Quantitative susceptibility mapping in the abdomen as an imaging biomarker of hepatic iron overload

SIPAS: A comprehensive susceptibility imaging process and analysis studio

Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images. In this paper, we develop a comprehensive susceptibility imaging process and analysis studio (SIPAS) that can accomplish reliable QSM processing and offer a standardized evaluation system. Specifically, SIPAS integrates multiple methods for each step, enabling users to select algorithm combinations according to data conditions, and QSM maps could be evaluated by two aspects, including image quality indicators within all voxels and region-of-interest (ROI) analysis. Through a sophisticated design of user-friendly interfaces, the results of each procedure are able to be exhibited in axial, coronal, and sagittal views in real-time, meanwhile ROIs can be displayed in 3D rendering visualization. The accuracy and compatibility of SIPAS are demonstrated by experiments on multiple in vivo human brain datasets acquired from 3T, 5T, and 7T MRI scanners of different manufacturers. We also validate the QSM maps obtained by various algorithm combinations in SIPAS, among which the combination of iRSHARP and SFCR achieves the best results on its evaluation system. SIPAS is a comprehensive, sophisticated, and reliable toolkit that may prompt the QSM application in scientific research and clinical practice.

Comparison of R2* and FerriScan liver iron concentration (LIC) quantification in the clinical classification of Iron overload states

PURPOSE

This study assessed the clinical classification performance of an R2*-based MRI technique for LIC quantification relative to FerriScan, with intra-patient FerriScan LIC uncertainty taken into account. The variabilities of R2* and FerriScan LIC were also assessed.

MATERIALS AND METHODS

This was an ethics approved retrospective study, performed on patients undergoing chelation treatment for iron overload. 126 patients (69 women, 57 men), with an age of 42 +/- 16 years (range 19-86 years) were included. FerriScan and R2* MRI at 1.5 T were performed as part of a routine liver iron assessment protocol. For R2* MRI, a commercially available pulse sequence and reconstruction implementation was used, together with a previously derived calibration curve to convert R2* to LIC. Clinical classifications arising from R2*-derived LIC estimates were compared to those based on FerriScan. The accuracy and precision of the R2* technique was calculated. The variabilities of FerriScan- and R2*-derived estimates of LIC were compared with a Wilcoxon Signed Rank test. Significance was set at the 95% confidence level.

RESULTS

The precision of R2* ranged from 0.59 to 0.92, with an overall accuracy of 72%. When intra-patient FerriScan LIC uncertainty was considered, precision and accuracy increased to >94% and 97% respectively. The R2*-LIC variability (=17%) was significantly lower than the FerriScan-LIC variability (34%) at the 95% confidence level (p < 10-3).

CONCLUSION

MRI R2*-based LIC estimates provided a similar clinical classification as FerriScan. The intra-patient uncertainty of R2*-based LIC estimates was significantly lower than FerriScan.

Value of Quantitative Susceptibility Mapping in Clinical Neuroradiology

Quantitative susceptibility mapping (QSM) is a unique technique for providing quantitative information on tissue magnetic susceptibility using phase image data. QSM can provide valuable information regarding physiological and pathological processes such as iron deposition, hemorrhage, calcification, and myelin. QSM has been considered for use as an imaging biomarker to investigate physiological status and pathological changes. Although various studies have investigated the clinical applications of QSM, particularly regarding the use of QSM in clinical practice, have not been examined well. This review provides on an overview of the basics of QSM and its clinical applications in neuroradiology. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Narrative review of magnetic resonance imaging in quantifying liver iron load

Objective

To summarize the research progress of magnetic resonance imaging (MRI) in quantifying liver iron load.

Methods

To summarize the current status and progress of MRI technology in the quantitative study of liver iron load through reviewing the relevant literature at home and abroad.

Results

Different MRI sequence examination techniques have formed a series of non-invasive methods for the examination of liver iron load. These techniques have important clinical significance in the imaging diagnosis of liver iron load. So far, the main MRI methods used to assess liver iron load are: signal intensity measurement method (signal intensity, SI) [signal intensity ratio (SIR) and difference in in-phase and out-of-phase signal intensity], T2/R2 measurement (such as FerriScan technique), ultra-short echo time (UTE) imaging technique, and susceptibility weighted imaging (including conventional susceptibility weighted imaging) (SWI), quantitative susceptibility mapping (QSM), T2*/R2* measurement, Dixon and its derivative techniques.

Conclusion

MRI has become the first choice for the non-invasive examination of liver iron overload, and it is helpful to improve the early detection of liver injury, liver fibrosis, liver cirrhosis and liver cancer caused by liver iron overload.

A short-TR single-echo spin-echo breath-hold method for assessing liver T2

OBJECTIVE

Conventional single-echo spin-echo T2 mapping used for liver iron quantification is too long for breath-holding. This study investigated a short TR (~100 ms) single-echo spin-echo T2 mapping technique wherein each image (corresponding to a single TE) could be acquired in ~17 s-short enough for a breath-hold. TE images were combined for T2 fitting. To avoid T1 bias, each TE acquisition incremented TR to maintain a constant TR-TE.

MATERIALS AND METHODS

Experiments at 1.5T validated the technique's accuracy in phantoms, 9 healthy volunteers, and 5 iron overload patients. In phantoms and healthy volunteers, the technique was compared to the conventional approach of constant TR for all TEs. Iron overload results were compared to FerriScan.

RESULTS

In phantoms, the constant TR-TE technique provided unbiased estimates of T2, while the conventional constant TR approach underestimated it. In healthy volunteers, there was no significant discrepancy at the 95% confidence level between constant TR-TE and reference T2 values, whereas there was for constant TR scans. In iron overload patients, there was a high correlation between constant TR-TE and FerriScan T2 values (r2 = 0.95), with a discrepancy of 0.6+/- 1.4 ms.

DISCUSSION

The short-TR single-echo breath-hold spin-echo technique provided unbiased estimates of T2 in phantoms and livers.

A latent code based multi-variable modulation network for susceptibility mapping

Quantitative susceptibility mapping (QSM) is a technique for obtaining quantitative information on tissue susceptibility and has shown promising potential for clinical applications, in which the magnetic susceptibility is calculated by solving an ill-posed inverse problem. Recently, deep learning-based methods are proposed to address this issue, but the diversity of data distribution was not well considered, and thus the model generalization is limited in clinical applications. In this paper, we propose a Latent Code based Multi-Variable modulation network for QSM reconstruction (LCMnet). Particularly, a specific modulation module is exploited to incorporate three variables, i.e., field map, magnitude image, and initial susceptibility. The latent code in the modulated convolution is learned from feature maps of the field data using the encoder-decoder framework. The susceptibility map pre-estimated from simple thresholding is the constant input of the module, thereby enhancing the network stability and accelerating training convergence. As another input, multi-level features generated by a cross-fusion block integrate the information of field and magnitude data effectively. Experimental results on in vivo human brain data, challenge data, clinical data and synthetic data demonstrate that the proposed method LCMnet can achieve outstanding performance on accurate susceptibility measurement and also excellent generalization.

Magnetic susceptibility and R2*-based texture analysis for evaluating liver fibrosis in chronic liver disease

PURPOSE

To explore potential feasibility of texture features in magnetic susceptibility and R2* maps for evaluating liver fibrosis.

METHODS

Thirty-one patients (median age 46 years; 22 male) with chronic liver disease were prospectively recruited and underwent magnetic resonance imaging (MRI), blood tests, and liver biopsy. Susceptibility and R2* maps were obtained using a 3-dimensional volumetric interpolated breath-hold examination sequence with a 3T MRI scanner. Texture features, including histogram, gray-level co-occurrence matrix (GLCM), gray-level dependence matrix (GLDM), gray-level run length matrix (GLRLM), gray-level size zone matrix (GLSZM), and neighboring gray tone difference matrix (NGTDM) features, were extracted. Texture features and blood test results of non-significant (Ishak-F < 3) and significant fibrosis patients (Ishak-F ≥ 3) were compared, and correlations with Ishak-F stages were analyzed. Areas under the curve (AUCs) were calculated to determine the efficacy for evaluating liver fibrosis.

RESULTS

Nine texture features of susceptibility maps and 19 features of R2* maps were significantly different between non-significant and significant fibrosis groups (all P < 0.05). Large dependence high gray-level emphasis (LDHGLE) of GLDM and long run high gray-level emphasis (LRHGLE) of GLRLM in R2* maps showed significantly negative and good correlations with Ishak-F stages (r = -0.616, P < 0.001; r = -0.637, P < 0.001). Busyness (NGTDM) in susceptibility maps, LDHGLE of GLDM and LRHGLE of GLRLM in R2* maps yield the highest AUCs (AUC = 0.786, P = 0.007; AUC = 0.807, P = 0.004; AUC = 0.819, P = 0.003).

CONCLUSION

Texture characteristics of susceptibility and R2* maps revealed possible staging values for liver fibrosis. Susceptibility and R2*-based texture analysis may be a useful and noninvasive method for staging liver fibrosis.

Free-breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction

PURPOSE

To enable free-breathing and high isotropic resolution liver quantitative susceptibility mapping (QSM) using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction.

METHODS

Using 3D multi-echo UTE cones MRI, a respiratory motion was estimated from the k-space center of the imaging data. After sorting the k-space data with estimated motion, respiratory motion state-resolved reconstruction was performed for multi-echo data followed by nonlinear least-squares fitting for proton density fat fraction (PDFF),R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , and fat-corrected B0 field maps. PDFF and B0 field maps were subsequently used for QSM reconstruction. The proposed method was compared with motion-averaged (gridding) reconstruction and conventional 3D multi-echo Cartesian MRI in moving gadolinium phantom and in vivo studies. Region of interest (ROI)-based linear regression analysis was performed on these methods to investigate correlations between gadolinium concentration and QSM in the phantom study and betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM in in vivo study.

RESULTS

Cones with motion-resolved reconstruction showed sharper image quality compared to motion-averaged reconstruction with a substantial reduction of motion artifacts in both moving phantom and in vivo studies. For ROI-based linear regression analysis of the phantom study, susceptibility values from cones with motion-resolved reconstruction (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.31 × gadolinium mM + $$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.05,R 2 $$ {R}^2 $$  = 0.999) and Cartesian without motion (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.32× gadolinium mM + $$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.04,R 2 $$ {R}^2 $$  = 1.000) showed linear relationships with gadolinium concentrations and showed good agreement with each other. For in vivo, motion-resolved reconstruction showed higher goodness of fit (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.00261 × R 2 s - 1 * - $$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.524,R 2 $$ {R}^2 $$  = 0.977) compared to motion-averaged reconstruction (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.0021 × R 2 s - 1 * - $$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.572,R 2 $$ {R}^2 $$ = 0.723) in ROI-based linear regression analysis betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM.

CONCLUSION

Feasibility of free-breathing liver QSM was demonstrated with motion-resolved 3D multi-echo UTE cones MRI, achieving high isotropic resolution currently unachievable in conventional Cartesian MRI.

Robust breast quantitative susceptibility mapping in the presence of silicone

PURPOSE

To (a) develop a preconditioned water-fat-silicone total field inversion (wfsTFI) algorithm that directly estimates the susceptibility map from complex multi-echo data in the breast in the presence of silicone and to (b) evaluate the performance of wfsTFI for breast quantitative susceptibility mapping (QSM) in silico and in vivo in comparison with formerly proposed methods.

METHODS

Numerical simulations and in vivo multi-echo gradient echo breast measurements were performed to compare wfsTFI to a previously proposed field map-based linear total field inversion algorithm (lTFI) with and without the consideration of the chemical shift of silicone in the field map estimation step. Specifically, a simulation based on an in vivo scan and data from five patients were included in the analysis.

RESULTS

In the simulation, wfsTFI is able to significantly decrease the normalized root mean square error from lTFI without (4.46) and with (1.77) the consideration of the chemical shift of silicone to 0.68. Both the in silico and in vivo wfsTFI susceptibility maps show reduced shadowing artifacts in local tissue adjacent to silicone, reduced streaking artifacts and no erroneous single voxels of diamagnetic susceptibility in proximity to silicone.

CONCLUSION

The proposed wfsTFI method can automatically distinguish between subjects with and without silicone. Furthermore wfsTFI accounts for the presence of silicone in the QSM dipole inversion and allows for the robust estimation of susceptibility in proximity to silicone breast implants and hence allows the visualization of structures that would otherwise be dominated by artifacts on susceptibility maps.

Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping

PURPOSE

To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM.

METHODS

An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC). The proposed method was compared to the previously proposed and validated approach in liver QSM for two multi-echo spoiled gradient-recalled echo protocols with different acquisition parameters at 3T. Linear regression was used for evaluation of QSM methods against a reference FDA-approvedR 2 $$ {R}_2 $$ -based LIC measure andR 2 ∗ $$ {R}_2^{\ast } $$ measurements; repeatability/reproducibility were assessed by Bland-Altman analysis.

RESULTS

The data-adaptive method produced susceptibility maps with higher subjective quality due to reduced shading artifacts. For both acquisition protocols, higher linear correlation with bothR 2 $$ {R}_2 $$ - andR 2 ∗ $$ {R}_2^{\ast } $$ -based measurements were observed for the data-adaptive method (r 2 = 0 . 74 / 0 . 69 $$ {r}^2=0.74/0.69 $$ forR 2 $$ {R}_2 $$ ,0 . 97 / 0 . 95 $$ 0.97/0.95 $$ forR 2 ∗ $$ {R}_2^{\ast } $$ ) than the standard method (r 2 = 0 . 60 / 0 . 66 $$ {r}^2=0.60/0.66 $$ and0 . 79 / 0 . 88 $$ 0.79/0.88 $$ ). For both protocols, the data-adaptive method enabled better test-retest repeatability (repeatability coefficients 0.19/0.30 ppm for the data-adaptive method, 0.38/0.47 ppm for the standard method) and reproducibility across protocols (reproducibility coefficient 0.28 vs. 0.53ppm) than the standard method.

CONCLUSIONS

The proposed data-adaptive QSM algorithm may enable quantification of LIC with improved repeatability/reproducibility across different acquisition parameters as 3T.

Quantitative MRI of diffuse liver diseases: techniques and tissue-mimicking phantoms

Quantitative magnetic resonance imaging (MRI) techniques are emerging as non-invasive alternatives to biopsy for assessment of diffuse liver diseases of iron overload, steatosis and fibrosis. For testing and validating the accuracy of these techniques, phantoms are often used as stand-ins to human tissue to mimic diffuse liver pathologies. However, currently, there is no standardization in the preparation of MRI-based liver phantoms for mimicking iron overload, steatosis, fibrosis or a combination of these pathologies as various sizes and types of materials are used to mimic the same liver disease. Liver phantoms that mimic specific MR features of diffuse liver diseases observed in vivo are important for testing and calibrating new MRI techniques and for evaluating signal models to accurately quantify these features. In this study, we review the liver morphology associated with these diffuse diseases, discuss the quantitative MR techniques for assessing these liver pathologies, and comprehensively examine published liver phantom studies and discuss their benefits and limitations.

QSM Throughout the Body

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.

Toward a realistic in silico abdominal phantom for QSM

PURPOSE

QSM outside the brain has recently gained interest, particularly in the abdominal region. However, the absence of reliable ground truths makes difficult to assess reconstruction algorithms, whose quality is already compromised by additional signal contributions from fat, gases, and different kinds of motion. This work presents a realistic in silico phantom for the development, evaluation and comparison of abdominal QSM reconstruction algorithms.

METHODS

Synthetic susceptibility andR 2 * $$ {R}_2^{\ast } $$ maps were generated by segmenting and postprocessing the abdominal 3T MRI data from a healthy volunteer. Susceptibility andR 2 * $$ {R}_2^{\ast } $$ values in different tissues/organs were assigned according to literature and experimental values and were also provided with realistic textures. The signal was simulated using as input the synthetic QSM andR 2 * $$ {R}_2^{\ast } $$ maps and fat contributions. Three susceptibility scenarios and two acquisition protocols were simulated to compare different reconstruction algorithms.

RESULTS

QSM reconstructions show that the phantom allows to identify the main strengths and limitations of the acquisition approaches and reconstruction algorithms, such as in-phase acquisitions, water-fat separation methods, and QSM dipole inversion algorithms.

CONCLUSION

The phantom showed its potential as a ground truth to evaluate and compare reconstruction pipelines and algorithms. The publicly available source code, designed in a modular framework, allows users to easily modify the susceptibility,R 2 * $$ {R}_2^{\ast } $$ and TEs, and thus creates different abdominal scenarios.

Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation

Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.

Validation of liver quantitative susceptibility mapping across imaging parameters at 1.5 T and 3.0 T using SQUID susceptometry as reference

PURPOSE

To validate QSM-based biomagnetic liver susceptometry (BLS) to measure liver iron overload at 1.5 T and 3.0 T using superconducting quantum interference devices (SQUID)-based BLS as reference.

METHODS

Subjects with known or suspected iron overload were recruited for QSM-BLS at 1.5 T and 3.0 T using eight different protocols. SQUID-BLS was also obtained in each subject to provide susceptibility reference. A recent QSM method based on data-adaptive regularization was used to obtain susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps. Measurements of susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were obtained in the right liver lobe. Linear mixed-effects analysis was used to estimate the contribution of specific acquisition parameters to QSM-BLS. Linear regression and Bland-Altman analyses were used to assess the relationship between QSM-BLS and SQUID-BLS/ R 2 * $$ {\mathrm{R}}_2^{\ast } $$ .

RESULTS

Susceptibility maps showed high subjective quality for each acquisition protocol across different iron levels. High linear correlation was observed between QSM-BLS and SQUID-BLS at 1.5 T (r² range, [0.82, 0.84]) and 3.0 T (r² range, [0.77, 0.85]) across different acquisition protocols. QSM-BLS and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were highly correlated at both field strengths (r² range at 1.5 T, [0.94, 0.99]; 3.0 T, [0.93, 0.99]). High correlation (r²  = 0.99) between 1.5 T and 3.0 T QSM-BLS, with narrow reproducibility coefficients (range, [0.13, 0.21] ppm) were observed for each protocol.

CONCLUSION

This work evaluated the feasibility and performance of liver QSM-BLS across iron levels and acquisition protocols at 1.5 T and 3.0 T. High correlation and reproducibility were observed between QSM-BLS and SQUID-BLS across protocols and field strengths. In summary, QSM-BLS may enable reliable and reproducible quantification of liver iron concentration.

On the water-fat in-phase assumption for quantitative susceptibility mapping

PURPOSE

To (a) define multi-peak fat model-based effective in-phase echo times for quantitative susceptibility mapping (QSM) in water-fat regions, (b) analyze the relationship between fat fraction, field map quantification bias and susceptibility bias, and (c) evaluate the susceptibility mapping performance of the proposed effective in-phase echoes in comparison to single-peak in-phase echoes and water-fat separation for regions where both water and fat are present.

METHODS

Effective multipeak in-phase echo times for a bone marrow and a liver fat spectral model were derived from a single voxel simulation. A Monte Carlo simulation was performed to assess the field map estimation error as a function of fat fraction for the different in-phase echoes. Additionally, a phantom scan and in vivo scans in the liver, spine, and breast were performed and evaluated with respect to quantification accuracy.

RESULTS

The use of single-peak in-phase echoes can introduce a worst-case susceptibility bias of 0.43 $$ 0.43 $$  ppm. The use of effective multipeak in-phase echoes shows a similar quantitative performance in the numerical simulation, the phantom and in all in vivo anatomies when compared to water-fat separation-based QSM.

CONCLUSION

QSM based on the proposed effective multipeak in-phase echoes can alleviate the quantification bias present in QSM based on single-peak in-phase echoes. When compared to water-fat separation-based QSM the proposed effective in-phase echo times achieve a similar quantitative performance while drastically reducing the computational expense for field map estimation.

Quantitative susceptibility mapping (QSM) of the cardiovascular system: challenges and perspectives

Quantitative susceptibility mapping (QSM) is a powerful, non-invasive, magnetic resonance imaging (MRI) technique that relies on measurement of magnetic susceptibility. So far, QSM has been employed mostly to study neurological disorders characterized by iron accumulation, such as Parkinson's and Alzheimer's diseases. Nonetheless, QSM allows mapping key indicators of cardiac disease such as blood oxygenation and myocardial iron content. For this reason, the application of QSM offers an unprecedented opportunity to gain a better understanding of the pathophysiological changes associated with cardiovascular disease and to monitor their evolution and response to treatment. Recent studies on cardiovascular QSM have shown the feasibility of a non-invasive assessment of blood oxygenation, myocardial iron content and myocardial fibre orientation, as well as carotid plaque composition. Significant technical challenges remain, the most evident of which are related to cardiac and respiratory motion, blood flow, chemical shift effects and susceptibility artefacts. Significant work is ongoing to overcome these challenges and integrate the QSM technique into clinical practice in the cardiovascular field.

Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications

Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic susceptibility. Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and is a substance-specific value. Recently, QSM has been widely used to estimate various levels of substances in the brain, including iron, hemosiderin, and deoxyhemoglobin (paramagnetism), as well as calcification (diamagnetism). By visualizing iron distribution in the brain, it is possible to identify anatomic structures that are not evident on conventional images and to evaluate various neurodegenerative diseases. It has been challenging to apply QSM in areas outside the brain because of motion artifacts from respiration and heartbeats, as well as the presence of fat, which has a different frequency to the proton. In this review, the authors provide a brief overview of the theoretical background and analyze methods of converting MRI phase images to QSM. Moreover, we provide an overview of the current clinical applications of QSM. Online supplemental material is available for this article. ^©RSNA, 2022.

Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities

Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo. Thereby, QSM can reveal pathological changes of these key components in a variety of diseases. QSM requires multiple processing steps such as phase unwrapping, background field removal and field-to-source inversion. Current state-of-the-art techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and require a careful choice of regularization parameters. With the recent success of deep learning using convolutional neural networks for solving ill-posed reconstruction problems, the QSM community also adapted these techniques and demonstrated that the QSM processing steps can be solved by efficient feed forward multiplications not requiring either iterative optimization or the choice of regularization parameters. Here, we review the current status of deep learning-based approaches for processing QSM, highlighting limitations and potential pitfalls, and discuss the future directions the field may take to exploit the latest advances in deep learning for QSM.

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.

Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction

BACKGROUND

Compared with conventional magnetic resonance imaging methods, the quantitative magnetic susceptibility mapping (QSM) technique can quantitatively measure the magnetic susceptibility distribution of tissues, which has an important clinical application value in the investigations of brain micro-bleeds, Parkinson's, and liver iron deposition, etc. However, the quantitative susceptibility mapping algorithm is an ill-posed inverse problem due to the near-zero value in the dipole kernel, and high-quality QSM reconstruction with effective streaking artifact suppression remains a challenge. In recent years, the performance of sparse representation has been well validated in improving magnetic resonance image (MRI) reconstruction.

METHODS

In this study, by incorporating feature learning into sparse representation, we propose an edge prior guided dictionary learning-based reconstruction method for the dipole inversion in quantitative susceptibility mapping reconstruction. The structure feature dictionary relies on magnitude images for susceptibility maps have similar structures with magnitude images, and this structure feature dictionary and edge prior information are used in the dipole inversion step.

RESULTS

The performance of the proposed algorithm is assessed through in vivo human brain clinical data, leading to high-quality susceptibility maps with improved streaking artifact suppression, structural recovery, and quantitative metrics.

CONCLUSIONS

The proposed edge prior guided dictionary learning method for dipole inversion in QSM achieves improved performance in streaking artifacts suppression, structural recovery and deep gray matter reconstruction.

Comparison of Phase Estimation Methods for Quantitative Susceptibility Mapping Using a Rotating-Tube Phantom

Quantitative Susceptibility Mapping (QSM) is an MRI tool with the potential to reveal pathological changes from magnetic susceptibility measurements. Before phase data can be used to recover susceptibility (Δχ), the QSM process begins with two steps: data acquisition and phase estimation. We assess the performance of these steps, when applied without user intervention, on several variations of a phantom imaging task. We used a rotating-tube phantom with five tubes ranging from Δχ=0.05 ppm to Δχ=0.336 ppm. MRI data was acquired at nine angles of rotation for four different pulse sequences. The images were processed by 10 phase estimation algorithms including Laplacian, region-growing, branch-cut, temporal unwrapping, and maximum-likelihood methods, resulting in approximately 90 different combinations of data acquisition and phase estimation methods. We analyzed errors between measured and expected phases using the probability mass function and Cumulative Distribution Function. Repeatable acquisition and estimation methods were identified based on the probability of relative phase errors. For single-echo GRE and segmented EPI sequences, a region-growing method was most reliable with Pr (relative error <0.1) = 0.95 and 0.90, respectively. For multiecho sequences, a maximum-likelihood method was most reliable with Pr (relative error <0.1) = 0.97. The most repeatable multiecho methods outperformed the most repeatable single-echo methods. We found a wide range of repeatability and reproducibility for off-the-shelf MRI acquisition and phase estimation approaches, and this variability may prevent the techniques from being widely integrated in clinical workflows. The error was dominated in many cases by spatially discontinuous phase unwrapping errors. Any postprocessing applied on erroneous phase estimates, such as QSM's background field removal and dipole inversion, would suffer from error propagation. Our paradigm identifies methods that yield consistent and accurate phase estimates that would ultimately yield consistent and accurate Δχ estimates.

QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping

PURPOSE

Quantitative susceptibility mapping (QSM) estimates the spatial distribution of tissue magnetic susceptibilities from the phase of a gradient-echo signal. QSM algorithms require a signal mask to delineate regions with reliable phase for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artifacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing. Moreover, this method is integrated within an open-source software framework: QSMxT.

METHODS

A robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information and suppressing streaking artifacts.

RESULTS

Compared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artifacts caused by unreliable phase and high dynamic ranges of susceptibility sources. It is also robust across a range of acquisitions at 3 T in volunteers and phantoms, at 7 T in tumor patients, and in an in silico head phantom, with significant artifact and error reductions, greater anatomical detail, and minimal parameter tuning.

CONCLUSION

The two-pass masking and reconstruction procedure separates reliable from less reliable phase regions, enabling a more accurate QSM reconstruction that mitigates artifacts, operates without anatomical priors, and requires minimal parameter tuning. The technique and its integration within QSMxT makes QSM processing more accessible and robust to streaking artifacts.

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.

Gender-specific liver aging and magnetic resonance imaging

The number of imaging studies performed on elderly individuals will increase in the next several decades. It is important to understand normal age-related changes in the structural and functional imaging appearance of the liver. This article highlights a number of liver aging aspects which are particularly relevant to magnetic resonance imaging (MRI). Physiology of aging liver is associated with a reduction in size, in perfusion, and in function. Pulsed echo-Doppler showed substantial reduction of portal flow in elderly subjects, particularly those after the age of 75 years old. An MRI biomarker diffusion derived vessel density (DDVD) demonstrated that liver microperfusion volume in healthy females starts to decrease even before menopause age. Liver fat content and iron content increase with aging, and the change is more substantial in women after menopause. Adult men have higher liver fat and iron contents than women from the start and change less during aging. Nonalcoholic fatty liver disease (NAFLD) is very common among assumed healthy subjects. There is a male predominance of NAFLD from the paediatric population up to fifth decade of life in adults. After the age of 60 years, women overtake their male counterparts in prevalence of NAFLD. Higher liver fat leads to decreased apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM)-D_slow measures. Higher liver iron content shortens T2* measure, lower ADC and IVIM-D_slow measures, increases imaging noises and decreases liver visibility. Young women have high liver T1rho value and then decrease substantially, while liver T1rho in men remains relatively unchanged with aging. In positron emission tomography (PET) studies, aging is associated with an increase of both liver fluorine-18-fluorodeoxyglucose maximum standard uptake and mean standard uptake values.

Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training

PURPOSE

To use a deep neural network (DNN) for solving the optimization problem of water/fat separation and to compare supervised and unsupervised training.

METHODS

The current T 2 ∗ -IDEAL algorithm for solving water/fat separation is dependent on initialization. Recently, DNN has been proposed to solve water/fat separation without the need for suitable initialization. However, this approach requires supervised training of DNN using the reference water/fat separation images. Here we propose 2 novel DNN water/fat separation methods: 1) unsupervised training of DNN (UTD) using the physical forward problem as the cost function during training, and 2) no training of DNN using physical cost and backpropagation to directly reconstruct a single dataset. The supervised training of DNN, unsupervised training of DNN, and no training of DNN methods were compared with the reference T 2 ∗ -IDEAL.

RESULTS

All DNN methods generated consistent water/fat separation results that agreed well with T 2 ∗ -IDEAL under proper initialization.

CONCLUSION

The water/fat separation problem can be solved using unsupervised deep neural networks.

Magnetic resonance quantitative susceptibility mapping in the evaluation of hepatic fibrosis in chronic liver disease: a feasibility study

Background

Noninvasive methods for the early diagnosis and staging of hepatic fibrosis are needed. The present study aimed to investigate the alteration of magnetic susceptibility in the liver of patients with various fibrosis stages and to evaluate the feasibility of using susceptibility to stage hepatic fibrosis.

Methods

A total of 30 consecutive patients with chronic liver diseases (CLDs) underwent magnetic resonance imaging (MRI) and liver biopsy evaluation of hepatic fibrosis, necroinflammatory activity, iron load, and steatosis. Quantitative susceptibility mapping (QSM), R2* and proton density fat fraction (PDFF) images were postprocessed from the same gradient-echo data for quantitative tissue characterization using region of interest (ROI) analysis. The differences for MRI measurements between cohorts of non-significant (Ishak-F <3) and significant fibrosis (Ishak-F ≥3) and the correlation of MRI measurements with fibrosis stages and necroinflammatory activity grades were tested. Receiver operating characteristic (ROC) analysis was also performed.

Results

There was a significant difference in liver susceptibility between the cohorts of significant and non-significant fibrosis (Z=-2.880, P=0.004). A moderate negative correlation between the stages of liver fibrosis and liver susceptibility was observed (r=-0.471, P=0.015). Liver magnetic susceptibility differentiated non-significant from significant hepatic fibrosis with an area under the receiver operating curve (AUC) of 0.836 (P=0.004). A highly sensitive diagnostic performance with an AUC of 0.933 was obtained using magnetic susceptibility and PDFF together (P<0.001).

Conclusions

A noninvasive liver QSM-based evaluation promises an accurate assessment of significant fibrosis in patients with CLDs.

Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload

BACKGROUND

R2*-MRI is clinically used to noninvasively assess hepatic iron content (HIC) to guide potential iron chelation therapy. However, coexisting pathologies, such as fibrosis and steatosis, affect R2* measurements and may thus confound HIC estimations.

PURPOSE

To evaluate whether a multispectral auto regressive moving average (ARMA) model can be used in conjunction with quantitative susceptibility mapping (QSM) to measure magnetic susceptibility as a confounder-free predictor of HIC.

STUDY TYPE

Phantom study and in vivo cohort.

SUBJECTS

Nine iron phantoms covering clinically relevant R2* range (20-1200/second) and 48 patients (22 male, 26 female, median age 18 years).

FIELD STRENGTH/SEQUENCE

Three-dimensional (3D) and two-dimensional (2D) multi-echo gradient echo (GRE) at 1.5 T.

ASSESSMENT

ARMA-QSM modeling was performed on the complex 3D GRE signal to estimate R2*, fat fraction (FF), and susceptibility measurements. R2*-based dry clinical HIC values were calculated from the 2D GRE acquisition using a published R2*-HIC calibration curve as reference standard.

STATISTICAL TESTS

Linear regression analysis was performed to compare ARMA R2* and susceptibility-based estimates to iron concentrations and dry clinical HIC values in phantoms and patients, respectively.

RESULTS

In phantoms, the ARMA R2* and susceptibility values strongly correlated with iron concentrations (R²  ≥ 0.9). In patients, the ARMA R2* values highly correlated (R²  = 0.97) with clinical HIC values with slope = 0.026, and the susceptibility values showed good correlation (R²  = 0.82) with clinical dry HIC values with slope = 3.3 and produced a dry-to-wet HIC ratio of 4.8.

DATA CONCLUSION

This study shows the feasibility that ARMA-QSM can simultaneously estimate susceptibility-based wet HIC, R2*-based dry HIC and FFs from a single multi-echo GRE acquisition. Our results demonstrate that both, R2* and susceptibility-based wet HIC values estimated with ARMA-QSM showed good association with clinical dry HIC values with slopes similar to published R2*-biopsy HIC calibration and dry-to-wet tissue weight ratio, respectively. Hence, our study shows that ARMA-QSM can provide potentially confounder-free assessment of hepatic iron overload.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

[Reproducibility analysis of quantitative susceptibility mapping of cerebral subcortical nuclei in healthy adults]

OBJECTIVE

To investigate the intra- and inter-scanner reproducibility of quantitative susceptibility mapping (QSM) of cerebral subcortical nuclei in healthy adults.

METHODS

QSM was performed in 21 healthy adults on two different 3.0T MR scanners, and the region of interest (ROI) method was used to measure the magnetic susceptibility value of the left subcortical nuclei (the head of the caudate, putamen, globus pallidus, thalamus, substantia nigra and red nucleus). The intraclass correlation coefficient (ICC) and Bland-Altman method were used to evaluate the inter-scanner and intra-scanner reliability.

RESULTS

The ICCs of the susceptibility value ranged from 0.90 to 0.99 for all the subcortical gray nuclei except for the head of the caudate nucleus measured on the same MR scanner by the same observer. Bland-Altman analysis revealed that the points with susceptibility differences for all the subcortical gray nuclei except for substantia nigra located in the 95% CI of limits of agreement for the same MR scanner. The ICCs of the susceptibility value for the inter-scanner was 0.49 (0.08-0.75) for the head of the caudate nuleus, 0.80 (0.57-0.91) for the putamen, 0.77 (0.51-0.90) for the globus pallidus, 0.78 (0.54-0.91) for the thalamus, 0.80 (0.56-0.91) for the substantia nigra and 0.93 (0.83-0.97) for the red nucleus. The points with susceptibility difference (95.2%, 20/21) located in the 95% CI of limits of agreement for the putamen and the thalamus measured on two different MR scanners.

CONCLUSIONS

The intra-scanner reproducibility of QSM of the subcortical gray nuclei is superior to the inter-scanner reproducibility in healthy adults.

Feasibility of quantitative susceptibility mapping (QSM) of the human kidney

Objective

To evaluate the feasibility of in-vivo quantitative susceptibility mapping (QSM) of the human kidney.

Methods

An axial single-breath-hold 3D multi-echo sequence (acquisition time 33 s) was completed on a 3 T-MRI-scanner (Magnetom Prisma, Siemens Healthineers, Erlangen, Germany) in 19 healthy volunteers. Graph-cut-based unwrapping combined with the T₂*-IDEAL approach was performed to remove the chemical shift of fat and to quantify QSM of the upper abdomen. Mean susceptibility values of the entire, renal cortex and medulla in both kidneys and the liver were determined and compared. Five subjects were measured twice to examine the reproducibility. One patient with severe renal fibrosis was included in the study to evaluate the potential clinical relevance of QSM.

Results

QSM was successful in 17 volunteers and the patient with renal fibrosis. Anatomical structures in the abdomen were clearly distinguishable by QSM and the susceptibility values obtained in the liver were comparable to those found in the literature. The results showed a good reproducibility. Besides, the mean renal QSM values obtained in healthy volunteers (0.04 ± 0.07 ppm for the right and − 0.06 ± 0.19 ppm for the left kidney) were substantially higher than that measured in the investigated fibrotic kidney (− 0.43 ± − 0.02 ppm).

Conclusion

QSM of the human kidney could be a promising approach for the assessment of information about microscopic renal tissue structure. Therefore, it might further improve functional renal MR imaging.

Electronic supplementary material

The online version of this article (10.1007/s10334-020-00895-9) contains supplementary material, which is available to authorized users.

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.

R1ρ at high spin-lock frequency could be a complementary imaging biomarker for liver iron overload quantification

PURPOSE

To compare the correlations among the R1ρ, R2, and R2* relaxation rates with liver iron concentration (LIC) in the assessment of rat liver iron content and explore the application potential of R1ρ in assessing liver iron content.

METHODS

Iron dextran (dosage of 0, 25, 50, 100, and 200 mg/kg body weight) was injected into 35 male rats to increase the amount of iron storage in the liver. After one week, all rats were euthanized with isoflurane. A portion of the largest hepatic lobe was extracted to quantify the LIC by inductively coupled plasma, and the remaining liver tissue was stored in 4% buffered paraformaldehyde for 24 h before MRI. Spin-lock preparation with a RARE (rapid acquisition with relaxation enhancement) readout (9 different spin-lock times and 7 different spin-lock frequencies (FSLs)) and multi-echo UTE (ultrashort TE) pulses were developed to quantify R1ρ and R2 * on a Bruker 11.7 T MR system. For comparisons with R1ρ and R2*, R2 was acquired using the CPMG sequence.

RESULTS

Mean R1ρ values displayed dispersion, with decrease in R1ρ at higher FSLs. Spearman's correlation analysis (two-tailed) indicated that the R1ρ values were significantly associated with LIC at FSL = 2000, 2500, and 3000 Hz (r = 0.365 and P = 0.031, r = 0.608 and P < 0.001, and r = 0.764 and P < 0.001, respectively), and were not significantly associated with LIC at FSL = 500, 1000, 1250, and 1500 Hz (all P > 0.05). R2 and R2* showed significant linear correlations with LIC (r = 0.787 and P < 0.001, and r = 0.859 and P < 0.001, respectively). Correlation analysis across R1ρ, R2, and R* also suggested that the correlation strength between R1ρ and R2 and between R1ρ and R* showed an increasing trend with increase in FSL.

CONCLUSION

In this study, a strong association was observed between R1ρ and LIC at high FSLs further confirming previous findings. The results demonstrated that R1ρ at high FSL might serve as a complementary imaging biomarker for liver iron overload quantification.

Diffusion-regularized susceptibility tensor imaging (DRSTI) of tissue microstructures in the human brain

Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.

Feasibility of QSM in the human placenta

PURPOSE

Quantitative susceptibility mapping (QSM) is an emerging tool for the precise characterization of human tissue, including regional oxygenation. A critical function of the human placenta is oxygen transfer to the developing fetus, which remains difficult to study in utero. The purpose of this study is to investigate the feasibility of performing QSM in the human placenta in utero.

METHODS

In healthy pregnant women, 3D gradient echo data of the placenta were acquired with prospective respiratory gating at 1.5 Tesla and 3 Tesla. A brief period (6-7 min) of maternal hyperoxia was induced to increase placental oxygenation in a subset of women scanned at 3 Tesla, and data were acquired before and during oxygen administration. Susceptibility and T 2 ∗ / R 2 ∗ maps were reconstructed from gradient echo data, and mean and SD of these measures within the whole placenta were calculated.

RESULTS

A total of 54 women were studied at a mean gestational age of 30.7 ± 4.2 (range: 24 5/7-38 4/7) weeks. Susceptibility and T 2 ∗ maps demonstrated lobular contrast reflecting regional oxygenation difference at both field strengths. SD of susceptibilities, mean R 2 ∗ , and SD of R 2 ∗ of the placenta showed a linear relationship with gestational age (P < .01 for all). These measures were also responsive to maternal hyperoxia, and there was an increasing response with advancing gestational age (P < .01 for all).

CONCLUSION

This study demonstrates the feasibility of performing placental QSM in pregnant women and supports the potential for placental QSM to provide noninvasive in vivo assessment of placental oxygenation.

Decreasing iron susceptibility with temperature in quantitative susceptibility mapping: A phantom study

To clarify the temperature dependence of susceptibility estimated by quantitative susceptibility mapping (QSM) analysis, we investigated the relationship between temperature and susceptibility using a cylinder phantom with varying temperatures. Six solutions with various concentrations of superparamagnetic iron oxide (SPIO) nanoparticles were employed. These tubes were placed in a cylinder phantom and surrounded with water. The temperature of the circulated water was adjusted to change the temperature in the cylinder phantom from 25.8 °C to 42.5 °C. The cylinder phantom was scanned via a three-dimensional multiple spoiled gradient-echo sequence for R2* and QSM analyses with varying temperatures. The relationships between temperature, susceptibility, and R2* values were determined. Moreover, the temperature coefficients of susceptibility (χ-Tc) and (R2*-Tc) were calculated at each concentration and the linearities in these indices against each SPIO concentration were validated. Significant inverse correlations were found between temperature, susceptibility, and R2* values at each SPIO concentration due to the decrease in paramagnetic iron susceptibility that occurred with increasing temperature based on Curie's law. Moreover, although there were significant correlations between the susceptibility and R2* values at any temperature, the slopes of the regression lines grew in height with greater temperatures. The percentage of difference per Celsius degree in susceptibility in any SPIO concentration was lower than the corresponding finding among the R2* results. There were strong linearities between the SPIO concentration, χ-Tc (r = -0.994; p < 0.001), and R2*-Tc (r = -0.998; p < 0.001). The χ-Tc and R2*-Tc outcomes in a particular voxel varied considerably with the iron contents. Although there was an inverse correlation noted between temperature and susceptibility, the susceptibility analysis showed smaller temperature dependence relative to the R2* analysis. QSM analysis might be a more suitable option for magnetic resonance-based iron quantification in comparison with R2* relaxometry.

Complex confounder-corrected R2* mapping for liver iron quantification with MRI

OBJECTIVES

MRI-based R2* mapping may enable reliable and rapid quantification of liver iron concentration (LIC). However, the performance and reproducibility of R2* across acquisition protocols remain unknown. Therefore, the objective of this work was to evaluate the performance and reproducibility of complex confounder-corrected R2* across acquisition protocols, at both 1.5 T and 3.0 T.

METHODS

In this prospective study, 40 patients with suspected iron overload and 10 healthy controls were recruited with IRB approval and informed written consent and imaged at both 1.5 T and 3.0 T. For each subject, acquisitions included four different R2* mapping protocols at each field strength, and an FDA-approved R2-based method performed at 1.5 T as a reference for LIC. R2* maps were reconstructed from the complex data acquisitions including correction for noise effects and fat signal. For each subject, field strength, and R2* acquisition, R2* measurements were performed in each of the nine liver Couinaud segments and the spleen. R2* measurements were compared across protocols and field strength (1.5 T and 3.0 T), and R2* was calibrated to LIC for each acquisition and field strength.

RESULTS

R2* demonstrated high reproducibility across acquisition protocols (p > 0.05 for 96/108 pairwise comparisons across 2 field strengths and 9 liver segments, ICC > 0.91 for each field strength/segment combination) and high predictive ability (AUC > 0.95 for four clinically relevant LIC thresholds). Calibration of R2* to LIC was LIC = - 0.04 + 2.62 × 10^-2 R2* at 1.5 T and LIC = 0.00 + 1.41 × 10^-2 R2* at 3.0 T.

CONCLUSIONS

Complex confounder-corrected R2* mapping enables LIC quantification with high reproducibility across acquisition protocols, at both 1.5 T and 3.0 T.

KEY POINTS

• Confounder-corrected R2* of the liver provides reproducible R2* across acquisition protocols, including different spatial resolutions, echo times, and slice orientations, at both 1.5 T and 3.0 T. • For all acquisition protocols, high correlation with R2-based liver iron concentration (LIC) quantification was observed. • The calibration between confounder-corrected R2* and LIC, at both 1.5 T and 3.0 T, is determined in this study.

A geometric approach to separate the effects of magnetic susceptibility and chemical shift/exchange in a phantom with isotropic magnetic susceptibility

PURPOSE

To separate the effects of magnetic susceptibility and chemical shift/exchange in a phantom with isotropic magnetic susceptibility, and to generate a chemical shift/exchange-corrected QSM result.

METHODS

Magnetic susceptibility and chemical shift/exchange are the properties of a material. Both are known to induce the resonance frequency shift in MRI. In current QSM, the susceptibility is reconstructed from the frequency shift, ignoring the contribution of the chemical shift/exchange. In this work, a simple geometric approach, which averages the frequency shift maps from three orthogonal B₀ directions to generate a chemical shift/exchange map, is developed using the fact that the average nullifies the (isotropic) susceptibility effects. The resulting chemical shift/exchange map is subtracted from the total frequency shift, producing a frequency shift map solely from susceptibility. Finally, this frequency shift map is reconstructed to a susceptibility map using a QSM algorithm. The proposed method is validated in numerical simulations and applied to phantom experiments with olive oil, bovine serum albumin, ferritin, and iron oxide solutions.

RESULTS

Both simulations and experiments confirm that the method successfully separates the contributions of the susceptibility and chemical shift/exchange, reporting the susceptibility and chemical shift/exchange of olive oil (susceptibility: 0.62 ppm, chemical shift: -3.60 ppm), bovine serum albumin (susceptibility: -0.059 ppm, chemical shift: 0.008 ppm), ferritin (susceptibility: 0.125 ppm, chemical shift: -0.005 ppm), and iron oxide (susceptibility: 0.30 ppm, chemical shift: -0.039 ppm) solutions.

CONCLUSION

The proposed method successfully separates the susceptibility and chemical shift/exchange in phantoms with isotropic magnetic susceptibility.

Sensitivity of quantitative relaxometry and susceptibility mapping to microscopic iron distribution

PURPOSE

Determine the impact of the microscopic spatial distribution of iron on relaxometry and susceptibility-based estimates of iron concentration.

METHODS

Monte Carlo simulations and in vitro experiments of erythrocytes were used to create different microscopic distributions of iron. Measuring iron with intact erythrocyte cells created a heterogeneous distribution of iron, whereas lysing erythrocytes was used to create a homogeneous distribution of iron. Multi-echo spin echo and spoiled gradient echo acquisitions were then used to estimate relaxation parameters ( R 2 and R 2 * ) and susceptibility.

RESULTS

Simulations demonstrate that R 2 and R 2 * measurements depend on the spatial distribution of iron even for the same iron concentration and volume susceptibility. Similarly, in vitro experiments demonstrate that R 2 and R 2 * measurements depend on the microscopic spatial distribution of iron whereas the quantitative susceptibility mapping (QSM) susceptibility estimates reflect iron concentration without sensitivity to spatial distribution.

CONCLUSIONS

R 2 and R 2 * for iron quantification depend on the spatial distribution or iron. QSM-based estimation of iron concentration is insensitive to the microscopic spatial distribution of iron, potentially providing a distribution independent measure of iron concentration.

Quantitative ferumoxytol-enhanced MRI in pregnancy: A feasibility study in the nonhuman primate

OBJECTIVES

To assess the feasibility of ferumoxytol-enhanced MRI in pregnancy with a nonhuman primate model.

MATERIALS AND METHODS

In this prospective study, eleven pregnant rhesus macaques at day 98 ± 5 of gestation were divided into three groups, untreated control (UC) (n = 3), saline control (SC) (n = 4) and interleukin 1 beta (IL-1β) treated (IT) (n = 4), which were administered with either saline or IL-1β into the amniotic fluid. All animals were imaged at multiple time points before and after ferumoxytol administration (4 mg/kg). Longitudinal R2* and susceptibility of tissues were obtained using region-of-interest analysis and the longitudinal changes were assessed using linear mixed models and Student's t-test.

RESULTS

In fetuses, a slope of 0.3 s-1/day (P = 0.008), 0.00 ppm/day (P = 0.699) and - 0.2 s-1/day (P = 0.023) was observed in liver R2*, liver susceptibility, and lung R2*, respectively. In placentas, R2* and susceptibility increased immediately after ferumoxytol administration (P < 0.001) and decreased to baseline within two days. The mean change from baseline showed no significant difference between the SC group and the IT group at all scan time points. In maternal livers, R2* increased immediately after ferumoxytol administration, further increased at one-day, and then decreased but remained elevated (P < 0.001). The mean change from baseline showed no significant difference between the SC group and the IT group at all scan time points.

CONCLUSIONS

This work demonstrates the feasibility of quantitative ferumoxytol-enhanced MRI to measure dynamics of ferumoxytol delivery and washout in the placenta. Stable MRI measurements indicated no evidence of iron deposition in fetal tissues of nonhuman primates after maternal ferumoxytol exposure.

Constraints in estimating the proton density fat fraction

The study evaluates four physically motivated constraints in the estimation of the proton density fat fraction (PDFF). Least squares approaches were developed for constraining the parameters in PDFF quantification based on the physics of magnetic resonance imaging. These were smooth fieldmap, smooth initial phase, nonnegative proton density and moderate R₂^∗ values. The constraints were evaluated in terms of their influence on the bias and standard deviation of the estimated parameters using numerical simulations and in vivo data acquired at 0.35 T. Results show that unconstrained least squares estimation is noisy and biased and that constraints can be effective at reducing both the standard deviation and bias.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

Quantitative susceptibility mapping of the spine using in-phase echoes to initialize inhomogeneous field and R2* for the nonconvex optimization problem of fat-water separation

Quantitative susceptibility mapping (QSM) of human spinal vertebrae from a multi-echo gradient-echo (GRE) sequence is challenging, because comparable amounts of fat and water in the vertebrae make it difficult to solve the nonconvex optimization problem of fat-water separation (R2*-IDEAL) for estimating the magnetic field induced by tissue susceptibility. We present an in-phase (IP) echo initialization of R2*-IDEAL for QSM in the spinal vertebrae. Ten healthy human subjects were recruited for spine MRI. A 3D multi-echo GRE sequence was implemented to acquire out-phase and IP echoes. For the IP method, the R2* and field maps estimated by separately fitting the magnitude and phase of IP echoes were used to initialize gradient search R2*-IDEAL to obtain final R2*, field, water, and fat maps, and the final field map was used to generate QSM. The IP method was compared with the existing Zero method (initializing the field to zero), VARPRO-GC (variable projection using graphcuts but still initializing the field to zero), and SPURS (simultaneous phase unwrapping and removal of chemical shift using graphcuts for initialization) on both simulation and in vivo data. The single peak fat model was also compared with the multi-peak fat model. There was no substantial difference on QSM between the single peak and multi-peak fat models, but there were marked differences among different initialization methods. The simulations demonstrated that IP provided the lowest error in the field map. Compared to Zero, VARPRO-GC and SPURS, the proposed IP method provided substantially improved spine QSM in all 10 subjects.

Susceptibility based multiparametric quantification of liver disease: Non-invasive evaluation of steatosis and iron overload

PURPOSE

To evaluate if single-voxel MR spectroscopy (MRS) of iron and fat correlates with biopsy results of hepatic steatosis and iron overload, and to compare MR-measurements with room-temperature susceptometer (RTS), ultrasound, controlled attenuation parameter (CAP) and serum ferritin.

MATERIAL AND METHODS

In this prospective study, a set of 42 patients out of 47 screened patients with several chronic liver diseases underwent MRI-examination at 1.5 T including R2-measurements by single-voxel high-speed T2-corrected multiecho spectroscopy, additional liver biopsy, abdominal ultrasound, CAP, and RTS. Routine blood and serum parameters were determined, including ferritin. Atomic absorption spectroscopy (AAS) and histologically confirmed extent of hepatic steatosis from liver biopsy were used as reference standard. For correlation of R2, RTS, CAP, ferritin, and ultrasound with results of AAS and histologically determined fat fraction of liver biopsy specimen, Spearman's and Pearson's correlation as well as receiver operating characteristics curve (ROC) analysis with cut-off values determined by maximizing Youden index was used.

RESULTS

MRS iron assessment correlated best with AAS, with a Pearson correlation coefficient of 0.715 (p < 0.001), followed by RTS 0.520 (p < 0.001), and serum ferritin 0.213 (p = 0.088, not significant). MRS fat quantification correlated best with the histological confirmed extent of steatosis hepatis with a Spearman correlation coefficient of 0.836 (p < 0.001), followed by CAP 0.604 (p < 0.001) and sonographically diagnosed steatosis 0.358 (p = 0.013).

CONCLUSION

MRS by T2-corrected multiecho single-voxel spectroscopy correlated best with histological results of hepatic fat and iron content compared to RTS, CAP, abdominal ultrasound, and ferritin. Non-invasive methods to assess hepatic fat and iron are of clinical interest for follow-up examinations of patients with chronic liver diseases, where repeated biopsy is not indicated.

Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging

Quantitative Susceptibility Mapping (QSM) and Susceptibility Weighted Imaging (SWI) are MRI techniques that measure and display differences in the magnetization that is induced in tissues, i.e. their magnetic susceptibility, when placed in the strong external magnetic field of an MRI system. SWI produces images in which the contrast is heavily weighted by the intrinsic tissue magnetic susceptibility. It has been applied in a wide range of clinical applications. QSM is a further advancement of this technique that requires sophisticated post-processing in order to provide quantitative maps of tissue susceptibility. This review explains the steps involved in both SWI and QSM as well as describing some of their uses in both clinical and research applications.

Evaluation of a motion-robust 2D chemical shift-encoded technique for R2* and field map quantification in ferumoxytol-enhanced MRI of the placenta in pregnant rhesus macaques

BACKGROUND

3D chemical shift-encoded (CSE)-MRI techniques enable assessment of ferumoxytol concentration but are unreliable in the presence of motion.

PURPOSE

To evaluate a motion-robust 2D-sequential CSE-MRI for R2* and B0 mapping in ferumoxytol-enhanced MRI of the placenta.

STUDY TYPE

Prospective.

ANIMAL MODEL

Pregnant rhesus macaques.

FIELD STRENGTH/SEQUENCE

3.0T/CSE-MRI.

ASSESSMENT

2D-sequential CSE-MRI was compared with 3D respiratory-gated CSE-MRI in placental imaging of 11 anesthetized animals at multiple timepoints before and after ferumoxytol administration, and in ferumoxytol phantoms (0 μg/mL-440 μg/mL). Motion artifacts of CSE-MRI in 10 pregnant women without ferumoxytol administration were assessed retrospectively by three blinded readers (4-point Likert scale). The repeatability of CSE-MRI in seven pregnant women was also prospectively studied.

STATISTICAL TESTS

Placental R2* and boundary B0 field measurements (ΔB0) were compared between 2D-sequential and 3D respiratory-gated CSE-MRI using linear regression and Bland-Altman analysis.

RESULTS

In phantoms, a slope of 0.94 (r² = 0.99, concordance correlation coefficient ρ = 0.99), and bias of -4.8 s^-1 (limit of agreement [LOA], -41.4 s^-1 , +31.8 s^-1 ) in R2*, and a slope of 1.07 (r² = 1.00, ρ = 0.99) and bias of 11.4 Hz (LOA -12.0 Hz, +34.8 Hz) in ΔB0 were obtained in 2D CSE-MRI compared with 3D CSE-MRI for reference R2* ≤390 s^-1 . In animals, a slope of 0.92 (r² = 0.97, ρ = 0.98) and bias of -2.2 s^-1 (LOA -55.6 s^-1 , +51.3 s^-1 ) in R2*, and a slope of 1.05 (r² = 0.95, ρ = 0.97) and bias of 0.4 Hz (LOA -9.0 Hz, +9.7 Hz) in ΔB0 were obtained. In humans, motion-impaired R2* maps in 3D CSE-MRI (Reader 1: 1.8 ± 0.6, Reader 2: 1.3 ± 0.7, Reader 3: 1.9 ± 0.6), while 2D CSE-MRI was motion-free (Reader 1: 2.9 ± 0.3, Reader 2: 3.0 ± 0, Reader 3: 3.0 ± 0). A mean difference of 0.66 s^-1 and coefficient of repeatability of 9.48 s^-1 for placental R2* were observed in the repeated 2D CSE-MRI.

DATA CONCLUSION

2D-sequential CSE-MRI provides accurate R2* and B0 measurements in ferumoxytol-enhanced placental MRI of animals in the presence of respiratory motion, and motion-robustness in human placental imaging.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:580-592.

SHARQnet - Sophisticated harmonic artifact reduction in quantitative susceptibility mapping using a deep convolutional neural network

Quantitative susceptibility mapping (QSM) reveals pathological changes in widespread diseases such as Parkinson's disease, Multiple Sclerosis, or hepatic iron overload. QSM requires multiple processing steps after the acquisition of magnetic resonance imaging (MRI) phase measurements such as unwrapping, background field removal and the solution of an ill-posed field-to-source-inversion. Current techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and lead to suboptimal or over-regularized solutions requiring a careful choice of parameters that make a clinical application of QSM challenging. We have previously demonstrated that a deep convolutional neural network can invert the magnetic dipole kernel with a very efficient feed forward multiplication not requiring iterative optimization or the choice of regularization parameters. In this work, we extended this approach to remove background fields in QSM. The prototype method, called SHARQnet, was trained on simulated background fields and tested on 3T and 7T brain datasets. We show that SHARQnet outperforms current background field removal procedures and generalizes to a wide range of input data without requiring any parameter adjustments. In summary, we demonstrate that the solution of ill-posed problems in QSM can be achieved by learning the underlying physics causing the artifacts and removing them in an efficient and reliable manner and thereby will help to bring QSM towards clinical applications.