Phase-corrected bipolar gradients in multi-echo gradient-echo sequences for quantitative susceptibility mapping

Res-Net-Based Modeling and Morphologic Analysis of Deep Medullary Veins Using Multi-Echo GRE at 7 T MRI

The pathological changes in deep medullary veins (DMVs) have been reported in various diseases. However, accurate modeling and quantification of DMVs remain challenging. We aim to propose and assess an automated approach for modeling and quantifying DMVs at 7 Tesla (7 T) MRI. A multi-echo-input Res-Net was developed for vascular segmentation, and a minimum path loss function was used for modeling and quantifying the geometric parameter of DMVs. Twenty-one patients diagnosed as subcortical vascular dementia (SVaD) and 20 condition matched controls were included in this study. The amplitude and phase images of gradient echo with five echoes were acquired at 7 T. Ten GRE images were manually labeled by two neurologists and compared with the results obtained by our proposed method. Independent samples t test and Pearson correlation were used for statistical analysis in our study, and p value < 0.05 was considered significant. No significant offset was found in centerlines obtained by human labeling and our algorithm (p = 0.734). The length difference between the proposed method and manual labeling was smaller than the error between different clinicians (p < 0.001). Patients with SVaD exhibited fewer DMVs (mean difference = -60.710 ± 21.810, p = 0.011) and higher curvature (mean difference = 0.12 ± 0.022, p < 0.0001), corresponding to their higher Vascular Dementia Assessment Scale-Cog (VaDAS-Cog) scores (mean difference = 4.332 ± 1.992, p = 0.036) and lower Mini-Mental State Examination (MMSE) (mean difference = -3.071 ± 1.443, p = 0.047). The MMSE scores were positively correlated with the numbers of DMVs (r = 0.437, p = 0.037) and were negatively correlated with the curvature (r = -0.426, p = 0.042). In summary, we proposed a novel framework for automated quantifying the morphologic parameters of DMVs. These characteristics of DMVs are expected to help the research and diagnosis of cerebral small vessel diseases with DMV lesions.

Trajectory correction enables free-running chemical shift encoded imaging for accurate cardiac proton-density fat fraction quantification at 3T

BACKGROUND

Metabolic diseases can negatively alter epicardial fat accumulation and composition, which can be probed using quantitative cardiac chemical shift encoded (CSE) cardiovascular magnetic resonance (CMR) by mapping proton-density fat fraction (PDFF). To obtain motion-resolved high-resolution PDFF maps, we proposed a free-running cardiac CSE-CMR framework at 3T. To employ faster bipolar readout gradients, a correction for gradient imperfections was added using the gradient impulse response function (GIRF) and evaluated on intermediate images and PDFF quantification.

METHODS

Ten minutes free-running cardiac 3D radial CSE-CMR acquisitions were compared in vitro and in vivo at 3T. Monopolar and bipolar readout gradient schemes provided 8 echoes (TE1/ΔTE = 1.16/1.96 ms) and 13 echoes (TE1/ΔTE = 1.12/1.07 ms), respectively. Bipolar-gradient free-running cardiac fat and water images and PDFF maps were reconstructed with or without GIRF correction. PDFF values were evaluated in silico, in vitro on a fat/water phantom, and in vivo in 10 healthy volunteers and 3 diabetic patients.

RESULTS

In monopolar mode, fat-water swaps were demonstrated in silico and confirmed in vitro. Using bipolar readout gradients, PDFF quantification was reliable and accurate with GIRF correction with a mean bias of 0.03% in silico and 0.36% in vitro while it suffered from artifacts without correction, leading to a PDFF bias of 4.9% in vitro and swaps in vivo. Using bipolar readout gradients, in vivo PDFF of epicardial adipose tissue was significantly lower compared to subcutaneous fat (80.4 ± 7.1% vs 92.5 ± 4.3%, P < 0.0001).

CONCLUSIONS

Aiming for an accurate PDFF quantification, high-resolution free-running cardiac CSE-MRI imaging proved to benefit from bipolar echoes with k-space trajectory correction at 3T. This free-breathing acquisition framework enables to investigate epicardial adipose tissue PDFF in metabolic diseases.

Feasibility of ultrashort echo time quantitative susceptibility mapping with a 3D cones trajectory in the human brain

Purpose

Quantitative susceptibility mapping (QSM) has surfaced as a promising non-invasive quantitative biomarker that provides information about tissue composition and microenvironment. Recently, ultrashort echo time quantitative susceptibility mapping (UTE-QSM) has been investigated to achieve QSM of short T2 tissues. As the feasibility of UTE-QSM has not been demonstrated in the brain, the goal of this study was to develop a UTE-QSM with an efficient 3D cones trajectory and validate it in the human brain.

Materials and methods

An ultrashort echo time (UTE) cones sequence was implemented in a 3T clinical MRI scanner. Six images were acquired within a single acquisition, including UTE and gradient recalled echo (GRE) images. To achieve QSM, a morphology-enabled dipole inversion (MEDI) algorithm was incorporated, which utilizes both magnitude and phase images. Three fresh cadaveric human brains were scanned using the 3D cones trajectory with eight stretching factors (SFs) ranging from 1.0 to 1.7. In addition, five healthy volunteers were recruited and underwent UTE-QSM to demonstrate the feasibility in vivo. The acquired data were processed with the MEDI-QSM pipeline.

Results

The susceptibility maps estimated by UTE-QSM showed reliable tissue contrast. In the ex vivo experiment, high correlations were found between the baseline (SF of 1.0) and SFs from 1.1 to 1.7 with Pearson's correlations of 0.9983, 0.9968, 0.9959, 0.9960, 0.9954, 0.9943, and 0.9879, respectively (all p-values < 0.05). In the in vivo experiment, the measured QSM values in cortical gray matter, juxtacortical white matter, corpus callosum, caudate, and putamen were 25.4 ± 4.0, -21.8 ± 3.2, -22.6 ± 10.0, 77.5 ± 18.8, and 53.8 ± 7.1 ppb, consistent with the values reported in the literature.

Conclusion

Ultrashort echo time quantitative susceptibility mapping enables direct estimation of the magnetic susceptibility in the brain with a dramatically reduced total scan time by use of a stretched 3D cones trajectory. This technique provides a new biomarker for susceptibility mapping in the in vivo brain.

Automated Segmentation of Midbrain Structures in High-Resolution Susceptibility Maps Based on Convolutional Neural Network and Transfer Learning

Background

Accurate delineation of the midbrain nuclei, the red nucleus (RN), substantia nigra (SN) and subthalamic nucleus (STN), is important in neuroimaging studies of neurodegenerative and other diseases. This study aims to segment midbrain structures in high-resolution susceptibility maps using a method based on a convolutional neural network (CNN).

Methods

The susceptibility maps of 75 subjects were acquired with a voxel size of 0.83 × 0.83 × 0.80 mm³ on a 3T MRI system to distinguish the RN, SN, and STN. A deeply supervised attention U-net was pre-trained with a dataset of 100 subjects containing susceptibility maps with a voxel size of 0.63 × 0.63 × 2.00 mm³ to provide initial weights for the target network. Five-fold cross-validation over the training cohort was used for all the models’ training and selection. The same test cohort was used for the final evaluation of all the models. Dice coefficients were used to assess spatial overlap agreement between manual delineations (ground truth) and automated segmentation. Volume and magnetic susceptibility values in the nuclei extracted with automated CNN delineation were compared to those extracted by manual tracing. Consistencies of volume and magnetic susceptibility values by different extraction strategies were assessed by Pearson correlation coefficients and Bland-Altman analyses.

Results

The automated CNN segmentation method achieved mean Dice scores of 0.903, 0.864, and 0.777 for the RN, SN, and STN, respectively. There were no significant differences between the achieved Dice scores and the inter-rater Dice scores (p > 0.05 for each nucleus). The overall volume and magnetic susceptibility values of the nuclei extracted by the automatic CNN method were significantly correlated with those by manual delineation (p < 0.01).

Conclusion

Midbrain structures can be precisely segmented in high-resolution susceptibility maps using a CNN-based method.

Comparison of MRI methods for measuring whole‐brain oxygen extraction fraction under different geometric conditions at 7T

Background and Purpose

Methods

Results

Conclusion

Noninvasive assessment of steatosis and viability of cold-stored human liver grafts by MRI

PURPOSE

A shortage of suitable donor livers is driving increased use of higher risk livers for transplantation. However, current biomarkers are not sensitive and specific enough to predict posttransplant liver function. This is limiting the expansion of the donor pool. Therefore, better noninvasive tests are required to determine which livers will function following implantation and hence can be safely transplanted. This study assesses the temperature sensitivity of proton density fat fraction and relaxometry parameters and examines their potential for assessment of liver function ex vivo.

METHODS

Six ex vivo human livers were scanned during static cold storage following normothermic machine perfusion. Proton density fat fraction, T1 , T2 , and T 2 ∗ were measured repeatedly during cooling on ice. Temperature corrections were derived from these measurements for the parameters that showed significant variation with temperature.

RESULTS

Strong linear temperature sensitivities were observed for proton density fat fraction (R2 = 0.61, P < .001) and T1 (R2 = 0.78, P < .001). Temperature correction according to a linear model reduced the coefficient of repeatability in these measurements by 41% and 36%, respectively. No temperature dependence was observed in T2 or T 2 ∗ measurements. Comparing livers deemed functional and nonfunctional during normothermic machine perfusion by hemodynamic and biochemical criteria, T1 differed significantly: 516 ± 50 ms for functional versus 679 ± 60 ms for nonfunctional, P = .02.

CONCLUSION

Temperature correction is essential for robust measurement of proton density fat fraction and T1 in cold-stored human livers. These parameters may provide a noninvasive measure of viability for transplantation.

Optimization of quantitative susceptibility mapping for regional estimation of oxygen extraction fraction in the brain

PURPOSE

We sought to determine the degree to which oxygen extraction fraction (OEF) estimated using quantitative susceptibility mapping (QSM) depends on two critical acquisition parameters that have a significant impact on acquisition time: voxel size and final echo time.

METHODS

Four healthy volunteers were imaged using a range of isotropic voxel sizes and final echo times. The 0.7 mm data were downsampled at different stages of QSM processing by a factor of 2 (to 1.4 mm), 3 (2.1 mm), or 4 (2.8 mm) to determine the impact of voxel size on each analysis step. OEF was estimated from 11 veins of varying diameter. Inter- and intra-session repeatability were estimated for the optimal protocol by repeat scanning in 10 participants.

RESULTS

Final echo time was found to have no significant effect on OEF. The effect of voxel size was significant, with larger voxel sizes underestimating OEF, depending on the proximity of the vein to the superficial surface of the brain and on vein diameter. The last analysis step of estimating vein OEF values from susceptibility images had the largest dependency on voxel size. Inter-session coefficients of variation on OEF estimates of between 5.2% and 8.7% are reported, depending on the vein.

CONCLUSION

QSM acquisition times can be minimized by reducing the final echo time but an isotropic voxel size no larger than 1 mm is needed to accurately estimate OEF in most medium/large veins in the brain. Such acquisitions can be achieved in under 4 min.

Superficial white matter imaging: Contrast mechanisms and whole-brain in vivo mapping

Superficial white matter (SWM) contains the most cortico-cortical white matter connections in the human brain encompassing the short U-shaped association fibers. Despite its importance for brain connectivity, very little is known about SWM in humans, mainly due to the lack of noninvasive imaging methods. Here, we lay the groundwork for systematic in vivo SWM mapping using ultrahigh resolution 7 T magnetic resonance imaging. Using biophysical modeling informed by quantitative ion beam microscopy on postmortem brain tissue, we demonstrate that MR contrast in SWM is driven by iron and can be linked to the microscopic iron distribution. Higher SWM iron concentrations were observed in U-fiber-rich frontal, temporal, and parietal areas, potentially reflecting high fiber density or late myelination in these areas. Our SWM mapping approach provides the foundation for systematic studies of interindividual differences, plasticity, and pathologies of this crucial structure for cortico-cortical connectivity in humans.

Rapid automated liver quantitative susceptibility mapping

BACKGROUND

Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC.

PURPOSE

To develop a rapid, robust, and automated liver QSM for clinical practice.

STUDY TYPE

Prospective.

POPULATION

13 healthy subjects and 22 patients.

FIELD STRENGTH/SEQUENCES

1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence.

ASSESSMENT

Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T2 *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22).

STATISTICAL TESTS

IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R2 *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC).

RESULTS

Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T2 *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97).

DATA CONCLUSION

Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.

Magnetic Susceptibility in Normal Brains of Young Adults Based on Quantitative Susceptibility Mapping

OBJECTIVES

To explore the changes of brain susceptibility of different sides and genders in healthy young adults using quantitative susceptibility mapping (QSM).

METHODS

Totally 42 healthy young right-handed adults underwent conventional brain magnetic resonance imaging and QSM scans, and the susceptibility maps were obtained by image post-processing software. Then the regions-of-interest (ROI) of bilateral frontal gray matter (FGM), frontal white matter (FWM), caudate (CA), globus pallidus (GP), putamen (PU), thalamus (TH), substantia nigra (SN), red nucleus (RN), dentate nucleus (DN), pons (PO), and corpus callosum (CC) were manually drawn to obtain magnetic susceptibility on the susceptibility maps. The magnetic susceptibility of each ROI was compared between 2 sides and genders by Wilcoxon rank sum test.

RESULTS

Magnetic susceptibility of bilateral ROI was the highest in GP, followed by SN, and the lowest in FWM. No statistically significant difference was found in susceptibility of bilateral FGM, FWM, CA, GP, PU, TH, SN, RN, DN, PO, or CC. Magnetic susceptibility in CA significantly different genders.

CONCLUSION

Brain magnetic susceptibility measured by QSM can be used to quantitatively assess brain iron concentrations.

Appropriate echo time selection for quantitative susceptibility mapping

The purpose of our study was to clarify the dependence of quantitative susceptibility mapping (QSM) on echo time (TE). We constructed a phantom consisting of six tubes; three tubes were filled with different concentrations (0.5, 1.0, and 2.5 mM) of gadopentetate dimeglumine (Gd-DTPA), and three were filled with different concentrations (100, 200, and 350 mg/mL) of calcium hydroxyapatite. Real and imaginary images from multi-echo spoiled gradient-echo data (12 echoes) were acquired. We then used four datasets with three serial echoes. The QSM procedure consists of four steps: field map estimation, phase unwrapping, background removal, and dipole inversion. For each sample, we compared the measured mean susceptibility value with the theoretical susceptibility value and conducted a linear regression analysis. Accordingly, the relationship between the measured susceptibility and concentration of Gd-DTPA was shown to agree well with the theoretical values (TEs = 16.4, 20.8, and 25.2 ms; slope = 0.24, R² = 1.00). Furthermore, the relationship between the measured susceptibility and concentration of hydroxyapatite also showed good linearity (TEs = 16.4, 20.8, and 25.2 ms; slope = - 0.00121, R² = 1.00). In conclusion, the optimization of the TE in QSM makes it possible to obtain more detailed information regarding the susceptibility of biomaterials.

Hierarchical iterative linear-fitting algorithm (HILA) for phase correction in fat quantification by bipolar multi-echo sequence

Background

Multi-echo gradient echo (GRE) sequence with bipolar readout gradients can reduce achievable echo spacing and thus have higher acquisition efficiency compared to unipolar readout gradients for fat fraction (FF) quantification. However, the eddy current induced phase (EC-phase) in a bipolar sequence corrupts the phase consistency between echoes and can lead to inaccurate fat quantification.

Methods

A hierarchical iterative linear-fitting algorithm (HILA) was proposed for EC-phase correction. In each iteration, image blocks were divided into sub-blocks. The EC-phase was fitted to a linear model in each sub-block. The estimated linear phase in each sub-block was then used as a starting value for the next iteration. Finally, a weighted average over all levels was calculated to obtain the final EC-phase map. Monte Carlo simulations were adopted to evaluate how the residual EC-phase would affect FF quantification accuracy. The performance of the proposed HILA method was then compared to the well-established unipolar acquisition method in phantom and in vivo experiments on 3T.

Results

The simulations showed that certain ΔTE values, such as ΔTE =~0.80/1.50/1.95 ms, allowed for FF estimation that were relatively robust to the residual EC-phase ranging from -2π/15 to 2π/15 for a 6-echo bipolar acquisition on 3T. The phantom study showed that the maximum mean FF error, after EC-phase correction with the proposed HILA method, was smaller than 2%, implying that HILA can approximate the high-order term of the EC-phase through step-wise linear fitting. There was no significant difference between the FFs from bipolar and unipolar acquisitions on the two MR systems in the in vivo experiments.

Conclusions

The proposed HILA method provides a simple and efficient EC-phase correction method for bipolar acquisition without acquiring additional data. The appropriate choice of TEs may further reduce the effect of the residual EC-phase on accurate FF quantification with bipolar readout sequence.

True phase quantitative susceptibility mapping using continuous single-point imaging: a feasibility study

PURPOSE

In this study, we explore the feasibility of a new imaging scheme for quantitative susceptibility mapping (QSM): continuous single-point imaging (CSPI), which uses a pure phase encoding strategy to achieve true phase imaging and improve QSM accuracy.

METHODS

The proposed CSPI is a modification of conventional SPI to allow acquisition of multiple echoes in a single scan. Immediately following a phase encoding gradient, the free induction decay is continuously sampled with extremely high temporal resolution to obtain k-space data at a fixed spatial frequency (i.e., at a fixed k-space coordinate). By having near-0 readout duration, CSPI results in a true snapshot of the transverse magnetization at each TE. Additionally, parallel imaging with autocalibration is utilized to reduce scan time, and an optional temporal averaging strategy is presented to improve signal-to-noise ratio for objects with low proton density or short T2* decay. The reconstructed CSPI images were input to a QSM framework based on morphology enabled dipole inversion.

RESULT

In an experiment performed using iron phantoms, susceptibility estimated using CSPI showed high linearity (R² = 0.9948) with iron concentration. Additionally, reconstructed CSPI phase images showed much reduced ringing artifact compared with phase images obtained using a frequency encoding strategy. In an ex vivo experiment performed using human tibia samples, estimated susceptibilities ranged from -1.6 to -2.1 ppm, in agreement with values reported in the literature (ranging from -1.2 to -2.2 ppm).

CONCLUSION

We have demonstrated the feasibility of using CSPI to obtain true phase images for QSM.

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.