Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition

Myelin water imaging and R2* mapping in neonates: Investigating R2* dependence on myelin and fibre orientation in whole brain white matter

R₂^* relaxation provides a semiquantitative method of detecting myelin, iron and white matter fibre orientation angles. Compared with standard histogram-based analyses, angle-resolved analysis of R₂^* has previously been shown to substantially improve the detection of subtle differences in the brain between healthy siblings of subjects with multiple sclerosis and unrelated healthy controls. Neonates, who are born with very little myelin and iron, and an underdeveloped connectome, provide researchers with an opportunity to investigate whether R₂^* is intimately linked with fibre-angle or myelin content as it is in adults, which may in future studies be explored as a potential white matter developmental biomarker. Five healthy adult volunteers (mean age [±SD] = 31.2 [±8.3] years; three males) were recruited from Vancouver, Canada. Eight term neonates (mean age = 38.6 ± 1.2 weeks; five males) were recruited from the Children's Hospital of Chongqing Medical University neonatal ward. All subjects were scanned on identical 3 T Philips Achieva scanners equipped with an eight-channel SENSE head coil and underwent a multiecho gradient echo scan, a 32-direction DTI scan and a myelin water imaging scan. For both neonates and adults, bin-averaged R₂^* variation across the brain's white matter was found to be best explained by fibre orientation. For adults, this represented a difference in R₂^* values of 3.5 Hz from parallel to perpendicular fibres with respect to the main magnetic field. In neonates, the fibre orientation dependency displayed a cosine wave shape, with a small R₂^* range of 0.4 Hz. This minor relationship in neonates provides further evidence for the key role myelin probably plays in creating this fibre orientation dependence later in life, but suggests limited clinical application in newborn populations. Future studies should investigate fibre-orientation dependency in infants in the first 5 years, when substantial myelin development occurs.

Elevated brain oxygen extraction fraction measured by MRI susceptibility relates to perfusion status in acute ischemic stroke

Recent clinical trials of new revascularization therapies in acute ischemic stroke have highlighted the importance of physiological imaging to identify optimal treatments for patients. Oxygen extraction fraction (OEF) is a hallmark of at-risk tissue in stroke, and can be quantified from the susceptibility effect of deoxyhemoglobin molecules in venous blood on MRI phase scans. We measured OEF within cerebral veins using advanced quantitative susceptibility mapping (QSM) MRI reconstructions in 20 acute stroke patients. Absolute OEF was elevated in the affected (29.3 ± 3.4%) versus the contralateral hemisphere (25.5 ± 3.1%) of patients with large diffusion-perfusion lesion mismatch (P = 0.032). In these patients, OEF negatively correlated with relative CBF measured by dynamic susceptibility contrast MRI (P = 0.004), suggesting compensation for reduced flow. Patients with perfusion-diffusion match or no hypo-perfusion showed less OEF difference between hemispheres. Nine patients received longitudinal assessment and showed OEF ratio (affected to contralateral) of 1.2 ± 0.1 at baseline that normalized (decreased) to 1.0 ± 0.1 at follow-up three days later (P = 0.03). Our feasibility study demonstrates that QSM MRI can non-invasively quantify OEF in stroke patients, relates to perfusion status, and is sensitive to OEF changes over time. Clinical trial registration: Longitudinal MRI examinations of patients with brain ischemia and blood brain barrier permeability; clinicaltrials.org :NCT02077582.

QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field

Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous neurological disorders. However, the intrinsic ill-posed dipole inversion problem greatly affects the accuracy of the susceptibility map. We propose QSMGAN: a 3D deep convolutional neural network approach based on a 3D U-Net architecture with increased receptive field of the input phase compared to the output and further refined the network using the WGAN with gradient penalty training strategy. Our method generates accurate QSM maps from single orientation phase maps efficiently and performs significantly better than traditional non-learning-based dipole inversion algorithms. The generalization capability was verified by applying the algorithm to an unseen pathology--brain tumor patients with radiation-induced cerebral microbleeds.

APOE4 moderates effects of cortical iron on synchronized default mode network activity in cognitively healthy old-aged adults

INTRODUCTION

Apolipoprotein E ε4 (APOE4)-related genetic risk for sporadic Alzheimer's disease is associated with an early impairment of cognitive brain networks. The current study determines relationships between APOE4 carrier status, cortical iron, and cortical network-functionality.

METHODS

Sixty-nine cognitively healthy old-aged individuals (mean age [SD] 66.1 [± 7.2] years; Mini-Mental State Exam [MMSE] 29.3 ± 1.1) were genotyped for APOE4 carrier-status and received 3 Tesla magnetic resonance imaging (MRI) for blood oxygen level-dependent functional magnetic resonance imaging (MRI) at rest, three-dimensional (3D)-gradient echo (six echoes) for cortical gray-matter, non-heme iron by quantitative susceptibility mapping, and 18F-flutemetamol positron emission tomography for amyloid-β.

RESULTS

A spatial pattern consistent with the default mode network (DMN) could be identified by independent component analysis. DMN activity was enhanced in APOE4 carriers and related to cortical iron burden. APOE4 and cortical iron synergistically interacted with DMN activity. Secondary analysis revealed a positive, APOE4 associated, relationship between cortical iron and DMN connectivity.

DISCUSSION

Our findings suggest that APOE4 moderates effects of iron on brain functionality prior to manifestation of cognitive impairment.

Different iron deposition patterns in hemodialysis patients with and without restless legs syndrome: a quantitative susceptibility mapping study

OBJECTIVE

Brain iron deposition in hemodialysis (HD) patients increases over time. Iron deficiency in gray matter nuclei has been reported to lead to idiopathic restless legs syndrome (RLS) symptoms. Regardless of unpleasant RLS sensations, the patterns of iron deposition between hemodialysis patients with RLS (HD-RLS) and hemodialysis patients without RLS (HD-nRLS) are still unclear. To evaluate the differences in iron deposition patterns between HD-RLS and HD-nRLS patients, we utilized quantitative susceptibility mapping (QSM).

METHODS

In sum, 24 HD-RLS patients, 25 HD-nRLS patients and 30 age- and sex-matched healthy controls (HCs) were enrolled. The QSM was used to assess susceptibility values of the regions of interest (ROIs), including the caudate nucleus (CN), putamen (PUT), globus pallidus (GP), thalamus (THA), substantia nigra (SN), red nucleus (RN) and dentate nucleus (DN).

RESULTS

HD duration was significantly longer in HD-RLS patients than in HD-nRLS patients (P < 0.05). The susceptibility of HD-RLS and HD-nRLS patients in PUT was higher than that in HCs (P < 0.05), illustrating elevated iron content in the nucleus. Compared with HD-nRLS patients, HD-RLS patients demonstrated reduced susceptibility in CN and PUT (both P < 0.05). Compared with HCs, HD-RLS patients displayed decreased susceptibility in DN (P < 0.05).

CONCLUSIONS

Different iron deposition patterns between HD-RLS and HD-nRLS patients in PUT and DN, which further support disturbed sensory processing in RLS, may be involved in RLS pathogenesis in HD patients.

A preliminary attempt to visualize nigrosome 1 in the substantia nigra for Parkinson's disease at 3T: An efficient susceptibility map-weighted imaging (SMWI) with quantitative susceptibility mapping using deep neural network (QSMnet)

PURPOSE

Visibility of nigrosome 1 in the substantia nigra (SN) is used as an MR imaging biomarker for Parkinson's disease. Because of lower susceptibility induced tissue contrast and SNR visualization of the SN pars compacta (SNPC) using conventional imaging technique in the clinical field strength (≤3T) has been limited. Susceptibility map-weighted imaging (SMWI) has been proposed to visualize SNPC at 3T. To better visualize nigrosome 1 and SN areas using SMWI, accurate estimation of the quantitative susceptibility mapping (QSM) map is essential. In SMWI processing, however, QSM processing time using conventional algorithms is the most time-consuming step and may limit clinical use. In this study, we introduce an efficient SMWI processing approach using the deep neural network (QSMnet). To improve the processing speed of SMWI while maintaining similar image quality to that obtained with the conventional method, QSMnet was applied to generate a susceptibility mask for SMWI processing.

METHODS

To conduct a deep learning-based image to image operation modified QSMnet was utilized. The network was trained with in vivo MR data from 57 healthy controls. To validate SMWI results from QSMnet, four datasets from healthy controls were used as the test datasets. As a preliminary attempt to explore the clinical applicability, Parkinson's disease patient data were additionally tested. The SWMI images generated by QSMnet and conventional model-based QSM outputs were compared. To validate SMWI results, region of interest (ROI) analysis was performed. The mean signal values at the nigrosome 1 and the surrounding regions were measured to calculate contrast-to-noise ratio (CNR).

RESULTS

The experimental results confirmed that the proposed approach using QSMnet provided similar QSM and SMWI compared to that obtained with conventional iLSQR while the processing speed was much improved (5.4 times faster). The QSM results from QSMnet show similar tissue contrast with results from iLSQR. When compared, the absolute mean intensity difference between two methods near the nigrosome 1 was 0.015 ppm. SMWI results using susceptibility masks from QSMnet demonstrated signal distribution and tissue contrast that was comparable with those results from the conventional iLSQR method. The absolute difference maps of SMWI were calculated to show the similarity between the two methods. The overall mean absolute difference value in the presented ROIs obtained from healthy controls (n = 4) and a PD patient (n = 1) were 2.31 and 1.81, respectively. Mean CNR values (10 ROIs; n = 5; including both sides; 1.42 for QSMnet; 1.43 for iLSQR) between SN and nigrosome 1 in SMWI results obtained by ROI analysis were similar (P = 0.724).

CONCLUSIONS

In this study, we assessed an efficient approach for SMWI visualizing SN and nigrosome 1 on 3T. QSMnet provides a similar SMWI image to that obtained with the conventional iterative QSM algorithm and improves QSM processing speed by avoiding iterative computation. Since QSM is the most time-consuming step of SMWI processing, QSMnet can help to achieve a higher processing speed of SMWI. These results suggest that SMWI imaging with susceptibility masks using QSMnet is a more efficient approach.

Probing demyelination and remyelination of the cuprizone mouse model using multimodality MRI

BACKGROUND

Various studies by MRI exhibit that the corpus callosum (CC) is the most vulnerable to cuprizone administration, detecting the demyelination and remyelination process using different MRI parameters are, however, lacking.

PURPOSE

To investigate the sensitivity of multiparametric MRI both in vivo and ex vivo for demyelination and remyelination.

STUDY TYPE

Prospective.

ANIMAL MODEL

A cuprizone mice model with an age-matched control group (n = 5), 4-week cuprizone exposure group followed by 9-week on a normal diet (n = 6), and a 13-week cuprizone exposure group (n = 6).

FIELD STRENGTH/SEQUENCE

3D gradient recalled echo, T2 -weighted, and diffusion tensor imaging (DTI) at 7.0T and 9.4T.

ASSESSMENT

Quantification of DTI metrics, quantitative susceptibility mapping (QSM), and T2 -weighted imaging intensity in major white matter bundles.

STATISTICAL TESTS

Nonparametric permutation tests were used with a cluster-forming threshold as 3.09 (equivalent to P = 0.001), and the significant level as P = 0.05 with family-wise correction.

RESULTS

In vivo susceptibility values increased from -11.7 to -0.7 ppb (P < 0.001) in CC and from -13.7 to -5.1 ppb (P < 0.001) in the anterior commissure (AC) after the 13-week cuprizone exposure. Ex vivo susceptibility values increased from -25.4 to 7.4 ppb (P < 0.001) in CC and from -41.6 to -15.8 ppb (P < 0.001) in AC. Susceptibility values showed high variations to demyelination for in vivo studies (94.0% in CC, 62.8% in AC). Susceptibility values exhibited higher variations than radial diffusivity for ex vivo studies (129.1% vs. 28.3% in CC, 62.0% vs. 25.0% in AC). In addition to the differential susceptibility variations in different white matter tracts, intraregional demyelination variation was also present not only in CC but also in the AC area by voxel-based analysis.

DATA CONCLUSION

QSM is sensitive to the demyelination process of cuprizone exposure, which can be a complementary technique to conventional T2 -weighted images and DTI metrics.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1852-1865.

Characterization of age-related microstructural changes in locus coeruleus and substantia nigra pars compacta

Locus coeruleus (LC) and substantia nigra pars compacta (SNpc) degrade with normal aging, but not much is known regarding how these changes manifest in MRI images, or whether these markers predict aspects of cognition. Here, we use high-resolution diffusion-weighted MRI to investigate microstructural and compositional changes in LC and SNpc in young and older adult cohorts, as well as their relationship with cognition. In LC, the older cohort exhibited a significant reduction in mean and radial diffusivity, but a significant increase in fractional anisotropy compared with the young cohort. We observed a significant correlation between the decrease in LC mean, axial, and radial diffusivities and measures examining cognition (Rey Auditory Verbal Learning Test delayed recall) in the older adult cohort. This observation suggests that LC is involved in retaining cognitive abilities. In addition, we observed that iron deposition in SNpc occurs early in life and continues during normal aging.

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

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

Multi-site harmonization of 7 tesla MRI neuroimaging protocols

Increasing numbers of 7 T (7 T) magnetic resonance imaging (MRI) scanners are in research and clinical use. 7 T MRI can increase the scanning speed, spatial resolution and contrast-to-noise-ratio of many neuroimaging protocols, but technical challenges in implementation have been addressed in a variety of ways across sites. In order to facilitate multi-centre studies and ensure consistency of findings across sites, it is desirable that 7 T MRI sites implement common high-quality neuroimaging protocols that can accommodate different scanner models and software versions.

With the installation of several new 7 T MRI scanners in the United Kingdom, the UK7T Network was established with an aim to create a set of harmonized structural and functional neuroimaging sequences and protocols. The Network currently includes five sites, which use three different scanner platforms, provided by two different vendors.

Here we describe the harmonization of functional and anatomical imaging protocols across the three different scanner models, detailing the necessary changes to pulse sequences and reconstruction methods. The harmonized sequences are fully described, along with implementation details. Example datasets acquired from the same subject on all Network scanners are made available. Based on these data, an evaluation of the harmonization is provided. In addition, the implementation and validation of a common system calibration process is described.

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease

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Radiomics features from QSM data have significant clinical value for the diagnosis of PD.

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CNN features, which is better than Radiomics Features, are also useful in the diagnosis of PD.

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The combination of radiomics features and CNN features can enhance the diagnostic accuracy.

Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheimer's disease. The aetiology and pathogenesis of Parkinson's disease (PD) are still unclear, but the loss of dopaminergic cells and the excessive iron deposition in the substantia nigra (SN) are associated with the pathophysiology. As an imaging technique that can quantitatively reflect the amount of iron deposition, Quantitative Susceptibility Mapping (QSM) has been shown to be a promising modality for the diagnosis of PD. In the present work, we propose a hybrid feature extraction method for PD diagnosis using QSM images. First, we extract radiomics features from the SN using QSM and employ machine learning algorithms to classify PD and normal controls (NC). This approach allows us to investigate which features are most vulnerable to the effects of the disease. Along with this approach, we propose a Convolutional Neural Network (CNN) based method which can extract different features from the QSM image to further support the diagnosis of PD. Finally, we combine these two types of features and we find that the radiomics features and CNN features are complementary to each other, which helps further improve the classification (diagnostic) performance. We conclude that: (1) radiomics features from QSM data have significant clinical value for the diagnosis of PD; (2) CNN features are also useful in the diagnosis of PD; and (3) the combination of radiomics features and CNN features can enhance the diagnostic accuracy.

Coil combination using linear deconvolution in k-space for phase imaging

Background

The combination of multi-channel data is a critical step for the imaging of phase and susceptibility contrast in magnetic resonance imaging (MRI). Magnitude-weighted phase combination methods often produce noise and aliasing artifacts in the magnitude images at accelerated imaging sceneries. To address this issue, an optimal coil combination method through deconvolution in k-space is proposed in this paper.

Methods

The proposed method firstly employs the sum-of-squares and phase aligning method to yield a complex reference coil image which is then used to calculate the coil sensitivity and its Fourier transform. Then, the coil k-space combining weights is computed, taking into account the truncated frequency data of coil sensitivity and the acquired k-space data. Finally, combining the coil k-space data with the acquired weights generates the k-space data of proton distribution, with which both phase and magnitude information can be obtained straightforwardly. Both phantom and in vivo imaging experiments were conducted to evaluate the performance of the proposed method.

Results

Compared with magnitude-weighted method and MCPC-C, the proposed method can alleviate the phase cancellation in coil combination, resulting in a less wrapped phase.

Conclusions

The proposed method provides an effective and efficient approach to combine multiple coil image in parallel MRI reconstruction, and has potential to benefit routine clinical practice in the future.

Mapping the human brainstem: Brain nuclei and fiber tracts at 3 T and 7 T

Structural high-resolution imaging of the brainstem can be of high importance in clinical practice. However, ultra-high field magnetic resonance imaging (MRI) is still restricted in use due to limited availability. Therefore, quantitative MRI techniques (quantitative susceptibility mapping [QSM], relaxation measurements [ R2* , R₁ ], diffusion tensor imaging [DTI]) and T₂ - and proton density (PD)-weighted imaging in the human brainstem at 3 T and 7 T are compared. Five healthy volunteers (mean age: 21.5 ± 1.9 years) were measured at 3 T and 7 T using multi-echo gradient echo sequences for susceptibility mapping and R2* relaxometry, magnetization-prepared 2 rapid acquisition gradient echo sequences for R₁ relaxometry, turbo-spin echo sequences for PD- and T₂ -weighted imaging and readout-segmented echo planar sequences for DTI. Susceptibility maps were computed using Laplacian-based phase unwrapping, V-SHARP for background field removal and the streaking artifact reduction for QSM algorithm for dipole inversion. Contrast-to-noise ratios (CNRs) were determined at 3 T and 7 T in ten volumes of interest (VOIs). Data acquired at 7 T showed higher CNR. However, in four VOIs, lower CNR was observed for R2* at 7 T. QSM was shown to be the contrast with which the highest number of structures could be identified. The depiction of very fine tracts such as the medial longitudinal fasciculus throughout the brainstem was only possible in susceptibility maps acquired at 7 T. DTI effectively showed the main tracts (crus cerebri, transverse pontine fibers, corticospinal tract, middle and superior cerebellar peduncle, pontocerebellar tract, and pyramid) at both field strengths. Assessing the brainstem with quantitative MRI methods such as QSM, R2* , as well as PD- and T₂ -weighted imaging with great detail, is also possible at 3 T, especially when using susceptibility mapping calculated from a gradient echo sequence with a wide range of echo times from 10.5 to 52.5 ms. However, tracing smallest structures strongly benefits from imaging at ultra-high field.

Quantitative susceptibility mapping in atypical Parkinsonisms

Background and purpose

Differential diagnosis between Parkinson's disease (PD) and Atypical Parkinsonisms, mainly Progressive Supranuclear Palsy (PSP) and Multiple System Atrophy (MSA), remains challenging. The low sensitivity of macroscopic findings at imaging might limit early diagnosis. The availability of iron-sensitive MR techniques and high magnetic field MR scanners provides new insights in evaluating brain structures in degenerative parkinsonisms. Quantitative Susceptibility Mapping (QSM) allows quantifying tissue iron content and could be sensitive to microstructural abnormalities which precede the appearence of regional atrophy. We measured the magnetic susceptibility (χ) of nigral and extranigral regions in patients with PD, PSP and MSA to evaluate the potential utility of the QSM technique for differential diagnosis.

Materials and methods

65 patients (36 PD, 14 MSA, 15 PSP) underwent clinical and radiological evaluation with 3 T MRI. QSM maps were obtained from GRE sequences. ROI were drawn on substantia nigra (SN), red nucleus (RN), subthalamic nucleus (STN), putamen, globus pallidus and caudate. χ values were compared to detect inter-group differences.

Results

The highest diagnostic accuracy for PSP (area under the ROC curve, AUC, range 0.9–0.7) was observed for increased χ values in RN, STN and medial part of SN whereas in MSA (AUC range 0.8–0.7) iron deposition was significantly higher in the putamen, according to the patterns of pathological involvement that characterize the different diseases.

Conclusion

QSM could be used for iron quantification of nigral and extranigral structures in all degenerative parkinsonisms and should be tested longitudinally in order to identify early microscopical changes.

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The qualitative evaluation of the SN failed to discriminate PD and atypical parkinsonisms.

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QSM showed increased susceptibility values within nigral and extranigral regions in AP.

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In MSA susceptibility values of putamen, STN and RN were higher than in PD.

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In PSP susceptibility values of medial SN, STN, RN and putamen were higher than in PD.

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QSM seems to be a promising tool in distinguishing PD from AP and MSA from PSP.

Quantitative susceptibility map reconstruction using annihilating filter-based low-rank Hankel matrix approach

PURPOSE

Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space. This work proposes a novel and accurate QSM reconstruction method based on k-space low-rank Hankel matrix constraint, avoiding the over-smoothing problem and streaking artifacts.

THEORY AND METHODS

Based on the recent theory of annihilating filter-based low-rank Hankel matrix approach (ALOHA), QSM is formulated as deconvolution under low-rank Hankel matrix constraint in the k-space. The computational complexity and the high memory burden were reduced by successive reconstruction of 2-D planes along 3 independent axes of the 3-D phase image in Fourier domain. Feasibility of the proposed method was tested on a simulated phantom and human data and were compared with existing QSM reconstruction methods.

RESULTS

The proposed ALOHA-QSM effectively reduced streaking artifacts and accurately estimated susceptibility values in deep gray matter structures, compared to the existing QSM methods.

CONCLUSIONS

The suggested ALOHA-QSM algorithm successfully solves the 3-dimensional QSM dipole inversion problem using k-space low rank property with no anatomical constraint. ALOHA-QSM can provide detailed brain structures and accurate susceptibility values with no streaking artifacts.

Assessment of Melanin Content and its Influence on Susceptibility Contrast in Melanoma Metastases

PURPOSE

To quantify the influence of melanin content on magnetic susceptibility of cerebral melanoma metastases.

METHODS

Patients with non-hemorrhagic metastases were included based on the absence of susceptibility blooming artifacts. Susceptibility maps were calculated from 3D gradient echo data, using Laplacian-based phase unwrapping, sophisticated harmonic artefact reduction for phase data (V-SHARP) with varying spherical kernel sizes for background field removal and the iLSQR algorithm for the inversion of phase data. Susceptibility maps were referenced to cerebrospinal fluid. Non-hemorrhagic metastases were identified on contrast-enhanced T1-weighted images and susceptibility weighted images. Metastases masks were drawn on T1-weighted post-contrast images and used to compute mean susceptibility values of each metastasis.

RESULTS

A total of 33 non-hemorrhagic melanoma brain metastases in 20 patients were quantitatively evaluated. Metastases without and with hyperintense signal on T1-weighted images, which corresponds to the melanin content, showed median susceptibility values of -0.028 ppm and -0.020 ppm, respectively. The susceptibility differences between metastases without and with T1-weighted hyperintense signal was not statistically significant (p ≥ 0.05).

CONCLUSION

Non-hemorrhagic cerebral melanoma metastases showed weak diamagnetic susceptibility values and susceptibility did not significantly correlate to T1-weighted signals. Therefore, melanin does not seem to be a major contributor to susceptibility in cerebral melanoma metastases.

MR susceptibility contrast imaging using a 2D simultaneous multi-slice gradient-echo sequence at 7T

Purpose

To develop a 7T simultaneous multi-slice (SMS) 2D gradient-echo sequence for susceptibility contrast imaging, and to compare its quality to 3D imaging.

Methods

A frequency modulated and phase cycled RF pulse was designed to simultaneously excite multiple slices in multi-echo 2D gradient-echo imaging. The imaging parameters were chosen to generate images with susceptibility contrast, including T₂*-weighted magnitude/phase images, susceptibility-weighted images and quantitative susceptibility/R₂* maps. To compare their image quality with 3D gradient-echo imaging, both 2D and 3D imaging were performed on 11 healthy volunteers and 4 patients with multiple sclerosis (MS). The signal to noise ratio (SNR) in gray and white matter and their contrast to noise ratio (CNR) was simulated for the 2D and 3D magnitude images using parameters from the imaging. The experimental SNRs and CNRs were measured in gray/white matter and deep gray matter structures on magnitude, phase, R₂* and QSM images from volunteers and the visibility of MS lesions on these images from patients was visually rated. All SNRs and CNRs were compared between the 2D and 3D imaging using a paired t-test.

Results

Although the 3D magnitude images still had significantly higher SNRs (by 13.0~17.6%), the 2D magnitude and QSM images generated significantly higher gray/white matter or globus pallidus/putamen contrast (by 13.3~87.5%) and significantly higher MS lesion contrast (by 5.9~17.3%).

Conclusion

2D SMS gradient-echo imaging can serve as an alternative to often used 3D imaging to obtain susceptibility-contrast-weighted images, with an advantage of providing better image contrast and MS lesion sensitivity.

Radiomic Features of the Nigrosome-1 Region of the Substantia Nigra: Using Quantitative Susceptibility Mapping to Assist the Diagnosis of Idiopathic Parkinson's Disease

Introduction: The loss of nigrosome-1, which is also referred to as the swallow tail sign (STS) in T2^*-weighted iron-sensitive magnetic resonance imaging (MRI), has recently emerged as a new biomarker for idiopathic Parkinson's disease (IPD). However, consistent recognition of the STS is difficult due to individual variations and different imaging parameters. Radiomics might have the potential to overcome these shortcomings. Therefore, we chose to explore whether radiomic features of nigrosome-1 of substantia nigra (SN) based on quantitative susceptibility mapping (QSM) could help to differentiate IPD patients from healthy controls (HCs). Methods: Three-dimensional multi-echo gradient-recalled echo images (0.86 × 0.86 × 1.00 mm³) were obtained at 3.0-T MRI for QSM in 87 IPD patients and 77 HCs. Regions of interest (ROIs) of the SN below the red nucleus were manually drawn on both sides, and subsequently, volumes of interest (VOIs) were segmented (these ROIs included four 1-mm slices). Then, 105 radiomic features (including 18 first-order features, 13 shape features, and 74 texture features) of bilateral VOIs in the two groups were extracted. Forty features were selected according to the ensemble feature selection method, which combined analysis of variance, random forest, and recursive feature elimination. The selected features were further utilized to distinguish IPD patients from HC using the SVM classifier with 10 rounds of 3-fold cross-validation. Finally, the representative features were analyzed using an unpaired t-test with Bonferroni correction and correlated with the UPDRS-III scores. Results: The classification results from SVM were as follows: area under curve (AUC): 0.96 ± 0.02; accuracy: 0.88 ± 0.03; sensitivity: 0.89 ± 0.06; and specificity: 0.87 ± 0.07. Five representative features were selected to show their detailed difference between IPD patients and HCs: 10th percentile and median in IPD patients were higher than those in HCs (all p < 0.00125), while Gray Level Run Length Matrix (GLRLM)-Long Run Low Gray Level Emphasis, Gray Level Size Zone Matrix (GLSZM)-Gray Level Non-Uniformity, and volume (all p < 0.00125) in IPD patients were lower than those in HCs. The 10th percentile was positively correlated with UPDRS-III score (r = 0.35, p = 0.001). Conclusion: Radiomic features of the nigrosome-1 region of SN based on QSM could be useful in the diagnosis of IPD and could serve as a surrogate marker for the STS.

DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping

Quantitative susceptibility mapping (QSM) is based on magnetic resonance imaging (MRI) phase measurements and has gained broad interest because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium in vivo. Thereby, QSM can also reveal pathological changes of these key components in widespread diseases such as Parkinson's disease, Multiple Sclerosis, or hepatic iron overload. While the ill-posed field-to-source-inversion problem underlying QSM is conventionally assessed by the means of regularization techniques, we trained a fully convolutional deep neural network - DeepQSM - to directly invert the magnetic dipole kernel convolution. DeepQSM learned the physical forward problem using purely synthetic data and is capable of solving the ill-posed field-to-source inversion on in vivo MRI phase data. The magnetic susceptibility maps reconstructed by DeepQSM enable identification of deep brain substructures and provide information on their respective magnetic tissue properties. In summary, DeepQSM can invert the magnetic dipole kernel convolution and delivers robust solutions to this ill-posed problem.

Quantitative Analysis of Punctate White Matter Lesions in Neonates Using Quantitative Susceptibility Mapping and R2* Relaxation

BACKGROUND AND PURPOSE

It is difficult to distinguish punctate white matter lesions from focal hemorrhagic lesions in neonates on conventional MR imaging because both kinds of lesions show increased signal intensity on T1-weighted images and, frequently, decreased signal intensity on T2-weighted images. Our aim was to distinguish punctate white matter lesions and focal hemorrhagic lesions using quantitative measures.

MATERIALS AND METHODS

In the current study, we acquired multiecho gradient recalled-echo MR imaging data from 24 neonates with hypoxic-ischemic encephalopathy and postprocessed them as R2* relaxation maps and quantitative susceptibility maps. Seven subjects who were found to have multifocal punctate white matter lesions and/or focal hemorrhagic lesions on R2* maps were included (mean gestational age at birth, 33 ± 4.28 weeks; mean gestational age at scanning, 38 ± 2 weeks). Manually drawing ROIs on R2* maps, we measured R2* and magnetic susceptibility values of the lesions, along with white matter regions within the corpus callosum as healthy comparison tissue.

RESULTS

R2* and magnetic susceptibility values were both found to easily distinguish punctate white matter lesions, focal hemorrhagic lesions, and healthy white matter tissue from each other (P < .05), with a large Hedge g. R2* and magnetic susceptibility values were significantly increased in focal hemorrhagic lesions compared with punctate white matter lesions and healthy white matter tissue. Punctate white matter lesions were also found to have significantly increased values over healthy white matter tissue.

CONCLUSIONS

R2* and quantitative susceptibility maps can be used to help clinicians distinguish and measure focal hemorrhages, punctate white matter lesions, and healthy white matter tissue.

Iron deposition in Parkinson's disease by quantitative susceptibility mapping

Background

Patients with Parkinson’s disease (PD) have elevated levels of brain iron, especially in the nigrostriatal dopaminergic system. The purpose of this study was to evaluate the iron deposition in the substantia nigra (SN) and other deep gray matter nuclei of PD patients using quantitative susceptibility mapping (QSM) and its clinical relationship, and to explore whether there is a gradient of iron deposition pattern in globus pallidus (GP)–fascicula nigrale (FN)–SN pathway.

Methods

Thirty-three PD patients and 26 age- and sex-matched healthy volunteers (HVs) were included in this study. Subjects underwent brain MRI and constructed QSM data. The differences in iron accumulation in the deep gray matter nuclei of the subjects were compared, including the PD group and the control group, the early-stage PD (EPD) group and the late-stage PD (LPD) group. The iron deposition pattern of the GP–FN–SN pathway was analyzed.

Results

The PD group showed increased susceptibility values in the FN, substantia nigra pars compacta (SNc), internal globus pallidus (GPi), red nucleus (RN), putamen and caudate nucleus compared with the HV group (P < 0.05). In both PD and HV group, iron deposition along the GP–FN–SN pathway did not show an increasing gradient pattern. The SNc, substantia nigra pars reticulata (SNr) and RN showed significantly increased susceptibility values in the LPD patients compared with the EPD patients.

Conclusion

PD is closely related to iron deposition in the SNc. The condition of PD patients is related to the SNc and the SNr. There is not an increasing iron deposition gradient along the GP–FN–SN pathway. The source and mechanism of iron deposition in the SN need to be further explored, as does the relationship between the iron deposition in the RN and PD.

Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths

Quantitative Susceptibility Mapping (QSM) provides a way of measuring iron concentration and myelination non-invasively and has the potential of becoming a tool of paramount importance in the study of a host of different pathologies. However, several experimental factors and the physical properties of magnetic susceptibility (χ) can impair the reliability of QSM, and it is therefore essential to assess QSM reproducibility for repeated acquisitions and different field strength. In particular, it has recently been demonstrated that QSM measurements strongly depend on echo time (TE): the same tissue, measured on the same scanner, exhibits different apparent frequency shifts depending on the TE used. This study aims to assess the influence of TE on intra-scanner and inter-scanner reproducibility of QSM, by using MRI systems operating at 3T and 7T. To maximize intra-scanner reproducibility it is necessary to match the TEs of the acquisition protocol, but the application of this rule leads to inconsistent QSM values across scanners operating at different static magnetic field. This study however demonstrates that, provided a careful choice of acquisition parameters, and in particular by using TEs at 3T that are approximately 2.6 times longer than those at 7T, highly reproducible whole-brain χ maps can be achieved also across different scanners, which renders QSM a suitable technique for longitudinal follow-up in clinical settings and in multi-center studies.

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.

Fast quantitative susceptibility reconstruction via total field inversion with improved weighted L0 norm approximation

Quantitative susceptibility mapping (QSM) is a meaningful MRI technique owing to its unique relation to actual physical tissue magnetic properties. The reconstruction of QSM is usually decomposed into three sub-problems, which are solved independently. However, this decomposition does not conform to the causes of the problems, and may cause discontinuity of parameters and error accumulation. In this paper, a fast reconstruction method named fast TFI based on total field inversion was proposed. It can accelerate the total field inversion by using a specially selected preconditioner and advanced solution of the weighted L₀ regularization. Due to the employment of an effective model, the proposed method can efficiently reconstruct the QSM of brains with lesions, where other methods may encounter problems. Experimental results from simulation and in vivo data verified that the new method has better reconstruction accuracy, faster convergence ability and excellent robustness, which may promote clinical application of QSM.

Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility

Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ± 0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ± 0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ± 0.08 to manual labels and 0.89 ± 0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology

Although iron is crucial for neuronal functioning, many aspects of cerebral iron biology await clarification. The ability to quantify specific iron forms in the living brain would open new avenues for diagnosis, therapeutic monitoring, and understanding pathogenesis of diseases. A modality that allows assessment of brain tissue composition in vivo, in particular of iron deposits or myelin content on a submillimeter spatial scale, is magnetic resonance imaging (MRI). Multimodal strategies combining MRI with complementary analytical techniques ex vivo have emerged, which may lead to improved specificity. Interdisciplinary collaborations will be key to advance beyond simple correlative analyses in the biological interpretation of MRI data and to gain deeper insights into key factors leading to iron accumulation and/or redistribution associated with neurodegeneration.

Mapping of apparent susceptibility yields promising diagnostic separation of progressive supranuclear palsy from other causes of parkinsonism

There is a need for methods that distinguish Parkinson’s disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), which have similar characteristics in the early stages of the disease. In this prospective study, we evaluate mapping of apparent susceptibility based on susceptibility weighted imaging (SWI) for differential diagnosis. We included 134 patients with PD, 11 with PSP, 10 with MSA and 44 healthy controls. SWI data were processed into maps of apparent susceptibility. In PSP, apparent susceptibility was increased in the red nucleus compared to all other groups, and in globus pallidus, putamen, substantia nigra and the dentate nucleus compared to PD and controls. In MSA, putaminal susceptibility was increased compared to PD and controls. Including all studied regions and using discriminant analysis between PSP and PD, 100% sensitivity and 97% specificity was achieved, and 91% sensitivity and 90% specificity in separating PSP from MSA. Correlations between putaminal susceptibility and disease severity in PD could warrant further research into using susceptibility mapping for monitoring disease progression and in clinical trials. Our study indicates that susceptibility in deep nuclei could play a role in the diagnosis of atypical parkinsonism, especially in PSP.

Distribution of brain iron accrual in adolescence: Evidence from cross-sectional and longitudinal analysis

To track iron accumulation and location in the brain across adolescence, we repurposed diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data acquired in 513 adolescents and validated iron estimates with quantitative susceptibility mapping (QSM) in 104 of these subjects. DTI and fMRI data were acquired longitudinally over 1 year in 245 male and 268 female, no-to-low alcohol-consuming adolescents (12-21 years at baseline) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. Brain region average signal values were calculated for susceptibility to nonheme iron deposition: pallidum, putamen, dentate nucleus, red nucleus, and substantia nigra. To estimate nonheme iron, the corpus callosum signal (robust to iron effects) was divided by regional signals to generate estimated R2 (edwR2 for DTI) and R2 * (eR2 * for fMRI). Longitudinal iron deposition was measured using the normalized signal change across time for each subject. Validation using baseline QSM, derived from susceptibility-weighted imaging, was performed on 46 male and 58 female participants. Normalized iron deposition estimates from DTI and fMRI correlated with age in most regions; both estimates indicated less iron in boys than girls. QSM results correlated highly with DTI and fMRI results (adjusted R2 = 0.643 for DTI, 0.578 for fMRI). Cross-sectional and longitudinal analyses indicated an initial rapid increase in iron, notably in the putamen and red nucleus, that slowed with age. DTI and fMRI data can be repurposed for identifying regional brain iron deposition in developing adolescents as validated with high correspondence with QSM.

Multimodal integration of diffusion MRI for better characterization of tissue biology

The contrast in diffusion-weighted MR images is due to variations of diffusion properties within the examined specimen. Certain microstructural information on the underlying tissues can be inferred through quantitative analyses of the diffusion-sensitized MR signals. In the first part of the paper, we review two types of approach for characterizing diffusion MRI signals: Bloch's equations with diffusion terms, and statistical descriptions. Specifically, we discuss expansions in terms of cumulants and orthogonal basis functions, the confinement tensor formalism and tensor distribution models. Further insights into the tissue properties may be obtained by integrating diffusion MRI with other techniques, which is the subject of the second part of the paper. We review examples involving magnetic susceptibility, structural tensors, internal field gradients, transverse relaxation and functional MRI. Integrating information provided by other imaging modalities (MR based or otherwise) could be a key to improve our understanding of how diffusion MRI relates to physiology and biology.

Altered brain iron content and deposition rate in Huntington's disease as indicated by quantitative susceptibility MRI

Altered brain iron content in the striatum of premanifest and manifest Huntington's disease (HD) has been reported. However, its natural history remains unclear. This study aims to investigate altered brain iron content in premanifest and early HD, and the iron deposition rate in these patients through a longitudinal one-year follow-up test, with quantitative magnetic susceptibility as an iron imaging marker. Twenty-four gene mutation carriers divided into three groups (further-from-onset, closer-to-onset and early HD) and 16 age-matched healthy controls were recruited at baseline, and of these, 14 carriers and 7 controls completed the one-year follow-up. Quantitative magnetic susceptibility and effective transverse relaxation rate ( R 2 ∗ ) were measured at 7.0 Tesla and correlated with atrophy and available clinical and cognitive measurements. Higher susceptibility values indicating higher iron content in the striatum and globus pallidus were only observed in closer-to-onset (N = 6, p < 0.05 in caudate and p < 0.01 in putamen) and early HD (N = 9, p < 0.05 in caudate and globus pallidus and p < 0.01 in putamen). Similar results were found by R 2 ∗ measurement. Such increases directly correlated with HD CAG-age product score and brain atrophy, but not with motor or cognitive scores. More importantly, a significantly higher iron deposition rate (11.9%/years in caudate and 6.1%/years in globus pallidus) was firstly observed in closer-to-onset premanifest HD and early HD as compared to the controls. These results suggest that monitoring brain iron may provide further insights into the pathophysiology of HD disease progression, and may provide a biomarker for clinical trials.

Noninvasive quantification of oxygen saturation in the portal and hepatic veins in healthy mice and those with colorectal liver metastases using QSM MRI

PURPOSE

This preclinical study investigated the use of QSM MRI to noninvasively measure venous oxygen saturation (SvO2) in the hepatic and portal veins.

METHODS

QSM data were acquired from a cohort of healthy mice (n = 10) on a 9.4 Tesla MRI scanner under normoxic and hyperoxic conditions. Susceptibility was measured in the portal and hepatic veins and used to calculate SvO2 in each vessel under each condition. Blood was extracted from the inferior vena cava of 3 of the mice under each condition, and SvO2 was measured with a blood gas analyzer for comparison. QSM data were also acquired from a cohort of mice bearing liver tumors under normoxic conditions. Susceptibility was measured, and SvO2 calculated in the portal and hepatic veins and compared to the healthy mice. Statistical significance was assessed using a Wilcoxon matched-pairs signed rank test (normoxic vs. hyperoxic) or a Mann-Whitney test (healthy vs. tumor bearing).

RESULTS

SvO2 calculated from QSM measurements in healthy mice under hyperoxia showed significant increases of 15% in the portal vein (P < 0.05) and 21% in the hepatic vein (P < 0.01) versus normoxia. These values agreed with inferior vena cava measurements from the blood gas analyzer (26% increase). SvO2 in the hepatic vein was significantly lower in the colorectal liver metastases cohort (30% ± 11%) than the healthy mice (53% ± 17%) (P < 0.05); differences in the portal vein were not significant.

CONCLUSION

QSM is a feasible tool for noninvasively measuring SvO2 in the liver and can detect differences due to increased oxygen consumption in livers bearing colorectal metastases.

Phase fMRI Reveals More Sparseness and Balance of Rest Brain Functional Connectivity Than Magnitude fMRI

Conventionally, brain function is inferred from the magnitude data of the complex-valued fMRI output. Since the fMRI phase image (unwrapped) provides a representation of brain internal magnetic fieldmap (by a constant scale difference), it can also be used to study brain function while providing a more direct representation of the brain's magnetic state. In this study, we collected a cohort of resting-state fMRI magnitude and phase data pairs from 600 subjects (age from 10 to 76, 346 males), decomposed the phase data by group independent component analysis (pICA), calculated the functional network connectivity (pFNC). In comparison with the magnitude-based brain function analysis (mICA and mFNC), we find that the pFNC matrix contains fewer significant functional connections (with p-value thresholding) than the mFNC matrix, which are sparsely distributed across the whole brain with near/far interconnections and positive/negative correlations in rough balance. We also find a few of brain rest sub-networks within the phase data, primarily in subcortical, cerebellar, and visual regions. Overall, our findings offer new insights into brain function connectivity in the context of a focus on the brain's internal magnetic state.

The use of Fourier-domain analyses for unwrapping phase images of low SNR

PURPOSE

We report a new postprocessing procedure that uses Fourier-domain data analyses to improve the accuracy and reliability of phase unwrapping for MRI data of low SNR.

METHODS

The developed method first identifies the Fourier-domain energy peak locations corresponding to different image-domain areas from which a robust measurement of image-domain phase gradients can be obtained even for MRI data of low SNR. The phase-gradient information measured from critical brain regions using the above-mentioned Fourier-domain analysis is then combined with the conventional temporal-domain or spatial-domain phase-unwrapping procedure to remove phase wraps. The developed method was tested with MRI data obtained from 30 healthy adult volunteers, and its performance was quantitatively evaluated.

RESULTS

The developed Fourier-domain analysis could robustly quantify image-domain phase gradients even for MRI data with low SNR (e.g., SNR ≃ 2). Experimental results show that the Fourier-domain analyses could further reduce phase wrap artifact in data produced by the conventional temporal-domain or spatial-domain phase-unwrapping procedures.

CONCLUSION

Our results demonstrate that the developed phase-unwrapping method can reduce residual phase wraps resulting from conventional procedures in critical brain regions (e.g., near the air-tissue interfaces) and should prove valuable for studies that require accurate measurements of MRI phase values, such as QSM, B₀ field mapping, and temperature mapping.

Imaging beta amyloid aggregation and iron accumulation in Alzheimer's disease using quantitative susceptibility mapping MRI

Beta amyloid is a protein fragment snipped from the amyloid precursor protein (APP). Aggregation of these peptides into amyloid plaques is one of the hallmarks of Alzheimer's disease. MR imaging of beta amyloid plaques has been attempted using various techniques, notably with T2* contrast. The non-invasive detectability of beta amyloid plaques in MR images has so far been largely attributed to focal iron deposition accompanying the plaques. It is believed that the T2* shortening effects of paramagnetic iron are the primary source of contrast between plaques and surrounding tissue. Amyloid plaque itself has been reported to induce no magnetic susceptibility effect. We hypothesized that aggregations of beta amyloid would increase electron density and induce notable changes in local susceptibility value, large enough to generate contrast relative to surrounding normal tissues that can be visualized by quantitative susceptibility mapping (QSM) MR imaging. To test this hypothesis, we first demonstrated in a phantom that beta amyloid is diamagnetic and can generate strong contrast on susceptibility maps. We then conducted experiments on a transgenic mouse model of Alzheimer's disease that is known to mimic the formation of human beta amyloid but without neurofibrillary tangles or neuronal death. Over a period of 18 months, we showed that QSM can be used to longitudinally monitor beta amyloid accumulation and accompanied iron deposition in vivo. Individual beta amyloid plaque can also be visualized ex vivo in high resolution susceptibility maps. Moreover, the measured negative susceptibility map and positive susceptibility map could provide histology-like image contrast for identifying deposition of beta amyloid plaques and iron. Finally, we demonstrated that the diamagnetic susceptibility of beta amyloid can also be observed in brain specimens of AD patients. The ability to assess beta amyloid aggregation non-invasively with QSM MR imaging may aid the diagnosis of Alzheimer's disease.

Weak-harmonic regularization for quantitative susceptibility mapping

PURPOSE

Background-field removal is a crucial preprocessing step for quantitative susceptibility mapping (QSM). Remnants from this step often contaminate the estimated local field, which in turn leads to erroneous tissue-susceptibility reconstructions. The present work aimed to mitigate this undesirable behavior with the development of a new approach that simultaneously decouples background contributions and local susceptibility sources on QSM inversion.

METHODS

Input phase data for QSM can be seen as a composite scalar field of local effects and residual background components. We developed a new weak-harmonic regularizer to constrain the latter and to separate the 2 components. The resulting optimization problem was solved with the alternating directions of multipliers method framework to achieve fast convergence. In addition, for convenience, a new alternating directions of multipliers method-based preconditioned nonlinear projection onto dipole fields solver was developed to enable initializations with wrapped-phase distributions. Weak-harmonic QSM, with and without nonlinear projection onto dipole fields preconditioning, was compared with the original (alternating directions of multipliers method-based) total variation QSM algorithm in phantom and in vivo experiments.

RESULTS

Weak-harmonic QSM returned improved reconstructions regardless of the method used for background-field removal, although the proposed nonlinear projection onto dipole fields method often obtained better results. Streaking and shadowing artifacts were substantially suppressed, and residual background components were effectively removed.

CONCLUSION

Weak-harmonic QSM with field preconditioning is a robust dipole inversion technique and has the potential to be extended as a single-step formulation for initialization with uncombined multi-echo data.

Longitudinal evaluation of iron concentration and atrophy in the dentate nuclei in friedreich ataxia

BACKGROUND

Friedreich ataxia is a recessively inherited, progressive neurological disease characterized by impaired mitochondrial iron metabolism. The dentate nuclei of the cerebellum are characteristic sites of neurodegeneration in the disease, but little is known of the longitudinal progression of abnormalities in these structures.

METHODS

Using in vivo magnetic resonance imaging, including quantitative susceptibility mapping, we investigated changes in iron concentration and volume in the dentate nuclei in individuals with Friedreich ataxia (n = 20) and healthy controls (n = 18) over a 2-year period.

RESULTS

The longitudinal rate of iron concentration was significantly elevated bilaterally in participants with Friedreich ataxia relative to healthy controls. Atrophy rates did not differ significantly between groups. Change in iron concentration and atrophy both correlated with baseline disease severity or duration, indicating sensitivity of these measures to disease stage. Specifically, atrophy was maximal in individuals early in the disease course, whereas the rate of iron concentration increased with disease progression.

CONCLUSIONS

Progressive dentate nucleus abnormalities are evident in vivo in Friedreich ataxia, and the rates of change of iron concentration and atrophy in these structures are sensitive to the disease stage. The findings are consistent with an increased rate of iron concentration and atrophy early in the disease, followed by iron accumulation and stable volume in later stages. This pattern suggests that iron dysregulation persists after loss of the vulnerable neurons in the dentate. The significant changes observed over a 2-year period highlight the utility of quantitative susceptibility mapping as a longitudinal biomarker and staging tool. © 2019 International Parkinson and Movement Disorder Society.

Spatiotemporal variations of magnetic susceptibility in the deep gray matter nuclei from 1 month to 6 years: A quantitative susceptibility mapping study

BACKGROUND

Quantitative susceptibility mapping (QSM) is emerging as a technique that quantifies the paramagnetic nonheme iron in brain tissue. Brain iron quantification during early development provides insights into the underlying mechanism of brain maturation.

PURPOSE

To quantify the spatiotemporal variations of brain iron-related magnetic susceptibility in deep gray matter nuclei during early development by using QSM.

STUDY TYPE

Retrospective.

SUBJECTS

Eighty-seven infants and children aged 1 month to 6 years.

FIELD STRENGTH/SEQUENCE

Enhanced T₂ *-weighted angiography using a 3D gradient-echo sequence at 3.0T.

ASSESSMENT

QSM was calculated by modified sophisticated harmonic artifact reduction for phase data and sparse linear equations and sparse least squares-based algorithm. Means of susceptibility in deep gray matter nuclei (caudate nucleus, putamen, globus pallidus, thalamus) relative to that in splenium of corpus callosum were measured.

STATISTICAL TESTS

Relationships of mean susceptibility with age and referenced iron concentration were tested by Pearson correlation. Differences of mean susceptibility between the selected nuclei in each age group were compared by one-way analysis of variance (ANOVA) and Fisher's Linear Significant Difference (LSD) test.

RESULTS

Positive correlations of susceptibility with both referenced iron concentration and age were found (P < 0.0001); particularly, globus pallidus showed the highest correlation with age (correlation coefficient, 0.882; slope, 1.203; P < 0.001) and greatest susceptibility (P < 0.05) among the selected nuclei.

DATA CONCLUSION

QSM allows the feasible quantification of iron deposition in deep gray matter nuclei in infants and young children, which exhibited gradual accumulation at different speeds. The fastest and highest iron accumulation was observed in the globus pallidus with increasing age during early development.

LEVEL OF EVIDENCE

4 Technical Efficacy:Stage 2 J. Magn. Reson. Imaging 2018.

Patents on Quantitative Susceptibility Mapping (QSM) of Tissue Magnetism

BACKGROUND

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

OBJECTIVE

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

METHOD

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

RESULTS

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

CONCLUSION

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

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

PURPOSE

Quantitative susceptibility mapping (QSM) is influenced by iron as well as myelin, which makes interpretation of pathologic changes challenging. Concurrent acquisition of MR sequences that are sensitive to axonal/myelin integrity, such as diffusion tensor imaging (DTI), may provide context for interpreting quantitative susceptibility (QS) signal. The purpose of our study was to investigate alterations in normal-appearing white matter (NAWM) in multiple sclerosis (MS) using QSM in conjunction with DTI.

METHODS

Twenty relapsing-remitting MS patients and 20 age-matched healthy controls (HC) were recruited for this prospective study. QS, radial diffusivity (RD), fractional anisotropy (FA), and R2* maps within the whole brain as well as individual tracts were generated for comparison between NAWM and HC white matter (HCWM).

RESULTS

MS lesions demonstrated significant differences in QS, FA, RD, and R2* compared to HCWM (p < 0.03). These metrics did not show a significant difference between whole-brain NAWM and HCWM. Among NAWM tracts, the cingulate gyri demonstrated significantly decreased QS compared to HCWM (p = 0.004). The forceps major showed significant differences in FA and RD without corresponding changes in QS (p < 0.01).

CONCLUSION

We found discordant changes in QSM and DTI metrics within the cingulate gyri and forceps major. This may potentially reflect the influence of paramagnetic substrates such as iron, which could be decreased along these NAWM tracts. Our results point to the potential role of QSM as a unique biomarker, although additional validation studies are needed.

The choice of embedding media affects image quality, tissue R2 * , and susceptibility behaviors in post-mortem brain MR microscopy at 7.0T

PURPOSE

The quality and precision of post-mortem MRI microscopy may vary depending on the embedding medium used. To investigate this, our study evaluated the impact of 5 widely used media on: (1) image quality, (2) contrast of high spatial resolution gradient-echo (T₁ and T₂ ^* -weighted) MR images, (3) effective transverse relaxation rate (R₂ ^* ), and (4) quantitative susceptibility measurements (QSM) of post-mortem brain specimens.

METHODS

Five formaldehyde-fixed brain slices were scanned using 7.0T MRI in: (1) formaldehyde solution (formalin), (2) phosphate-buffered saline (PBS), (3) deuterium oxide (D₂ O), (4) perfluoropolyether (Galden), and (5) agarose gel. SNR and contrast-to-noise ratii (SNR/CNR) were calculated for cortex/white matter (WM) and basal ganglia/WM regions. In addition, median R₂ ^* and QSM values were extracted from caudate nucleus, putamen, globus pallidus, WM, and cortical regions.

RESULTS

PBS, Galden, and agarose returned higher SNR/CNR compared to formalin and D₂ O. Formalin fixation, and its use as embedding medium for scanning, increased tissue R₂ ^* . Imaging with agarose, D₂ O, and Galden returned lower R₂ ^* values than PBS (and formalin). No major QSM offsets were observed, although spatial variance was increased (with respect to R₂ ^* behaviors) for formalin and agarose.

CONCLUSIONS

Embedding media affect gradient-echo image quality, R₂ ^* , and QSM in differing ways. In this study, PBS embedding was identified as the most stable experimental setup, although by a small margin. Agarose and Galden were preferred to formalin or D₂ O embedding. Formalin significantly increased R₂ ^* causing noisier data and increased QSM variance.

Monitoring Progressive Multiple Sclerosis with Novel Imaging Techniques

Imaging markers for monitoring disease progression in progressive multiple sclerosis (PMS) are scarce, thereby limiting the possibility to monitor disease evolution and to test effective treatments in clinical trials. Advanced imaging techniques that have the advantage of metrics with increased sensitivity to short-term tissue changes and increased specificity to the structural abnormalities characteristic of PMS have recently been applied in clinical trials of PMS. In this review, we (1) provide an overview of the pathological features of PMS, (2) summarize the findings of research and clinical trials conducted in PMS which have applied conventional and advanced magnetic resonance imaging techniques and (3) discuss recent advancements and future perspectives in monitoring PMS with imaging techniques.

Pros and cons of ultra-high-field MRI/MRS for human application

Magnetic resonance imaging and spectroscopic techniques are widely used in humans both for clinical diagnostic applications and in basic research areas such as cognitive neuroimaging. In recent years, new human MR systems have become available operating at static magnetic fields of 7 T or higher (≥300 MHz proton frequency). Imaging human-sized objects at such high frequencies presents several challenges including non-uniform radiofrequency fields, enhanced susceptibility artifacts, and higher radiofrequency energy deposition in the tissue. On the other side of the scale are gains in signal-to-noise or contrast-to-noise ratio that allow finer structures to be visualized and smaller physiological effects to be detected. This review presents an overview of some of the latest methodological developments in human ultra-high field MRI/MRS as well as associated clinical and scientific applications. Emphasis is given to techniques that particularly benefit from the changing physical characteristics at high magnetic fields, including susceptibility-weighted imaging and phase-contrast techniques, imaging with X-nuclei, MR spectroscopy, CEST imaging, as well as functional MRI. In addition, more general methodological developments such as parallel transmission and motion correction will be discussed that are required to leverage the full potential of higher magnetic fields, and an overview of relevant physiological considerations of human high magnetic field exposure is provided.

A robust multi-scale approach to quantitative susceptibility mapping

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

Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook

Phantoms, both numerical (software) and physical (hardware), can serve as a gold standard for the validation of MRI methods probing the brain microstructure. This review aims to provide guidelines on how to build, implement, or choose the right phantom for a particular application, along with an overview of the current state-of-the-art of phantoms dedicated to study brain microstructure with MRI. For physical phantoms, we discuss the essential requirements and relevant characteristics of both the (NMR visible) liquid and (NMR invisible) phantom materials that induce relevant microstructural features detectable via MRI, based on diffusion, intra-voxel incoherent motion, magnetization transfer or magnetic susceptibility weighted contrast. In particular, for diffusion MRI, many useful phantoms have been proposed, ranging from simple liquids to advanced biomimetic phantoms consisting of hollow or plain microfibers and capillaries. For numerical phantoms, the focus is on Monte Carlo simulations of random walk, for which the basic principles, along with useful criteria to check and potential pitfalls are reviewed, in addition to a literature overview highlighting recent advances. While many phantoms exist already, the current review aims to stimulate further research in the field and to address remaining needs.