Structural and functional quantitative susceptibility mapping from standard fMRI studies

Quantitative susceptibility mapping through model-based deep image prior (MoDIP)

The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32 % accuracy improvement than supervised deep learning methods. It is also 33 % more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 min.

Super-resolution QSM in little or no additional time for imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes

Quantitative Susceptibility Mapping has the potential to provide additional insights into neurological diseases but is typically based on a quite long (5-10 min) 3D gradient-echo scan which is highly sensitive to motion. We propose an ultra-fast acquisition based on three orthogonal (sagittal, coronal and axial) 2D simultaneous multi-slice EPI scans with 1 mm in-plane resolution and 3 mm thick slices. Images in each orientation are corrected for susceptibility-related distortions and co-registered with an iterative non-linear Minimum Deformation Averaging (Volgenmodel) approach to generate a high SNR, super-resolution data set with an isotropic resolution of close to 1 mm. The net acquisition time is 3 times the volume acquisition time of EPI or about 12 s, but the three volumes could also replace "dummy scans" in fMRI, making it feasible to acquire QSM in little or No Additional Time for Imaging (NATIve). NATIve QSM values agreed well with reference 3D GRE QSM in the basal ganglia in healthy subjects. In patients with multiple sclerosis, there was also a good agreement between the susceptibility values within lesions and control ROIs and all lesions which could be seen on 3D GRE QSMs could also be visualized on NATIve QSMs. The approach is faster than conventional 3D GRE by a factor of 25-50 and faster than 3D EPI by a factor of 3-5. As a 2D technique, NATIve QSM was shown to be much more robust to motion than the 3D GRE and 3D EPI, opening up the possibility of studying neurological diseases involving iron accumulation and demyelination in patients who find it difficult to lie still for long enough to acquire QSM data with conventional methods.

Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL)

The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.

Susceptibility source separation from gradient echo data using magnitude decay modeling

BACKGROUND AND PURPOSE

The objective is to demonstrate feasibility of separating magnetic sources in quantitative susceptibility mapping (QSM) by incorporating magnitude decay rates R 2 ∗ $R_2^{\rm{*}}$ in gradient echo (GRE) MRI.

METHODS

Magnetic susceptibility source separation was developed using R 2 ∗ $R_2^{\rm{*}}$ and compared with a prior method using R 2 ' = R 2 ∗ - R 2 ${R^{\prime}_2} = R_2^* - {R_2}$ that required an additional sequence to measure the transverse relaxation rate R₂ . Both susceptibility separation methods were compared in multiple sclerosis (MS) patients (n = 17). Susceptibility values of negative sources estimated with R 2 ∗ $R_2^{\rm{*}}$ -based source separation in a set of enhancing MS lesions (n = 44) were correlated against longitudinal myelin water fraction (MWF) changes.

RESULTS

In in vivo data, linear regression of the estimated χ + ${\chi}^{+}$ and χ - ${\chi}^{-}$ susceptibility values between the R 2 ∗ $R_2^*$ - and the R 2 ' ${R^{\prime}_2}$ -based separation methods performed across 182 segmented lesions revealed correlation coefficient r = .96 and slope close .99. Correlation analysis in enhancing lesions revealed a significant positive association between the χ - ${\chi}^{-}$ increase at 1-year post-onset relative to 0 year and the MWF increase at 1 year relative to 0 year (β = -0.144, 95% confidence interval: [-0.199, -0.1], p = .0008) and good agreement between R 2 ' ${R^{\prime}_2}$ and R 2 ∗ $R_2^*$ methods (r = .79, slope = .95).

CONCLUSIONS

Separation of magnetic sources based solely on GRE complex data is feasible by combining magnitude decay rate modeling and phase-based QSM and χ - ${\chi}^{-}$ change may serve as a biomarker for myelin recovery or damage in acute MS lesions.

Quantitative susceptibility mapping of the head-and-neck using SMURF fat-water imaging with chemical shift and relaxation rate corrections

PURPOSE

To address the challenges posed by fat-water chemical shift artifacts and relaxation rate discrepancies to quantitative susceptibility mapping (QSM) outside the brain, and to generate accurate susceptibility maps of the head-and-neck at 3 and 7 Tesla.

METHODS

Simultaneous Multiple Resonance Frequency (SMURF) imaging was extended to 7 Tesla and used to acquire head-and-neck gradient echo images at both 3 and 7 Tesla. Separated fat and water images were corrected for Type 1 (displacement) and Type 2 (phase discrepancy) chemical shift artefacts, and for the bias resulting from differences in T1 and T 2 ∗ relaxation rates, recombined and used as the basis for QSM. A novel phase signal-based masking approach was used to generate head-and-neck masks.

RESULTS

SMURF generated well-separated fat and water images of the head-and-neck. Corrections for chemical shift artefacts and relaxation rate differences removed overestimation of the susceptibility values, blurring in the susceptibility maps, and the disproportionate influence of fat in mixed voxels. The resulting susceptibility maps showed high correspondence between the paramagnetic areas and the locations of fatty tissues and the susceptibility estimates were similar to literature values. The proposed masking approach was shown to provide a simple means of generating head-and-neck masks.

CONCLUSION

Corrections for Type 1 and Type 2 chemical shift artefacts and for fat-water relaxation rate differences, mainly in T1 , were shown to be required for accurate susceptibility mapping of fatty-body regions. SMURF made it possible to apply these corrections and generate high-quality susceptibility maps of the entire head-and-neck at both 3 and 7 Tesla.

PRATEEK: Integration of Multimodal Neuroimaging Data to Facilitate Advanced Brain Research

BACKGROUND

In vivo neuroimaging modalities such as magnetic resonance imaging (MRI), functional MRI (fMRI), magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), and quantitative susceptibility mapping (QSM) are useful techniques to understand brain anatomical structure, functional activity, source localization, neurochemical profiles, and tissue susceptibility respectively. Integrating unique and distinct information from these neuroimaging modalities will further help to enhance the understanding of complex neurological diseases.

OBJECTIVE

To develop a processing scheme for multimodal data integration in a seamless manner on healthy young population, thus establishing a generalized framework for various clinical conditions (e.g., Alzheimer's disease).

METHODS

A multimodal data integration scheme has been developed to integrate the outcomes from multiple neuroimaging data (fMRI, MEG, MRS, and QSM) spatially. Furthermore, the entire scheme has been incorporated into a user-friendly toolbox- "PRATEEK".

RESULTS

The proposed methodology and toolbox has been tested for viability among fourteen healthy young participants. The data-integration scheme was tested for bilateral occipital cortices as the regions of interest and can also be extended to other anatomical regions. Overlap percentage from each combination of two modalities (fMRI-MRS, MEG-MRS, fMRI-QSM, and fMRI-MEG) has been computed and also been qualitatively assessed for combinations of the three (MEG-MRS-QSM) and four (fMRI-MEG-MRS-QSM) modalities.

CONCLUSION

This user-friendly toolbox minimizes the need of an expertise in handling different neuroimaging tools for processing and analyzing multimodal data. The proposed scheme will be beneficial for clinical studies where geometric information plays a crucial role for advance brain research.

Preconditioned water-fat total field inversion: Application to spine quantitative susceptibility mapping

PURPOSE

To (a) develop a preconditioned water-fat total field inversion (wfTFI) algorithm that directly estimates the susceptibility map from complex multi-echo gradient echo data for water-fat regions and to (b) evaluate the performance of the proposed wfTFI quantitative susceptibility mapping (QSM) method in comparison with a local field inversion (LFI) method and a linear total field inversion (TFI) method in the spine.

METHODS

Numerical simulations and in vivo spine multi-echo gradient echo measurements were performed to compare wfTFI to an algorithm based on disjoint background field removal (BFR) and LFI and to a formerly proposed TFI algorithm. The data from 1 healthy volunteer and 10 patients with metastatic bone disease were included in the analysis. Clinical routine computed tomography (CT) images were used as a reference standard to distinguish osteoblastic from osteolytic changes. The ability of the QSM methods to distinguish osteoblastic from osteolytic changes was evaluated.

RESULTS

The proposed wfTFI method was able to decrease the normalized root mean square error compared to the LFI and TFI methods in the simulation. The in vivo wfTFI susceptibility maps showed reduced BFR artifacts, noise amplification, and streaking artifacts compared to the LFI and TFI maps. wfTFI provided a significantly higher diagnostic confidence in differentiating osteolytic and osteoblastic lesions in the spine compared to the LFI method (p = .012).

CONCLUSION

The proposed wfTFI method can minimize BFR artifacts, noise amplification, and streaking artifacts in water-fat regions and can thus better differentiate between osteoblastic and osteolytic changes in patients with metastatic disease compared to LFI and the original TFI method.

Functional quantitative susceptibility mapping (fQSM) of rat brain during flashing light stimulation

Functional magnetic resonance imaging (fMRI) based on the blood oxygenation level-dependent (BOLD) contrast has become an indispensable tool in neuroscience. However, the BOLD signal is nonlocal, lacking quantitative measurement of oxygenation fluctuation. This preclinical study aimed to introduced functional quantitative susceptibility mapping (fQSM) to complement BOLD-fMRI to quantitatively assess the local susceptibility and venous oxygen saturation (SvO₂). Rats were subjected to a 5 Hz flashing light and the different inhaled oxygenation levels (30% and 100%) were used to observe the venous susceptibility to quantify SvO₂. Phase information was extracted to produce QSM, and the activation responses of magnitude (conventional BOLD) and the QSM time-series were analyzed. During light stimulation, the susceptibility change of fQSM was four times larger than the BOLD signal change in both inhalation oxygenation conditions. Moreover, the responses in the fQSM map were more restricted to the visual pathway, such as the lateral geniculate nucleus and superior colliculus, compared with the relatively diffuse distributions in the BOLD map. Also, the calibrated SvO₂ was approximately 84% (88%) when the task was on, 83% (87%) when the task was off during 30% (and during 100%) oxygen inhalation. This is the first fQSM study in a small animal model and increases our understanding of fQSM in the brains of small animals. This study demonstrated the feasibility, sensitivity, and specificity of fQSM using light stimulus, as fQSM provides quantitative clues as well as localized information, complementing the defects of BOLD-fMRI. In addition to neural activity, fQSM also assesses SvO₂ as supplementary information while BOLD-fMRI dose not. Accordingly, the fQSM technique could be a useful quantitative tool for functional studies, such as longitudinal follow up of neurodegenerative diseases, functional recovery after brain surgery, and negative BOLD studies.

Improved body quantitative susceptibility mapping by using a variable-layer single-min-cut graph-cut for field-mapping

PURPOSE

To develop a robust algorithm for field-mapping in the presence of water-fat components, large B 0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM).

METHODS

A framework solving the cost-function of the water-fat separation problem in a single-min-cut graph-cut based on the variable-layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field-mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph-cut algorithm and a formerly proposed single-min-cut graph-cut.

RESULTS

The proposed method was shown to yield accurate field-map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field-map and susceptibility results compared to iterative graph-cut field-mapping especially in regions with low SNR, strong field-map variations and high R 2 ∗ values.

CONCLUSIONS

A single-min-cut graph-cut field-mapping method with a variable-layer construction was developed for field-mapping in body water-fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids.

Multi-centre, multi-vendor reproducibility of 7T QSM and R2* in the human brain: Results from the UK7T study

Introduction

We present the reliability of ultra-high field T₂* MRI at 7T, as part of the UK7T Network's “Travelling Heads” study. T₂*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R₂* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R₂* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1.5–3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R₂* mapping at 7T, in readiness for future multi-site clinical studies.

Methods

Ten healthy volunteers were scanned with harmonised single- and multi-echo T₂*-weighted gradient echo pulse sequences. Participants were scanned five times at each “home” site and once at each of four other sites. The five sites had 1× Philips, 2× Siemens Magnetom, and 2× Siemens Terra scanners. QSM and R₂* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https://github.com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space.

Results and Discussion

Mean susceptibility (χ) and R₂* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0.001–0.005 ppm (χ) and 0.0005–0.001 ms⁻¹ (R₂*). For χ this is 2.1–4.8 fold better than 3T reports, and 1.1–3.4 fold better for R₂*. The median ICC from within- and cross-site R₂* data was 0.98 and 0.91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B₀ inhomogeneity such as the inferior frontal cortex. Across sites, R₂* values were more consistent than QSM in subcortical structures due to differences in B₀-shimming. On a between-subject level, our measured χ and R₂* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol.

Conclusion

The harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R₂* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.

Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction

Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. This inaccuracy has thus hindered the application of QSM for measuring susceptibility of tissues near the brain edges, e.g., quantifying cortical layers and generating superficial venography. To address these challenges, we propose a learning-based QSM reconstruction method that directly estimates the magnetic susceptibility from total phase images without the need for brain extraction and background phase removal, referred to as autoQSM. The neural network has a modified U-net structure and is trained using QSM maps computed by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82 years were employed for patch-wise network training. The network was validated on data dissimilar to the training data, e.g., in vivo mouse brain data and brains with lesions, which suggests that the network generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. Quantitative and qualitative comparisons were performed between autoQSM and other two-step QSM methods. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction, and high reconstruction speed demonstrate autoQSM's potential for future applications.

Quantitative Susceptibility Mapping to Assess Cerebral Vascular Compliance

This study explored whether autoregulatory shifts in cerebral blood volume induce susceptibility changes large enough to be depicted by quantitative susceptibility mapping. Eight healthy subjects underwent fast quantitative susceptibility mapping at 3T while lying down to slowly decrease mean arterial pressure. A linear relationship between mean arterial pressure and susceptibility was observed in cortical and subcortical structures, likely representing vessels involved in autoregulation. The slope of this relationship is assumed to indicate the extent of cerebral vascular compliance.

The effect of low resolution and coverage on the accuracy of susceptibility mapping

PURPOSE

Quantitative susceptibility mapping (QSM) has found increasing clinical applications. However, to reduce scan time, clinical acquisitions often use reduced resolution and coverage, particularly in the through-slice dimension. The effect of these factors on QSM has begun to be assessed using only balloon phantoms and downsampled brain images. Here, we investigate the effects (and their sources) of low resolution or coverage on QSM using both simulated and acquired images.

METHODS

Brain images were acquired at 1 mm isotropic resolution and full brain coverage, and low resolution (up to 6 mm slice thickness) or coverage (down to 20 mm) in 5 healthy volunteers. Images at reduced resolution or coverage were also simulated in these volunteers and in a new, anthropomorphic, numerical phantom. Mean susceptibilities in 5 brain regions, including white matter, were investigated over varying resolution and coverage.

RESULTS

The susceptibility map contrast decreased with increasing slice thickness and spacing, and with decreasing coverage below ~40 mm for 2 different QSM pipelines. Our simulations showed that calculated susceptibility values were erroneous at low resolution or very low coverage, because of insufficient sampling and overattenuation of the susceptibility-induced field perturbations. Susceptibility maps calculated from simulated and acquired images showed similar behavior.

CONCLUSIONS

Both low resolution and low coverage lead to loss of contrast and errors in susceptibility maps. The widespread clinical practice of using low resolution and coverage does not provide accurate susceptibility maps. Simulations in images of healthy volunteers and in a new, anthropomorphic numerical phantom were able to accurately model low-resolution and low-coverage acquisitions.

Patents on Quantitative Susceptibility Mapping (QSM) of Tissue Magnetism

BACKGROUND

Quantitative susceptibility mapping (QSM) depicts biodistributions of tissue magnetic susceptibility sources, including endogenous iron and calcifications, as well as exogenous paramagnetic contrast agents and probes. When comparing QSM with simple susceptibility weighted MRI, QSM eliminates blooming artifacts and shows reproducible tissue susceptibility maps independent of field strength and scanner manufacturer over a broad range of image acquisition parameters. For patient care, QSM promises to inform diagnosis, guide surgery, gauge medication, and monitor drug delivery. The Bayesian framework using MRI phase data and structural prior knowledge has made QSM sufficiently robust and accurate for routine clinical practice.

OBJECTIVE

To address the lack of a summary of US patents that is valuable for QSM product development and dissemination into the MRI community.

METHOD

We searched the USPTO Full-Text and Image Database for patents relevant to QSM technology innovation. We analyzed the claims of each patent to characterize the main invented method and we investigated data on clinical utility.

RESULTS

We identified 17 QSM patents; 13 were implemented clinically, covering various aspects of QSM technology, including the Bayesian framework, background field removal, numerical optimization solver, zero filling, and zero-TE phase.

CONCLUSION

Our patent search identified patents that enable QSM technology for imaging the brain and other tissues. QSM can be applied to study a wide range of diseases including neurological diseases, liver iron disorders, tissue ischemia, and osteoporosis. MRI manufacturers can develop QSM products for more seamless integration into existing MRI scanners to improve medical care.

A robust multi-scale approach to quantitative susceptibility mapping

Quantitative Susceptibility Mapping (QSM), best known as a surrogate for tissue iron content, is becoming a highly relevant MRI contrast for monitoring cellular and vascular status in aging, addiction, traumatic brain injury and, in general, a wide range of neurological disorders. In this study we present a new Bayesian QSM algorithm, named Multi-Scale Dipole Inversion (MSDI), which builds on the nonlinear Morphology-Enabled Dipole Inversion (nMEDI) framework, incorporating three additional features: (i) improved implementation of Laplace's equation to reduce the influence of background fields through variable harmonic filtering and subsequent deconvolution, (ii) improved error control through dynamic phase-reliability compensation across spatial scales, and (iii) scalewise use of the morphological prior. More generally, this new pre-conditioned QSM formalism aims to reduce the impact of dipole-incompatible fields and measurement errors such as flow effects, poor signal-to-noise ratio or other data inconsistencies that can lead to streaking and shadowing artefacts. In terms of performance, MSDI is the first algorithm to rank in the top-10 for all metrics evaluated in the 2016 QSM Reconstruction Challenge. It also demonstrated lower variance than nMEDI and more stable behaviour in scan-rescan reproducibility experiments for different MRI acquisitions at 3 and 7 Tesla. In the present work, we also explored new forms of susceptibility MRI contrast making explicit use of the differential information across spatial scales. Specifically, we show MSDI-derived examples of: (i) enhanced anatomical detail with susceptibility inversions from short-range dipole fields (hereby referred to as High-Pass Susceptibility Mapping or HPSM), (ii) high specificity to venous-blood susceptibilities for highly regularised HPSM (making a case for MSDI-based Venography or VenoMSDI), (iii) improved tissue specificity (and possibly statistical conditioning) for Macroscopic-Vessel Suppressed Susceptibility Mapping (MVSSM), and (iv) high spatial specificity and definition for HPSM-based Susceptibility-Weighted Imaging (HPSM-SWI) and related intensity projections.

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods.

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.

Simultaneous QSM and metabolic imaging of the brain using SPICE

PURPOSE

To map brain metabolites and tissue magnetic susceptibility simultaneously using a single three-dimensional 1 H-MRSI acquisition without water suppression.

METHODS

The proposed technique builds on a subspace imaging method called spectroscopic imaging by exploiting spatiospectral correlation (SPICE), which enables ultrashort echo time (TE)/short pulse repetition time (TR) acquisitions for 1 H-MRSI without water suppression. This data acquisition scheme simultaneously captures both the spectral information of brain metabolites and the phase information of the water signals that is directly related to tissue magnetic susceptibility variations. In extending this scheme for simultaneous QSM and metabolic imaging, we increase k-space coverage by using dual density sparse sampling and ramp sampling to achieve spatial resolution often required by QSM, while maintaining a reasonable signal-to-noise ratio (SNR) for the spatiospectral data used for metabolite mapping. In data processing, we obtain high-quality QSM from the unsuppressed water signals by taking advantage of the larger number of echoes acquired and any available anatomical priors; metabolite spatiospectral distributions are reconstructed using a union-of-subspaces model.

RESULTS

In vivo experimental results demonstrate that the proposed method can produce susceptibility maps at a resolution higher than 1.8 × 1.8 × 2.4 mm3 along with metabolite spatiospectral distributions at a nominal spatial resolution of 2.4 × 2.4 × 2.4 mm3 from a single 7-min MRSI scan. The estimated susceptibility values are consistent with those obtained using the conventional QSM method with 3D multi-echo gradient echo acquisitions.

CONCLUSION

This article reports a new capability for simultaneous susceptibility mapping and metabolic imaging of the brain from a single 1 H-MRSI scan, which has potential for a wide range of applications. Magn Reson Med 79:13-21, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative susceptibility mapping (QSM) and R2* in the human brain at 3T: Evaluation of intra-scanner repeatability

Quantitative susceptibility mapping (QSM) and the effective transverse relaxation rate (R₂*) can be used to monitor iron and myelin content in brain tissue, which are both subject to changes in many neurological diseases but also during healthy aging. In this study, we quantitatively assessed the repeatability of QSM and R₂* by applying four independent scans in eight young healthy, female subjects on a 3T MRI scanner. Since QSM does not yield absolute values for bulk magnetic susceptibilities, we additionally investigated the influence of the choice of a reference brain region for susceptibility by computing susceptibility differences with respect to five different brain structures (whole brain, frontal white matter (fWM), internal capsule (IC), cerebrospinal fluid (CSF) in the lateral ventricle, cortical gray matter (cGM)). The intra-class correlation coefficient (ICC), variance ratio (VR) and repeatability coefficient (RC) were used to evaluate the repeatability of the calculated susceptibility differences and the R₂* values in six different subcortical brain structures. Linear regression was used to analyze the correlation between susceptibility differences and R₂*. We found that the susceptibility differences with respect to each investigated reference region (0.868≤mean ICC≤0.914) and the R₂* values (mean ICC=0.923) were highly repeatable across the four times repeated scans. With consistently higher ICC, higher VR and lower RC, whole brain and cGM appeared to be the two most suitable reference regions for QSM with respect to repeatability.