptibility of applied contrast agent (Gd vs. dOHb), and/or larger magnitude of applied hypoxic bolus reduces the overestimation and increases precision of cerebral blood volume and flow. As well, we found that normalizing tissue to venous rather than arterial signal increases the accuracy of perfusion quantification across experimental paradigms. Furthermore, we found that shortening the bolus duration increases the accuracy and reduces the calculated values of mean transit time. In summary, we experimentally uncovered an array of perfusion quantification dependencies, which agreed with the simulation framework predictions, using a wider range of susceptibility values than previously investigated. We argue for caution when comparing absolute and relative perfusion values within and across subjects obtained from a standard DSC MRI analysis, particularly when employing different experimental paradigms and contrast agents.

Effects of bolus injection duration on perfusion estimates in dynamic CT and dynamic susceptibility contrast MRI

Estimates of cerebral blood flow (CBF) and tissue mean transit time (MTT) have been shown to differ between dynamic CT perfusion (CTP) and dynamic susceptibility contrast MRI (DSC-MRI). This study investigates whether these discrepancies regarding CBF and MTT between CTP and DSC-MRI can be attributed to the different injection durations of these techniques. Five subjects were scanned using CTP and DSC-MRI. Region-wise estimates of CBF, MTT, and cerebral blood volume (CBV) were derived based on oscillatory index regularized singular value decomposition. A parametric model that reproduced the shape of measured time curves and characteristics of resulting perfusion parameter estimates was developed and used to simulate data with injection durations typical for CTP and DSC-MRI for a clinically relevant set of perfusion scenarios and noise levels. In simulations, estimates of CBF/MTT showed larger negative/positive bias and increasing variability for CTP when compared to DSC-MRI, especially for high CBF levels. While noise also affected estimates, at clinically relevant levels, the injection duration effect was larger. There are several methodological differences between CTP and DSC-MRI. The results of this study suggest that the injection duration is among those that can explain differences in estimates of CBF and MTT between these bolus tracking techniques.

Whole-brain perfusion mapping in mice by dynamic BOLD MRI with transient hypoxia

Non-invasive mapping of cerebral perfusion is critical for understanding neurovascular and neurodegenerative diseases. However, perfusion MRI methods cannot be easily implemented for whole-brain studies in mice because of their small size. To overcome this issue, a transient hypoxia stimulus was applied to induce a bolus of deoxyhemoglobins as an endogenous paramagnetic contrast in blood oxygenation level-dependent (BOLD) MRI. Based on stimulus-duration-dependent studies, 5 s anoxic stimulus was chosen, which induced a decrease in arterial oxygenation to 59%. Dynamic susceptibility changes were acquired with whole-brain BOLD MRI using both all-vessel-sensitive gradient-echo and microvascular-sensitive spin-echo readouts. Cerebral blood flow (CBF) and cerebral blood volume (CBV) were quantified by modeling BOLD dynamics using a partial-volume-corrected arterial input function. In the mouse under ketamine/xylazine anesthesia, total CBF and CBV were 112.0 ± 15.0 ml/100 g/min and 3.39 ± 0.59 ml/100 g (n = 15 mice), respectively, whereas microvascular CBF and CBV were 85.8 ± 6.9 ml/100 g/min and 2.23 ± 0.27 ml/100 g (n = 7 mice), respectively. Regional total vs. microvascular perfusion metrics were highly correlated but a slight mismatch was observed in the large-vessel areas and cortical depth profiles. Overall, this non-invasive, repeatable, simple hypoxia BOLD-MRI approach is viable for perfusion mapping of rodents.

Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging

Background

Estimation of the oxygen extraction fraction (OEF) by quantitative susceptibility mapping (QSM) magnetic resonance imaging (MRI) is promising but requires systematic evaluation. Extraction of OEF-related information from the tissue residue function in dynamic susceptibility contrast MRI (DSC-MRI) has also been proposed. In this study, whole-brain OEF repeatability was investigated, as well as the relationships between QSM-based OEF and DSC-MRI-based parameters, i.e., mean transit time (MTT) and an oxygen extraction index, referred to as apparent OEF (AOEF).

Method

Test-retest data were obtained from 20 healthy volunteers at 3 T. QSM maps were reconstructed from 3D gradient-echo MRI phase data, using morphology-enabled dipole inversion. DSC-MRI was accomplished using gradient-echo MRI at a temporal resolution of 1.24 s.

Results

The whole-brain QSM-based OEF was (40.4±4.8) % and, in combination with a previously published cerebral blood flow (CBF) estimate, this corresponds to a cerebral metabolic rate of oxygen level of CMRO2 = 3.36 ml O2/min/100 g. The intra-class correlation coefficient [ICC(2,1)] for OEF test-retest data was 0.73. The MTT-versus-OEF and AOEF-versus-OEF relationships showed correlation coefficients of 0.61 (p = 0.004) and 0.52 (p = 0.019), respectively.

Discussion

QSM-based OEF showed a convincing absolute level and good test-retest results in terms of the ICC. Moderate to good correlations between QSM-based OEF and DSC-MRI-based parameters were observed. The present results constitute an indicator of the level of robustness that can be achieved without applying extraordinary resources in terms of MRI equipment, imaging protocol, QSM reconstruction, and OEF analysis.

Assessment of microvascular rarefaction in human brain disorders using physiological magnetic resonance imaging

Cerebral microvascular rarefaction, the reduction in number of functional or structural small blood vessels in the brain, is thought to play an important role in the early stages of microvascular related brain disorders. A better understanding of its underlying pathophysiological mechanisms, and methods to measure microvascular density in the human brain are needed to develop biomarkers for early diagnosis and to identify targets for disease modifying treatments. Therefore, we provide an overview of the assumed main pathophysiological processes underlying cerebral microvascular rarefaction and the evidence for rarefaction in several microvascular related brain disorders. A number of advanced physiological MRI techniques can be used to measure the pathological alterations associated with microvascular rarefaction. Although more research is needed to explore and validate these MRI techniques in microvascular rarefaction in brain disorders, they provide a set of promising future tools to assess various features relevant for rarefaction, such as cerebral blood flow and volume, vessel density and radius and blood-brain barrier leakage.

Evaluation of normal-appearing white matter with perfusion and diffusion MRI in patients with treated glioblastoma

OBJECTIVE

We tried to reveal how the normal appearing white matter (NAWM) was affected in patients with glioblastoma treated with chemo-radiotherapy (CRT) in the period following the treatment, by multiparametric MRI.

MATERIALS AND METHODS

43 multiparametric MRI examinations of 17 patients with glioblastoma treated with CRT were examined. A total of six different series or maps were analyzed in the examinations: Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy (FA) maps, Gradient Echo (GRE) sequence, Dynamic susceptibility contrast (DSC) and Arterial spin labeling (ASL) perfusion sequences. Each sequence in each examination was examined in detail with 14 Region of Interest (ROI) measurements. The obtained values were proportioned to the contralateral NAWM values and the results were recorded as normalized values. Time dependent changes of normalized values were statistically analyzed.

RESULTS

The most prominent changes in follow-up imaging occurred in the perilesional region. In perilesional NAWM, we found a decrease in normalized FA (nFA), rCBV (nrCBV), rCBF (nrCBF), ASL (nASL)values (p < 0.005) in the first 3 months after treatment, followed by a plateau and an increase approaching pretreatment values, although it did not reach. Similar but milder findings were present in other NAWM areas. In perilesional NAWM, nrCBV values were found to be positively high correlated with nrCBF and nASL, and negatively high correlated with nADC values (r: 0.963, 0.736, - 0.973, respectively). We also found high correlations between the mean values of nrCBV, nrCBF, nASL in other NAWM areas (r: 0.891, 0.864, respectively).

DISCUSSION

We showed that both DSC and ASL perfusion values decreased correlatively in the first 3 months and showed a plateau after 1 year in patients with glioblastoma treated with CRT, unlike the literature. Although it was not as evident as perfusion MRI, it was observed that the ADC values also showed a plateau pattern following the increase in the first 3 months. Further studies are needed to explain late pathophysiological changes. Because of the high correlation, our results support ASL perfusion instead of contrast enhanced perfusion methods.

Optimal Scaling Approaches for Perfusion MRI with Distorted Arterial Input Function (AIF) in Patients with Ischemic Stroke

Background: Diagnosis and timely treatment of ischemic stroke depends on the fast and accurate quantification of perfusion parameters. Arterial input function (AIF) describes contrast agent concentration over time as it enters the brain through the brain feeding artery. AIF is the central quantity required to estimate perfusion parameters. Inaccurate and distorted AIF, due to partial volume effects (PVE), would lead to inaccurate quantification of perfusion parameters. Methods: Fifteen patients suffering from stroke underwent perfusion MRI imaging at the Tri-Service General Hospital, Taipei. Various degrees of the PVE were induced on the AIF and subsequently corrected using rescaling methods. Results: Rescaled AIFs match the exact reference AIF curve either at peak height or at tail. Inaccurate estimation of CBF values estimated from non-rescaled AIFs increase with increasing PVE. Rescaling of the AIF using all three approaches resulted in reduced deviation of CBF values from the reference CBF values. In most cases, CBF map generated by rescaled AIF approaches show increased CBF and Tmax values on the slices in the left and right hemispheres. Conclusion: Rescaling AIF by VOF approach seems to be a robust and adaptable approach for correction of the PVE-affected multivoxel AIF. Utilizing an AIF scaling approach leads to more reasonable absolute perfusion parameter values, represented by the increased mean CBF/Tmax values and CBF/Tmax images.

MTT and Blood-Brain Barrier Disruption within Asymptomatic Vascular WM Lesions

BACKGROUND AND PURPOSE

White matter lesions of presumed ischemic origin are associated with progressive cognitive impairment and impaired BBB function. Studying the longitudinal effects of white matter lesion biomarkers that measure changes in perfusion and BBB patency within white matter lesions is required for long-term studies of lesion progression. We studied perfusion and BBB disruption within white matter lesions in asymptomatic subjects.

MATERIALS AND METHODS

Anatomic imaging was followed by consecutive dynamic contrast-enhanced and DSC imaging. White matter lesions in 21 asymptomatic individuals were determined using a Subject-Specific Sparse Dictionary Learning algorithm with manual correction. Perfusion-related parameters including CBF, MTT, the BBB leakage parameter, and volume transfer constant were determined.

RESULTS

MTT was significantly prolonged (7.88 [SD, 1.03] seconds) within white matter lesions compared with normal-appearing white (7.29 [SD, 1.14] seconds) and gray matter (6.67 [SD, 1.35] seconds). The volume transfer constant, measured by dynamic contrast-enhanced imaging, was significantly elevated (0.013 [SD, 0.017] minutes-1) in white matter lesions compared with normal-appearing white matter (0.007 [SD, 0.011] minutes-1). BBB disruption within white matter lesions was detected relative to normal white and gray matter using the DSC-BBB leakage parameter method so that increasing BBB disruption correlated with increasing white matter lesion volume (Spearman correlation coefficient = 0.44; P < .046).

CONCLUSIONS

A dual-contrast-injection MR imaging protocol combined with a 3D automated segmentation analysis pipeline was used to assess BBB disruption in white matter lesions on the basis of quantitative perfusion measures including the volume transfer constant (dynamic contrast-enhanced imaging), the BBB leakage parameter (DSC), and MTT (DSC). This protocol was able to detect early pathologic changes in otherwise healthy individuals.

The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas

OBJECTIVES

The present study aimed to study whether combined inflow-based vascular-space-occupancy (iVASO) MR imaging (MRI) and diffusion-weighted imaging (DWI) improve the diagnostic accuracy in the preoperative grading of gliomas.

METHODS

Fifty-one patients with histopathologically confirmed diffuse gliomas underwent preoperative structural MRI, iVASO, and DWI. We performed 2 qualitative consensus reviews: (1) structural MR images alone and (2) structural MR images with iVASO and DWI. Relative arteriolar cerebral blood volume (rCBVa) and minimum apparent diffusion coefficient (mADC) were compared between low-grade and high-grade gliomas. Receiver operating characteristic (ROC) curve analysis was performed to compare the tumor grading efficiency of rCBVa, mADC, and the combination of the two parameters.

RESULTS

Two observers diagnosed accurate tumor grade in 40 of 51 (78.4%) patients in the first review and in 46 of 51 (90.2%) in the second review. Both rCBVa and mADC showed significant differences between low-grade and high-grade gliomas. ROC analysis gave a threshold value of 1.52 for rCBVa and 0.85 × 10-3 mm2/s for mADC to provide a sensitivity and specificity of 88.0 and 81.2% and 100.0 and 68.7%, respectively. The area under the ROC curve (AUC) was 0.87 and 0.85 for rCBVa and mADC, respectively. The combination of rCBVa and mADC values increased the AUC to 0.92.

CONCLUSION

The combined application of iVASO and DWI may improve the diagnostic accuracy of glioma grading.

Dynamic contrast-enhanced QSM for perfusion imaging: a systematic comparison of ΔR2*- and QSM-based contrast agent concentration time curves in blood and tissue

OBJECTIVE

In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration.

MATERIAL AND METHODS

AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images.

RESULTS

AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s^-1 mM^-1, for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria.

DISCUSSION

Interestingly, arterial concentration time curves based on ΔR2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.

MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas

Objectives

To assess the combined role of tumor vascularity, estimated from perfusion MRI, and MGMT methylation status on overall survival (OS) in patients with glioblastoma.

Methods

A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships between MGMT and perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored by MGMT methylation in terms of OS.

Results

rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV < 10.73), MGMT methylation was a positive predictive factor for OS (HR = 2.73, p = 0.003, AUC = 0.70). In patients with highly vascularized tumors (rCBV > 10.73), however, there was no significant effect of MGMT methylation (HR = 1.72, p = 0.10, AUC = 0.56).

Conclusions

Our results indicate the existence of complementary prognostic information provided by MGMT methylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most from MGMT methylation. Not considering this information may lead to bias in the interpretation of clinical studies.

Key Points

• MRI perfusion provides complementary prognostic information to MGMT methylation.

• MGMT methylation improves prognosis in glioblastoma patients with moderate vascular profile.

• Failure to consider these relations may lead to bias in the interpretation of clinical studies.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07297-4) contains supplementary material, which is available to authorized users.

Correlation and Characteristics of Intravoxel Incoherent Motion and Arterial Spin Labeling Techniques Versus Multiple Parameters Obtained on Dynamic Susceptibility Contrast Perfusion MRI for Brain Tumors

Purpose : To compare data on brain tumors derived from intravoxel incoherent motion (IVIM) and arterial spin labeling (ASL) imaging with multiple parameters obtained on dynamic susceptibility contrast (DSC) perfusion MRI and to clarify the characteristics of IVIM and ASL perfusion data from the viewpoint of cerebral blood flow (CBF) analysis. Methods : ASL-CBF and IVIM techniques as well as DSC examination were performed in 24 patients with brain tumors. The IVIM data were analyzed with the two models. The relative blood flow (rBF), relative blood volume (rBV) corrected relative blood volume (crBV), mean transit time (MTT), and leakage coefficient (K2) were obtained from the DSC MRI data. Results : The ASL-CBF had the same tendency as the perfusion parameters derived from the DSC data, but the permeability from the vessels had less of an effect on the ASL-CBF. The diffusion coefficient of the fast component on IVIM contained more information on permeability than the f value. Conclusion : ASL-CBF is more suitable for the evaluation of perfusion in brain tumors than IVIM parameters. ASL-CBF and IVIM techniques should be carefully selected and the biological significance of each parameter should be understood for the correct comprehension of the pathological status of brain tumors. J. Med. Invest. 66 : 308-313, August, 2019.

MRI perfusion analysis using freeware, standard imaging software

Background

Perfusion-weighted imaging is only scarcely used in veterinary medicine. The exact reasons are unclear. One reason might be the typically high costs of the software packages for image analysis. In addition, a great variability concerning available programs makes it hard to compare results between different studies. Moreover, these algorithms are tuned for their usage in human medicine and often difficult to adapt to veterinary studies.

In order to address these issues, our aim is to deliver a free open source package for calculating quantitative perfusion parameters. We develop an “R package” calculating mean transit time, cerebral blood flow and cerebral blood volume from data obtained with freely imaging software (OsiriX Light®). We hope that the free availability, in combination with the fact that the underlying algorithm is open and adaptable, makes it easier for scientists in veterinary medicine to use, compare and adapt perfusion-weighted imaging analysis.

In order to demonstrate the usage of our software package, we reviewed previously acquired perfusion-weighted images from a group of eight purpose-breed healthy beagle dogs and twelve client-owned dogs with idiopathic epilepsy. In order to obtain the data needed for our algorithm, the following steps were performed: First, regions of interest (ROI) were drawn around different, previously reported, brain regions and the middle cerebral artery. Second, a ROI enhancement curve was generated for each ROI using a freely available PlugIn. Third, the signal intensity curves were exported as a comma-separated-value file. These files constitute the input to our software package, which then calculates the PWI parameters.

Results

We used our software package to re-assess perfusion weighted images from two previous studies. The clinical results were similar, showing a significant increase in the mean transit time and a significant decrease in cerebral blood flow for diseased dogs.

Conclusion

We provide an “R package” for computing the main perfusion parameters from measurements taken with standard imaging software and describe in detail how to obtain these measurements. We hope that our contribution enables users in veterinary medicine to easily obtain perfusion parameters using standard Open Source software in a standard, adaptable and comparable way.

In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound

Over the past decades, the field of in vivo magnetic resonance (MR) has built up an impressive repertoire of data acquisition and analysis technologies for anatomical, functional, physiological, and molecular imaging, the description of which requires many book volumes. As such it is impossible for a few authors to have an authoritative overview of the field and for a brief article to be inclusive. We will therefore focus mainly on data acquisition and attempt to give some insight into the principles underlying current advanced methods in the field and the potential for further innovation. In our view, the foreseeable future is expected to show continued rapid progress, for instance in imaging of microscopic tissue properties in vivo, assessment of functional and anatomical connectivity, higher resolution physiologic and metabolic imaging, and even imaging of receptor binding. In addition, acquisition speed and information content will continue to increase due to the continuous development of approaches for parallel imaging (including simultaneous multi-slice imaging), compressed sensing, and MRI fingerprinting. Finally, artificial intelligence approaches are becoming more realistic and will have a tremendous effect on both acquisition and analysis strategies. Together, these developments will continue to provide opportunity for scientific discovery and, in combination with large data sets from other fields such as genomics, allow the ultimate realization of precision medicine in the clinic.

Increased precision in the intravascular arterial input function with flow compensation

PURPOSE

In this study, we investigate the effects of pulsatile flow and inflow on dynamic susceptibility-contrast MRI intravascular arterial input function measurement in human brain arteries and measure how they are affected by first-order flow compensation.

METHODS

A dual-echo single-shot EPI sequence with alternating flow compensation gradients was used to acquire dynamic susceptibility-contrast images with electrocardiogram monitoring. The dynamic signal variations measured inside the middle cerebral and internal carotid arteries were associated to the pulsatile arterial blood velocities measured with a single-slice quantitative flow sequence throughout the cardiac cycle.

RESULTS

Major inverse correlations between intravascular signal and blood velocity were found for the standard single-shot EPI sequence. Flow compensation reduces these correlated variations that contribute to signal physiological noise. This causes a significant twofold increase of intravascular SNR in the middle cerebral and the internal carotid arteries (2.3 ± 0.9, P = 0.03) and (2.0 ± 0.9, P = 0.04), respectively; and reduced phase SD for the internal carotid arteries (0.72 ± 0.14, P = 0.004). The correction proposed in this work translates into a quantitative arterial input function with reduced noise in the internal carotid arteries.

CONCLUSION

The physiological noise added by pulsatile flow and inflow for intravascular arterial input function measurement in the brain arteries is significantly reduced by flow compensation.

Revealing hemodynamic heterogeneity of gliomas based on signal profile features of dynamic susceptibility contrast-enhanced MRI

Dynamic susceptibility contrast enhanced magnetic resonance imaging (DSC MRI) is widely used for studying blood perfusion in brain tumors. While the time-dependent change of MRI signals related to the concentration of the tracer is used to derive the hemodynamic parameters such as regional blood volume and flow into tumors, the tissue-specific information associated with variations in profiles of signal time course is often overlooked. We report a new approach of combining model free independent component analysis (ICA) identification of specific signal profiles of DSC MRI time course data and extraction of the features from those time course profiles to interrogate time course data followed by calculating the region specific blood volume based on selected individual time courses. Based on the retrospective analysis of DSC MRI data from 38 patients with pathology confirmed low (n = 18) and high (n = 20) grade gliomas, the results reveal the spatially defined intra-tumoral hemodynamic heterogeneity of brain tumors based on features of time course profiles. The hemodynamic heterogeneity as measured by the number of independent components of time course data is associated with the tumor grade. Using 8 selected signal profile features, machine-learning trained algorithm, e.g., logistic regression, was able to differentiate pathology confirmed low intra-tumoral and high grade gliomas with an accuracy of 86.7%. Furthermore, the new method can potentially extract more tumor physiological information from DSC MRI comparing to the traditional model-based analysis and morphological analysis of tumor heterogeneity, thus may improve the characterizations of gliomas for better diagnosis and treatment decisions.

•

Signal profiles of dynamic susceptibility contrast MRI data of brain tumors reflect hemodynamic properties of tumor tissue.

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Features in signal profiles extracted by machine learning methods revealed the hemodynamic heterogeneity of the gliomas.

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The reported approach is a new strategy to characterize the intra-tumor heterogeneity and physiological properties of gliomas.

Vascular aspects of multiple sclerosis: emphasis on perfusion and cardiovascular comorbidities

INTRODUCTION

Multiple sclerosis (MS) is a chronic inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. Over the last two decades, more favorable MS long-term outcomes have contributed toward increase in prevalence of the aged MS population. Emergence of age-associated pathology, such as cardiovascular diseases, may interact with the MS pathophysiology and further contribute to disease progression. Areas covered: This review summarizes the cardiovascular involvement in MS pathology, its disease activity, and progression. The cardiovascular health, the presence of various cardiovascular diseases, and their effect on MS cognitive performance are further explored. In similar fashion, the emerging evidence of a higher incidence of extracranial arterial pathology and its association with brain MS pathology are discussed. Finally, the authors outline the methodologies behind specific perfusion magnetic resonance imaging (MRI) and ultrasound Doppler techniques, which allow measurement of disease-specific and age-specific vascular changes in the aging population and MS patients. Expert opinion: Cardiovascular pathology significantly contributes to worse clinical and MRI-derived disease outcomes in MS. Global and regional cerebral hypoperfusion may be associated with poorer physical and cognitive performance. Prevention, improved detection, and treatment of the cardiovascular-based pathology may improve the overall long-term health of MS patients.

Quantification of intracranial arterial blood flow using noncontrast enhanced 4D dynamic MR angiography

PURPOSE

Noncontrast enhanced dynamic magnetic resonance angiography delineates the pattern of dynamic blood flow of the cerebral vasculature. A model-free solution was proposed to quantify arterial blood flow (aBF) by using the monotonic property of the residual function.

THEORY AND METHODS

Analytical simulations and in-vivo studies were performed to evaluate the performance of the proposed method by comparing the aBF values generated from the proposed and conventional singular value decomposition methods. The aBF values were compared with blood flow velocity measured by 2D phase contrast MRI, and compared between balanced steady-state free precession-based radial and spoiled GRE-based Cartesian acquisitions. Hemodynamic parametric maps were generated in 1 patient with arteriovenous malformation.

RESULTS

The proposed method generates reliable aBF measurement at different signal-to-noise ratio levels, whereas overestimation/underestimation of aBF was observed when a high/low threshold was applied in the singular value decomposition method. Average aBF in large vascular branches was 214.4 and 214.5 mL/mL/min with radial and Cartesian acquisitions, respectively. Significant correlations were found between aBF and blood flow velocity measured by phase contrast MRI (P = 0.0008), and between Cartesian and radial acquisitions (P < 0.0001). Altered hemodynamics were observed at the lesion site of the arteriovenous malformation patient.

CONCLUSION

A robust analytical solution was proposed for quantifying aBF. This model-free method is robust to noise, and its clinical value in the diagnosis of cerebrovascular disorders awaits further evaluation.

Arterial Input Functions and Tissue Response Curves in Dynamic Glucose-Enhanced (DGE) Imaging: Comparison Between glucoCEST and Blood Glucose Sampling in Humans

Dynamic glucose-enhanced (DGE) imaging uses chemical exchange saturation transfer magnetic resonance imaging to retrieve information about the microcirculation using infusion of a natural sugar (D-glucose). However, this new approach is not yet well understood with respect to the dynamic tissue response. DGE time curves for arteries, normal brain tissue, and cerebrospinal fluid (CSF) were analyzed in healthy volunteers and compared with the time dependence of sampled venous plasma blood glucose levels. The arterial response curves (arterial input function [AIF]) compared reasonably well in shape with the time curves of the sampled glucose levels but could also differ substantially. The brain tissue response curves showed mainly negative responses with a peak intensity that was of the order of 10 times smaller than the AIF peak and a shape that was susceptible to both noise and partial volume effects with CSF, attributed to the low contrast-to-noise ratio. The CSF response curves showed a rather large and steady increase of the glucose uptake during the scan, due to the rapid uptake of D-glucose in CSF. Importantly, and contrary to gadolinium studies, the curves differed substantially among volunteers, which was interpreted to be caused by variations in insulin response. In conclusion, while AIFs and tissue response curves can be measured in DGE experiments, partial volume effects, low concentration of D-glucose in tissue, and osmolality effects between tissue and blood may prohibit quantification of normal tissue perfusion parameters. However, separation of tumor responses from normal tissue responses would most likely be feasible.

Simultaneous perfusion and permeability assessments using multiband multi-echo EPI (M2-EPI) in brain tumors

PURPOSE

To study a multiband multi-echo EPI (M2-EPI) sequence for dynamic susceptibility contrast (DSC) perfusion imaging with leakage correction and vascular permeability measurements, and to evaluate the benefits of increased temporal resolution provided by this acquisition strategy on the accuracy of perfusion and permeability estimations.

METHODS

A novel M2-EPI sequence was developed, and a pharmacokinetic model accounting for contrast agent extravasation was used to produce perfusion maps and additional vascular permeability maps. The advantage of M2-EPI for DSC perfusion imaging was demonstrated in vivo in 5 patients with brain tumors, and numerical simulations were performed to evaluate the advantage of improved temporal resolution afforded by the technique.

RESULTS

In contrast to underestimations of cerebral blood volume (CBV) in tumors using the single-echo acquisition strategy, M2-EPI provided more plausible estimates of CBV. A quantitative evaluation showed higher estimated values of CBV and mean transit time in tumor tissues using M2-EPI (CBV: 3.08 ± 0.78 mL/100 g versus 1.56 ± 1.38 mL/100 g [P = .006]; mean transit time: 4.94 ± 1.17 seconds versus 1.83 ± 2.06 seconds [P = 0.033]). Numerical simulations showed that higher temporal resolution provided by M2-EPI was associated with more accurate estimates of cerebral blood flow, CBV, and permeability parameters.

CONCLUSION

The novel M2-EPI acquisition strategy for DSC imaging facilitates leakage-corrected perfusion measurements with additional permeability assessments and more accurate estimates of perfusion/permeability parameters, and may be used as a quantitative tool for the diagnosis, prognosis, and treatment monitoring of brain tumors.

Imaging the physiological evolution of the ischemic penumbra in acute ischemic stroke

We review the hemodynamic, metabolic and cellular parameters affected during early ischemia and their changes as a function of approximate cerebral blood flow ( CBF) thresholds. These parameters underlie the current practical definition of an ischemic penumbra, namely metabolically affected but still viable brain tissue. Such tissue is at risk of infarction under continuing conditions of reduced CBF, but can be rescued through timely intervention. This definition will be useful in clinical diagnosis only if imaging techniques exist that can rapidly, and with sufficient accuracy, visualize the existence of a mismatch between such a metabolically affected area and regions that have suffered cell depolarization. Unfortunately, clinical data show that defining the outer boundary of the penumbra based solely on perfusion-related thresholds may not be sufficiently accurate. Also, thresholds for CBF and cerebral blood volume ( CBV) differ for white and gray matter and evolve with time for both inner and outer penumbral boundaries. As such, practical penumbral imaging would involve parameters in which the physiology is immediately displayed in a manner independent of baseline CBF or CBF threshold, namely pH, oxygen extraction fraction ( OEF), diffusion constant and mean transit time ( MTT). Suitable imaging technologies will need to meet this requirement in a 10-20 min exam.

Perfusion Magnetic Resonance Imaging Changes in Normal Appearing Brain Tissue after Radiotherapy in Glioblastoma Patients may Confound Longitudinal Evaluation of Treatment Response

Background

The aim of this study was assess acute and early delayed radiation-induced changes in normal-appearing brain tissue perfusion as measured with perfusion magnetic resonance imaging (MRI) and the dependence of these changes on the fractionated radiotherapy (FRT) dose level.

Patients and methods

Seventeen patients with glioma WHO grade III-IV treated with FRT were included in this prospective study, seven were excluded because of inconsistent FRT protocol or missing examinations. Dynamic susceptibility contrast MRI and contrast-enhanced 3D-T1-weighted (3D-T1w) images were acquired prior to and in average (standard deviation): 3.1 (3.3), 34.4 (9.5) and 103.3 (12.9) days after FRT. Pre-FRT 3D-T1w images were segmented into white- and grey matter. Cerebral blood volume (CBV) and cerebral blood flow (CBF) maps were calculated and co-registered patient-wise to pre-FRT 3D-T1w images. Seven radiation dose regions were created for each tissue type: 0-5 Gy, 5-10 Gy, 10-20 Gy, 20-30 Gy, 30-40 Gy, 40-50 Gy and 50-60 Gy. Mean CBV and CBF were calculated in each dose region and normalised (nCBV and nCBF) to the mean CBV and CBF in 0-5 Gy white- and grey matter reference regions, respectively.

Results

Regional and global nCBV and nCBF in white- and grey matter decreased after FRT, followed by a tendency to recover. The response of nCBV and nCBF was dose-dependent in white matter but not in grey matter.

Conclusions

Our data suggest that radiation-induced perfusion changes occur in normal-appearing brain tissue after FRT. This can cause an overestimation of relative tumour perfusion using dynamic susceptibility contrast MRI, and can thus confound tumour treatment evaluation.

Brain Tumor Characterization Using Multibiometric Evaluation of MRI

The aim was to evaluate volume, diffusion, and perfusion metrics for better presurgical differentiation between high-grade gliomas (HGG), low-grade gliomas (LGG), and metastases (MET). For this retrospective study, 43 patients with histologically verified intracranial HGG (n = 18), LGG (n = 10), and MET (n = 15) were chosen. Preoperative magnetic resonance data included pre- and post-gadolinium contrast-enhanced T1-weighted fluid-attenuated inversion recover, cerebral blood flow (CBF), cerebral blood volume (CBV), fractional anisotropy, and apparent diffusion coefficient maps used for quantification of magnetic resonance biometrics by manual delineation of regions of interest. A binary logistic regression model was applied for multiparametric analysis and receiver operating characteristic (ROC) analysis. Statistically significant differences were found for normalized-ADC-tumor (nADC-T), normalized-CBF-tumor (nCBF-T), normalized-CBV-tumor (nCBV-T), and normalized-CBF-edema (nCBF-E) between LGG and HGG, and when these metrics were combined, HGG could be distinguished from LGG with a sensitivity and specificity of 100%. The only metric to distinguish HGG from MET was the normalized-ADC-E with a sensitivity of 68.8% and a specificity of 80%. LGG can be distinguished from MET by combining edema volume (Vol-E), Vol-E/tumor volume (Vol-T), nADC-T, nCBF-T, nCBV-T, and nADC-E with a sensitivity of 93.3% and a specificity of 100%. The present study confirms the usability of a multibiometric approach including volume, perfusion, and diffusion metrics in differentially diagnosing brain tumors in preoperative patients and adds to the growing body of evidence in the clinical field in need of validation and standardization.

Measurement of the perfusion fraction in brain tumors with intravoxel incoherent motion MR imaging: validation with histopathological vascular density in meningiomas

OBJECTIVE

To evaluate the quantification performance of the perfusion fraction (f) measured with intravoxel incoherent motion (IVIM) MR imaging in a comparison with the histological vascular density in meningiomas.

METHODS

29 consecutive patients with meningioma (59.0 ± 16.8 years old, 8 males and 21 females) who underwent a subsequent surgical resection were examined with both IVIM imaging and a histopathological analysis. IVIM imaging was conducted using a single-shot SE-EPI sequence with 13 b-factors (0, 10, 20, 30, 50, 80, 100, 200, 300, 400, 600, 800, 1000 s mm^-2) at 3T. The perfusion fraction (f) was calculated by fitting the IVIM bi-exponential model. The 90-percentile f-value in the tumor region-of-interest (ROI) was defined as the maximum f-value (f-max). Histopathological vascular density (%Vessel) was measured on CD31-immunostainted histopathological specimens. The correlation and agreement between the f-values and %Vessel was assessed.

RESULTS

The f-max (15.5 ± 5.5%) showed excellent agreement [intraclass correlation coefficient (ICC) = 0.754] and a significant correlation (r = 0.69, p < 0.0001) with the %Vessel (12.9 ± 9.4%) of the tumors. The Bland-Altman plot analysis showed excellent agreement between the f-max and %Vessel (bias, -2.6%; 95% limits of agreement, from -16.0 to 10.8%). The f-max was not significantly different among the histological subtypes of meningioma.

CONCLUSION

An excellent agreement and a significant correlation were observed between the f-values and %Vessel. The f-value can be used as a noninvasive quantitative imaging measure to directly assess the vascular volume fraction in brain tumors. Advances in knowledge: The f-value measured by IVIM imaging showed a significant correlation and an excellent agreement with the histological vascular density in the meningiomas. The f-value can be used as a noninvasive and quantitative imaging measure to directly assess the volume fraction of capillaries in brain tumors.

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.

Dynamic Susceptibility Contrast MRI at 7 T: Tail-Scaling Analysis and Inferences About Field Strength Dependence

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) following bolus injection of gadolinium contrast agent (CA) is widely used for the estimation of brain perfusion parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) for both clinical and research purposes. Although it is predicted that DSC-MRI will have superior performance at high magnetic field strengths, to the best of our knowledge, there are no reports of 7 T DSC-MRI in the literature. It is plausible that the transfer of DSC-MRI to 7 T may be accompanied by increased R₂* relaxivity in tissue and a larger difference in ΔR₂*-versus-concentration relationships between tissue and large vessels. If not accounted for, this will subsequently result in apparent CBV and CBF estimates that are higher than those reported previously at lower field strengths. The aims of this study were therefore to assess the feasibility of 7 T DSC-MRI and to investigate the apparent field-strength dependence of CBV and CBF estimates. In total, 8 healthy volunteers were examined using DSC-MRI at 7 T. A reduced CA dose of 0.05 mmol/kg was administered to decrease susceptibility artifacts. CBV, CBF, and MTT maps were calculated using standard DSC-MRI tracer-kinetic theory. Subject-specific arterial partial volume correction factors were obtained using a tail-scaling approach. Compared with literature values obtained using the tail-scaling approach at 1.5 T and 3 T, the CBV and CBF values of the present study were found to be further overestimated. This observation is potentially related to an inferred field-strength dependence of transverse relaxivities, although issues related to the CA dose must also be considered.

Assessment of MRI contrast agent concentration by quantitative susceptibility mapping (QSM): application to estimation of cerebral blood volume during steady state

Objective

One major issue in dynamic susceptibility contrast MRI (DSC-MRI) is to accurately determine contrast agent (CA) concentration, since T2* relaxivity in vivo is generally unknown and varies between blood and tissue. In this study, quantitative susceptibility mapping (QSM) was used for quantification of CA concentration.

Materials and methods

A DSC-MRI protocol, including phase data acquisition, was applied to 20 healthy volunteers in a test–retest study. By selecting a CSF reference region of interest (ROI), the values of all QSM images were shifted to show no CA-induced change in CSF. CA concentration and cerebral blood volume (CBV) were estimated using shifted QSM data. CSF reference ROI optimization was evaluated by investigation of CBV repeatability. The CBV age dependence was analysed and tissue T2* relaxivity was estimated.

Results

The best repeatability of CBV, using an optimal CSF reference ROI, showed test-versus-retest correlations of r = 0.81 and r = 0.91 for white and grey matter, respectively. A slight CBV decrease with age was observed, and the estimated in vivo T2* relaxivity was 85 mM⁻¹s⁻¹.

Conclusion

Provided that a carefully selected CSF reference ROI is used to shift QSM image values, susceptibility information can be used to estimate concentration of contrast agent and to calculate CBV.

Electronic supplementary material

The online version of this article (doi:10.1007/s10334-017-0637-9) contains supplementary material, which is available to authorized users.

Alterations of cerebral perfusion in asymptomatic internal carotid artery steno-occlusive disease

Patients with asymptomatic occlusion in the internal carotid arteries (ICA) have been shown to have a better preserved hemodynamic status of the brain as compared to patients with symptoms. This study was aimed to explore the cerebral perfusion alterations in asymptomatic patients using multi-parametric arterial spin-labeling (ASL) magnetic resonance (MR) imaging. Forty-two patients diagnosed with asymptomatic ICA stenosis/occlusion were prospectively included and divided into high-grade (ultrasonographic stenosis ≥70%, N = 20) and low-grade groups (N = 22). On a 3-Tesla clinical MR scanner, pseudo-continuous ASL was performed to measure cerebral blood flow CBF, arterial transit time ATT, and flow territory. Fisher's exact test indicates that the high-grade group has higher frequency in asymmetric ATT (p < 10-3) and asymmetric flow territory (p < 10-3) as compared to the low-grade group. The between-group difference in CBF asymmetry is marginal (p = 0.062). Logistic regression further reveals that hemispherical asymmetry in ATT and flow territory is associated with the existence of high-grade ICA stenosis (odds ratio = 12 and 21, respectively), whereas hemispherical asymmetry in CBF is not. Our data suggest that ATT and flow territory may be better predictors of asymptomatic high-grade ICA stenosis diagnosed by carotid ultrasonography than CBF.

Measurement of arteriolar blood volume in brain tumors using MRI without exogenous contrast agent administration at 7T

PURPOSE

Arteriolar cerebral-blood-volume (CBVa) is an important perfusion parameter that can be measured using inflow-based vascular-space-occupancy (iVASO) MRI without exogenous contrast agent administration. The purpose of this study is to assess the potential diagnostic value of CBVa in brain tumor patients by comparing it with total-CBV (including arterial, capillary and venous vessels) measured by dynamic-susceptibility-contrast (DSC) MRI.

MATERIALS AND METHODS

Twelve brain tumor patients were scanned using iVASO (on 7T as part of a research project) and DSC (on 3T as part of routine clinical protocols) MRI. Region-of-interest analysis was performed to compare the resulting perfusion measures between tumoral and contralateral regions, and to evaluate their associations with tumor grades.

RESULTS

CBVa measured by iVASO MRI significantly correlated with WHO grade (ρ = 0.37, P = 0.04). Total-CBV measured by DSC MRI showed a trend of correlation with WHO grade (ρ = 0.28, P = 0.5). The signal-to-noise ratio was comparable (P > 0.1) between the two methods, while the contrast-to-noise ratio between tumoral and contralateral regions was higher in iVASO-CBVa than DSC-CBV in WHO II/III patients (P < 0.05) but comparable in WHO IV patients (P > 0.1). A trend of positive correlation between DSC-CBV and iVASO-CBVa was observed (R2 = 0.28, P = 0.07).

CONCLUSION

In this initial patient study, CBVa demonstrated a stronger correlation with WHO grade than total-CBV. Further investigation with a larger cohort is warranted to validate whether CBVa can be a better classifier than total-CBV for the stratification of brain tumors, and whether iVASO MRI can be a useful alternative method for the assessment of tumor perfusion, especially when exogenous contrast agent administration is difficult in certain patient populations. J. Magn. Reson. Imaging 2016;44:1244-1255.

Insights into the pathogenesis and treatment of painful diabetic neuropathy

Painful diabetic distal symmetrical polyneuropathy (painful DPN) is a puzzle with two important missing pieces: Firstly we still do not understand why only some patients with neuropathy experience painful symptoms; Secondly we still do not have a complete understanding of how nociception generated in the peripheral nervous system is processed by the central nervous system (CNS). Available treatments offer only symptom relief and there is currently no effective treatment based on arresting or reversing the progression of disease. Therefore the management of painful DPN remains less than optimal because the complex pathophysiology of nociception and pain perception in health and disease is incompletely understood. Studies of the peripheral nervous system are investigating the molecular processes involved in signal transduction that have the potential to be interrupted or modified to ease pain. Magnetic resonance imaging techniques are helping to elucidate central pain processing pathways and describe the translation of nociception to pain. Combining the knowledge from these two streams of enquiry we will soon be able to predict accurately who will develop painful DPN, how we can halt or reverse the condition, or who will respond to symptomatic treatments. Future developments in the treatment of painful DPN will be underpinned by decoding the peripheral and central mechanisms of pain. Research is focusing on these areas of enquiry in the hope that answers will lead to effective treatments to alleviate pain and reverse pathology for those suffering from painful DPN.

Intravoxel Incoherent Motion Metrics as Potential Biomarkers for Survival in Glioblastoma

Objective

Intravoxel incoherent motion (IVIM) is an MRI technique with potential applications in measuring brain tumor perfusion, but its clinical impact remains to be determined. We assessed the usefulness of IVIM-metrics in predicting survival in newly diagnosed glioblastoma.

Methods

Fifteen patients with glioblastoma underwent MRI including spin-echo echo-planar DWI using 13 b-values ranging from 0 to 1000 s/mm². Parametric maps for diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were generated for contrast-enhancing regions (CER) and non-enhancing regions (NCER). Regions of interest were manually drawn in regions of maximum f and on the corresponding dynamic susceptibility contrast images. Prognostic factors were evaluated by Kaplan-Meier survival and Cox proportional hazards analyses.

Results

We found that f_CER and D*_CER correlated with rCBF_CER. The best cutoffs for 6-month survival were f_CER>9.86% and D*_CER>21.712 x10⁻³mm²/s (100% sensitivity, 71.4% specificity, 100% and 80% positive predictive values, and 80% and 100% negative predictive values; AUC:0.893 and 0.857, respectively). Treatment yielded the highest hazard ratio (5.484; 95% CI: 1.162–25.88; AUC: 0.723; P = 0.031); f_CER combined with treatment predicted survival with 100% accuracy.

Conclusions

The IVIM-metrics f_CER and D*_CER are promising biomarkers of 6-month survival in newly diagnosed glioblastoma.

Intravoxel incoherent motion diffusion-weighted imaging analysis of diffusion and microperfusion in grading gliomas and comparison with arterial spin labeling for evaluation of tumor perfusion

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;44:620-632.

Dynamic Glucose-Enhanced (DGE) MRI: Translation to Human Scanning and First Results in Glioma Patients

Recent animal studies have shown that d-glucose is a potential biodegradable magnetic resonance imaging (MRI) contrast agent for imaging glucose uptake in tumors. We show herein the first translation of that use of d-glucose to human studies. Chemical exchange saturation transfer (CEST) MRI at a single frequency offset optimized for detecting hydroxyl protons in d-glucose was used to image dynamic signal changes in the human brain at 7 T during and after d-glucose infusion. Dynamic glucose enhanced (DGE) image data from 4 normal volunteers and 3 glioma patients showed a strong signal enhancement in blood vessels, while a spatially varying enhancement was found in tumors. Areas of enhancement differed spatially between DGE and conventional gadolinium-enhanced imaging, suggesting complementary image information content for these 2 types of agents. In addition, different tumor areas enhanced with d-glucose at different times after infusion, suggesting a sensitivity to perfusion-related properties such as substrate delivery and blood-brain barrier (BBB) permeability. These preliminary results suggest that DGE MRI is feasible for studying glucose uptake in humans, providing a time-dependent set of data that contains information regarding arterial input function, tissue perfusion, glucose transport across the BBB and cell membrane, and glucose metabolism.

Advancing Cardiovascular, Neurovascular, and Renal Magnetic Resonance Imaging in Small Rodents Using Cryogenic Radiofrequency Coil Technology

Research in pathologies of the brain, heart and kidney have gained immensely from the plethora of studies that have helped shape new methods in magnetic resonance (MR) for characterizing preclinical disease models. Methodical probing into preclinical animal models by MR is invaluable since it allows a careful interpretation and extrapolation of data derived from these models to human disease. In this review we will focus on the applications of cryogenic radiofrequency (RF) coils in small animal MR as a means of boosting image quality (e.g., by supporting MR microscopy) and making data acquisition more efficient (e.g., by reducing measuring time); both being important constituents for thorough investigational studies on animal models of disease. This review attempts to make the (bio)medical imaging, molecular medicine, and pharmaceutical communities aware of this productive ferment and its outstanding significance for anatomical and functional MR in small rodents. The goal is to inspire a more intense interdisciplinary collaboration across the fields to further advance and progress non-invasive MR methods that ultimately support thorough (patho)physiological characterization of animal disease models. In this review, current and potential future applications for the RF coil technology in cardiovascular, neurovascular, and renal disease will be discussed.

Analysis of perfusion MRI in stroke: To deconvolve, or not to deconvolve

PURPOSE

There is currently controversy regarding the benefits of deconvolution-based parameters in stroke imaging, with studies suggesting a similar infarct prediction using summary parameters. We investigate here the performance of deconvolution-based parameters and summary parameters for dynamic-susceptibility contrast (DSC) MRI analysis, with particular emphasis on precision.

METHODS

Numerical simulations were used to assess the contribution of noise and arterial input function (AIF) variability to measurement precision. A realistic AIF range was defined based on in vivo data from an acute stroke clinical study. The simulated tissue curves were analyzed using two popular singular value decomposition (SVD) based algorithms, as well as using summary parameters.

RESULTS

SVD-based deconvolution methods were found to considerably reduce the AIF-dependency, but a residual AIF bias remained on the calculated parameters. Summary parameters, in turn, show a lower sensitivity to noise. The residual AIF-dependency for deconvolution methods and the large AIF-sensitivity of summary parameters was greatly reduced when normalizing them relative to normal tissue.

CONCLUSION

Consistent with recent studies suggesting high performance of summary parameters in infarct prediction, our results suggest that DSC-MRI analysis using properly normalized summary parameters may have advantages in terms of lower noise and AIF-sensitivity as compared to commonly used deconvolution methods. Magn Reson Med 76:1282-1290, 2016. © 2015 Wiley Periodicals, Inc.

Quantification of normal cerebral oxygen extraction and oxygen metabolism by phase-based MRI susceptometry: evaluation of repeatability using two different imaging protocols

INTRODUCTION

Global oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO₂ ) were quantified in a test-retest study. Cerebral blood flow (CBF) data, required for CMRO₂ estimation, were obtained using dynamic susceptibility contrast MRI (DSC-MRI). OEF and CMRO₂ were quantified using two separate data sets, that is, conventional high-resolution (HR) gradient echo (GRE) phase maps as well as echo planar imaging (EPI) phase maps taken from the baseline (precontrast) part of the DSC-MRI time series. The EPI phase data were included to elucidate whether an extra HR-GRE scan is needed to obtain information about OEF and CMRO₂ , or if this information can be extracted from the DSC-MRI experiment only.

METHODS

Twenty healthy volunteers were scanned using 3 T MRI on two occasions. Oxygen saturation levels were obtained from phase data measured in the great cerebral vein of Galen, based on HR-GRE as well as EPI phase maps. In combination with DSC-MRI CBF, this allowed for calculation of OEF and CMRO₂ .

RESULTS

High-resolution-gradient echo- and EPI-based phase images resulted in similar OEF spread and repeatability, with coefficients of variation/intraclass correlation coefficients of 0·26/0·95 and 0·23/0·81, respectively. Absolute OEF values (HR-GRE: 0·40 ± 0·11, EPI: 0·35 ± 0·08) were consistent with literature data. CMRO₂ showed similar repeatability, somewhat increased spread and reasonable absolute values (HR-GRE: 3·23 ± 1·26 ml O₂ /100 g min^-1 , EPI: 2·79 ± 0·89 ml O₂ /100 g min^-1 ).

DISCUSSION

In general, the results obtained by HR-GRE and EPI showed comparable characteristics. The EPI methodology could potentially be improved using a slightly modified DSC-MRI protocol (e.g. with regard to spatial resolution and slice gap).

Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients

OBJECTIVES

This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods.

METHODS

Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods.

RESULTS

CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not.

CONCLUSIONS

DSC-MRI is highly repeatable in high-grade glioma patients.