Improving susceptibility mapping using a threshold-based K-space/image domain iterative reconstruction approach

Quantifying iron content in magnetic resonance imaging

Measuring iron content has practical clinical indications in the study of diseases such as Parkinson's disease, Huntington's disease, ferritinopathies and multiple sclerosis as well as in the quantification of iron content in microbleeds and oxygen saturation in veins. In this work, we review the basic concepts behind imaging iron using T2, T2*, T2', phase and quantitative susceptibility mapping in the human brain, liver and heart, followed by the applications of in vivo iron quantification in neurodegenerative diseases, iron tagged cells and ultra-small superparamagnetic iron oxide (USPIO) nanoparticles.

Quantitative Susceptibility Mapping (QSM) Algorithms: Mathematical Rationale and Computational Implementations

Quantitative susceptibility mapping (QSM) solves the magnetic field-to-magnetization (tissue susceptibility) inverse problem under conditions of noisy and incomplete field data acquired using magnetic resonance imaging. Therefore, sophisticated algorithms are necessary to treat the ill-posed nature of the problem and are reviewed here. The forward problem is typically presented as an integral form, where the field is the convolution of the dipole kernel and tissue susceptibility distribution. This integral form can be equivalently written as a partial differential equation (PDE). Algorithmic challenges are to reduce streaking and shadow artifacts characterized by the fundamental solution of the PDE. Bayesian maximum a posteriori estimation can be employed to solve the inverse problem, where morphological and relevant biomedical knowledge (specific to the imaging situation) are used as priors. As the cost functions in Bayesian QSM framework are typically convex, solutions can be robustly computed using a gradient-based optimization algorithm. Moreover, one can not only accelerate Bayesian QSM, but also increase its effectiveness at reducing shadows using prior knowledge based preconditioners. Improving the efficiency of QSM is under active development, and a rigorous analysis of preconditioning needs to be carried out for further investigation.Quantitative susceptibility mapping (QSM) solves the magnetic field-to-magnetization (tissue susceptibility) inverse problem under conditions of noisy and incomplete field data acquired using magnetic resonance imaging. Therefore, sophisticated algorithms are necessary to treat the ill-posed nature of the problem and are reviewed here. The forward problem is typically presented as an integral form, where the field is the convolution of the dipole kernel and tissue susceptibility distribution. This integral form can be equivalently written as a partial differential equation (PDE). Algorithmic challenges are to reduce streaking and shadow artifacts characterized by the fundamental solution of the PDE. Bayesian maximum a posteriori estimation can be employed to solve the inverse problem, where morphological and relevant biomedical knowledge (specific to the imaging situation) are used as priors. As the cost functions in Bayesian QSM framework are typically convex, solutions can be robustly computed using a gradient-based optimization algorithm. Moreover, one can not only accelerate Bayesian QSM, but also increase its effectiveness at reducing shadows using prior knowledge based preconditioners. Improving the efficiency of QSM is under active development, and a rigorous analysis of preconditioning needs to be carried out for further investigation.

Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge

PURPOSE

The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully.

METHODS

Gradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions.

RESULTS

Twenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance.

CONCLUSION

Because QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria. Magn Reson Med 79:1661-1673, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Quantification of liver iron concentration using the apparent susceptibility of hepatic vessels

Background

The quantification of liver iron concentration (LIC) is important for the monitoring of the body iron level in patients with iron overload. Conventionally, LIC is quantified through R2 or R2* mapping using MRI. In this paper, we demonstrate an alternative approach for LIC quantification through measuring the apparent susceptibility of hepatic vessels using quantitative susceptibility mapping (QSM).

Methods

QSM was performed in the liver region with the iterative susceptibility weighted imaging and mapping (iSWIM) algorithm, using the geometry of the vessels extracted from magnitude images as constraints. The susceptibilities of liver tissue were estimated from the apparent susceptibility of the hepatic veins and then converted to LIC. The accuracy of the proposed method was first validated using simulations, and then confirmed using in vivo data collected on 8 healthy controls and 11 patients at 3T. The effects of data acquisition parameters were studied using simulations, and the LICs estimated using QSM were compared with those estimated using R2* mapping.

Results

Simulation results showed that the use of a 3D data acquisition protocol with higher image resolution led to improved accuracy in LIC quantification using QSM. Both simulations and in vivo data results demonstrated that the LICs estimated using the proposed QSM method agreed well with those estimated using R2* mapping. With the shortest echo time being 2.5ms in the multi-echo gradient echo sequence, simulations results showed that LIC up to 12.45 mg iron/g dry tissue can be quantified using the proposed QSM method. For the in vivo data, the highest LIC measured was 11.32 mg iron/g dry tissue.

Conclusions

The proposed method offers a reliable and flexible way to quantify LIC and has the potential to extend the range of LIC that can be accurately measured using R2* and QSM.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

Purpose

To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping.

Methods

A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ₀ +δχ, with δχ for BOLD magnetic perturbations and χ₀ for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis.

Results

Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance.

Conclusions

The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization.

STrategically Acquired Gradient Echo (STAGE) imaging, part II: Correcting for RF inhomogeneities in estimating T1 and proton density

PURPOSE

To develop a method for mapping the B₁ transmit (B_1t) and B₁ receive (B_1r) fields from two gradient echo datasets each with a different flip angle and from these two images obtain accurate T₁ and proton density (PD) maps of the brain.

METHODS

A strategically acquired gradient echo (STAGE) data set is collected using two flip angles each with multiple echoes. The B_1t field extraction was based on forcing cortical gray matter and white matter to have specific T₁ values and fitting the resulting B_1t field to a quadratic function. The B_1r field extraction was based on synthesizing isointense images despite there being two or three tissue types present in the brain. This method was tested on 10 healthy volunteers and 20 stroke patients from data acquired at 3.0Tesla.

RESULTS

With the knowledge of the B_1t and B_1r fields, the uniformity of tissue T₁ and PD maps was considerably improved. T₁ values were measured for both the midbrain and basal ganglia and found to be in good agreement with the literature.

DISCUSSION AND CONCLUSIONS

STAGE provides a practical way to assess the B_1t and the B_1r fields which can then be used to correct for spatial variations in the images.

Quantitative Susceptibility Mapping Reveals an Association between Brain Iron Load and Depression Severity

Previous studies have detected abnormal serum ferritin levels in patients with depression; however, the results have been inconsistent. This study used quantitative susceptibility mapping (QSM) for the first time to examine brain iron concentration in depressed patients and evaluated whether it is related to severity. We included three groups of age- and gender-matched participants: 30 patients with mild-moderate depression (MD), 14 patients with major depression disorder (MDD) and 20 control subjects. All participants underwent MR scans with a 3D gradient-echo sequence reconstructing for QSM and performed the 17-item Hamilton Depression Rating Scale (HDRS) test. In MDD, the susceptibility value in the bilateral putamen was significantly increased compared with MD or control subjects. In addition, a significant difference was also observed in the left thalamus in MDD patients compared with controls. However, the susceptibility values did not differ between MD patients and controls. The susceptibility values positively correlated with the severity of depression as indicated by the HDRS scores. Our results provide evidence that brain iron deposition may be associated with depression and may even be a biomarker for investigating the pathophysiological mechanism of depression.

Susceptibility weighted imaging and quantitative susceptibility mapping of the cerebral vasculature using ferumoxytol

PURPOSE

To demonstrate the potential of imaging cerebral arteries and veins with ferumoxytol using susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM).

MATERIALS AND METHODS

The relationships between ferumoxytol concentration and the apparent susceptibility at 1.5T, 3T, and 7T were determined using phantom data; the ability of visualizing subvoxel vessels was evaluated using simulations; and the feasibility of using ferumoxytol to enhance the visibility of small vessels was confirmed in three healthy volunteers at 7T(with doses 1 mg/kg to 4 mg/kg). The visualization of the lenticulostriate arteries and the medullary veins was assessed by two raters and the contrast-to-noise ratios (CNRs) of these vessels were measured.

RESULTS

The relationship between ferumoxytol concentration and susceptibility was linear with a slope 13.3 ± 0.2 ppm·mg^-1 ·mL at 7T. Simulations showed that SWI data with an increased dose of ferumoxytol, higher echo time (TE), and higher imaging resolution improved the detection of smaller vessels. With 4 mg/kg ferumoxytol, voxel aspect ratio = 1:8, TE = 10 ms, the diameter of the smallest detectable artery was approximately 50μm. The rating score for arteries was improved from 1.5 ± 0.5 (precontrast) to 3.0 ± 0.0 (post-4 mg/kg) in the in vivo data and the apparent susceptibilities of the arteries (0.65 ± 0.02 ppm at 4 mg/kg) agreed well with the expected susceptibility (0.71 ± 0.05 ppm).

CONCLUSION

The CNR for cerebral vessels with ferumoxytol can be enhanced using SWI, and the apparent susceptibilities of the arteries can be reliably quantified using QSM. This approach improves the imaging of the entire vascular system outside the capillaries and may be valuable for a variety of neurodegenerative diseases which involve the microvasculature.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:621-633.

Decreased susceptibility of major veins in mild traumatic brain injury is correlated with post-concussive symptoms: A quantitative susceptibility mapping study

Cerebral venous oxygen saturation (SvO₂) is an important biomarker of brain function. In this study, we aimed to explore the relative changes of regional cerebral SvO₂ among axonal injury (AI) patients, non-AI patients and healthy controls (HCs) using quantitative susceptibility mapping (QSM). 48 patients and 32 HCs were enrolled. The patients were divided into two groups depending on the imaging based evidence of AI. QSM was used to measure the susceptibility of major cerebral veins. Nonparametric testing was performed for susceptibility differences among the non-AI patient group, AI patient group and healthy control group. Correlation was performed between the susceptibility of major cerebral veins, elapsed time post trauma (ETPT) and post-concussive symptom scores. The ROC analysis was performed for the diagnostic efficiency of susceptibility to discriminate mTBI patients from HCs.

The susceptibility of the straight sinus in non-AI and AI patients was significantly lower than that in HCs (P < 0.001, P = 0.004, respectively, Bonferroni corrected), which may indicate an increased regional cerebral SvO₂ in patients. The susceptibility of the straight sinus in non-AI patients positively correlated with ETPT (r = 0.573, P = 0.003, FDR corrected) while that in AI patients negatively correlated with the Rivermead Post Concussion Symptoms Questionnaire scores (r = − 0.582, P = 0.018, FDR corrected). The sensitivity, specificity and AUC values of susceptibility for the discrimination between mTBI patients and HCs were 88%, 69% and 0.84. In conclusion, the susceptibility of the straight sinus can be used as a biomarker to monitor the progress of mild TBI and to differentiate mTBI patients from healthy controls.

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Mild traumatic brain injury caused decreased venous susceptibility.

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The venous susceptibility can discriminate mTBI patients from healthy controls.

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Decreased susceptibility may indicate increased venous oxygen saturation (SvO₂).

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Increased SvO₂ of patients without axonal injury decreased with time post-injury.

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Increased SvO₂ of axonal injury patients indicated severe post-concussive symptoms.

Structural and functional quantitative susceptibility mapping from standard fMRI studies

Standard functional MRI (fMRI), which includes resting-state or paradigm-driven designs, is widely used in studies of brain function, aging, and disease. These fMRI studies typically use two-dimensional gradient echo-planar imaging, which inherently contains phase data that enables quantitative susceptibility mapping (QSM). This work focuses on the dual value of QSM within fMRI studies, by providing both a localized analysis of functional changes in activated tissue, and iron-sensitive structural maps in deep grey matter (DGM). Using a visual paradigm fMRI study on healthy volunteers at clinical (1.5 T) and high field strength (4.7 T), we perform functional analysis of magnitude and QSM time series, and at the same time harness structural QSM of iron-rich DGM, including globus pallidus, putamen, caudate head, substantia nigra, and red nucleus. The effects of fMRI spatial resolution and time series variation on structural DGM QSM are investigated. Our results indicate that structural DGM QSM is feasible within existing fMRI studies, provided that the voxel dimensions are equal to or less than 3 mm, with higher resolutions preferred. The mean DGM QSM values were about 40 to 220 ppb, while the interquartile ranges of the DGM QSM time series varied from about 3 to 9 ppb, depending on structure and resolution. In contrast, the peak voxel functional QSM (fQSM) changes in activated visual cortex ranged from about -10 to -30 ppb, and functional clusters were consistently smaller on QSM than magnitude fMRI. Mean-level DGM QSM of the time series was successfully extracted in all cases, while fQSM results were more prone to residual background fields and showed less functional change compared with standard magnitude fMRI. Under the conditions prescribed, standard fMRI studies may be used for robust mean-level DGM QSM, enabling study of DGM iron accumulation, in addition to functional analysis. Copyright © 2016 John Wiley & Sons, Ltd.

Determination of detection sensitivity for cerebral microbleeds using susceptibility-weighted imaging

Cerebral microbleeds (CMBs) are small brain hemorrhages caused by the break down or structural abnormalities of small vessels of the brain. Owing to the paramagnetic properties of blood degradation products, CMBs can be detected in vivo using susceptibility-weighted imaging (SWI). SWI can be used not only to detect iron changes and CMBs, but also to differentiate them from calcifications, both of which may be important MR-based biomarkers for neurodegenerative diseases. Moreover, SWI can be used to quantify the iron in CMBs. SWI and gradient echo (GE) imaging are the two most common methods for the detection of iron deposition and CMBs. This study provides a comprehensive analysis of the number of voxels detected in the presence of a CMB on GE magnitude, phase and SWI composite images as a function of resolution, signal-to-noise ratio (SNR), TE, field strength and susceptibility using in silico experiments. Susceptibility maps were used to quantify the bias in the effective susceptibility value and to determine the optimal TE for CMB quantification. We observed a non-linear trend with susceptibility for CMB detection from the magnitude images, but a linear trend with susceptibility for CMB detection from the phase and SWI composite images. The optimal TE values for CMB quantification were found to be 3 ms at 7 T, 7 ms at 3 T and 14 ms at 1.5 T for a CMB of one voxel in diameter with an SNR of 20: 1. The simulations of signal loss and detectability were used to generate theoretical formulae for predictions. Copyright © 2016 John Wiley & Sons, Ltd.

Susceptibility-weighted imaging: current status and future directions

Susceptibility-weighted imaging (SWI) is a method that uses the intrinsic nature of local magnetic fields to enhance image contrast in order to improve the visibility of various susceptibility sources and to facilitate diagnostic interpretation. It is also the precursor to the concept of the use of phase for quantitative susceptibility mapping (QSM). Nowadays, SWI has become a widely used clinical tool to image deoxyhemoglobin in veins, iron deposition in the brain, hemorrhages, microbleeds and calcification. In this article, we review the basics of SWI, including data acquisition, data reconstruction and post-processing. In particular, the source of cusp artifacts in phase images is investigated in detail and an improved multi-channel phase data combination algorithm is provided. In addition, we show a few clinical applications of SWI for the imaging of stroke, traumatic brain injury, carotid vessel wall, siderotic nodules in cirrhotic liver, prostate cancer, prostatic calcification, spinal cord injury and intervertebral disc degeneration. As the clinical applications of SWI continue to expand both in and outside the brain, the improvement of SWI in conjunction with QSM is an important future direction of this technology. Copyright © 2016 John Wiley & Sons, Ltd.

The clinical utility of QSM: disease diagnosis, medical management, and surgical planning

Quantitative susceptibility mapping (QSM) is an MR technique that depicts and quantifies magnetic susceptibility sources. Mapping iron, the dominant susceptibility source in the brain, has many important clinical applications. Herein, we review QSM applications in the diagnosis, medical management, and surgical treatment of disease. To assist in early disease diagnosis, QSM can identify elevated iron levels in the motor cortex of amyotrophic lateral sclerosis patients, in the substantia nigra of Parkinson's disease (PD) patients, in the globus pallidus, putamen, and caudate of Huntington's disease patients, and in the basal ganglia of Wilson's disease patients. Additionally, QSM can distinguish between hemorrhage and calcification, which could prove useful in tumor subclassification, and can measure microbleeds in traumatic brain injury patients. In guiding medical management, QSM can be used to monitor iron chelation therapy in PD patients, to monitor smoldering inflammation of multiple sclerosis (MS) lesions after the blood-brain barrier (BBB) seals, to monitor active inflammation of MS lesions before the BBB seals without using gadolinium, and to monitor hematoma volume in intracerebral hemorrhage. QSM can also guide neurosurgical treatment. Neurosurgeons require accurate depiction of the subthalamic nucleus, a tiny deep gray matter nucleus, prior to inserting deep brain stimulation electrodes into the brains of PD patients. QSM is arguably the best imaging tool for depiction of the subthalamic nucleus. Finally, we discuss future directions, including bone QSM, cardiac QSM, and using QSM to map cerebral metabolic rate of oxygen. Copyright © 2016 John Wiley & Sons, Ltd.

Computational methods for image reconstruction

Reconstructing images from indirect measurements is a central problem in many applications, including the subject of this special issue, quantitative susceptibility mapping (QSM). The process of image reconstruction typically requires solving an inverse problem that is ill-posed and large-scale and thus challenging to solve. Although the research field of inverse problems is thriving and very active with diverse applications, in this part of the special issue we will focus on recent advances in inverse problems that are specific to deconvolution problems, the class of problems to which QSM belongs. We will describe analytic tools that can be used to investigate underlying ill-posedness and apply them to the QSM reconstruction problem and the related extensively studied image deblurring problem. We will discuss state-of-the-art computational tools and methods for image reconstruction, including regularization approaches and regularization parameter selection methods. We finish by outlining some of the current trends and future challenges. Copyright © 2016 John Wiley & Sons, Ltd.

Overview of quantitative susceptibility mapping

Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.

Quantitative Susceptibility Mapping Using the Multiple Dipole-inversion Combination with k-space Segmentation Method

Quantitative susceptibility mapping (QSM) is a new magnetic resonance imaging (MRI) technique for noninvasively estimating the magnetic susceptibility of biological tissue. Several methods for QSM have been proposed. One of these methods can estimate susceptibility with high accuracy in tissues whose contrast is consistent between magnitude images and susceptibility maps, such as deep gray-matter nuclei. However, the susceptibility of small veins is underestimated and not well depicted by using the above approach, because the contrast of small veins is inconsistent between a magnitude image and a susceptibility map. In order to improve the estimation accuracy and visibility of small veins without streaking artifacts, a method with multiple dipole-inversion combination with k-space segmentation (MUDICK) has been proposed. In the proposed method, k-space was divided into three domains (low-frequency, magic-angle, and high-frequency). The k-space data in low-frequency and magic-angle domains were obtained by L1-norm regularization using structural information of a pre-estimated susceptibility map. The k-space data in high-frequency domain were obtained from the pre-estimated susceptibility map in order to preserve small-vein contrasts. Using numerical simulation and human brain study at 3 Tesla, streaking artifacts and small-vein susceptibility were compared between MUDICK and conventional methods (MEDI and TKD). The numerical simulation and human brain study showed that MUDICK and MEDI had no severe streaking artifacts and MUDICK showed higher contrast and accuracy of susceptibility in small-veins compared to MEDI. These results suggest that MUDICK can improve the accuracy and visibility of susceptibility in small-veins without severe streaking artifacts.

Quantifying the changes in oxygen extraction fraction and cerebral activity caused by caffeine and acetazolamide

A quantitative estimate of cerebral blood oxygen saturation is of critical importance in the investigation of cerebrovascular disease. We aimed to measure the change in venous oxygen saturation (Y_v) before and after the intake of the vaso-dynamic agents caffeine and acetazolamide with high spatial resolution using susceptibility mapping. Caffeine and acetazolamide were administered on separate days to five healthy volunteers to measure the change in oxygen extraction fraction. The internal streaking artifacts in the susceptibility maps were reduced by giving an initial susceptibility value uniformly to the structure-of-interest, based on a priori information. Using this technique, Y_v for normal physiological conditions, post-caffeine and post-acetazolamide was measured inside the internal cerebral veins as Y_Normal = 69.1 ± 3.3%, Y_Caffeine = 60.5 ± 2.8%, and Y_Acet = 79.1 ± 4.0%. This suggests that susceptibility mapping can serve as a sensitive biomarker for measuring reductions in cerebro-vascular reserve through abnormal vascular response. The percentage change in oxygen extraction fraction for caffeine and acetazolamide were found to be +27.0 ± 3.8% and -32.6 ± 2.1%, respectively. Similarly, the relative changes in cerebral blood flow in the presence of caffeine and acetazolamide were found to be -30.3% and + 31.5%, suggesting that the cerebral metabolic rate of oxygen remains stable between normal and challenged brain states for healthy subjects.

Improved Quantification of Cerebral Vein Oxygenation Using Partial Volume Correction

Purpose: Quantitative susceptibility mapping (QSM) enables cerebral venous characterization and physiological measurements, such as oxygen extraction fraction (OEF). The exquisite sensitivity of QSM to deoxygenated blood makes it possible to image small veins; however partial volume effects must be addressed for accurate quantification. We present a new method, Iterative Cylindrical Fitting (ICF), to estimate voxel-based partial volume effects for susceptibility maps and use it to improve OEF quantification of small veins with diameters between 1.5 and 4 voxels.

Materials and Methods: Simulated QSM maps were generated to assess the performance of the ICF method over a range of vein geometries with varying echo times and noise levels. The ICF method was also applied to in vivo human brain data to assess the feasibility and behavior of OEF measurements compared to the maximum intensity voxel (MIV) method.

Results: Improved quantification of OEF measurements was achieved for vessels with contrast to noise greater than 3.0 and vein radii greater than 0.75 voxels. The ICF method produced improved quantitative accuracy of OEF measurement compared to the MIV approach (mean OEF error 7.7 vs. 12.4%). The ICF method provided estimates of vein radius (mean error <27%) and partial volume maps (root mean-squared error <13%). In vivo results demonstrated consistent estimates of OEF along vein segments.

Conclusion: OEF quantification in small veins (1.5–4 voxels in diameter) had lower error when using partial volume estimates from the ICF method.

Imaging of nigrosome 1 in substantia nigra at 3T using multiecho susceptibility map-weighted imaging (SMWI)

PURPOSE

To enhance the visibility of nigrosome 1 in substantia nigra, which has recently been suggested as an imaging biomarker for Parkinson's disease (PD) at 3T magnetic resonance imaging (MRI).

MATERIALS AND METHODS

The substantia nigra structure was visualized at 3T MRI using multiecho susceptibility map-weighted imaging (SMWI) in 15 healthy volunteers and 6 patients with Parkinson's disease (PD). The visibility of nigrosome 1 was further enhanced by acquiring data in an oblique-coronal imaging plane at a high spatial resolution (0.5 × 0.5 × 1.0 mm³ ). To compare the visibility, the contrast-to-noise ratios (CNR) of the nigrosome 1 structure relative to the neighboring substantia nigra structure were evaluated in the SMWI and other conventional susceptibility contrast images (magnitude, frequency, quantitative susceptibility map [QSM] and susceptibility-weighted image).

RESULTS

In healthy volunteers, the CNRs of the nigrosome 1 structure were 1.04 ± 0.38, 0.84 ± 0.32, 1.04 ± 0.40, 0.86 ± 0.41, and 1.45 ± 0.48 for magnitude, frequency, quantitative susceptibility map, susceptibility-weighted image, and SMWI, respectively. Compared to conventional susceptibility contrast images, the SMWI method significantly improved the CNR of nigrosome 1 (P = 0.014 for magnitude, P = 0.030 for QSM, and P < 0.001 for frequency and SWI, respectively). The magnetic susceptibility difference between nigrosome 1 and neighboring substantia nigra structures was 0.037 ± 0.016 ppm (measured in QSM, P < 0.001) in healthy volunteers. In the PD patients, the visibility of the nigrosome 1 structures was reduced.

CONCLUSION

The SMWI method enhances the visibility of nigrosome 1 structures at 3T MRI when compared to conventional susceptibility contrast images.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:528-536.

Quantitative Susceptibility Mapping Using Structural Feature Based Collaborative Reconstruction (SFCR) in the Human Brain

The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l 1 norm constraint and a voxel fidelity based l 2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k -space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result.

Evaluating the Role of Reduced Oxygen Saturation and Vascular Damage in Traumatic Brain Injury Using Magnetic Resonance Perfusion-Weighted Imaging and Susceptibility-Weighted Imaging and Mapping

The cerebral vasculature, along with neurons and axons, is vulnerable to biomechanical insult during traumatic brain injury (TBI). Trauma-induced vascular injury is still an underinvestigated area in TBI research. Cerebral blood flow and metabolism could be important future treatment targets in neural critical care. Magnetic resonance imaging offers a number of key methods to probe vascular injury and its relationship with traumatic hemorrhage, perfusion deficits, venous blood oxygen saturation changes, and resultant tissue damage. They make it possible to image the hemodynamics of the brain, monitor regional damage, and potentially show changes induced in the brain's function not only acutely but also longitudinally following treatment. These methods have recently been used to show that even mild TBI (mTBI) subjects can have vascular abnormalities, and thus they provide a major step forward in better diagnosing mTBI patients.

Metallic implant geometry and susceptibility estimation using multispectral B0 field maps

PURPOSE

To estimate the susceptibility and the geometry of metallic implants from multispectral imaging (MSI) information, to separate the metal implant region from the surrounding signal loss region.

THEORY AND METHODS

The susceptibility map of signal-void regions is estimated from MSI B₀ field maps using total variation (TV) regularized inversion. Voxels with susceptibility estimates above a predetermined threshold are identified as metal. The accuracy of the estimated susceptibility and implant geometry was evaluated in simulations, phantom, and in vivo experiments.

RESULTS

The proposed method provided more accurate susceptibility estimation compared with a previous method without TV regularization, in both simulations and phantom experiments. In the phantom experiment where the actual implant was 40% of the signal-void region, the mean estimated susceptibility was close to the susceptibility in literature, and the precision and recall of the estimated geometry was 85% and 93%. In vivo studies in subjects with hip implants also demonstrated that the proposed method can distinguish implants from surrounding low-signal tissues, such as cortical bone.

CONCLUSION

The proposed method can improve the delineation of metallic implant geometry by distinguishing metal voxels from artificial signal voids and low-signal tissues by estimating the susceptibility maps. Magn Reson Med 77:2402-2413, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Novel Pattern of Iron Deposition in the Fascicula Nigrale in Patients with Parkinson's Disease: A Pilot Study

Background and Purpose. To determine whether the pattern of iron deposition in the fascicula nigrale in patients with Parkinson's disease would be different from age-matched controls by utilizing quantitative susceptibility mapping to measure susceptibility change. Methods. MRIs of the brain were obtained from 34 subjects, 18 with Parkinson's disease and 16 age- and gender-matched controls. Regions of interest were drawn around the fascicula nigrale and substantia nigra using SWI mapping software by blinded investigators. Statistical analyses were performed to determine susceptibility patterns of both of these regions. Results. Measurements showed significantly increased susceptibility in the substantia nigra in Parkinson's patients and an increased rostral-caudal deposition of iron in the fascicula nigrale in all subjects. This trend was exaggerated with significant correlation noted with increasing age in the Parkinson group. Conclusion. The pattern of an exaggerated iron deposition gradient of the fascicula nigrale in the Parkinson group could represent underlying tract dysfunction. Significant correlation of increasing iron deposition with increasing age may be a cumulative effect, possibly related to disease duration.

Echo time-dependent quantitative susceptibility mapping contains information on tissue properties

PURPOSE

Magnetic susceptibility is a physical property of matter that varies depending on chemical composition and abundance of different molecular species. Interest is growing in mapping of magnetic susceptibility in the human brain using magnetic resonance imaging techniques, but the influences affecting the mapped values are not fully understood.

METHODS

We performed quantitative susceptibility mapping on 7 Tesla (T) multiple echo time gradient recalled echo data and evaluated the trend in 10 regions of the human brain. Temporal plots of susceptibility were performed in the caudate, pallidum, putamen, thalamus, insula, red nucleus, substantia nigra, internal capsule, corpus callosum, and fornix. We implemented an existing three compartment signal model and used optimization to fit the experimental result to assess the influences that could be responsible for our findings.

RESULTS

The temporal trend in susceptibility is different for different brain regions, and subsegmentation of specific regions suggests that differences are likely to be attributable to variations in tissue structure and composition. Using a signal model, we verified that a nonlinear temporal behavior in experimentally computed susceptibility within imaging voxels may be the result of the heterogeneous composition of tissue properties.

CONCLUSIONS

Decomposition of voxel constituents into meaningful parameters may lead to informative measures that reflect changes in tissue microstructure. Magn Reson Med 77:1946-1958, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Quantitative Susceptibility Mapping-Based Microscopy of Magnetic Resonance Venography (QSM-mMRV) for In Vivo Morphologically and Functionally Assessing Cerebromicrovasculature in Rat Stroke Model

Abnormal cerebral oxygenation and vessel structure is a crucial feature of stroke. An imaging method with structural and functional information is necessary for diagnosis of stroke. This study applies QSM-mMRV (quantitative susceptibility mapping-based microscopic magnetic resonance venography) for noninvasively detecting small cerebral venous vessels in rat stroke model. First, susceptibility mapping is optimized and calculated from magnetic resonance (MR) phase images of a rat brain. Subsequently, QSM-mMRV is used to simultaneously provide information on microvascular architecture and venous oxygen saturation (SvO₂), both of which can be used to evaluate the physiological and functional characteristics of microvascular changes for longitudinally monitoring and therapeutically evaluating a disease model. Morphologically, the quantification of vessel sizes using QSM-mMRV was 30% smaller than that of susceptibility-weighted imaging (SWI), which eliminated the overestimation of conventional SWI. Functionally, QSM-mMRV estimated an average SvO₂ ranging from 73% to 85% for healthy rats. Finally, we also applied QSM to monitor the revascularization of post-stroke vessels from 3 to 10 days after reperfusion. QSM estimations of SvO₂ were comparable to those calculated using the pulse oximeter standard metric. We conclude that QSM-mMRV is useful for longitudinally monitoring blood oxygen and might become clinically useful for assessing cerebrovascular diseases.

Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping

Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS.

Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping

Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS.

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA)

BACKGROUND

Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map.

NEW METHODS

A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace.

RESULTS

With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic.

COMPARISON WITH EXISTING METHODS

For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps.

CONCLUSION

χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA.

Foundations of MRI phase imaging and processing for Quantitative Susceptibility Mapping (QSM)

Quantitative Susceptibility Mapping (QSM) is a novel MRI based technique that relies on estimates of the magnetic field distribution in the tissue under examination. Several sophisticated data processing steps are required to extract the magnetic field distribution from raw MRI phase measurements. The objective of this review article is to provide a general overview and to discuss several underlying assumptions and limitations of the pre-processing steps that need to be applied to MRI phase data before the final field-to-source inversion can be performed. Beginning with the fundamental relation between MRI signal and tissue magnetic susceptibility this review covers the reconstruction of magnetic field maps from multi-channel phase images, background field correction, and provides an overview of state of the art QSM solution strategies.

Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range

Quantitative susceptibility mapping (QSM) is a novel MRI technique for the measurement of tissue magnetic susceptibility in three dimensions. Although numerous algorithms have been developed to solve this ill-posed inverse problem, the estimation of susceptibility maps with a wide range of values is still problematic. In cases such as large veins, contrast agent uptake and intracranial hemorrhages, extreme susceptibility values in focal areas cause severe streaking artifacts. To enable the reduction of these artifacts, whilst preserving subtle susceptibility contrast, a two-level QSM reconstruction algorithm (streaking artifact reduction for QSM, STAR-QSM) was developed in this study by tuning a regularization parameter to automatically reconstruct both large and small susceptibility values. Compared with current state-of-the-art QSM methods, such as the improved sparse linear equation and least-squares (iLSQR) algorithm, STAR-QSM significantly reduced the streaking artifacts, whilst preserving the sharp boundaries for blood vessels of mouse brains in vivo and fine anatomical details of high-resolution mouse brains ex vivo. Brain image data from patients with cerebral hematoma and multiple sclerosis further illustrated the superiority of this method in reducing streaking artifacts caused by large susceptibility sources, whilst maintaining sharp anatomical details. STAR-QSM is implemented in STI Suite, a comprehensive shareware for susceptibility imaging and quantification.

A fully flow-compensated multiecho susceptibility-weighted imaging sequence: The effects of acceleration and background field on flow compensation

PURPOSE

To present a fully flow-compensated multiecho gradient echo sequence that can be used for MR angiography (MRA), susceptibility weighted imaging (SWI), and quantitative susceptibility mapping (QSM) and to study the effects of flow acceleration and background field gradients on flow compensation.

METHODS

The quality of flow compensation was evaluated using the data from eight volunteers. The effects of flow acceleration were studied by changing the polarities of the readout gradients in two consecutive scans. The background field was used to estimate the phase errors of flow compensation in the presence of field inhomogeneities. SWI and QSM data were generated with confounding arterial phase removed. T2 * maps were obtained from the multiecho data to estimate T2 * of arterial blood.

RESULTS

Reasonable flow compensation was achieved. Nevertheless, background field gradients and acceleration-induced phase errors were found to be as large as π/2 and π/3, respectively, both in agreement with theory. T2 * was measured as 82 ± 4 ms and 74 ± 9 ms for arteries inside and outside the brain, respectively, at 3T.

CONCLUSION

High-quality MRA, SWI, and QSM data can be obtained simultaneously. Masking out the arteries to remove the phase due to flow acceleration and background field gradients improves the quality of both SWI and QSM data. Magn Reson Med 76:478-489, 2016. © 2015 Wiley Periodicals, Inc.

Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications

Quantitative susceptibility mapping (QSM) is a recently developed magnetic resonance imaging (MRI) technique for quantifying the spatial distribution of magnetic susceptibility within biological tissues. It first uses the frequency shift in the MRI signal to map the magnetic field profile within the tissue. The resulting field map is then used to determine the spatial distribution of the underlying magnetic susceptibility by solving an inverse problem. The solution is achieved by deconvolving the field map with a dipole field, under the assumption that the magnetic field results from a superposition of the dipole fields generated by all voxels and that each voxel has its own unique magnetic susceptibility. QSM provides an improved contrast-to-noise ratio for certain tissues and structures compared with its magnitude counterpart. More importantly, magnetic susceptibility directly reflects the molecular composition and cellular architecture of the tissue. Consequently, by quantifying magnetic susceptibility, QSM is becoming a quantitative imaging approach for characterizing normal and pathological tissue properties. This article reviews the mechanism that generates susceptibility contrast within tissues and some associated applications.

Susceptibility and size quantification of small human veins from an MRI method

Recently a method called CISSCO (Complex Image Summation around a Spherical or a Cylindrical Object) was introduced for accurately quantifying the susceptibility and the radius of any narrow cylindrical object at any orientation using a typical two-echo gradient echo sequence. This work further optimizes the method for quantifying oxygen saturation in small cerebral veins in the human brain. The revised method is first validated through numerical simulations and then applied to data from phantom and human brain. The effect of phase high pass filtering on the quantified parameters is studied and procedures for mitigating its adverse effects are suggested. Uncertainty of each measurement is estimated from the error propagation method. It is shown that the revised method allows for accurate quantification of both the vessel size and its oxygen saturation even in the case of a low SNR (signal to noise ratio) in the vein. The results are self consistent across different veins within a given subject with a variation of less than 6%. Finally, imaging parameters and some procedures are suggested for accurate susceptibility and radius quantifications of small human veins.

Quantitative Susceptibility Mapping: Concepts and Applications

PURPOSE

To review the fundamental principles of susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM), and to discuss recent clinical developments.

METHODS

SWI is a magnetic resonance imaging method that takes advantage of magnitude signal loss and phase information to reveal anatomic and physiologic information about tissue and venous vasculature. The method enhances image contrast qualitatively, relying on phase shifts due to differences in magnetic susceptibility between tissues. QSM, extending SWI in an elegant way, is a new sophisticated postprocessing technique that numerically solves the inverse source-effect problem to derive local tissue magnetic susceptibility (source) from the measured magnetic field distribution (effect) as it is reflected in the phase images of gradient-echo sequences.

RESULTS

SWI has meanwhile been established in numerous clinical as well as basic biomedical applications due to its ability to highlight tissue structures and compounds that are difficult to detect by conventional magnetic resonance imaging (MRI), including iron, calcifications, small veins, blood, and bones. The field of QSM has also progressed rapidly, both in terms of optimizing the post-processing strategies and algorithms as well as in gaining ground for new clinical applications that take advantage of its quantitative nature and improved specificity to identify the magnetic signature of lesions.

CONCLUSIONS

Though magnetic susceptibility may be a major nuisance producing image artifacts in MRI, recent work has transformed it into a useful source of image contrast. Both SWI and QSM are gaining increasing acceptance in clinical practice. In particular, QSM provides new insights into tissue composition and organization due to its more direct relation to the actual physical tissue magnetic properties.

Susceptibility Weighted Imaging and Mapping of Micro-Hemorrhages and Major Deep Veins after Traumatic Brain Injury

Micro-hemorrhages are a common result of traumatic brain injury (TBI), which can be quantified with susceptibility weighted imaging and mapping (SWIM), a quantitative susceptibility mapping approach. A total of 23 TBI patients (five women, 18 men; median age, 41.25 years old; range, 21.69-67.75 years) with an average Glasgow Coma Scale score of 7 (range, 3-15) at admission were recruited at mean 149 d (range, 57-366) after injury. Susceptibility-weighted imaging data were collected and post-processed to create SWIM images. The susceptibility value of small hemorrhages (diameter ≤10 mm) and major deep veins (right septal, left septal, central septal, right thalamostriate, left thalamostriate, internal cerebral, right basal vein of Rosenthal, left basal vein of Rosenthal, and pial veins) were evaluated. Different susceptibility thresholds were tested to determine SWIM's sensitivity and specificity for differentiating hemorrhages from the veins. A total of 253 deep veins and 173 small hemorrhages were identified and evaluated. The mean susceptibility of hemorrhages was 435±206 parts per billion (ppb) and the mean susceptibility of deep veins was 108±56 ppb. Hemorrhages showed a significantly higher susceptibility than all deep veins (p<0.001). With different thresholds (250, 227 and 200 ppb), the specificity was 97%, 95%, and 92%, and the sensitivity was 84%, 90%, and 92%, respectively. These results show that SWIM could be used to differentiate hemorrhages from veins in TBI patients in a semi-automated manner with reasonable sensitivity and specificity. A larger cohort will be needed to validate these findings.

Enhancing k-space quantitative susceptibility mapping by enforcing consistency on the cone data (CCD) with structural priors

PURPOSE

The inversion from the magnetic field to the magnetic susceptibility distribution is ill-posed because the dipole kernel, which relates the magnetic susceptibility to the magnetic field, has zeroes at a pair of cone surfaces in the k-space, leading to streaking artifacts on the reconstructed quantitative susceptibility maps (QSM). A method to impose consistency on the cone data (CCD) with structural priors is proposed to improve the solutions of k-space methods.

METHODS

The information in the cone region is recovered by enforcing structural consistency with structural prior, while information in the noncone trust region is enforced to be consistent with the magnetic field measurements in k-space. This CCD method was evaluated by comparing the initial results of existing QSM algorithms to the QSM results after CCD enhancement with respect to the COSMOS results in simulation, phantom, and in vivo human brain.

RESULTS

The proposed method demonstrated suppression of streaking artifacts and the resulting QSM showed better agreement with reference standard QSM compared with other k-space based methods.

CONCLUSION

By enforcing consistency with structural priors in the cone region, the missing data in the cone can be recovered and the streaking artifacts in QSM can be suppressed.

Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2

PURPOSE

To evaluate the sensitivity and specificity of quantitative magnetic resonance (MR) iron mapping including R2, R2* and magnetic susceptibility to differentiate patients with Parkinson's disease (PD) from healthy controls.

MATERIALS AND METHODS

Thirty (30) healthy controls (HC) (64±7years old) and 20 patients with idiopathic PD (66±8years old) were studied using a 3T MR imaging scanner. R2 maps were generated from GRASE sequence while R2*, and quantitative susceptibility mapping (QSM) were obtained from a conventional multi-echo gradient-echo sequence. R2, R2* and relative susceptibility (Δχ) values of structures in the basal ganglia were measured for each patient and control. An analysis of sensitivity and specificity and unpaired t-test was applied to the two groups.

RESULTS

A significant difference (p<0.05) was found for R2 and ∆χ values in the substantia nigra as a whole and in the pars compacta for PD patients. The R2* values were different significantly (p<0.05) only on the substantia nigra pars compacta. QSM presented the highest sensitivity and specificity to differentiate the two populations.

CONCLUSION

The QSM map was the most sensitive quantitative technique for detecting a significant increase of iron for PD. The highest significant difference between controls and patients was found in the substantia nigra pars compacta using QSM.

Cerebral hemodynamic changes of mild traumatic brain injury at the acute stage

Mild traumatic brain injury (mTBI) is a significant public health care burden in the United States. However, we lack a detailed understanding of the pathophysiology following mTBI and its relation to symptoms and recovery. With advanced magnetic resonance imaging (MRI), we can investigate brain perfusion and oxygenation in regions known to be implicated in symptoms, including cortical gray matter and subcortical structures. In this study, we assessed 14 mTBI patients and 18 controls with susceptibility weighted imaging and mapping (SWIM) for blood oxygenation quantification. In addition to SWIM, 7 patients and 12 controls had cerebral perfusion measured with arterial spin labeling (ASL). We found increases in regional cerebral blood flow (CBF) in the left striatum, and in frontal and occipital lobes in patients as compared to controls (p = 0.01, 0.03, 0.03 respectively). We also found decreases in venous susceptibility, indicating increases in venous oxygenation, in the left thalamostriate vein and right basal vein of Rosenthal (p = 0.04 in both). mTBI patients had significantly lower delayed recall scores on the standardized assessment of concussion, but neither susceptibility nor CBF measures were found to correlate with symptoms as assessed by neuropsychological testing. The increased CBF combined with increased venous oxygenation suggests an increase in cerebral blood flow that exceeds the oxygen demand of the tissue, in contrast to the regional hypoxia seen in more severe TBI. This may represent a neuroprotective response following mTBI, which warrants further investigation.

An improved method for susceptibility and radius quantification of cylindrical objects from MRI

A new method is developed to measure the magnetic susceptibilities and radii of small cylinder-like objects at arbitrary orientations accurately. This method for most biological substances only requires a standard gradient echo sequence with one or two echo times, depending on the orientation of an object relative to the main magnetic field. For objects oriented at the magic angle, however, this method is not applicable. As a byproduct of this method, the cross-sectional area as well as signals inside and outside the object can be determined. The uncertainty of each measurement is estimated from the error propagation method. Partial volume, dephasing, and phase aliasing effects are naturally included in the equations of this method. A number of simulations, phantom, and pilot in-vivo human studies are carried out to validate the theory. When the maximal phase value at the boundary of a given cylindrical object is larger than 3 radians, and the phase inside the object is more than 1 radian, the susceptibility can be accurately quantified within 15%. The radius of the object can be determined to subpixel accuracy. This is the case when the signal-to-noise ratio inside the object is about 6:1 or higher and the radius of the object is about one pixel or larger. These conditions are realistic when considering medullary and pial veins for example.

Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker

In MRI, the main magnetic field polarizes the electron cloud of a molecule, generating a chemical shift for observer protons within the molecule and a magnetic susceptibility inhomogeneity field for observer protons outside the molecule. The number of water protons surrounding a molecule for detecting its magnetic susceptibility is vastly greater than the number of protons within the molecule for detecting its chemical shift. However, the study of tissue magnetic susceptibility has been hindered by poor molecular specificities of hitherto used methods based on MRI signal phase and T2* contrast, which depend convolutedly on surrounding susceptibility sources. Deconvolution of the MRI signal phase can determine tissue susceptibility but is challenged by the lack of MRI signal in the background and by the zeroes in the dipole kernel. Recently, physically meaningful regularizations, including the Bayesian approach, have been developed to enable accurate quantitative susceptibility mapping (QSM) for studying iron distribution, metabolic oxygen consumption, blood degradation, calcification, demyelination, and other pathophysiological susceptibility changes, as well as contrast agent biodistribution in MRI. This paper attempts to summarize the basic physical concepts and essential algorithmic steps in QSM, to describe clinical and technical issues under active development, and to provide references, codes, and testing data for readers interested in QSM.

Quantitative susceptibility mapping: current status and future directions

Quantitative susceptibility mapping (QSM) is a new technique for quantifying magnetic susceptibility. It has already found various applications in quantifying in vivo iron content, calcifications and changes in venous oxygen saturation. The accuracy of susceptibility mapping is dependent on several factors. In this review, we evaluate the entire process of QSM from data acquisition to individual data processing steps. We also show preliminary results of several new concepts introduced in this review in an attempt to improve the quality and accuracy for certain steps. The uncertainties in estimating susceptibility differences using susceptibility maps, phase images, and T2* maps are analyzed and compared. Finally, example clinical applications are presented. We conclude that QSM holds great promise in quantifying iron and becoming a standard clinical tool.

Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique that enhances image contrast by using the susceptibility differences between tissues. It is created by combining both magnitude and phase in the gradient echo data. SWI is sensitive to both paramagnetic and diamagnetic substances which generate different phase shift in MRI data. SWI images can be displayed as a minimum intensity projection that provides high resolution delineation of the cerebral venous architecture, a feature that is not available in other MRI techniques. As such, SWI has been widely applied to diagnose various venous abnormalities. SWI is especially sensitive to deoxygenated blood and intracranial mineral deposition and, for that reason, has been applied to image various pathologies including intracranial hemorrhage, traumatic brain injury, stroke, neoplasm, and multiple sclerosis. SWI, however, does not provide quantitative measures of magnetic susceptibility. This limitation is currently being addressed with the development of quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI). While QSM treats susceptibility as isotropic, STI treats susceptibility as generally anisotropic characterized by a tensor quantity. This article reviews the basic principles of SWI, its clinical and research applications, the mechanisms governing brain susceptibility properties, and its practical implementation, with a focus on brain imaging.

Decreased oxygen saturation in asymmetrically prominent cortical veins in patients with cerebral ischemic stroke

Decreased oxygen saturation in asymmetrically prominent cortical veins (APCV) seen in ischemic stroke has been hypothesized to correlate with an increase of de-oxygenated hemoglobin. Our goal is to quantify magnetic susceptibility to define APCV by establishing a cutoff above which the deoxyhemoglobin levels are considered abnormal. A retrospective study was conducted on 26 patients with acute ischemic stroke in one cerebral hemisphere that exhibited APCV with 30 age- and sex-matched healthy controls. Quantitative susceptibility mapping (QSM) was used to calculate the magnetic susceptibility of the cortical veins. A paired t-test was used to compare the susceptibility of the cortical veins in the left and right hemispheres for healthy controls as well as in the contralateral hemisphere for stroke patients with APCV. The change in oxygen saturation in the APCV relative to the contralateral side was calculated after thresholding the susceptibility using the mean plus two standard deviations of the contralateral side for each individual. The thresholded susceptibility value of the APCVs in the stroke hemisphere was 254±48 ppb which was significantly higher (p<0.05) than that in the contralateral hemisphere (123±12 ppb) and in healthy controls (125±8 ppb). There was a decrease of oxygen saturation in the APCV ranging from 16% to 44% relative to the veins of the contralateral hemisphere. In conclusion, APCV seen in SWI correspond to reduced levels of oxygen saturation and these abnormal veins can be identified using a susceptibility threshold on the QSM data.

Measuring venous blood oxygenation in fetal brain using susceptibility-weighted imaging

PURPOSE

To evaluate fetal cerebral venous blood oxygenation, Yv, using principles of MR susceptometry.

MATERIALS AND METHODS

A cohort of 19 pregnant subjects, with a mean gestational age of 31.6 ± 4.7 weeks were imaged using a modified susceptibility-weighted imaging (SWI) sequence. Data quality was first assessed for feasibility of oxygen saturation measurement, and data from five subjects (mean ± std gestational age of 33.7 ± 3.6 weeks) were then chosen for further quantitative analysis. SWI phase in the superior sagittal sinus was used to evaluate oxygen saturation using the principles of MR susceptometry. Systematic error in the measured Y(v) values was studied through simulations.

RESULTS

Simulations showed that the systematic error in Yv depended upon the assumed angle of the vessel, θ, relative to the main magnetic field and the error in that vessel angle δθ. For the typical vessel angle of θ = 30° encountered in the fetal data analyzed, a δθ as large as ±20° led to an absolute error, δYv, of less than 11%. The measured mean oxygen saturation across the five fetuses was 66% ± 9.4%. This average cerebral venous blood oxygenation value is in close agreement with values in the published literature.

CONCLUSION

We have reported the first in vivo measurement of human fetal cerebral venous oxygen saturation using MRI.

Imaging the effects of oxygen saturation changes in voluntary apnea and hyperventilation on susceptibility-weighted imaging

BACKGROUND AND PURPOSE

Cerebrovascular oxygenation changes during respiratory challenges have clinically important implications for brain function, including cerebral autoregulation and the rate of brain metabolism. SWI is sensitive to venous oxygenation level by exploitation of the magnetic susceptibility of deoxygenated blood. We assessed cerebral venous blood oxygenation changes during simple voluntary breath-holding (apnea) and hyperventilation by use of SWI at 3T.

MATERIALS AND METHODS

We performed SWI scans (3T; acquisition time of 1 minute, 28 seconds; centered on the anterior commissure and the posterior commissure) on 10 healthy male volunteers during baseline breathing as well as during simple voluntary hyperventilation and apnea challenges. The hyperventilation and apnea tasks were separated by a 5-minute resting period. SWI venograms were generated, and the signal changes on SWI before and after the respiratory stress tasks were compared by means of a paired Student t test.

RESULTS

Changes in venous vasculature visibility caused by the respiratory challenges were directly visualized on the SWI venograms. The venogram segmentation results showed that voluntary apnea decreased the mean venous blood voxel number by 1.6% (P < .0001), and hyperventilation increased the mean venous blood voxel number by 2.7% (P < .0001). These results can be explained by blood CO2 changes secondary to the respiratory challenges, which can alter cerebrovascular tone and cerebral blood flow and ultimately affect venous oxygen levels.

CONCLUSIONS

These results highlight the sensitivity of SWI to simple and noninvasive respiratory challenges and its potential utility in assessing cerebral hemodynamics and vasomotor responses.