Contrast agents and cerebral hemodynamics

Sedentary behaviour and brain health in middle-aged and older adults: a systematic review

Sedentary behaviour may increase the risk of dementia. Studying physiological effects of sedentary behaviour on cerebral health may provide new insights into the nature of this association. Accordingly, we reviewed if and how acute and habitual sedentary behaviour relate to brain health factors in middle-aged and older adults (≥45 years). Four databases were searched. Twenty-nine studies were included, with mainly cross-sectional designs. Nine studies examined neurotrophic factors and six studied functional brain measures, with the majority of these studies finding no associations with sedentary behaviour. The results from studies on sedentary behaviour and cerebrovascular measures were inconclusive. There was a tentative association between habitual sedentary behaviour and structural white matter health. An explanatory pathway for this effect might relate to the immediate vascular effects of sitting, such as elevation of blood pressure. Nevertheless, due to the foremost cross-sectional nature of the available evidence, reverse causality could also be a possible explanation. More prospective studies are needed to understand the potential of sedentary behaviour as a target for brain health.

Non-parametric deconvolution using Bézier curves for quantification of cerebral perfusion in dynamic susceptibility contrast MRI

Objective

Deconvolution is an ill-posed inverse problem that tends to yield non-physiological residue functions R(t) in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). In this study, the use of Bézier curves is proposed for obtaining physiologically reasonable residue functions in perfusion MRI.

Materials and methods

Cubic Bézier curves were employed, ensuring R(0) = 1, bounded-input, bounded-output stability and a non-negative monotonically decreasing solution, resulting in 5 parameters to be optimized. Bézier deconvolution (BzD), implemented in a Bayesian framework, was tested by simulation under realistic conditions, including effects of arterial delay and dispersion. BzD was also applied to DSC-MRI data from a healthy volunteer.

Results

Bézier deconvolution showed robustness to different underlying residue function shapes. Accurate perfusion estimates were observed, except for boxcar residue functions at low signal-to-noise ratio. BzD involving corrections for delay, dispersion, and delay with dispersion generally returned accurate results, except for some degree of cerebral blood flow (CBF) overestimation at low levels of each effect. Maps of mean transit time and delay were markedly different between BzD and block-circulant singular value decomposition (oSVD) deconvolution.

Discussion

A novel DSC-MRI deconvolution method based on Bézier curves was implemented and evaluated. BzD produced physiologically plausible impulse response, without spurious oscillations, with generally less CBF underestimation than oSVD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10334-021-00995-0.

A Novel Statistical Optimization Algorithm for Estimating Perfusion Curves in Susceptibility Contrast-Enhanced MRI

Dynamic susceptibility contrast-enhanced magnetic resonance imaging is an important tool for evaluating intravascular indicator dynamics, which in turn is valuable for understanding brain physiology and pathophysiology. This procedure usually involves fitting a gamma-variate function to observed concentration-time curves in order to eliminate undesired effects of recirculation and the leakage of contrast agents. Several conventional curve-fitting approaches are routinely applied. The nonlinear optimization methods typically are computationally expensive and require reliable initial values to guarantee success, whereas a logarithmic linear least-squares (LL-LS) method is more stable and efficient, and does not suffer from the initial-value problem, but it can show degraded performance, especially when a few data or outliers are present. In this paper, we demonstrate, that the original perfusion curve-fitting problem can be transformed into a gamma-distribution-fitting problem by treating the concentration-time curves as a random sample from a gamma distribution with time as the random variable. A robust maximum-likelihood estimation (MLE) algorithm can then be readily adopted to solve this problem. The performance of the proposed method is compared with the nonlinear Levenberg-Marquardt (L-M) method and the LL-LS method using both synthetic and real data. The results show that the performance of the proposed approach is far superior to those of the other two methods, while keeping the advantages of the LL-LS method, such as easy implementation, low computational load, and dispensing with the need to guess the initial values. We argue that the proposed method represents an attractive alternative option for assessing intravascular indicator dynamics in clinical applications. Moreover, we also provide valuable suggestions on how to select valid data points and set the initial values in the two traditional approaches (LL-LS and nonlinear L-M methods) to achieve more reliable estimations.

Validation of vessel size imaging (VSI) in high-grade human gliomas using magnetic resonance imaging, image-guided biopsies, and quantitative immunohistochemistry

To evaluate the association between a vessel size index (VSIMRI) derived from dynamic susceptibility contrast (DSC) perfusion imaging using a custom spin-and-gradient echo echoplanar imaging (SAGE-EPI) sequence and quantitative estimates of vessel morphometry based on immunohistochemistry from image-guided biopsy samples. The current study evaluated both relative cerebral blood volume (rCBV) and VSIMRI in eleven patients with high-grade glioma (7 WHO grade III and 4 WHO grade IV). Following 26 MRI-guided glioma biopsies in these 11 patients, we evaluated tissue morphometry, including vessel density and average radius, using an automated procedure based on the endothelial cell marker CD31 to highlight tumor vasculature. Measures of rCBV and VSIMRI were then compared to histological measures. We demonstrate good agreement between VSI measured by MRI and histology; VSIMRI = 13.67 μm and VSIHistology = 12.60 μm, with slight overestimation of VSIMRI in grade III patients compared to histology. rCBV showed a moderate but significant correlation with vessel density (r = 0.42, p = 0.03), and a correlation was also observed between VSIMRI and VSIHistology (r = 0.49, p = 0.01). The current study supports the hypothesis that vessel size measures using MRI accurately reflect vessel caliber within high-grade gliomas, while traditional measures of rCBV are correlated with vessel density and not vessel caliber.

Stepwise occlusion of the carotid arteries of the rat: MRI assessment of the effect of donepezil and hypoperfusion-induced brain atrophy and white matter microstructural changes

Bilateral common carotid artery occlusion (BCCAo) in the rat is a widely used animal model of vascular dementia and a valuable tool for preclinical pharmacological drug testing, although the varying degrees of acute focal ischemic lesions it induces could interfere with its translational value. Recently, a modification to the BCCAo model, the stepwise occlusion of the two carotid arteries, has been introduced. To acquire objective translatable measures, we used longitudinal multimodal magnetic resonance imaging (MRI) to assess the effects of semi-chronic (8 days) donepezil treatment in this model, with half of the Wistar rats receiving the treatment one week after the stepwise BCCAo. With an ultrahigh field MRI, we measured high-resolution anatomy, diffusion tensor imaging, cerebral blood flow measurements and functional MRI in response to whisker stimulation, to evaluate both the structural and functional effects of the donepezil treatment and stepwise BCCAo up to 5 weeks post-occlusion. While no large ischemic lesions were detected, atrophy in the striatum and in the neocortex, along with widespread white matter microstructural changes, were found. Donepezil ameliorated the transient drop in the somatosensory BOLD response in distant cortical areas, as detected 2 weeks after the occlusion but the drug had no effect on the long term structural changes. Our results demonstrate a measurable functional MRI effect of the donepezil treatment and the importance of diffusion MRI and voxel based morphometry (VBM) analysis in the translational evaluation of the rat BCCAo model.

An Update on the Approach to the Imaging of Brain Tumors

PURPOSE OF REVIEW

Neuroimaging plays a critical role in diagnosis of brain tumors and in assessment of response to therapy. However, challenges remain, including accurately and reproducibly assessing response to therapy, defining endpoints for neuro-oncology trials, providing prognostic information, and differentiating progressive disease from post-therapeutic changes particularly in the setting of antiangiogenic and other novel therapies.

RECENT FINDINGS

Recent advances in the imaging of brain tumors include application of advanced MRI imaging techniques to assess tumor response to therapy and analysis of imaging features correlating to molecular markers, grade, and prognosis. This review aims to summarize recent advances in imaging as applied to current diagnostic and therapeutic neuro-oncologic challenges.

Implications of neurovascular uncoupling in functional magnetic resonance imaging (fMRI) of brain tumors

Functional magnetic resonance imaging (fMRI) serves as a critical tool for presurgical mapping of eloquent cortex and changes in neurological function in patients diagnosed with brain tumors. However, the blood-oxygen-level-dependent (BOLD) contrast mechanism underlying fMRI assumes that neurovascular coupling remains intact during brain tumor progression, and that measured changes in cerebral blood flow (CBF) are correlated with neuronal function. Recent preclinical and clinical studies have demonstrated that even low-grade brain tumors can exhibit neurovascular uncoupling (NVU), which can confound interpretation of fMRI data. Therefore, to avoid neurosurgical complications, it is crucial to understand the biophysical basis of NVU and its impact on fMRI. Here we review the physiology of the neurovascular unit, how it is remodeled, and functionally altered by brain cancer cells. We first discuss the latest findings about the components of the neurovascular unit. Next, we synthesize results from preclinical and clinical studies to illustrate how brain tumor induced NVU affects fMRI data interpretation. We examine advances in functional imaging methods that permit the clinical evaluation of brain tumors with NVU. Finally, we discuss how the suppression of anomalous tumor blood vessel formation with antiangiogenic therapies can "normalize" the brain tumor vasculature, and potentially restore neurovascular coupling.

Dynamic Susceptibility Contrast MR Imaging in Glioma: Review of Current Clinical Practice

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

Response Assessment in Neuro-Oncology Criteria and Clinical Endpoints

The Response Assessment in Neuro-Oncology (RANO) Working Group is an international multidisciplinary group whose goal is to improve response criteria and define endpoints for neuro-oncology trials. The RANO criteria for high-grade gliomas attempt to address the issues of pseudoprogression, pseudoresponse, and nonenhancing tumor progression. Incorporation of advanced MR imaging may eventually help improve the ability of these criteria to define enhancing and nonenhancing disease better. The RANO group has also developed criteria for neurologic response and evaluation of patients receiving immunologic therapies. RANO criteria have been developed for brain metastases and are in progress for meningiomas, leptomeningeal disease, spinal tumors, and pediatric tumors.

Additive value of 320-section low-dose dynamic volume CT in relation to 3-T MRI for the preoperative evaluation of brain tumors

PURPOSE

To assess whether 320-section low-dose dynamic volume computed tomography (320-LDVCT) with adaptive iterative dose reduction (AIDR) adds value to 3-T MRI for the preoperative evaluation of brain tumors.

METHODS

The study population was comprised of 16 consecutive patients with brain tumors who, in addition to preoperative 3-T MRI, underwent 320-LDVCT with AIDR. Two radiologists independently evaluated the CT and MRI studies; one measured the relative cerebral blood volume (rCBV) in the tumor and contralateral brain on CT and MR perfusion maps. Interobserver agreement was assessed by κ statistics.

RESULTS

In 3 of 16 patients (19 %), 320-LDVCT added diagnostic value to 3-T MRI studies with respect to the visualization of feeders (κ = 0.77), and in 12 (75 %) it helped the delineation of venous structures (κ = 0.71) and the relationship between the tumor and adjacent vessels (κ = 0.85). The average standardized rCBV value was 12.2 ± 2.40 (range 0.7-36.6) on MR and 8.80 ± 2.77 (range 0.8-38.0) on CT perfusion studies; the correlation between these values was very strong (r = 0.92, p < 0.0001). According to the neurosurgeons, 320-LDVCT added helpful information for surgery in 4 patients (25 %).

CONCLUSION

The 320-LDVCT can add value to 3-T MRI for the tumor feeders and relationship between the tumor and adjacent vessels.

Imaging Tumor Vascularity and Response to Anti-Angiogenic Therapy Using Gaussia Luciferase

We developed a novel approach to assess tumor vascularity using recombinant Gaussia luciferase (rGluc) protein and bioluminescence imaging. Upon intravenous injection of rGluc followed by its substrate coelenterazine, non-invasive visualization of tumor vascularity by bioluminescence imaging was possible. We applied this method for longitudinal monitoring of tumor vascularity in response to the anti-angiogenic drug tivozanib. This simple and sensitive method could be extended to image blood vessels/vasculature in many different fields.

High magnetic field induced otolith fusion in the zebrafish larvae

Magnetoreception in animals illustrates the interaction of biological systems with the geomagnetic field (geoMF). However, there are few studies that identified the impact of high magnetic field (MF) exposure from Magnetic Resonance Imaging (MRI) scanners (>100,000 times of geoMF) on specific biological targets. Here, we investigated the effects of a 14 Tesla MRI scanner on zebrafish larvae. All zebrafish larvae aligned parallel to the B0 field, i.e. the static MF, in the MRI scanner. The two otoliths (ear stones) in the otic vesicles of zebrafish larvae older than 24 hours post fertilization (hpf) fused together after the high MF exposure as short as 2 hours, yielding a single-otolith phenotype with aberrant swimming behavior. The otolith fusion was blocked in zebrafish larvae under anesthesia or embedded in agarose. Hair cells may play an important role on the MF-induced otolith fusion. This work provided direct evidence to show that high MF interacts with the otic vesicle of zebrafish larvae and causes otolith fusion in an "all-or-none" manner. The MF-induced otolith fusion may facilitate the searching for MF sensors using genetically amenable vertebrate animal models, such as zebrafish.

Response Assessment and Magnetic Resonance Imaging Issues for Clinical Trials Involving High-Grade Gliomas

There exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in nonenhancing T2 hyperintensity, and the phenomena of pseudoresponse and pseudoprogression in the setting of antiangiogenic and chemoradiation therapies, respectively. Advanced physiological magnetic resonance imaging (MRI), including diffusion and perfusion (dynamic susceptibility contrast MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multicenter trials for high-grade gliomas. This review chapter highlights the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.

Simultaneous assessment of cerebral blood volume and diffusion heterogeneity using hybrid IVIM and DK MR imaging: initial experience with brain tumors

Objectives

To investigate the feasibility of simultaneously assessing cerebral blood volume and diffusion heterogeneity using hybrid diffusion-kurtosis (DK) and intravoxel-incoherent-motion (IVIM) MR imaging.

Methods

Fifteen healthy volunteers and 30 patients with histologically proven brain tumours (25 WHO grade II–IV gliomas and five metastases) were recruited. On a 3-T system, diffusion-weighted imaging was performed with six b-values ranging from 0 to 1,700 s/mm². Nonlinear least-squares fitting was employed to extract diffusion coefficient (D), diffusion kurtosis coefficient (K, a measure of the degree of non-Gaussian and heterogeneous diffusion) and intravascular volume fraction (f, a measure proportional to cerebral blood volume). Repeated-measures multivariate analysis of variance and receiver operating characteristic analysis were performed to assess the ability of D/K/f in differentiating contrast-enhanced tumour from peritumoral oedema and normal-appearing white matter.

Results

Based on our imaging setting (baseline signal-to-noise ratio = 32–128), coefficient of variation was 14–20 % for K, ~6 % for D and 26–44 % for f. The indexes were able to differentiate contrast-enhanced tumour (Wilks’ λ = 0.026, p < 10^-3), and performance was greatest with K, followed by f and D.

Conclusions

Hybrid DK IVIM imaging is capable of simultaneously measuring cerebral perfusion and diffusion indexes that together may improve brain tumour diagnosis.

Key Points

• Hybrid DK-IVIM imaging allows simultaneous measurement of K, D and f.

• Combined K/D/f better demarcates contrast-enhanced tumour than they do separately.

• f correlates better with contrast-leakage-corrected CBV_DSCthan with uncorrected CBV_DSC.

Nonlinear estimation of BOLD signals with the aid of cerebral blood volume imaging

BACKGROUND

The hemodynamic balloon model describes the change in coupling from underlying neural activity to observed blood oxygen level dependent (BOLD) response. It plays an increasing important role in brain research using magnetic resonance imaging (MRI) techniques. However, changes in the BOLD signal are sensitive to the resting blood volume fraction (i.e., [Formula: see text]) associated with the regional vasculature. In previous studies the value was arbitrarily set to a physiologically plausible value to circumvent the ill-posedness of the inverse problem. These approaches fail to explore actual [Formula: see text] value and could yield inaccurate model estimation.

METHODS

The present study represents the first empiric attempt to derive the actual [Formula: see text] from data obtained using cerebral blood volume imaging, with the aim of augmenting the existing estimation schemes. Bimanual finger tapping experiments were performed to determine how [Formula: see text] influences the model estimation of BOLD signals within a single-region and multiple-regions (i.e., dynamic causal modeling). In order to show the significance of applying the true [Formula: see text], we have presented the different results obtained when using the real [Formula: see text] and assumed [Formula: see text] in terms of single-region model estimation and dynamic causal modeling.

RESULTS

The results show that [Formula: see text] significantly influences the estimation results within a single-region and multiple-regions. Using the actual [Formula: see text] might yield more realistic and physiologically meaningful model estimation results.

CONCLUSION

Incorporating regional venous information in the analysis of the hemodynamic model can provide more reliable and accurate parameter estimations and model predictions, and improve the inference about brain connectivity based on fMRI data.

Preparation of linear poly(glycerol) as a T1 contrast agent for tumor-targeted magnetic resonance imaging

Macromolecular contrast agents (CAs) labeled with targeting molecules are gaining remarkable interest as promising materials overcoming the defects of small-molecule CAs.

Radiogenomics and imaging phenotypes in glioblastoma: novel observations and correlation with molecular characteristics

Radiogenomics is a provocative new area of research based on decades of previous work examining the association between radiological and histological features. Many generalized associations have been established linking anatomical imaging traits with underlying histopathology, including associations between contrast-enhancing tumor and vascular and tumor cell proliferation, hypointensity on pre-contrast T1-weighted images and necrotic tissue, and associations between hyperintensity on T2-weighted images and edema or nonenhancing tumor. Additionally, tumor location, tumor size, composition, and descriptive features tend to show significant associations with molecular and genomic factors, likely related to the cell of origin and growth characteristics. Additionally, physiologic MRI techniques also show interesting correlations with underlying histology and genomic programs, including associations with gene expression signatures and histological subtypes. Future studies extending beyond simple radiology-histology associations are warranted in order to establish radiogenomic analyses as tools for prospectively identifying patient subtypes that may benefit from specific therapies.

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.

Advanced magnetic resonance imaging of the physical processes in human glioblastoma

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research."

Pitfalls in the neuroimaging of glioblastoma in the era of antiangiogenic and immuno/targeted therapy - detecting illusive disease, defining response

Glioblastoma, the most common malignant primary brain tumor in adults is a devastating diagnosis with an average survival of 14–16 months using the current standard of care treatment. The determination of treatment response and clinical decision making is based on the accuracy of radiographic assessment. Notwithstanding, challenges exist in the neuroimaging evaluation of patients undergoing treatment for malignant glioma. Differentiating treatment response from tumor progression is problematic and currently combines long-term follow-up using standard magnetic resonance imaging (MRI), with clinical status and corticosteroid-dependency assessments. In the clinical trial setting, treatment with gene therapy, vaccines, immunotherapy, and targeted biologicals similarly produces MRI changes mimicking disease progression. A neuroimaging method to clearly distinguish between pseudoprogression and tumor progression has unfortunately not been found to date. With the incorporation of antiangiogenic therapies, a further pitfall in imaging interpretation is pseudoresponse. The Macdonald criteria that correlate tumor burden with contrast-enhanced imaging proved insufficient and misleading in the context of rapid blood–brain barrier normalization following antiangiogenic treatment that is not accompanied by expected survival benefit. Even improved criteria, such as the RANO criteria, which incorporate non-enhancing disease, clinical status, and need for corticosteroid use, fall short of definitively distinguishing tumor progression, pseudoresponse, and pseudoprogression. This review focuses on advanced imaging techniques including perfusion MRI, diffusion MRI, MR spectroscopy, and new positron emission tomography imaging tracers. The relevant image analysis algorithms and interpretation methods of these promising techniques are discussed in the context of determining response and progression during treatment of glioblastoma both in the standard of care and in clinical trial context.

Outcome of radiosurgery for recurrent malignant gliomas: assessment of treatment response using relative cerebral blood volume

Gamma knife radiosurgery (GKS) is efficacious for treating recurrent malignant gliomas as a salvage treatment. However, contrast enhancement alone on MR imaging remains difficult to determine the treatment response following GKS. The purpose of this study was to evaluate the radiosurgical effect for recurrent malignant gliomas and to clarify if relative cerebral blood volume (rCBV) derived from dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MR imaging could represent the treatment response. Between March 2006 and December 2008, 38 patients underwent GKS for recurrent malignant gliomas. Before and after GKS, DSC perfusion MR imaging datasets were retrospectively reprocessed and regions of interest were drawn around the contrast-enhancing region targeted with GKS. DSC-perfusion MR scans were assessed at a regular interval of two months. Following GKS for the recurrent lesions, MR images showed response (stable disease or partial response) in 26 of 38 patients (68.4 %) at post-GKS 2 months and 18 of 38 patients (47.3 %) at post-GKS 4 months. Initial mean rCBV value was 2.552 (0.586-6.178) at the pre-GKS MRI. In the response group, mean rCBV value was significantly decreased (P < 0.05) at the follow up of 2 and 4 months. However, in the treatment-failure group, mean rCBV value had no significant change. We suggest that GKS is an alternative treatment choice for the recurrent glioma. DSC-perfusion MR images are helpful to predict the treatment response after GKS.

Vessel caliber--a potential MRI biomarker of tumour response in clinical trials

Our understanding of the importance of blood vessels and angiogenesis in cancer has increased considerably over the past decades, and the assessment of tumour vessel calibre and structure has become increasingly important for in vivo monitoring of therapeutic response. The preferred method for in vivo imaging of most solid cancers is MRI, and the concept of vessel-calibre MRI has evolved since its initial inception in the early 1990s. Almost a quarter of a century later, unlike traditional contrast-enhanced MRI techniques, vessel-calibre MRI remains widely inaccessible to the general clinical community. The narrow availability of the technique is, in part, attributable to limited awareness and a lack of imaging standardization. Thus, the role of vessel-calibre MRI in early phase clinical trials remains to be determined. By contrast, regulatory approvals of antiangiogenic agents that are not directly cytotoxic have created an urgent need for clinical trials incorporating advanced imaging analyses, going beyond traditional assessments of tumour volume. To this end, we review the field of vessel-calibre MRI and summarize the emerging evidence supporting the use of this technique to monitor response to anticancer therapy. We also discuss the potential use of this biomarker assessment in clinical imaging trials and highlight relevant avenues for future research.

Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques

Perfusion is a fundamental biological function that refers to the delivery of oxygen and nutrients to tissue by means of blood flow. Perfusion MRI is sensitive to microvasculature and has been applied in a wide variety of clinical applications, including the classification of tumors, identification of stroke regions, and characterization of other diseases. Perfusion MRI techniques are classified with or without using an exogenous contrast agent. Bolus methods, with injections of a contrast agent, provide better sensitivity with higher spatial resolution, and are therefore more widely used in clinical applications. However, arterial spin-labeling methods provide a unique opportunity to measure cerebral blood flow without requiring an exogenous contrast agent and have better accuracy for quantification. Importantly, MRI-based perfusion measurements are minimally invasive overall, and do not use any radiation and radioisotopes. In this review, we describe the principles and techniques of perfusion MRI. This review summarizes comprehensive updated knowledge on the physical principles and techniques of perfusion MRI.

An efficient computational approach to characterize DSC-MRI signals arising from three-dimensional heterogeneous tissue structures

The systematic investigation of susceptibility-induced contrast in MRI is important to better interpret the influence of microvascular and microcellular morphology on DSC-MRI derived perfusion data. Recently, a novel computational approach called the Finite Perturber Method (FPM), which enables the study of susceptibility-induced contrast in MRI arising from arbitrary microvascular morphologies in 3D has been developed. However, the FPM has lower efficiency in simulating water diffusion especially for complex tissues. In this work, an improved computational approach that combines the FPM with a matrix-based finite difference method (FDM), which we call the Finite Perturber the Finite Difference Method (FPFDM), has been developed in order to efficiently investigate the influence of vascular and extravascular morphological features on susceptibility-induced transverse relaxation. The current work provides a framework for better interpreting how DSC-MRI data depend on various phenomena, including contrast agent leakage in cancerous tissues and water diffusion rates. In addition, we illustrate using simulated and micro-CT extracted tissue structures the improved FPFDM along with its potential applications and limitations.

Arterial input function in perfusion MRI: a comprehensive review

Cerebral perfusion, also referred to as cerebral blood flow (CBF), is one of the most important parameters related to brain physiology and function. The technique of dynamic-susceptibility contrast (DSC) MRI is currently the most commonly used MRI method to measure perfusion. It relies on the intravenous injection of a contrast agent and the rapid measurement of the transient signal changes during the passage of the bolus through the brain. Central to quantification of CBF using this technique is the so-called arterial input function (AIF), which describes the contrast agent input to the tissue of interest. Due to its fundamental role, there has been a lot of progress in recent years regarding how and where to measure the AIF, how it influences DSC-MRI quantification, what artefacts one should avoid, and the design of automatic methods to measure the AIF. The AIF is also directly linked to most of the major sources of artefacts in CBF quantification, including partial volume effect, bolus delay and dispersion, peak truncation effects, contrast agent non-linearity, etc. While there have been a number of good review articles on DSC-MRI over the years, these are often comprehensive but, by necessity, with limited in-depth discussion of the various topics covered. This review article covers in greater depth the issues associated with the AIF and their implications for perfusion quantification using DSC-MRI.

Cerebral blood volume MRI with intravascular superparamagnetic iron oxide nanoparticles

The cerebral blood volume (CBV) is a crucial physiological indicator of tissue viability and vascular reactivity. Thus, noninvasive CBV mapping has been of great interest. For this, ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles, including monocrystalline iron oxide nanoparticles, can be used as long-half-life, intravascular susceptibility agents of CBV MRI measurements. Moreover, CBV-weighted functional MRI (fMRI) with USPIO nanoparticles provides enhanced sensitivity, reduced large vessel contribution and improved spatial specificity relative to conventional blood oxygenation level-dependent fMRI, and measures a single physiological parameter that is easily interpretable. We review the physiochemical and magnetic properties, and pharmacokinetics, of USPIO nanoparticles in brief. We then extensively discuss quantifications of baseline CBV, vessel size index and functional CBV change. We also provide reviews of dose-dependent sensitivity, vascular filter function, specificity, characteristics and impulse response function of CBV fMRI. Examples of CBV fMRI specificity at the laminar and columnar resolution are provided. Finally, we briefly review the application of CBV measurements to functional and pharmacological studies in animals. Overall, the use of USPIO nanoparticles can determine baseline CBV and its changes induced by functional activity and pharmacological interventions.

Robustness of quantitative compressive sensing MRI: the effect of random undersampling patterns on derived parameters for DCE- and DSC-MRI

Compressive sensing (CS) in Cartesian magnetic resonance imaging (MRI) involves random partial Fourier acquisitions. The random nature of these acquisitions can lead to variance in reconstruction errors. In quantitative MRI, variance in the reconstructed images translates to an uncertainty in the derived quantitative maps. We show that for a spatially regularized 2 ×-accelerated human breast CS DCE-MRI acquisition with a 192 (2) matrix size, the coefficients of variation (CoVs) in voxel-level parameters due to the random acquisition are 1.1%, 0.96%, and 1.5% for the tissue parameters K(trans), v(e), and v(p), with an average error in the mean of -2.5%, -2.0%, and -3.7%, respectively. Only 5% of the acquisition schemes had a systematic underestimation larger than than 4.2%, 3.7%, and 6.1%, respectively. For a 2 × -accelerated rat brain CS DSC-MRI study with a 64(2) matrix size, the CoVs due to the random acquisition were 19%, 9.5%, and 15% for the cerebral blood flow and blood volume and mean transit time, respectively, and the average errors in the tumor mean were 9.2%, 0.49%, and -7.0%, respectively. Across 11 000 different CS reconstructions, we saw no outliers in the distribution of parameters, suggesting that, despite the random undersampling schemes, CS accelerated quantitative MRI may have a predictable level of performance.

Combined spin- and gradient-echo perfusion-weighted imaging

In this study, a spin- and gradient-echo echo-planar imaging (SAGE EPI) MRI pulse sequence is presented that allows simultaneous measurements of gradient-echo and spin-echo dynamic susceptibility-contrast perfusion-weighted imaging data. Following signal excitation, five readout trains were acquired using spin- and gradient-echo echo-planar imaging, all of them with echo times of less than 100 ms. Contrast agent concentrations in brain tissue were determined based on absolute R2* and R(2) estimates rather than relative changes in the signals of individual echo trains, producing T(1)-independent dynamic susceptibility-contrast perfusion-weighted imaging data. Moreover, this acquisition technique enabled vessel size imaging through the simultaneous quantification of R2* and R(2), without an increase in acquisition time. In this work, the concepts of SAGE EPI pulse sequence and results in stroke and tumor imaging are presented. Overall, SAGE EPI combined the advantages of higher sensitivity to contrast agent passage of gradient-echo perfusion-weighted imaging with better microvascular selectivity of spin-echo perfusion-weighted imaging.

Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details

Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners.

A technique for rapid single-echo spin-echo T2 mapping

A rapid technique for mapping of T(2) relaxation times is presented. The method is based on the conventional single-echo spin echo approach but uses a much shorter pulse repetition time to accelerate data acquisition. The premise of the new method is the use of a constant difference between the echo time and pulse repetition time, which removes the conventional and restrictive requirement of pulse repetition time >> T(1). Theoretical and simulation investigations were performed to evaluate the criteria for accurate T(2) measurements. Measured T(2)s were shown to be within 1% error as long as the key criterion of pulse repetition time/T(2) > or =3 is met. Strictly, a second condition of echo time/T(1) << 1 is also required. However, violations of this condition were found to have minimal impact in most clinical scenarios. Validation was conducted in phantoms and in vivo T(2) mapping of healthy cartilage and brain. The proposed method offers all the advantages of single-echo spin echo imaging (e.g., immunity to stimulated echo effects, robustness to static field inhomogeneity, flexibility in the number and choice of echo times) in a considerably reduced amount of time and is readily implemented on any clinical scanner.

Longitudinal functional magnetic resonance imaging in animal models

Functional magnetic resonance imaging (fMRI) has had an essential role in furthering our understanding of brain physiology and function. fMRI techniques are nowadays widely applied in neuroscience research, as well as in translational and clinical studies. The use of animal models in fMRI studies has been fundamental in helping elucidate the mechanisms of cerebral blood-flow regulation, and in the exploration of basic neuroscience questions, such as the mechanisms of perception, behavior, and cognition. Because animals are inherently non-compliant, most fMRI performed to date have required the use of anesthesia, which interferes with brain function and compromises interpretability and applicability of results to our understanding of human brain function. An alternative approach that eliminates the need for anesthesia involves training the animal to tolerate physical restraint during the data acquisition. In the present chapter, we review these two different approaches to obtaining fMRI data from animal models, with a specific focus on the acquisition of longitudinal data from the same subjects.

Blood flow quantification of the human retina with MRI

The purpose of this study was to investigate the feasibility of measuring blood flow to the retina using arterial spin labeling MRI, a quantitative, noninvasive tomographic technique. Blood flow imaging was performed in a single axial slice through both eyes of five healthy volunteers with no history of retinal diseases. The imaging was optimized to minimize the errors from motion and nonuniform magnetic fields caused by proximity to the sinuses. Key hemodynamic factors for flow quantification, including arterial transit delay and the apparent decay time of the signal, were estimated by repeated measurements with different arterial spin labeling timing. A clearly elevated signal, consistent with the anatomical location of the retina, was observed in all subjects. The measured blood flow to a 1 cm × 1.47 cm section of the retina, centered on the fovea, was 1.75 ± 0.54 µL/mm(2) /min (total blood flow of 261 ± 87 µL/min). The arterial transit delay from a labeling plane 5 cm below the slice was 1137 ± 288 ms. These results establish the feasibility of measuring blood flow to the retina with MRI, and support the future characterization of the healthy and diseased ocular circulation with this method.

Glioblastoma: a method for predicting response to antiangiogenic chemotherapy by using MR perfusion imaging--pilot study

PURPOSE

To derive a magnetic resonance (MR)-based imaging metric that reflects local perfusion changes resulting from the administration of angiogenic-inhibiting chemotherapy in patients with recurrent glioblastoma multiforme (GBM).

MATERIALS AND METHODS

In this retrospective Institutional Review Board-approved HIPAA-compliant study, 16 patients (12 men, four women; mean age, 51.8 years + or - 15.1 [standard deviation]) with recurrent GBM received bevacizumab every 3 weeks (15 mg per kilogram of body weight) as part of a clinical trial. Baseline MR images were acquired, and follow-up images were acquired every 6 weeks thereafter until tumor progression or death. Imaging included perfusion and T1-weighted contrast material-enhanced MR imaging. Perfusion images were analyzed both with and without correction for contrast material leakage. The volumes of interest were selected as enhancing voxels on T1-weighted contrast-enhanced MR images. Relative cerebral blood volume (rCBV) maps were created from analysis of MR perfusion images. The volumes of interest were used to calculate the following parameters: size, mean rCBV, mean leakage coefficient K(2), and hyperperfusion volume (HPV), which is the fraction of the tumor with an rCBV higher than a predetermined threshold. Percent change in each parameter from baseline to first follow-up was compared with time to progression (TTP) by using a Cox proportional hazards model with calculation of hazard ratios.

RESULTS

The most significant hazard ratio was seen with a DeltaHPV cutoff of rCBV greater than 1.00 (hazard ratio, 1.077; 95% confidence interval: 1.026, 1.130; P = .002). The only significant ratios greater than one were those that resulted from perfusion calculated as mean rCBV and DeltaHPV. The ratios were also higher after correction for leakage.

CONCLUSION

This pilot study derived an imaging metric (HPV) that reflects local perfusion changes in GBMs. This metric was found to show a significantly improved correlation to TTP as compared with more commonly used metrics.

[Functional magnetic resonance imaging in psychiatry and psychotherapy]

technical improvements, functional magnetic resonance imaging (fMRI) has become the most popular and versatile imaging method in psychiatric research. The scope of this manuscript is to briefly introduce the basics of MR physics, the blood oxygenation level-dependent (BOLD) contrast as well as the principles of MR study design and functional data analysis. The presentation of exemplary studies on emotion recognition and empathy in schizophrenia patients will highlight the importance of MR methods in psychiatry. Finally, we will demonstrate insights into new developments that will further boost MR techniques in clinical research and will help to gain more insight into dysfunctional neural networks underlying cognitive and emotional deficits in psychiatric patients. Moreover, some techniques such as neurofeedback seem promising for evaluation of therapy effects on a behavioral and neural level.

MR molecular imaging of tumor vasculature and vascular targets

Tumor angiogenesis and the ability of cancer cells to induce neovasculature continue to be a fascinating area of research. As the delivery network that provides substrates and nutrients, as well as chemotherapeutic agents to cancer cells, but allows cancer cells to disseminate, the tumor vasculature is richly primed with targets and mechanisms that can be exploited for cancer cure or control. The spatial and temporal heterogeneity of tumor vasculature, and the heterogeneity of response to targeting, make noninvasive imaging essential for understanding the mechanisms of tumor angiogenesis, tracking vascular targeting, and detecting the efficacy of antiangiogenic therapies. With its noninvasive characteristics, exquisite spatial resolution and range of applications, magnetic resonance imaging (MRI) techniques have provided a wealth of functional and molecular information on tumor vasculature in applications spanning from "bench to bedside". The integration of molecular biology and chemistry to design novel imaging probes ensures the continued evolution of the molecular capabilities of MRI. In this review, we have focused on developments in the characterization of tumor vasculature with functional and molecular MRI.

Periprocedural MRI perfusion imaging to assess and monitor the hemodynamic impact of intracranial angioplasty and stenting for symptomatic atherosclerotic stenosis

We aimed to assess the clinical value of MRI perfusion imaging in the periprocedural management of intracranial atherosclerosis, analyzing if changes in mean transit time (MTT), cerebral blood volume (CBV) and cerebral blood flow (CBF) correlated with angiographic outcomes. Pre-procedural and post-procedural MRI perfusion was performed on six patients who underwent angioplasty and/or stenting for symptomatic intracranial atherosclerosis. MTT, CBV and CBF were analyzed and graded. In 83% of patients, perfusion imaging correlated with angiographic outcomes. Perfusion parameters improved to normal in two patients. Two showed marked improvement and one showed mild improvement. In one patient, the results of the post-procedural MRI perfusion prompted an angiogram, which confirmed stent occlusion. Semi-quantitative scores of MTT and CBF changed over time (p=0.05, p=0.03) whereas CBV did not change significantly (p>0.05). We conclude that MRI perfusion appears a promising technique for analyzing the impact of intracranial stenosis on cerebral hemodynamics before and after treatment.

3D mapping of somatotopic reorganization with small animal functional MRI

There are few in vivo noninvasive methods to study neuroplasticity in animal brains. Functional MRI (fMRI) has been developed for animal brain mapping, but few fMRI studies have analyzed functional alteration due to plasticity in animal models. One major limitation is that fMRI maps are characterized by statistical parametric mapping making the apparent boundary dependent on the statistical threshold used. Here, we developed a method to characterize the location of center-of-mass in fMRI maps that is shown not to be sensitive to statistical threshold. Utilizing centers-of-mass as anchor points to fit the spatial distribution of the BOLD response enabled quantitative group analysis of altered boundaries of functional somatosensory maps. This approach was used to study cortical reorganization in the rat primary somatosensory cortex (S1) after sensory deprivation to the barrel cortex by follicle ablation (F.A.). FMRI demonstrated an enlarged nose S1 representation in the 3D somatotopic functional maps. This result clearly demonstrates that fMRI enables the spatial mapping of functional changes that can characterize multiple regions of S1 cortex and still be sensitive to changes due to plasticity.

White matter hemodynamic abnormalities precede sub-cortical gray matter changes in multiple sclerosis

BACKGROUND

Hypoperfusion has been reported in lesions, normal-appearing white (NAWM) and gray matter (NAGM) of patients with clinically definite multiple sclerosis (MS) by using perfusion MRI. However, it is still unknown how early such changes in perfusion occur. The aim of our study was to assess the presence of hemodynamic changes in the NAWM and subcortical NAGM of patients with clinically isolated syndrome (CIS) in comparison to healthy controls and to patients with early relapsing-remitting (RR) MS.

METHODS

Absolute cerebral blood flow (CBF), blood volume (CBV) and mean transit time (MTT) were measured in the periventricular and frontal NAWM, thalamus and putamen nuclei of 12 patients with CIS, 12 with early RR-MS and 12 healthy controls using dynamic susceptibility contrast enhanced (DSC) T2*-weighted MRI.

RESULTS

Compared to controls, CBF was significantly decreased in the periventricular NAWM of CIS patients and in the periventricular NAWM and putamen of RR-MS patients. Compared to CIS, RR-MS patients showed a significant CBF decrease in the putamen.

CONCLUSIONS

CBF was decreased in the NAWM of both CIS and RR-MS patients and in the subcortical NAGM of RR-MS patients suggesting a continuum of tissue perfusion decreases beginning in white matter and spreading to gray matter, as the disease progresses.

Method for rapid calculation of quantitative cerebral perfusion

PURPOSE

To evaluate an algorithm based on algebraic estimation of T1 values (three-point estimation) in comparison with computational curve-fitting for the postprocessing of quantitative cerebral perfusion scans.

MATERIALS AND METHODS

Computer simulations were performed to quantify the magnitude of the expected error on T1 and consequently cerebral perfusion using the three-point estimation technique on a Look-Locker (LL) EPI scan. In 50 patients, quantitative cerebral perfusion was calculated using the bookend method with three-point estimation and curve-fitting. The bookend method, a novel approach for calculating quantitative cerebral perfusion based on changes in T1 values after a contrast injection, is currently being validated. The number of computations was used as a measure of computation speed for each method. Student's paired t-test, Bland-Altman, and correlation analyses were performed to evaluate the accuracy of estimation.

RESULTS

There was a 99.65% reduction in the number of computations with three-point estimation. Student's t-test showed no significant difference in cerebral perfusion (P=0.80, 0.49, paired t-test N=50, quantitative cerebral blood flow-white matter [qCBF-WM], qCBF-gray matter [qCBF-GM]) when compared to curve-fitting. The results of the two techniques were strongly correlated in patients (slope=0.99, intercept=1.58 mL/(100 g/minute), r=0.86) with a small systemic bias of -0.97 mL/(100 g/minute) in Bland-Altman analysis.

CONCLUSION

The three-point estimation technique is adequate for rapid calculation of qCBF. The estimation scheme drastically reduces processing time, thus making the method feasible for clinical use.

Magnetic resonance perfusion imaging in neuro-oncology

Recent advances in magnetic resonance imaging (MRI) have seen the development of techniques that allow quantitative imaging of a number of anatomical and physiological descriptors. These techniques have been increasingly applied to cancer imaging where they can provide some insight into tumour microvascular structure and physiology. This review details technical approaches and application of quantitative MRI, focusing particularly on perfusion imaging and its role in neuro-oncology.

Prognostic value of perfusion MR imaging of high-grade astrocytomas: long-term follow-up study

BACKGROUND AND PURPOSE

Although the prognostic value of perfusion MR imaging in various gliomas has been investigated, that in high-grade astrocytomas alone has not been fully evaluated. The purpose of this study was to evaluate retrospectively whether the tumor maximum relative cerebral blood volume (rCBV) on pretreatment perfusion MR imaging is of prognostic value in patients with high-grade astrocytoma.

MATERIALS AND METHODS

Between January 1999 and December 2002, 49 patients (30 men, 19 women; age range, 23-76 years) with supratentorial high-grade astrocytoma underwent MR imaging before the inception of treatment. The patient age, sex, symptom duration, neurologic function, mental status, Karnofsky Performance Scale, extent of surgery, histopathologic diagnosis, tumor component enhancement, and maximum rCBV were assessed to identify factors affecting survival. Kaplan-Meier survival curves, the logrank test, and the multivariate Cox proportional hazards model were used to evaluate prognostic factors.

RESULTS

The maximum rCBV was significantly higher in the 31 patients with glioblastoma multiforme than in the 18 with anaplastic astrocytoma (P < .03). The 2-year overall survival rate was 67% for 27 patients with a low (< or =2.3) and 9% for 22 patients with a high (>2.3) maximum rCBV value (P < .001). Independent important prognostic factors were the histologic diagnosis (hazard ratio = 9.707; 95% confidence interval (CI), 3.163-29.788), maximum rCBV (4.739; 95% CI, 1.950-11.518), extent of surgery (2.692; 95% CI, 1.196-6.061), and sex (2.632; 95% CI, 1.153-6.010).

CONCLUSION

The maximum rCBV at pretreatment perfusion MR imaging is a useful clinical prognostic biomarker for survival in patients with high-grade astrocytoma.

Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging

PURPOSE

To retrospectively determine whether relative cerebral blood volume (CBV) measurements can be used to predict clinical outcome in patients with high-grade gliomas (HGGs) and low-grade gliomas (LGGs) and specifically whether patients who have gliomas with a high initial relative CBV have more rapid progression than those who have gliomas with a low relative CBV.

MATERIALS AND METHODS

Approval for this retrospective HIPAA-compliant study was obtained from the Institutional Board of Research Associates, with waiver of informed consent. One hundred eighty-nine patients (122 male and 67 female patients; median age, 43 years; range, 4-80 years) were examined with dynamic susceptibility-weighted contrast material-enhanced perfusion magnetic resonance (MR) imaging and were followed up clinically with MR imaging (median follow-up, 334 days). Log-rank tests were used to evaluate the association between relative CBV and time to progression by using Kaplan-Meier curves. Binary logistic regression was used to determine whether age, sex, and relative CBV were associated with an adverse event (progressive disease or death).

RESULTS

Values for the mean relative CBV for patients according to each clinical response were as follows: 1.41 +/- 0.13 (standard deviation) for complete response (n = 4), 2.36 +/- 1.78 for stable disease (n = 41), 4.84 +/- 3.32 for progressive disease (n = 130), and 3.82 +/- 1.93 for death (n = 14). Kaplan-Meier estimates of median time to progression in days indicated that patients with a relative CBV of less than 1.75 had a median time to progression of 3585 days, whereas patients with a relative CBV of more than 1.75 had a time to progression of 265 days. Age and relative CBV were also independent predictors for clinical outcome.

CONCLUSION

Dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging can be used to predict median time to progression in patients with gliomas, independent of pathologic findings. Patients who have HGGs and LGGs with a high relative CBV (>1.75) have a significantly more rapid time to progression than do patients who have gliomas with a low relative CBV.