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

Reduced oxygen extraction fraction in deep cerebral veins associated with cognitive impairment in multiple sclerosis

Studying the relationship between cerebral oxygen utilization and cognitive impairment is essential to understanding neuronal functional changes in the disease progression of multiple sclerosis (MS). This study explores the potential of using venous susceptibility in internal cerebral veins (ICVs) as an imaging biomarker for cognitive impairment in relapsing-remitting MS (RRMS) patients. Quantitative susceptibility mapping derived from fully flow-compensated MRI phase data was employed to directly measure venous blood oxygen saturation levels (SvO2) in the ICVs. Results revealed a significant reduction in the susceptibility of ICVs (212.4 ± 30.8 ppb vs 239.4 ± 25.9 ppb) and a significant increase of SvO2 (74.5 ± 1.89% vs 72.4 ± 2.23%) in patients with RRMS compared with age- and sex-matched healthy controls. Both the susceptibility of ICVs (r = 0.508, p = 0.031) and the SvO2 (r = -0.498, p = 0.036) exhibited a moderate correlation with cognitive decline in these patients assessed by the Paced Auditory Serial Addition Test, while no significant correlation was observed with clinical disability measured by the Expanded Disability Status Scale. The findings suggest that venous susceptibility in ICVs has the potential to serve as a specific indicator of oxygen metabolism and cognitive function in RRMS. .

In vivo mapping of hippocampal venous vasculature and oxygenation using susceptibility imaging at 7T

Mapping the small venous vasculature of the hippocampus in vivo is crucial for understanding how functional changes of hippocampus evolve with age. Oxygen utilization in the hippocampus could serve as a sensitive biomarker for early degenerative changes, surpassing hippocampal tissue atrophy as the main source of information regarding tissue degeneration. Using an ultrahigh field (7T) susceptibility-weighted imaging (SWI) sequence, it is possible to capture oxygen-level dependent contrast of submillimeter-sized vessels. Moreover, the quantitative susceptibility mapping (QSM) results derived from SWI data allow for the simultaneous estimation of venous oxygenation levels, thereby enhancing the understanding of hippocampal function. In this study, we proposed two potential imaging markers in a cohort of 19 healthy volunteers aged between 20 and 74 years. These markers were: 1) hippocampal venous density on SWI images and 2) venous susceptibility (Δχvein) in the hippocampus-associated draining veins (the inferior ventricular veins (IVV) and the basal veins of Rosenthal (BVR) using QSM images). They were chosen specifically to help characterize the oxygen utilization of the human hippocampus and medial temporal lobe (MTL). As part of the analysis, we demonstrated the feasibility of measuring hippocampal venous density and Δχvein in the IVV and BVR at 7T with high spatial resolution (0.25 × 0.25 × 1 mm3). Our results demonstrated the in vivo reconstruction of the hippocampal venous system, providing initial evidence regarding the presence of the venous arch structure within the hippocampus. Furthermore, we evaluated the age effect of the two quantitative estimates and observed a significant increase in Δχvein for the IVV with age (p=0.006, r2 = 0.369). This may suggest the potential application of Δχvein in IVV as a marker for assessing changes in atrophy-related hippocampal oxygen utilization in normal aging and neurodegenerative diseases such as AD and dementia.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Vascular Aging in the Choroid Plexus: A 7T Ultrasmall Superparamagnetic Iron Oxide (USPIO)-MRI Study

BACKGROUND

The choroid plexus (ChP), a densely vascularized structure, has drawn increasing attention for its involvement in brain homeostasis and waste clearance. While the volumetric changes have been explored in many imaging studies, few studies have investigated the vascular degeneration associated with aging in the ChP.

PURPOSE

To investigate the sub-structural characteristics of the ChP, particularly the vascular compartment using high-resolution 7T imaging enhanced with Ferumoxytol, an ultrasmall super-paramagnetic iron oxide, which greatly increase the susceptibility contrast for vessels.

STUDY TYPE

Prospective.

SUBJECTS

Forty-nine subjects without neurological disorders (age: 21-80 years; 42 ± 17 years; 20 females).

FIELD STRENGTH/SEQUENCE

7-T with 2D and 3D T2* GRE, 3D MPRAGE T1, 2D TSE T2, and 2D FLAIR.

ASSESSMENT

The vascular and stromal compartments of the ChP were segmented using K-means clustering on post-contrast 2D GRE images. Visual and qualitative assessment of ChP vascular characteristics were conducted independently by three observers. Vascular density (Volvessel/VolChP ratio) and susceptibility change (Δχ) induced by Ferumoxytol were analyzed on 3D GRE-derived susceptibility-weighted imaging and quantitative susceptibility mapping, respectively.

STATISTICAL TESTS

Independent t-test, Mann-Whitney U test, and Chi-square test were utilized for group comparisons. The relationship between age and ChP's vascular alterations was examined using Pearson's correlation. Intra-class coefficient was calculated for inter-observer agreement. A P value <0.05 was considered statistically significant.

RESULTS

2D GRE images demonstrated superior contrast and accurate delineation of ChP substructures (ICC = 0.86). Older subjects exhibited a significantly smaller vascular density (16.5 ± 4.34%) and lower Δχ (22.10 ± 12.82 ppb) compared to younger subjects (24.85 ± 6.84% and 34.64 ± 12.69 ppb). Vascular density and mean Δχ within the ChP negatively correlated with age (r = -0.48, and r = -0.45).

DATA CONCLUSION

Ferumoxytol-enhanced 7T images can demonstrate ChP alterations in elderly with decreased vascular density and expansion of nonvascular compartment.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Strategically Acquired Gradient Echo (STAGE) Imaging, part IV: Constrained Reconstruction of White Noise (CROWN) Processing as a Means to Improve Signal-to-Noise in STAGE Imaging at 3 Tesla

Increasing the signal-to-noise ratio (SNR) has always been of critical importance for magnetic resonance imaging. Although increasing field strength provides a linear increase in SNR, it is more and more costly as field strength increases. Therefore, there is a major effort today to use signal processing methods to improve SNR since it is more efficient and economical. There are a variety of methods to improve SNR such as averaging the data at the expense of imaging time, or collecting the data with a lower resolution, all of these methods, including imaging processing methods, usually come at the expense of loss of image detail or image blurring. Therefore, we developed a new mathematical approach called CROWN (Constrained Reconstruction of White Noise) to enhance SNR without loss of structural detail and without affecting scanning time. In this study, we introduced and tested the concept behind CROWN specifically for STAGE (strategically acquired gradient echo) imaging. The concept itself is presented first, followed by simulations to demonstrate its theoretical effectiveness. Then the SNR improvement on proton spin density (PSD) and R2⁎ maps was investigated using brain STAGE data acquired from 10 healthy controls (HCs) and 10 patients with Parkinson's disease (PD). For the PSD and R2* maps, the SNR and CNR between white matter and gray matter were improved by a factor of 1.87 ± 0.50 and 1.72 ± 0.88, respectively. The white matter hyperintensity lesions in PD patients were more clearly defined after CROWN processing. Using these improved maps, simulated images for any repeat time, echo time or flip angle can be created with improved SNR. The potential applications of this technology are to trade off the increased SNR for higher resolution images and/or faster imaging.

Enhancing Nigrosome-1 Sign Identification via Interpretable AI using True Susceptibility Weighted Imaging

BACKGROUND

Nigrosome 1 (N1), the largest nigrosome region in the ventrolateral area of the substantia nigra pars compacta, is identifiable by the "N1 sign" in long echo time gradient echo MRI. The N1 sign's absence is a vital Parkinson's disease (PD) diagnostic marker. However, it is challenging to visualize and assess the N1 sign in clinical practice.

PURPOSE

To automatically detect the presence or absence of the N1 sign from true susceptibility weighted imaging by using deep-learning method.

STUDY TYPE

Prospective.

POPULATION/SUBJECTS

453 subjects, including 225 PD patients, 120 healthy controls (HCs), and 108 patients with other movement disorders, were prospectively recruited including 227 males and 226 females. They were divided into training, validation, and test cohorts of 289, 73, and 91 cases, respectively.

FIELD STRENGTH/SEQUENCE

3D gradient echo SWI sequence at 3T; 3D multiecho strategically acquired gradient echo imaging at 3T; NM-sensitive 3D gradient echo sequence with MTC pulse at 3T.

ASSESSMENT

A neuroradiologist with 5 years of experience manually delineated substantia nigra regions. Two raters with 2 and 36 years of experience assessed the N1 sign on true susceptibility weighted imaging (tSWI), QSM with high-pass filter, and magnitude data combined with MTC data. We proposed NINet, a neural model, for automatic N1 sign identification in tSWI images.

STATISTICAL TESTS

We compared the performance of NINet to the subjective reference standard using Receiver Operating Characteristic analyses, and a decision curve analysis assessed identification accuracy.

RESULTS

NINet achieved an area under the curve (AUC) of 0.87 (CI: 0.76-0.89) in N1 sign identification, surpassing other models and neuroradiologists. NINet localized the putative N1 sign within tSWI images with 67.3% accuracy.

DATA CONCLUSION

Our proposed NINet model's capability to determine the presence or absence of the N1 sign, along with its localization, holds promise for enhancing diagnostic accuracy when evaluating PD using MR images.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Reduced Oxygen Extraction Fraction in Deep Cerebral Veins Associated with Cognitive Impairment in Multiple Sclerosis

Studying the relationship between cerebral oxygen utilization and cognitive impairment is essential to understanding neuronal functional changes in the disease progression of multiple sclerosis (MS). This study explores the potential of using venous susceptibility in internal cerebral veins (ICVs) as an imaging biomarker for cognitive impairment in relapsing-remitting MS (RRMS) patients. Quantitative susceptibility mapping derived from fully flow-compensated MRI phase data was employed to directly measure venous blood oxygen saturation levels (SvO2) in the ICVs. Results revealed a significant reduction in the susceptibility of ICVs (212.4 ± 30.8 ppb vs 239.4 ± 25.9 ppb) and a significant increase of SvO2 (74.5 ± 1.89 % vs 72.4 ± 2.23 %) in patients with RRMS compared with age- and sex-matched healthy controls. Both the susceptibility of ICVs (r = 0.646, p = 0.004) and the SvO2 (r = -0.603, p = 0.008) exhibited a strong correlation with cognitive decline in these patients assessed by the Paced Auditory Serial Addition Test, while no significant correlation was observed with clinical disability measured by the Expanded Disability Status Scale. The findings suggest that venous susceptibility in ICVs has the potential to serve as a specific indicator of oxygen metabolism and cognitive function in RRMS.

The iron burden of cerebral microbleeds contributes to brain atrophy through the mediating effect of white matter hyperintensity

The goal of this work was to explore the total iron burden of cerebral microbleeds (CMBs) using a semi-automatic quantitative susceptibility mapping and to establish its effect on brain atrophy through the mediating effect of white matter hyperintensities (WMH). A total of 95 community-dwelling people were enrolled. Quantitative susceptibility mapping (QSM) combined with a dynamic programming algorithm (DPA) was used to measure the characteristics of 1309 CMBs. WMH were evaluated according to the Fazekas scale, and brain atrophy was assessed using a 2D linear measurement method. Histogram analysis was used to explore the distribution of CMBs susceptibility, volume, and total iron burden, while a correlation analysis was used to explore the relationship between volume and susceptibility. Stepwise regression analysis was used to analyze the risk factors for CMBs and their contribution to brain atrophy. Mediation analysis was used to explore the interrelationship between CMBs and brain atrophy. We found that the frequency distribution of susceptibility of the CMBs was Gaussian in nature with a mean of 201 ppb and a standard deviation of 84 ppb; however, the volume and total iron burden of CMBs were more Rician in nature. A weak but significant correlation between the susceptibility and volume of CMBs was found (r = -0.113, P < 0.001). The periventricular WMH (PVWMH) was a risk factor for the presence of CMBs (number: β = 0.251, P = 0.014; volume: β = 0.237, P = 0.042; total iron burden: β = 0.238, P = 0.020) and was a risk factor for brain atrophy (third ventricle width: β = 0.325, P = 0.001; Evans's index: β = 0.323, P = 0.001). PVWMH had a significant mediating effect on the correlation between CMBs and brain atrophy. In conclusion, QSM along with the DPA can measure the total iron burden of CMBs. PVWMH might be a risk factor for CMBs and may mediate the effect of CMBs on brain atrophy.

An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1-weighted images

Parkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution in deep gray matter (DGM) nuclei. We hypothesized that deep learning (DL) could be used to automatically segment all DGM nuclei and use relevant features for a better differentiation between PD and healthy controls (HC). In this study, we proposed a DL-based pipeline for automatic PD diagnosis based on QSM and T1-weighted (T1W) images. This consists of (1) a convolutional neural network model integrated with multiple attention mechanisms which simultaneously segments caudate nucleus, globus pallidus, putamen, red nucleus, and substantia nigra from QSM and T1W images, and (2) an SE-ResNeXt50 model with an anatomical attention mechanism, which uses QSM data and the segmented nuclei to distinguish PD from HC. The mean dice values for segmentation of the five DGM nuclei are all >0.83 in the internal testing cohort, suggesting that the model could segment brain nuclei accurately. The proposed PD diagnosis model achieved area under the the receiver operating characteristic curve (AUCs) of 0.901 and 0.845 on independent internal and external testing cohorts, respectively. Gradient-weighted class activation mapping (Grad-CAM) heatmaps were used to identify contributing nuclei for PD diagnosis on patient level. In conclusion, the proposed approach can potentially be used as an automatic, explainable pipeline for PD diagnosis in a clinical setting.

Quantitative susceptibility mapping using multi-channel convolutional neural networks with dipole-adaptive multi-frequency inputs

Quantitative susceptibility mapping (QSM) quantifies the distribution of magnetic susceptibility and shows great potential in assessing tissue contents such as iron, myelin, and calcium in numerous brain diseases. The accuracy of QSM reconstruction was challenged by an ill-posed field-to-susceptibility inversion problem, which is related to the impaired information near the zero-frequency response of the dipole kernel. Recently, deep learning methods demonstrated great capability in improving the accuracy and efficiency of QSM reconstruction. However, the construction of neural networks in most deep learning-based QSM methods did not take the intrinsic nature of the dipole kernel into account. In this study, we propose a dipole kernel-adaptive multi-channel convolutional neural network (DIAM-CNN) method for the dipole inversion problem in QSM. DIAM-CNN first divided the original tissue field into high-fidelity and low-fidelity components by thresholding the dipole kernel in the frequency domain, and it then inputs the two components as additional channels into a multichannel 3D Unet. QSM maps from the calculation of susceptibility through multiple orientation sampling (COSMOS) were used as training labels and evaluation reference. DIAM-CNN was compared with two conventional model-based methods [morphology enabled dipole inversion (MEDI) and improved sparse linear equation and least squares (iLSQR) and one deep learning method (QSMnet)]. High-frequency error norm (HFEN), peak signal-to-noise-ratio (PSNR), normalized root mean squared error (NRMSE), and the structural similarity index (SSIM) were reported for quantitative comparisons. Experiments on healthy volunteers demonstrated that the DIAM-CNN results had superior image quality to those of the MEDI, iLSQR, or QSMnet results. Experiments on data with simulated hemorrhagic lesions demonstrated that DIAM-CNN produced fewer shadow artifacts around the bleeding lesion than the compared methods. This study demonstrates that the incorporation of dipole-related knowledge into the network construction has a potential to improve deep learning-based QSM reconstruction.

Diagnosing Parkinson's disease by combining neuromelanin and iron imaging features using an automated midbrain template approach

BACKGROUND AND PURPOSE

Early diagnosis of Parkinson's disease (PD) is still a clinical challenge. Most previous studies using manual or semi-automated methods for segmenting the substantia nigra (SN) are time-consuming and, despite raters being well-trained, individual variation can be significant. In this study, we used a template-based, automatic, SN subregion segmentation pipeline to detect the neuromelanin (NM) and iron features in the SN and SN pars compacta (SNpc) derived from a single 3D magnetization transfer contrast (MTC) gradient echo (GRE) sequence in an attempt to develop a comprehensive imaging biomarker that could be used to diagnose PD.

MATERIALS AND METHODS

A total of 100 PD patients and 100 age- and sex-matched healthy controls (HCs) were imaged on a 3T scanner. NM-based SN (SN_NM) boundaries and iron-based SN (SN_QSM) boundaries and their overlap region (representing the SNpc) were delineated automatically using a template-based SN subregion segmentation approach based on quantitative susceptibility mapping (QSM) and NM images derived from the same MTC-GRE sequence. All PD and HC subjects were evaluated for the nigrosome-1 (N1) sign by two raters independently. Receiver Operating Characteristic (ROC) analyses were performed to evaluate the utility of SN_NM volume, SN_QSM volume, SNpc volume and iron content with a variety of thresholds as well as the N1 sign in diagnosing PD. Correlation analyses were performed to study the relationship between these imaging measures and the clinical scales in PD.

RESULTS

In this study, we verified the value of the fully automatic template based midbrain deep gray matter mapping approach in differentiating PD patients from HCs. The automatic segmentation of the SN in PD patients led to satisfactory DICE similarity coefficients and volume ratio (VR) values of 0.81 and 1.17 for the SN_NM, and 0.87 and 1.05 for the SN_QSM, respectively. For the HC group, the average DICE similarity coefficients and VR values were 0.85 and 0.94 for the SN_NM, and 0.87 and 0.96 for the SN_QSM, respectively. The SN_QSM volume tended to decrease with age for both the PD and HC groups but was more severe for the PD group. For diagnosing PD, the N1 sign performed reasonably well by itself (Area Under the Curve (AUC) = 0.783). However, combining the N1 sign with the other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an improved diagnosis of PD with an AUC as high as 0.947 (using an SN threshold of 50ppb and an NM threshold of 0.15). Finally, the SN_QSM volume showed a negative correlation with the MDS-UPDRS III (R² = 0.1, p = 0.036) and the Hoehn and Yahr scale (R² = 0.04, p = 0.013) in PD patients.

CONCLUSION

In summary, this fully automatic template based deep gray matter mapping approach performs well in the segmentation of the SN and its subregions for not only HCs but also PD patients with SN degeneration. The combination of the N1 sign with other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an AUC of 0.947 and provided a comprehensive set of imaging biomarkers that, potentially, could be used to diagnose PD clinically.

Quantifying calcium changes in the fetal spine using quantitative susceptibility mapping as extracted from STAGE imaging

OBJECTIVES

To evaluate calcium deposition in the fetal spine in vivo during the second and third trimesters using quantitative susceptibility mapping (QSM).

METHODS

Fifty-four pregnant women in their second and third trimesters underwent a 2D multi-echo STrategically Acquired Gradient Echo (STAGE) MR imaging protocol at 3T covering the fetal spine. The first echo data was used for QSM processing. A linear regression model was used to assess the correlation between magnetic susceptibility and gestational age (GA). A paired sample t-test was used to compare the consistency of QSM measurements from each sequence.

RESULTS

The magnetic susceptibility of the fetal spine decreased linearly with advancing GA, with a slope of -52.3 parts per billion (ppb)/week and a Pearson correlation coefficient (r) of 0.83 (p < 0.001). In 37 subjects for whom the STAGE local QSM data were available from both flip angles, the average magnetic susceptibility values were -1111 ± 278 ppb and -1081 ± 262 ppb for FA = 8° and FA = 40°, respectively. These means were not statistically different according to a paired sample t-test (p = 0.156).

CONCLUSIONS

QSM is a reliable technique for evaluating calcium deposition and bone mineral density of fetal vertebrae. Our results demonstrate an increase in fetal calcium levels as a function of GA. These measures might be able to provide reference values for calcium content in the fetal spine during the second and third trimesters.

KEY POINTS

• Calcium deposition and mineralization in the fetal spine, evaluated by vertebral magnetic susceptibility, increased with advancing gestational age. • Our results provide reference values for calcium content in the fetal spine during the second and third trimesters.

Neurovascular decoupling measured with quantitative susceptibility mapping is associated with cognitive decline in patients with type 2 diabetes

Disturbance of neurovascular coupling (NVC) is suggested to be one potential mechanism in type 2 diabetes mellitus (T2DM) associated mild cognitive impairment (MCI). However, NVC evidence derived from functional magnetic resonance imaging ignores the relationship of neuronal activity with vascular injury. Twenty-seven T2DM patients without MCI and thirty healthy controls were prospectively enrolled. Brain regions with changed susceptibility detected by quantitative susceptibility mapping (QSM) were used as seeds for functional connectivity (FC) analysis. NVC coefficients were estimated using combined degree centrality (DC) with susceptibility or cerebral blood flow (CBF). Partial correlations between neuroimaging indicators and cognitive decline were investigated. In T2DM group, higher susceptibility values in right hippocampal gyrus (R.PHG) were found and were negatively correlated with Naming Ability of Montreal Cognitive Assessment. FC increased remarkably between R.PHG and right middle temporal gyrus (R.MTG), right calcarine gyrus (R.CAL). Both NVC coefficients (DC-QSM and DC-CBF) reduced in R.PHG and increased in R.MTG and R.CAL. Both NVC coefficients in R.PHG and R.MTG increased with the improvement of cognitive ability, especially for executive function. These demonstrated that QSM and DC-QSM coefficients can be promising biomarkers for early evaluation of cognitive decline in T2DM patients and help to better understand the mechanism of NVC.

Quantitative Susceptibility Mapping of Brain Iron Deposition in Patients With Recurrent Depression

OBJECTIVE

Recurrence is the most significant feature of depression and the relationship between iron and recurrent depression is still lack of direct evidence in vivo.

METHODS

Twenty-one patients with depression and twenty control subjects were included. Gradient-recalled echo, T1 and T2 images were acquired using a 3.0T MRI system. After quantitative susceptibility mapping were reconstructed and standardized, a whole-brain and the regions of interest were respectively analyzed.

RESULTS

Significant increases in susceptibility were found in multiple recurrent depression patients, which involved several brain regions (frontal lobes, temporal lobe structures, occipital lobes hippocampal regions, putamen, thalamus, cingulum, and cerebellum). Interestingly, no susceptibility changes after treatment compared to pre-treatment (all p>0.05) and no significant correlation between susceptibility and Hamilton Depression Rating Scale were found. Besides, it was close to significance that those with a higher relapse frequency or a longer mean duration of single episode had a higher susceptibility in the putamen, thalamus, and hippocampus. Further studies showed susceptibility across the putamen (ρ2=0.27, p<0.001), thalamus (ρ2=0.21, p<0.001), and hippocampus (ρ2=0.19, p<0.001) were strongly correlated with total course of disease onset.

CONCLUSION

Brain iron deposition is related to the total course of disease onset, but not the severity of depression, which suggest that brain iron deposition may be a sign of brain damage in multiple recurrent depression.

Quantifying Brain Iron in Hereditary Hemochromatosis Using R2* and Susceptibility Mapping

BACKGROUND AND PURPOSE

Brain iron dyshomeostasis is increasingly recognized as an important contributor to neurodegeneration. Hereditary hemochromatosis is the most commonly inherited disorder of systemic iron overload. Although there is an increasing interest in excessive brain iron deposition, there is a paucity of evidence showing changes in brain iron exceeding that in healthy controls. Quantitative susceptibility mapping and R2* mapping are established MR imaging techniques that we used to noninvasively quantify brain iron in subjects with hereditary hemochromatosis.

MATERIALS AND METHODS

Fifty-two patients with hereditary hemochromatosis and 47 age- and sex-matched healthy controls were imaged using a multiecho gradient-echo sequence at 3T. Quantitative susceptibility mapping and R2* data were generated, and regions within the deep gray matter were manually segmented. Mean susceptibility and R2* relaxation rates were calculated for each region, and iron content was compared between the groups.

RESULTS

We noted elevated iron levels in patients with hereditary hemochromatosis compared with healthy controls using both R2* and QSM methods in the caudate nucleus, putamen, pulvinar thalamus, red nucleus, and dentate nucleus. Additionally, the substantia nigra showed increased susceptibility while the thalamus showed an increased R2* relaxation rate compared with healthy controls, respectively.

CONCLUSIONS

Both quantitative susceptibility mapping and R2* showed abnormal levels of brain iron in subjects with hereditary hemochromatosis compared with controls. Quantitative susceptibility mapping and R2* can be acquired in a single MR imaging sequence and are complementary in quantifying deep gray matter iron.

Three-dimensional simultaneous brain mapping of T1, T2, T2∗ and magnetic susceptibility with MR Multitasking

PURPOSE

To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T 2 ∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan.

METHODS

The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T 2 ∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined.

RESULTS

High quality, co-registered T1 , T2 , and T 2 ∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T 2 ∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images.

CONCLUSION

The MR Multitasking-based 3D brain mapping of T1 , T2 , T 2 ∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.

Vascular Mapping of the Human Hippocampus Using Ferumoxytol-Enhanced MRI

The hippocampus is a small but complex grey matter structure that plays an important role in spatial and episodic memory and can be affected by a wide range of pathologies including vascular abnormalities. In this work, we introduce the use of Ferumoxytol, an ultra-small superparamagnetic iron oxide (USPIO) agent, to induce susceptibility in the arteries (as well as increase the susceptibility in the veins) to map the hippocampal micro-vasculature and to evaluate the quantitative change in tissue fractional vascular density (FVD), in each of its subfields. A total of 39 healthy subjects (aged 35.4 ± 14.2 years, from 18 to 81 years old) were scanned with a high-resolution (0.22×0.44×1 mm³) dual-echo SWI sequence acquired at four time points during a gradual increase in Ferumoxytol dose (final dose = 4 mg/kg). The volumes of each subfield were obtained automatically from the pre-contrast T₁ -weighted data. The dynamically acquired SWI data were co-registered and adaptively combined to reduce the blooming artifacts from large vessels, preserving the contrast from smaller vessels. The resultant SWI data were used to segment the hippocampal vasculature and to measure the FVD ((volume occupied by vessels)/(total volume)) for each subfield. The hippocampal fissure, along with the fimbria, granular cell layer of the dentate gyrus and cornu ammonis layers (except for CA1), showed higher micro-vascular FVD than the other parts of hippocampus. The CA1 region exhibited a significant correlation with age (R = −0.37, p < 0.05). demonstrating an overall loss of hippocampal vascularity in the normal aging process. Moreover, the vascular density reduction was more prominent than the age correlation with the volume reduction (R = −0.1, p > 0.05) of the CA1 subfield, which would suggest that vascular degeneration may precede tissue atrophy.

Automatic detection of neuromelanin and iron in the midbrain nuclei using a magnetic resonance imaging ‐based brain template

Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in‐vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC‐GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC‐GRE sequence was used to find the NM‐rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45–81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine‐tuned the boundaries in the original space using a dynamic programming algorithm to match the details of each individual's NM and iron features. A dual mapping approach was used to improve the performance of the morphological mapping of the midbrain of any given individual to the template space. A threshold approach was used in the NM‐rich region and susceptibility maps to optimize the DICE similarity coefficients and the volume ratios. The results for the NM of the SN as well as the iron containing SN, STN, and RN all indicate a strong agreement with manually drawn structures. The DICE similarity coefficients and volume ratios for these structures were 0.85, 0.87, 0.75, and 0.92 and 0.93, 0.95, 0.89, 1.05, respectively, before applying any threshold on the data. Using this fully automatic template‐based deep gray matter mapping approach, it is possible to accurately measure the tissue properties such as volumes, iron content, and NM content of the midbrain nuclei.

Streaking artifact suppression of quantitative susceptibility mapping reconstructions via L1-norm data fidelity optimization (L1-QSM)

PURPOSE

The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts.

METHODS

QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages.

RESULTS

The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups.

CONCLUSION

The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers.

A Comparison of Magnetic Resonance Imaging Methods to Assess Multiple Sclerosis Lesions: Implications for Patient Characterization and Clinical Trial Design

Magnetic resonance imaging (MRI) is a sensitive imaging modality for identifying inflammatory and/or demyelinating lesions, which is critical for a clinical diagnosis of MS and evaluating drug responses. There are many unique means of probing brain tissue status, including conventional T1 and T2 weighted imaging (T1WI, T2WI), T2 fluid attenuated inversion recovery (FLAIR), magnetization transfer, myelin water fraction, diffusion tensor imaging (DTI), phase-sensitive inversion recovery and susceptibility weighted imaging (SWI), but no study has combined all of these modalities into a single well-controlled investigation. The goals of this study were to: compare different MRI measures for lesion visualization and quantification; evaluate the repeatability of various imaging methods in healthy controls; compare quantitative susceptibility mapping (QSM) with myelin water fraction; measure short-term longitudinal changes in the white matter of MS patients and map out the tissue properties of the white matter hyperintensities using STAGE (strategically acquired gradient echo imaging). Additionally, the outcomes of this study were anticipated to aid in the choice of an efficient imaging protocol reducing redundancy of information and alleviating patient burden. Of all the sequences used, T2 FLAIR and T2WI showed the most lesions. To differentiate the putative demyelinating lesions from inflammatory lesions, the fusion of SWI and T2 FLAIR was used. Our study suggests that a practical and efficient imaging protocol combining T2 FLAIR, T1WI and STAGE (with SWI and QSM) can be used to rapidly image MS patients to both find lesions and study the demyelinating and inflammatory characteristics of the lesions.

QSM reconstruction challenge 2.0: Design and report of results

PURPOSE

The aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data.

METHODS

A two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground truth data available to mimic the clinical setting. At the second stage, ground truth data were provided for parameter optimization. Submissions were evaluated using eight numerical metrics and visual ratings.

RESULTS

A total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. Algorithms based on iterative approaches and total variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art.

CONCLUSION

The synthetic data provide a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithms produced the best results among all metrics. Future QSM challenges should assess whether this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.

Visualization of iron-rich subcortical structures in non-human primates in vivo by quantitative susceptibility mapping at 3T MRI

Magnetic resonance imaging (MRI) is now an essential tool in the field of neuroscience involving non-human primates (NHP). Structural MRI scanning using T1-weighted (T1w) or T2-weighted (T2w) images provides anatomical information, particularly for experiments involving deep structures such as the basal ganglia and cerebellum. However, for certain subcortical structures, T1w and T2w image contrasts are insufficient for their detection of important anatomical details. To better visualize such structures in the macaque brain, we applied a relatively new method called quantitative susceptibility mapping (QSM), which enhances tissue contrast based on the local tissue magnetic susceptibility. The QSM significantly improved the visualization of important structures, including the ventral pallidum (VP), globus pallidus external and internal segments (GPe and GPi), substantia nigra (SN), subthalamic nucleus (STN) in the basal ganglia and the dentate nucleus (DN) in the cerebellum. We quantified this the contrast enhancement by systematically comparing of contrast-to-noise ratios (CNRs) of QSM images relative to the corresponding T1w and T2w images. In addition, QSM values of some structures were correlated to the age of the macaque subjects. These results identify the QSM method as a straightforward and useful tool for clearly visualizing details of subcortical structures that are invisible with more traditional scanning sequences.

A role for magnetic susceptibility in synthetic computed tomography

PURPOSE

Radiotherapy treatment planning based on magnetic resonance imaging (MRI) benefits from increased soft-tissue contrast and functional imaging. MRI-only planning is attractive but limited by the lack of electron density information required for dose calculation, and the difficulty to differentiate air and bone. MRI can map magnetic susceptibility to separate bone from air. A method is introduced to produce synthetic CT (sCT) through automatic voxel-wise assignment of CT numbers from an MRI dataset processed that includes magnetic susceptibility mapping.

METHODS

Volumetric multi-echo gradient echo datasets were acquired in the heads of five healthy volunteers and fourteen patients with cancer using a 3 T MRI system. An algorithm for CT synthesis was designed using the volunteer data, based on fuzzy c-means clustering and adaptive thresholding of the MR data (magnitude, fat, water, and magnetic susceptibility). Susceptibility mapping was performed using a modified version of the iterative phase replacement algorithm. On patient data, the algorithm was assessed by direct comparison to X-ray computed tomography (CT) scans.

RESULTS

The skull, spine, teeth, and major sinuses were clearly distinguished in all sCT, from healthy volunteers and patients. The mean absolute CT number error between X-ray CT and sCT in patients ranged from 78 and 134 HU.

CONCLUSION

Susceptibility mapping using MRI can differentiate air and bone for CT synthesis. The proposed method is automated, fast, and based on a commercially available MRI pulse sequence. The method avoids registration errors and does not rely on a priori information, making it suitable for nonstandard anatomy.

Computed inverse MRI (CIMRI) for intrinsic brain magnetic susceptibility mapping

In magnetic resonance imaging (MRI), tissue magnetization in the main field B₀ is a necessary preparation for magnetic resonance signal formation that imposes an inherent dipole effect on MRI signals, which predisposes an artifact on tissue MRI. In the MRI principle, T2*-weighted MRI can be described by a cascade of data transformations: from the source of tissue magnetic susceptibility (denoted by χ) to the output of complex-valued T2* image (in a magnitude and phase pair). Under the linear approximation of the T2* phase MRI, we can computationally reconstruct the source χ by quantitative susceptibility mapping (QSM), which is an inverse solution that is modeled by computed inverse MRI (CIMRI). For a brain function study using MRI (fMRI), we can reconstruct a timeseries of brain χ images to represent the intrinsic brain function activity called functional QSM (fQSM). This intrinsic depiction is defined as the removal of the artifactual dipole effect and other MRI-introduced distortions from phase data through inverse mapping. With one high-resolution QSM experiment and one group (20 subjects) low-resolution fQSM experiment, we show that the dipole effect manifests as ripples around vessels and a spatial split at a local activation blob and that the dipole effect could be removed by CIMRI. In the context of inverse imaging or undoing MRI transformations (including dipole convolution), we computationally achieve brain intrinsic structural depiction by QSM and intrinsic functional depiction by fQSM.

An interictal measurement of cerebral oxygen extraction fraction in MRI-negative refractory epilepsy using quantitative susceptibility mapping

PURPOSE

Oxygen extraction fraction (OEF) can be a factor to identify brain tissue's disability in epileptic patients. This study aimed to assess the OEF's level measurement in refractory epileptic patients (REPs) using a quantitative susceptibility mapping (QSM) method and to determine whether the OEF parameters change.

METHODS

QSM-OEF maps of 26 REPs and 16 healthy subjects were acquired using 3T MRI with a 64-channel coil. Eighteen regions-of-interest (ROIs) were chosen around the cortex in one appropriate slice of the brain and the mean QSM-OEF for each ROI was obtained. The correlations of QSM-OEF among different clinical characteristics of the disease, as well as between the patients and normal subjects, were also investigated.

RESULTS

QSM-OEF was shown to be significantly higher in REPs (44.9 ± 5.8) than that in HS (41.9 ± 6.2) (p < 0.05). Mean QSM-OEF was statistically lower in the ipsilateral side (44.5 ± 6.6) compared to the contralateral side (46.4 ± 6.8) (P < 0.01). QSM-OEF was illustrated to have a strong positive correlation with the attack duration (r = 0.6), and a moderate negative correlation with the attack frequency (r = -0.3). Using an optimized support vector machine algorithm, we could predict the disease in subjects having abnormal OEF values in the brain-selected-ROIs with sensitivity, specificity, AUC, and the precision of 0.96, 1, 0.98, and 1, respectively.

CONCLUSIONS

The results of this study revealed that QSM-OEF of the REPs' brain is higher than that of HS, which indicates that QSM-OEF is associated with disease activity.

Reduced regional cerebral venous oxygen saturation is a risk factor for the cognitive impairment in hemodialysis patients: a quantitative susceptibility mapping study

The purpose of this study was to noninvasively evaluate the changes of regional cerebral venous oxygen saturation (rSvO₂) in hemodialysis patients using quantitative susceptibility mapping (QSM) and investigate the relationship with clinical risk factors and neuropsychological testing. Fifty four (54) hemodialysis patients and 54 age, gender and education matched healthy controls (HCs) were recruited in this prospective study. QSM data were reconstructed from the original phase data of susceptibility weighted imaging to measure the susceptibility of cerebral regional major veins in all subjects and calculate their rSvO₂. The differences in rSvO₂ between hemodialysis patients and HCs were investigated using analysis of covariance adjusting for age and gender as covariates. Stepwise multiple regression and correlation analysis were performed between the cerebral rSvO₂ and clinical factors including neuropsychological testing. The SvO₂ of the bilateral cortical, thalamostriate, septal, cerebral internal and basal veins in hemodialysis patients was significantly lower than that in HCs (p < 0.001, Bonferroni corrected). The cerebral rSvO₂ in all these veins was reduced by 1.67% to 2.30%. The hematocrit, iron, glucose, pre-and post-dialysis diastolic blood pressure (DBP) were independent predictive factors for the cerebral rSvO₂ (all P < 0.05). The Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores were both lower in patients than those in HCs (both P < 0.05). The SvO₂ of the left cerebral internal vein correlated with MoCA scores (r = 0.492; P = 0.02, FDR corrected). In conclusion, our study indicated that the cerebral rSvO₂ was reduced in hemodialysis patients, which was the risk factor for neurocognitive impairment. The hematocrit, iron, glucose, pre-and post-dialysis DBP were independent risk factors for the cerebral rSvO₂.

Estimating cerebral venous oxygenation in human fetuses with ventriculomegaly using quantitative susceptibility mapping

RATIONALE AND OBJECTIVES

The goal of this study was to estimate venous blood oxygen saturation (SvO2) in the superior sagittal sinus (SSS) in fetal brains with ventriculomegaly (VM) using quantitative susceptibility mapping (QSM).

MATERIALS AND METHODS

A radiofrequency spoiled gradient echo sequence was used to evaluate data on 19 fetuses with VM (gestational age(GA): median = 29.9 weeks (range 23 to 37.3 weeks)) and 20 healthy fetuses (GA: median = 30.9 (range 22.7 to 38.7 weeks)) at 1.5 T. Susceptibility weighted images encompassing the entire fetal brain were acquired within 1 min. An iterative, geometry constraint-based thresholded k-space division algorithm was used for generating QSM data of the fetal brain. The venous oxygen saturation was calculated using the magnetic susceptibility of the SSS obtained from the QSM data. Mixed-model analysis of variance and interobserver variability assessment were used to analyze the results.

RESULTS

The median SvO2 values in the entire VM cohort as well as for second and third trimester fetuses (with interquartile range) were: 67.8% (63.2%, 73.6%), 73.1% (69.1%, 77.3%) and 63.8% (59.4%, 68.1%), respectively. The corresponding median SvO2 value in the healthy control group was: 65.3% (58.3%, 68.2%), 67.5% (61.7%, 69.2%) and 60.8% (53.6%, 68.2%), respectively. However, the difference of SvO2 between VM and control groups was not significant at the p = 0.05 level (p = 0.076). The SvO2 was found decreasing significantly with GA in the healthy control group (p < 0.05).

CONCLUSIONS

We report for the first time the estimation of cerebral SvO2 in human fetuses with VM using QSM. This measure of oxygen saturation might be beneficial in assessing and monitoring the metabolic status of the fetus in various clinical conditions.

Quantitative Susceptibility Mapping of Venous Vessels in Neonates with Perinatal Asphyxia

BACKGROUND AND PURPOSE

Cerebral venous oxygen saturation can be used as an indirect measure of brain health, yet it often requires either an invasive procedure or a noninvasive technique with poor sensitivity. We aimed to test whether cerebral venous oxygen saturation could be measured using quantitative susceptibility mapping, an MR imaging technique, in 3 distinct groups: healthy term neonates, injured term neonates, and preterm neonates.

MATERIALS AND METHODS

We acquired multiecho gradient-echo MR imaging data in 16 neonates with perinatal asphyxia and moderate or severe hypoxic-ischemic encephalopathy (8 term age: average, 40.0 [SD, 0.8]  weeks' gestational age; 8 preterm, 33.5 [SD, 2.0]  weeks' gestational age) and in 8 healthy term-age controls (39.3 [SD, 0.6] weeks, for a total of n = 24. Data were postprocessed as quantitative susceptibility mapping images, and magnetic susceptibility was measured in cerebral veins by thesholding out 99.95% of lower magnetic susceptibility values.

RESULTS

The mean magnetic susceptibility value of the cerebral veins was found to be 0.36 (SD, 0.04) ppm in healthy term neonates, 0.36 (SD, 0.06) ppm in term injured neonates, and 0.29 (SD, 0.04) ppm in preterm injured neonates. Correspondingly, the derived cerebral venous oxygen saturation values were 73.6% (SD, 2.8%), 71.5% (SD, 7.4%), and 72.2% (SD, 5.9%). There was no statistically significant difference in cerebral venous oxygen saturation among the 3 groups (P = .751).

CONCLUSIONS

Quantitative susceptibility mapping-derived oxygen saturation values in preterm and term neonates agreed well with values in past literature. Cerebral venous oxygen saturation in preterm and term neonates with hypoxic-ischemic encephalopathy, however, was not found to be significantly different between neonates or healthy controls.

VC-Net: Deep Volume-Composition Networks for Segmentation and Visualization of Highly Sparse and Noisy Image Data

The fundamental motivation of the proposed work is to present a new visualization-guided computing paradigm to combine direct 3D volume processing and volume rendered clues for effective 3D exploration. For example, extracting and visualizing microstructures in-vivo have been a long-standing challenging problem. However, due to the high sparseness and noisiness in cerebrovasculature data as well as highly complex geometry and topology variations of micro vessels, it is still extremely challenging to extract the complete 3D vessel structure and visualize it in 3D with high fidelity. In this paper, we present an end-to-end deep learning method, VC-Net, for robust extraction of 3D microvascular structure through embedding the image composition, generated by maximum intensity projection (MIP), into the 3D volumetric image learning process to enhance the overall performance. The core novelty is to automatically leverage the volume visualization technique (e.g., MIP - a volume rendering scheme for 3D volume images) to enhance the 3D data exploration at the deep learning level. The MIP embedding features can enhance the local vessel signal (through canceling out the noise) and adapt to the geometric variability and scalability of vessels, which is of great importance in microvascular tracking. A multi-stream convolutional neural network (CNN) framework is proposed to effectively learn the 3D volume and 2D MIP feature vectors, respectively, and then explore their inter-dependencies in a joint volume-composition embedding space by unprojecting the 2D feature vectors into the 3D volume embedding space. It is noted that the proposed framework can better capture the small/micro vessels and improve the vessel connectivity. To our knowledge, this is the first time that a deep learning framework is proposed to construct a joint convolutional embedding space, where the computed vessel probabilities from volume rendering based 2D projection and 3D volume can be explored and integrated synergistically. Experimental results are evaluated and compared with the traditional 3D vessel segmentation methods and the state-of-the-art in deep learning, by using extensive public and real patient (micro- )cerebrovascular image datasets. The application of this accurate segmentation and visualization of sparse and complicated 3D microvascular structure facilitated by our method demonstrates the potential in a powerful MR arteriogram and venogram diagnosis of vascular disease.

Imaging iron and neuromelanin simultaneously using a single 3D gradient echo magnetization transfer sequence: Combining neuromelanin, iron and the nigrosome-1 sign as complementary imaging biomarkers in early stage Parkinson's disease

Diagnosing early stage Parkinson's disease (PD) is still a clinical challenge. Previous studies using iron, neuromelanin (NM) or the Nigrosome-1 (N1) sign in the substantia nigra (SN) by themselves have been unable to provide sufficiently high diagnostic performance for these methods to be adopted clinically. Our goal in this study was to extract the NM complex volume, iron content and volume representing the entire SN, and the N1 sign as potential complementary imaging biomarkers using a single 3D magnetization transfer contrast (MTC) gradient echo sequence and to evaluate their diagnostic performance and clinical correlations in early stage PD. A total of 40 early stage idiopathic PD subjects and 40 age- and sex-matched healthy controls (HCs) were imaged at 3T. NM boundaries (representing the SN pars compacta (SNpc) and parabrachial pigmented nucleus) and iron boundaries representing the total SN (SNpc and SN pars reticulata) were determined semi-automatically using a dynamic programming (DP) boundary detection algorithm. Receiver operating characteristic analyses were performed to evaluate the utility of these imaging biomarkers in diagnosing early stage PD. A correlation analysis was used to study the relationship between these imaging measures and the clinical scales. We also introduced the concept of NM and total iron overlap volumes to demonstrate the loss of NM relative to the iron containing SN. Furthermore, all 80 cases were evaluated for the N1 sign independently. The NM and SN volumes were lower while the iron content was higher in the SN for PD subjects compared to HCs. Interestingly, the PD subjects with bilateral loss of the N1 sign had the highest iron content. The area under the curve (AUC) values for the average of both hemispheres for single measures were: .960 for NM complex volume; .788 for total SN volume; .740 for SN iron content and .891 for the N1 sign. Combining NM complex volume with each of the following measures through binary logistic regression led to AUC values for the averaged right and left sides of: .976 for total iron content; .969 for total SN volume, .965 for overlap volume and .983 for the N1 sign. We found a negative correlation between SN volume and UPDRS-III (R² = .22, p = .002). While the N1 sign performed well, it does not contain any information about iron content or NM quantitatively, therefore, marrying this sign with the NM and iron measures provides a better physiological explanation of what is happening when the N1 sign disappears in PD subjects. In summary, the combination of NM complex volume, SN volume, iron content and the N1 sign as derived from a single MTC sequence provides complementary information for understanding and diagnosing early stage PD.

Quantitative susceptibility-weighted imaging may be an accurate method for determining stroke hypoperfusion and hypoxia of penumbra

OBJECTIVES

To quantitatively evaluate the volume of the ischemic penumbra using susceptibility-weighted imaging and mapping (SWIM) of asymmetrical prominent cortical veins (APCVs) in patients with acute ischemic stroke.

METHODS

Eighty-five eligible patients with acute ischemic stroke on admission within 12 h from symptom onset were studied. The APCVs on SWIM were quantitatively (SWI-volume) and semi-quantitatively (SWI-Alberta Stroke Program Early CT Score, SWI-ASPECTS) evaluated to calculate mismatch. To assess the diagnostic efficacy of APCVs on SWIM, comparative analyses were performed between SWI_volume-DWI mismatch and SWI_ASPECTS-DWI mismatch, using PWI-DWI mismatch as a reference. Correlations were calculated between the mismatches, as well as between SWI-volume and time-to-maximum (Tmax) > 6 s volume. Additionally, each of these mismatches was correlated with the National Institute of Health Stroke Scale (NIHSS).

RESULTS

The sensitivity, negative predictive value, and accuracy of SWI_volume-DWI mismatch were demonstrably higher than SWI_ASPECTS-DWI mismatch (100% vs. 53.7%, 100% vs. 9.5%, 97.7% vs. 54.5%, respectively). A significant positive correlation was found between SWI_volume-DWI and PWI-DWI mismatch (r = 0.691, p < 0.01), as well as between SWI-volume and Tmax > 6 s volume (r = 0.786, p < 0.001). A significant negative correlation was found between SWI_volume-DWI mismatch and NIHSS (r = - 0.360, p = 0.022), as well as between SWI_ASPECTS-DWI mismatch and NIHSS (r = - 0.499, p = 0.001).

CONCLUSIONS

SWI_volume-DWI mismatch had higher diagnostic efficacy than SWI_ASPECTS-DWI mismatch in defining the ischemic penumbra and showed good consistency with PWI-DWI mismatch in acute ischemic stroke. Quantitation of APCVs using SWIM provided an accurate method for determining hypoperfusion and provided a reliable method to reflect the hypoxia of penumbra.

KEY POINTS

• SWI_volume-DWI mismatch has higher diagnostic efficacy than SWI_ASPECTS-DWI mismatch in defining the ischemic penumbra. • SWI_volume-DWI mismatch shows good consistency with PWI-DWI mismatch in managing penumbra in acute ischemic stroke. • Quantitation of APCV volume using SWIM provided an accurate method for determining the hypoperfusion area and provided a reliable method to reflect the hypoxia of penumbra.

Quantitative MRI using STrategically Acquired Gradient Echo (STAGE): optimization for 1.5 T scanners and T1 relaxation map validation

OBJECTIVES

The strategically acquired gradient echo (STAGE) protocol, developed for 3T scanners, allows one to derive quantitative maps such as T1, T2*, proton density, and quantitative susceptibility mapping in about 5 min. Our aim was to adapt the STAGE sequences for 1.5T scanners which are still commonly used in clinical practice. Furthermore, the accuracy and repeatability of the STAGE-derived T1 estimate were tested.

METHODS

Flip angle (FA) optimization was performed using a theoretical simulation by maximizing signal-to-noise ratio, contrast-to-noise ratio, and T1 precision. The FA choice was further refined with the ISMRM/NIST phantom and in vivo acquisitions. The accuracy of the T1 estimate was assessed by comparing STAGE-derived T1 values with T1 maps obtained with an inversion recovery sequence. T1 accuracy was investigated for both the phantom and in vivo data. Finally, one subject was acquired 10 times once a week and a group of 27 subjects was scanned once. The T1 coefficient of variation (COV) was computed to assess scan-rescan and physiological variability, respectively.

RESULTS

The FA_1,2 = 7°,38° were identified as the optimal FA pair at 1.5T. The T1 estimate errors were below 3% and 5% for phantom and in vivo measurements, respectively. COV for different tissues ranged from 1.8 to 4.8% for physiological variability, and between 0.8 and 2% for scan-rescan repeatability.

CONCLUSION

The optimized STAGE protocol can provide accurate and repeatable T1 mapping along with other qualitative images and quantitative maps in about 7 min on 1.5T scanners. This study provides the groundwork to assess the role of STAGE in clinical settings.

KEY POINTS

• The STAGE imaging protocol was optimized for use on 1.5T field strength scanners. • A practical STAGE protocol makes it possible to derive quantitative maps (i.e., T1, T2*, PD, and QSM) in about 7 min at 1.5T. • The T1 estimate derived from the STAGE protocol showed good accuracy and repeatability.

Iron Content in Deep Gray Matter as a Function of Age Using Quantitative Susceptibility Mapping: A Multicenter Study

PURPOSE

To evaluate the effect of resolution on iron content using quantitative susceptibility mapping (QSM); to verify the consistency of QSM across field strengths and manufacturers in evaluating the iron content of deep gray matter (DGM) of the human brain using subjects from multiple sites; and to establish a susceptibility baseline as a function of age for each DGM structure using both a global and regional iron analysis.

METHODS

Data from 623 healthy adults, ranging from 20 to 90 years old, were collected across 3 sites using gradient echo imaging on one 1.5 Tesla and two 3.0 Tesla MR scanners. Eight subcortical gray matter nuclei were semi-automatically segmented using a full-width half maximum threshold-based analysis of the QSM data. Mean susceptibility, volume and total iron content with age correlations were evaluated for each measured structure for both the whole-region and RII (high iron content regions) analysis. For the purpose of studying the effect of resolution on QSM, a digitized model of the brain was applied.

RESULTS

The mean susceptibilities of the caudate nucleus (CN), globus pallidus (GP) and putamen (PUT) were not significantly affected by changing the slice thickness from 0.5 to 3 mm. But for small structures, the susceptibility was reduced by 10% for 2 mm thick slices. For global analysis, the mean susceptibility correlated positively with age for the CN, PUT, red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN). There was a negative correlation with age in the thalamus (THA). The volumes of most nuclei were negatively correlated with age. Apart from the GP, THA, and pulvinar thalamus (PT), all the other structures showed an increasing total iron content despite the reductions in volume with age. For the RII regional high iron content analysis, mean susceptibility in most of the structures was moderately to strongly correlated with age. Similar to the global analysis, apart from the GP, THA, and PT, all structures showed an increasing total iron content.

CONCLUSION

A reasonable estimate for age-related iron behavior can be obtained from a large cross site, cross manufacturer set of data when high enough resolutions are used. These estimates can be used for correcting for age related iron changes when studying diseases like Parkinson's disease, Alzheimer's disease, and other iron related neurodegenerative diseases.

Revealing vascular abnormalities and measuring small vessel density in multiple sclerosis lesions using USPIO

BACKGROUND AND PURPOSE

Multiple Sclerosis (MS) is a progressive, inflammatory, neuro-degenerative disease of the central nervous system (CNS) characterized by a wide range of histopathological features including vascular abnormalities. In this study, an ultra-small superparamagnetic iron oxide (USPIO) contrast agent, Ferumoxytol, was administered to induce an increase in susceptibility for both arteries and veins to help better reveal the cerebral microvasculature. The purpose of this work was to examine the presence of vascular abnormalities and vascular density in MS lesions using high-resolution susceptibility weighted imaging (SWI).

METHODS

Six subjects with relapsing remitting MS (RRMS, age = 47.3 ± 11.8 years with 3 females and 3 males) and fourteen age-matched healthy controls were scanned at 3 T with SWI acquired before and after the infusion of Ferumoxytol. Composite data was generated by registering the FLAIR data to the high resolution SWI data in order to highlight the vascular information in MS lesions. Both the central vein sign (CVS) and, a new measure, the multiple vessel sign (MVS) were identified, along with any vascular abnormalities, in the lesions on pre- and post-contrast SWI-FLAIR fusion data. The small vessel density within the periventricular normal-appearing white matter (NAWM) and the periventricular lesions were compared for all subjects.

RESULTS

Averaged across two independent raters, a total of 530 lesions were identified across all patients. The total number of lesions with vascularity on pre- and post-contrast data were 287 and 488, respectively. The lesions with abnormal vascular behavior were broken up into following categories: small lesions appearing only at the vessel boundary; dilated vessels within the lesions; and developmental venous angiomas. These vessel abnormalities observed within lesions increased from 55 on pre-contrast data to 153 on post-contrast data. Finally, across all the patients, the periventricular lesional vessel density was significantly higher (p < 0.05) than that of the periventricular NAWM.

CONCLUSIONS

By inducing a super-paramagnetic susceptibility in the blood using Ferumoxytol, the vascular abnormalities in the RRMS patients were revealed and small vessel densities were obtained. This approach has the potential to monitor the venous vasculature present in MS lesions, catalogue their characteristics and compare the vascular structures spatially to the presence of lesions. These enhanced vascular features may provide new insight into the pathophysiology of MS.

Multi-Echo Quantitative Susceptibility Mapping for Strategically Acquired Gradient Echo (STAGE) Imaging

Purpose

To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging.

Methods

The proposed QSM reconstruction algorithm, referred to as “structurally constrained Susceptibility Weighted Imaging and Mapping” scSWIM, performs an ℓ₁ and ℓ₂ regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The measured susceptibility values from scSWIM for both simulated and in vivo data were compared to the: original susceptibility model (for simulated data only), the multi orientation COSMOS (for in vivo data only), truncated k-space division (TKD), iterative susceptibility weighted imaging and mapping (iSWIM), and morphology enabled dipole inversion (MEDI) algorithms. Goodness of fit was quantified by measuring the root mean squared error (RMSE) and structural similarity index (SSIM). Additionally, scSWIM was assessed in ten healthy subjects.

Results

The unique contrast and tissue boundaries from T1WE and iSWIM enable the accurate definition of edges of high susceptibility regions. For the simulated brain model without the addition of microbleeds and calcium, the RMSE was best at 5.21ppb for scSWIM and 8.74ppb for MEDI thanks to the reduced streaking artifacts. However, by adding the microbleeds and calcium, MEDI’s performance dropped to 47.53ppb while scSWIM performance remained the same. The SSIM was highest for scSWIM (0.90) and then MEDI (0.80). The deviation from the expected susceptibility in deep gray matter structures for simulated data relative to the model (and for the in vivo data relative to COSMOS) as measured by the slope was lowest for scSWIM + 1%(−1%); MEDI + 2%(−11%) and then iSWIM −5%(−10%). Finally, scSWIM measurements in the basal ganglia of healthy subjects were in agreement with literature.

Conclusion

This study shows that using a data fidelity term and structural constraints results in reduced noise and streaking artifacts while preserving structural details. Furthermore, the use of STAGE imaging with multi-echo and multi-flip data helps to improve the signal-to-noise ratio in QSM data and yields less artifacts.

Longitudinal Magnetic Resonance Imaging of Cerebral Microbleeds in Multiple Sclerosis Patients

We hypothesized that cerebral microbleeds (CMBs) in multiple sclerosis (MS) patients will be detected with higher prevalence compared to healthy controls (HC) and that quantitative susceptibility mapping (QSM) will help remove false positives seen in susceptibility weighted imaging (SWI). A cohort of 100 relapsing remitting MS subjects scanned at 3T were used to validate a set of CMB detection guidelines specifically using QSM. A second longitudinal cohort of 112 MS and 25 HCs, also acquired at 3T, was reviewed across two time points. Both cohorts were imaged with SWI and fluid attenuated inversion recovery. Fourteen subjects in the first cohort (14%, 95% CI 8-21%) and twenty-one subjects in the second cohort (18.7%, 95% CI 11-27%) had at least one CMB. The combined information from SWI and QSM allowed us to discern stable CMBs and new CMBs from potential mimics and evaluate changes over time. The longitudinal results demonstrated that longer disease duration increased the chance to develop new CMBs. Higher age was also associated with increased CMB prevalence for MS and HC. We observed that MS subjects developed new CMBs between time points, indicating the need for longitudinal quantitative imaging of CMBs.

Imaging patients pre and post deep brain stimulation: Localization of the electrodes and their targets

PURPOSE

Deep brain stimulation (DBS) has become a widely performed surgical procedure for patients with medically refractory movement disorders and mental disorders. It is clinically important to set up a MRI protocol to map the brain targets and electrodes of the patients before and after DBS and to understand the imaging artifacts caused by the electrodes.

METHODS

Five patients with DBS electrodes implanted in the habenula (Hb), fourteen patients with globus pallidus internus (GPi) targeted DBS, three pre-DBS patients and seven healthy controls were included in the study. The MRI protocol consisted of magnetization prepared rapid acquisition gradient echo T1 (MPRAGE T1W), 3D multi-echo gradient recalled echo (ME-GRE) and 2D fast spin echo T2 (FSE T2W) sequences to map the brain targets and electrodes of the patients. Phantom experiments were also run to determine both the artifacts and the susceptibility of the electrodes. Signal to noise ratio (SNR) on T1W, T2W and GRE datasets were measured. The visibility of the brain structures was scored according to the Rose criterion. A detailed analysis of the characteristics of the electrodes in all three sequence types was performed to confirm the reliability of the postoperative MRI approach. In order to understand the signal behavior, we also simulated the corresponding magnitude data using the same imaging parameters as in the phantom sequences.

RESULTS

The mean ± inter-subject variability of the SNRs, across the subjects for T1W, T2W, and GRE datasets were 20.1 ± 8.1, 14.9 ± 3.2, and 43.0 ± 7.6, respectively. High resolution MPRAGE T1W and FSE T2W data both showed excellent contrast for the habenula and were complementary to each other. The mean visibility of the habenula in the 25 cases for the MPRAGE T1W data was 5.28 ± 1.11; and the mean visibility in the 20 cases for the FSE T2W data was 5.78 ± 1.30. Quantitative susceptibility mapping (QSM), reconstructed from the ME-GRE sequence, provided sufficient contrast to distinguish the substructures of the globus pallidus. The susceptibilities of the GPi and globus pallidus externa (GPe) were 0.087 ± 0.013 ppm and 0.115 ± 0.015 ppm, respectively. FSE T2W sequences provided the best image quality with smallest image blooming of stimulator leads compared to MPRAGE T1W images and GRE sequence images, the measured diameters of electrodes were 1.91 ± 0.22, 2.77 ± 0.22, and 2.72 ± 0.20 mm, respectively. High resolution, high bandwidth and short TE (TE = 2.6 ms) GRE helped constrain the artifacts to the area of the electrodes and the dipole effect seen in the GRE filtered phase data provided an effective mean to locate the end of the DBS lead.

CONCLUSION

The imaging protocol consisting of MPRAGE T1W, FSE T2W and ME-GRE sequences provided excellent pre- and post-operative visualization of the brain targets and electrodes for patients undergoing DBS treatment. Although the artifacts around the electrodes can be severe, sometimes these same artifacts can be useful in identifying their location.

Subvoxel vascular imaging of the midbrain using USPIO-Enhanced MRI

There is an urgent need for better detection and understanding of vascular abnormalities at the micro-level, where critical vascular nourishment and cellular metabolic changes occur. This is especially the case for structures such as the midbrain where both the feeding and draining vessels are quite small. Being able to monitor and diagnose vascular changes earlier will aid in better understanding the etiology of the disease and in the development of therapeutics. In this work, thirteen healthy volunteers were scanned with a dual echo susceptibility weighted imaging (SWI) sequence, with a resolution of 0.22 ​× ​0.44 ​× ​1 ​mm³ at 3T. Ultra-small superparamagnetic iron oxides (USPIO) were used to induce an increase in susceptibility in both arteries and veins. Although the increased vascular susceptibility enhances the visibility of small subvoxel vessels, the accompanying strong signal loss of the large vessels deteriorates the local tissue contrast. To overcome this problem, the SWI data were acquired at different time points during a gradual administration (final concentration ​= ​4 ​mg/kg) of the USPIO agent, Ferumoxytol, and the data was processed to combine the SWI data dynamically, in order to see through these blooming artifacts. The major vessels and their tributaries (such as the collicular artery, peduncular artery, peduncular vein and the lateral mesencephalic vein) were identified on the combined SWI data using arterio-venous maps. Dynamically combined SWI data was then compared with previous histological work to validate that this protocol was able to detect small vessels on the order of 50 ​μm-100 ​μm. A complex division-based phase unwrapping was also employed to improve the quality of quantitative susceptibility maps by reducing the artifacts due to aliased voxels at the vessel boundaries. The smallest detectable vessel size was then evaluated by revisiting numerical simulations, using estimated true susceptibilities for the basal vein and the posterior cerebral artery in the presence of Ferumoxytol. These simulations suggest that vessels as small as 50 ​μm should be visible with the maximum dose of 4 ​mg/kg.

Intracranial iron distribution and quantification in aceruloplasminemia: A case study

OBJECTIVES

Aceruloplasminemia (ACP) is a rare autosomal recessive disorder characterized by intracranial and visceral iron overload. With R2*-based imaging or quantitative susceptibility mapping (QSM), it is feasible to measure iron in the brain quantitatively, although to date this has not yet been done for patients with ACP. The aim of this study was to provide quantitative iron measurements for each affected brain region in an ACP patient with the potential to do so in all future ACP patients. This may shed light on the link between brain iron metabolism and the territories affected by ceruloplasmin function.

METHODS

We imaged a patient with ACP using a 3T magnetic resonance imaging scanner with a fifteen-channel head coil. We manually demarcated gray matter and white matter on the Strategically Acquired Gradient Echo (STAGE) images, and calculated values for susceptibility and R2* in these regions. Correlation analysis was performed between the R2* values and the susceptibility values.

RESULTS

Besides the usual territories affected in ACP, we also discovered that the mammillary bodies and the lateral habenulae had significant increases in iron, and the hippocampus was severely affected both in terms of iron content and abnormal tissue signal. We also noted that the iron in the cortical gray matter appeared to be deposited in the inner layers. Moreover, several pathways between the superior colliculus and the pulvinar thalamus, between the caudate and putamen anteriorly and between the caudate and pulvinar thalamus posteriorly were also evident. Finally, R2* correlated strongly with the QSM data (R² = 0.67, t = 6.78, p < 0.001).

CONCLUSION

QSM and R2* have proven to be sensitive and quantitative means by which to measure iron content in the brain. Our findings included several newly noted affected brain regions of iron overload and provided some new aspects of iron metabolism in ACP that may be further applicable to other pathologic conditions. Furthermore, our study may pave the way for assessing efficacy of iron chelation therapy in these patients and for other common iron related neurodegenerative disorders.

Imaging the Nigrosome 1 in the substantia nigra using susceptibility weighted imaging and quantitative susceptibility mapping: An application to Parkinson's disease

Parkinson's disease (PD) is a clinically heterogeneous chronic progressive neuro-degenerative disease with loss of dopaminergic neurons in the nigrosome 1 (N1) territory of the substantia nigra pars compacta (SNpc). To date, there has been a major effort to identify changes in the N1 territory by monitoring increases of iron in the SNpc. However, there is no standard protocol being used to visualize or characterize the N1 territory. Therefore, the purpose of this study was to create a robust high quality, rapid imaging protocol, determine a slice by slice characterization of the appearance of N1 (the "N1 sign") and evaluate the loss of the N1 sign in order to differentiate healthy controls (HCs) from patients with PD. Firstly, one group of 10 HCs was used to determine the choice of imaging parameters. Secondly, another group of 80 HCs was used to characterize the appearance of the N1 sign and train the raters. In this step, the magnitude, susceptibility weighted images (SWI), quantitative susceptibility maps (QSM) and true SWI (tSWI) images were all reviewed using data from a 3D gradient recalled echo sequence. A resolution of 0.67 mm × 0.67 mm × 1.34 mm was chosen based on the ability to cover all the basal ganglia, midbrain and dentate nucleus with good signal-to-noise with echo times of 11 ms and 20 ms. Thirdly, 80 Parkinsonism and related disorders patients [idiopathic Parkinson's disease (IPD): 57; atypical parkinsonian syndromes (APs): 14; essential tremor (ET): 9] and one additional group of 80 age-matched HCs were blindly analyzed for the presence or absence of the N1 sign for a differential diagnosis. From the first group of 80 HCs, all of the 76 (100%) cases (4 were excluded due to motion artifacts) showed the N1 sign in one form or another after reviewing the first 5 caudal slices of the SN. For the second group of 80 HCs, 78 (97.5%) showed the N1 sign in at least 2 slices. Of the 80 Parkinsonism and related disorders patients, 32 (56.1%, 32/57) IPD and 6 (42.9%, 6/14) APs showed a bilateral loss of the N1 sign, 12 (21.1%, 12/57) IPD and 6 (42.9%, 6/14) APs showed the N1 sign unilaterally and 13 (22.8%, 13/57) IPD and 2 (14.2%, 2/14) APs showed the N1 sign bilaterally. Also, all 9 (100%, 9/9) ET patients showed the N1 sign bilaterally. The mean total structure and mean high susceptibility region for the SN for both IPD and APs patients with bilateral loss of N1 were higher than those of the HCs (p < 0.002). In conclusion, the N1 sign can be consistently visualized using tSWI with a resolution of at least 0.67 mm × 0.67 mm × 1.34 mm and can be seen in 95% of HCs.

Visualizing the lateral habenula using susceptibility weighted imaging and quantitative susceptibility mapping

The habenulae consist of a pair of small nuclei which bridge the limbic forebrain and midbrain monoaminergic centers. They are implicated in major depressive disorders due to abnormal phasic response when provoked by a conditioned stimulus. The lateral habenula (Lhb) is believed to be involved in dopamine metabolism and is now a target for deep brain stimulation, a treatment which has shown promising anti-depression effects. We imaged the habenulae with susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) in order to localize the lateral habenula. Fifty-six healthy controls were recruited for this study. For the quantitative assessment, we traced the structure to compute volume from magnitude images and mean susceptibility bilaterally for the habenula on QSM. Thresholding methods were used to delineate the Lhb habenula on QSM. SWI, true SWI (tSWI), and QSM data were subjectively reviewed for increased Lhb contrast. SWI, QSM, and tSWI showed bilateral signal changes in the posterior location of the habenulae relative to the anterior location, which may indicate increased putative iron content within the Lhb. This signal behavior was shown in 41/44 (93%) subjects. In summary, it is possible to localize the lateral component of the habenula using SWI and QSM at 3 T.

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.

Susceptibility mapping of the dural sinuses and other superficial veins in the brain

Quantitative susceptibility mapping (QSM) is a means to obtain direct measurements of local tissue susceptibility distribution. Usually the focus is on imaging tissues in the brain, and the region of the brain studied is dictated by an eroded skull stripped mask. Producing the pristine local phase behavior for regions at the edge of the brain has been difficult in the past. For structures such as the superior sagittal sinus (SSS) that run alongside the surface of the brain and under the skull bones, a considerable part of the external phase from the dipole effect is lost due to the short T2* of the bones. In this paper, we propose a method that seeks to reconstruct the susceptibility distribution inside the dural sinuses by ensuring that the entire geometry of the dural sinuses is preserved with the help of an MR angiogram and venogram (MRAV). Having a geometrical model of the vessels makes it possible to estimate the missing phase outside the brain as well, by using the forward phase model and, hence, allowing a complete phase map to be reconstructed. Fifteen healthy volunteers were scanned using a susceptibility weighted imaging (SWI) sequence with interleaved rephased-dephased echoes. QSM results were compared between the conventional techniques and the proposed method of phase preservation outside the brain and inside the dural sinuses. This method demonstrates the reconstruction of the SSS, whereas conventional methods are either unable to preserve this structure or unable to provide complete phase information. The mean and standard deviation inside the SSS for all volunteers was 435 ± 5 ppb (this is the inter-subject error). To validate the proposed approach, the mean susceptibility inside the straight sinus showed good agreement between conventional approach and the proposed method. The results presented in this study indicate the potential of generating the susceptibility map for the whole brain, including the SSS (as well as potentially all the cortical veins).

Quantitative susceptibility mapping in the human fetus to measure blood oxygenation in the superior sagittal sinus

OBJECTIVES

To present the feasibility of performing quantitative susceptibility mapping (QSM) in the human fetus to evaluate the oxygenation (S_vO₂) of cerebral venous blood in vivo.

METHODS

Susceptibility weighted imaging (SWI) data were acquired from healthy pregnant subjects (n = 21, median = 31.3 weeks, interquartile range = 8.8 weeks). The susceptibility maps were generated from the SWI-phase images using a modified QSM processing pipeline, optimised for fetal applications. The processing pipeline is as follows: (1) mild high-pass filtering followed by quadratic fitting of the phase images to eliminate background phase variations; (2) manual creation of a fetal brain mask that includes the superior sagittal sinus (SSS); (3) inverse filtering of the resultant masked phase images using a truncated k-space approach with geometric constraint. Further, the magnetic susceptibility, ∆χ_v and corresponding putative S_vO₂ of the SSS were quantified from the generated susceptibility maps. Systematic error in the measured S_vO₂ due to the modified pipeline was also studied through simulations.

RESULTS

Simulations showed that the systematic error in S_vO₂ when using a mask that includes a minimum of 5 voxels around the SSS and five slices remains < 3% for different orientations of the vessel relative to the main magnetic field. The average ∆χ_v in the SSS quantified across all gestations was 0.42 ± 0.03 ppm. Based on ∆χ_v, the average putative S_vO₂ in the SSS across all fetuses was 67% ± 7%, which is in good agreement with published studies.

CONCLUSIONS

This in vivo study demonstrates the feasibility of using QSM in the human fetal brain to estimate ∆χ_v and S_vO₂.

KEY POINTS

• A modified quantitative susceptibility mapping (QSM) processing pipeline is tested and presented for the human fetus. • QSM is feasible in the human fetus for measuring magnetic susceptibility and oxygenation of venous blood in vivo. • Blood magnetic susceptibility values from MR susceptometry and QSM agree with each other in the human fetus.

Subcortical brain iron deposition and cognitive performance in older women with breast cancer receiving adjuvant chemotherapy: A pilot MRI study

As the number of older adults in the U.S. increases, so too will the incidence of cancer and cancer-related cognitive impairment (CRCI). However, the exact underlying biological mechanism for CRCI is not yet well understood. We utilized susceptibility-weighted imaging with quantitative susceptibility mapping, a non-invasive MRI-based technique, to assess longitudinal iron deposition in subcortical gray matter structures and evaluate its association with cognitive performance in women age 60+ with breast cancer receiving adjuvant chemotherapy and age-matched women without breast cancer as controls. Brain MRI scans and neurocognitive scores from the NIH Toolbox for Cognition were obtained before chemotherapy (time point 1) and within one month after the last infusion of chemotherapy for the patients and at matched intervals for the controls (time point 2). There were 14 patients age 60+ with breast cancer (mean age 66.3 ± 5.3 years) and 13 controls (mean age 68.2 ± 6.1 years) included in this study. Brain iron increased as age increased. There were no significant between- or within- group differences in neurocognitive scores or iron deposition at time point 1 or between time points 1 and 2 (p > 0.01). However, there was a negative correlation between iron in the globus pallidus and the fluid cognition composite scores in the control group at time point 1 (r = -0.71; p < 0.01), but not in the chemotherapy group. Baseline iron in the putamen was negatively associated with changes in the oral reading recognition scores in the control group (r = 0.74, p < 0.01), but not in the chemotherapy group. Brain iron assessment did not indicate cancer or chemotherapy related short-term differences, yet some associations with cognition were observed. Studies with larger samples and longer follow-up intervals are warranted.

Morphology-adaptive total variation for the reconstruction of quantitative susceptibility map from the magnetic resonance imaging phase

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging technique that quantifies the magnetic susceptibility distribution within biological tissues. QSM calculates the underlying magnetic susceptibility by deconvolving the tissue magnetic field map with a unit dipole kernel. However, this deconvolution problem is ill-posed. The morphology enabled dipole inversion (MEDI) introduces total variation (TV) to regularize the susceptibility reconstruction. However, MEDI results still contain artifacts near tissue boundaries because MEDI only imposes TV constraint on voxels inside smooth regions. We introduce a Morphology-Adaptive TV (MATV) for improving TV-regularized QSM. The MATV method first classifies imaging target into smooth and nonsmooth regions by thresholding magnitude gradients. In the dipole inversion for QSM, the TV regularization weights are a monotonically decreasing function of magnitude gradients. Thus, voxels inside smooth regions are assigned with larger weights than those in nonsmooth regions. Using phantom and in vivo datasets, we compared the performance of MATV with that of MEDI. MATV results had better visual quality than MEDI results, especially near tissue boundaries. Preliminary brain imaging results illustrated that MATV has potential to improve the reconstruction of regions near tissue boundaries.

Quantifying iron content in magnetic resonance imaging

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