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Chunlei Liu

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31 papers

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YNIMG Journal 2025 Journal Article

Robust computation of subcortical functional connectivity guided by quantitative susceptibility mapping: An application in Parkinson’s disease diagnosis

Jianmei Qin
Haoting Wu
Chenqing Wu
Tao Guo
Cheng Zhou
Xiaojie Duanmu
Sijia Tan
Jiaqi Wen

Previous resting state functional MRI (rs-fMRI) analyses of the basal ganglia in Parkinson's disease heavily relied on T1-weighted imaging (T1WI) atlases. However, subcortical structures are characterized by subtle contrast differences, making their accurate delineation challenging on T1WI. In this study, we aimed to introduce and validate a method that incorporates quantitative susceptibility mapping (QSM) into the rs-fMRI analytical pipeline to achieve precise subcortical nuclei segmentation and improve the stability of RSFC measurements in Parkinson's disease. A total of 321 participants (148 patients with Parkinson's Disease and 173 normal controls) were enrolled. We performed cross-modal registration at the individual level for rs-fMRI to QSM (FUNC2QSM) and T1WI (FUNC2T1), respectively.The consistency and accuracy of resting state functional connectivity (RSFC) measurements in two registration approaches were assessed by intraclass correlation coefficient and mutual information. Bootstrap analysis was performed to validate the stability of the RSFC differences between Parkinson's disease and normal controls. RSFC-based machine learning models were constructed for Parkinson's disease classification, using optimized hyperparameters (RandomizedSearchCV with 5-fold cross-validation). The consistency of RSFC measurements between the two registration methods was poor, whereas the QSM-guided approach showed better mutual information values, suggesting higher registration accuracy. The disruptions of RSFC identified with the QSM-guided approach were more stable and reliable, as confirmed by bootstrap analysis. In classification models, the QSM-guided method consistently outperformed the T1WI-guided method, achieving higher test-set ROC-AUC values (FUNC2QSM: 0.87-0.90, FUNC2T1: 0.67-0.70). The QSM-guided approach effectively enhanced the accuracy of subcortical segmentation and the stability of RSFC measurement, thus facilitating future biomarker development in Parkinson's disease.

YNIMG Journal 2023 Journal Article

High angular resolution susceptibility imaging and estimation of fiber orientation distribution functions in primate brain

Dimitrios G. Gkotsoulias
Roland Müller
Carsten Jäger
Torsten Schlumm
Toralf Mildner
Cornelius Eichner
André Pampel
Jennifer Jaffe

Uncovering brain-tissue microstructure including axonal characteristics is a major neuroimaging research focus. Within this scope, anisotropic properties of magnetic susceptibility in white matter have been successfully employed to estimate primary axonal trajectories using mono-tensorial models. However, anisotropic susceptibility has not yet been considered for modeling more complex fiber structures within a voxel, such as intersecting bundles, or an estimation of orientation distribution functions (ODFs). This information is routinely obtained by high angular resolution diffusion imaging (HARDI) techniques. In applications to fixed tissue, however, diffusion-weighted imaging suffers from an inherently low signal-to-noise ratio and limited spatial resolution, leading to high demands on the performance of the gradient system in order to mitigate these limitations. In the current work, high angular resolution susceptibility imaging (HARSI) is proposed as a novel, phase-based methodology to estimate ODFs. A multiple gradient-echo dataset was acquired in an entire fixed chimpanzee brain at 61 orientations by reorienting the specimen in the magnetic field. The constant solid angle method was adapted for estimating phase-based ODFs. HARDI data were also acquired for comparison. HARSI yielded information on whole-brain fiber architecture, including identification of peaks of multiple bundles that resembled features of the HARDI results. Distinct differences between both methods suggest that susceptibility properties may offer complementary microstructural information. These proof-of-concept results indicate a potential to study the axonal organization in post-mortem primate and human brain at high resolution.

YNIMG Journal 2023 Journal Article

The diamagnetic component map from quantitative susceptibility mapping (QSM) source separation reveals pathological alteration in Alzheimer’s disease-driven neurodegeneration

Maruf Ahmed
Jingjia Chen
Arvin Arani
Matthew L. Senjem
Petrice M. Cogswell
Clifford R. Jack
Chunlei Liu

A sensitive and accurate imaging technique capable of tracking the disease progression of Alzheimer's Disease (AD) driven amnestic dementia would be beneficial. A currently available method for pathology detection in AD with high accuracy is Positron Emission Tomography (PET) imaging, despite certain limitations such as low spatial resolution, off-targeting error, and radiation exposure. Non-invasive MRI scanning with quantitative magnetic susceptibility measurements can be used as a complementary tool. To date, quantitative susceptibility mapping (QSM) has widely been used in tracking deep gray matter iron accumulation in AD. The present work proposes that by compartmentalizing quantitative susceptibility into paramagnetic and diamagnetic components, more holistic information about AD pathogenesis can be acquired. Particularly, diamagnetic component susceptibility (DCS) can be a powerful indicator for tracking protein accumulation in the gray matter (GM), demyelination in the white matter (WM), and relevant changes in the cerebrospinal fluid (CSF). In the current work, voxel-wise group analysis of the WM and the CSF regions show significantly lower |DCS| (the absolute value of DCS) value for amnestic dementia patients compared to healthy controls. Additionally, |DCS| and τ PET standardized uptake value ratio (SUVr) were found to be associated in several GM regions typically affected by τ deposition in AD. Therefore, we propose that the separated diamagnetic susceptibility can be used to track pathological neurodegeneration in different tissue types and regions of the brain. With the initial evidence, we believe the usage of compartmentalized susceptibility demonstrates substantive potential as an MRI-based technique for tracking AD-driven neurodegeneration.

YNIMG Journal 2022 Journal Article

Altered brain iron depositions from aging to Parkinson's disease and Alzheimer's disease: A quantitative susceptibility mapping study

Xiaojun Guan
Tao Guo
Cheng Zhou
Jingjing Wu
Qingze Zeng
Kaicheng Li
Xiao Luo
Xueqin Bai

Brain iron deposition is a promising marker for human brain health, providing insightful information for understanding aging as well as neurodegenerations, e. g. , Parkinson's disease (PD) and Alzheimer's disease (AD). To comprehensively evaluate brain iron deposition along with aging, PD-related neurodegeneration, from prodromal PD (pPD) to clinical PD (cPD), and AD-related neurodegeneration, from mild cognitive impairment (MCI) to AD, a total of 726 participants from July 2013 to December 2020, including 100 young adults, 189 old adults, 184 pPD, 171 cPD, 31 MCI and 51 AD patients, were included. Quantitative susceptibility mapping data were acquired and used to quantify regional magnetic susceptibility, and the resulting spatial standard deviations were recorded. A general linear model was applied to perform the inter-group comparison. As a result, relative to young adults, old adults showed significantly higher iron deposition with higher spatial variation in all of the subcortical nuclei (p < 0. 01). pPD showed a high spatial variation of iron distribution in the subcortical nuclei except for substantia nigra (SN); and iron deposition in SN and red nucleus (RN) were progressively increased from pPD to cPD (p < 0. 01). AD showed significantly higher iron deposition in caudate and putamen with higher spatial variation compared with old adults, pPD and cPD (p < 0. 01), and significant iron deposition in SN compared with old adults (p < 0. 01). Also, linear regression models had significances in predicting motor score in pPD and cPD (Rmean = 0. 443, Ppermutation = 0. 001) and cognition score in MCI and AD (Rmean = 0. 243, Ppermutation = 0. 037). In conclusion, progressive iron deposition in the SN and RN may characterize PD-related neurodegeneration, namely aging to cPD through pPD. On the other hand, extreme iron deposition in the caudate and putamen may characterize AD-related neurodegeneration.

JBHI Journal 2022 Journal Article

Regularized Asymmetric Susceptibility Tensor Imaging in the Human Brain in Vivo

Yuting Shi
Steven Cao
Xu Li
Ruimin Feng
Jie Zhuang
Yuyao Zhang
Chunlei Liu
Hongjiang Wei

Susceptibility tensor imaging (STI) is a promising tool for studying orientation-dependent tissue magnetic susceptibility and for mapping white matter fiber orientations complementary to diffusion tensor imaging (DTI). However, the limited head rotation range within modern head coils for data acquisition makes in vivo STI reconstruction ill-conditioned. Conventional STI reconstruction method is usually vulnerable to noise and requires sufficiently large head rotations to solve this ill-conditioned inverse problem. In this study, based on the recently proposed asymmetric STI (aSTI) model, a new method termed aSTI+ was proposed to improve in vivo STI reconstruction by enforcing isotropic susceptibility tensor inside cerebrospinal fluid (CSF) and applying morphology constraint in white matter. Experimental results showed superior performance of the proposed method with reduced noise, improved tissue contrast and better fiber orientation estimation over previous methods. Thus aSTI+ may promote in vivo human brain STI studies on white matter and myelin-related brain diseases.

YNICL Journal 2022 Journal Article

Thrombus magnetic susceptibility is associated with recanalization and clinical outcome in patients with ischemic stroke

Jie Chen
Zhe Zhang
Ximing Nie
Yuyuan Xu
Chunlei Liu
Xingquan Zhao
Zhongrong Miao
Yongjun Wang

In acute ischemic stroke patients with large vessel occlusion, the characteristics of the occluding thrombus on neuroimaging may be associated with recanalization after endovascular thrombectomy (EVT); however, the relationship between magnetic susceptibility of thrombus and clinical outcome remains unclear. We utilized quantitative susceptibility mapping (QSM) MRI to assess the magnetic susceptibility of thrombus in acute ischemic stroke patients undergoing EVT, and to evaluate its relationship with recanalization and functional outcomes. Patients with documented intracranial artery occlusion were consecutively recruited from one research center of the RESCUE-RE study (a registration study for Critical Care of Acute Ischemic Stroke After Recanalization). All the recruited patients underwent a 3D multi-echo MRI scan on a 3.0 T scanner for both susceptibility-weighted imaging (SWI) and QSM quantification of the thrombus. Among 61 patients included in the analyses, 51 (75.0 %) patients achieved thrombolysis in cerebral infarction (TICI) 2b/3 and 22 (36.1 %) patients had favorable functional outcomes. Successful recanalization was significantly associated with a higher thrombus magnetic susceptibility mean value (0.27 ± 0.09 vs 0.20 ± 0.09 ppm, p = 0.020) and lower coefficient of variation (0.42 ± 0.12 vs 0.52 ± 0.19, p = 0.024). ROC curve analysis showed the optimal cutoff value for thrombus susceptibility for predicting good clinical outcomes was 0.25 ppm (sensitivity 86.4 %, specificity 69.2 %). In multivariable logistic regression analyses, increased thrombus magnetic susceptibility was independently and significantly associated with good functional outcomes (adjusted odds ratio 15.11 [95 % confidence interval 2.64-86.46], p = 0.002). This study demonstrated that the increased thrombus magnetic susceptibility is associated with successful recanalization and favorable functional outcomes for intracranial artery occluded stroke patients.

YNIMG Journal 2021 Journal Article

Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data

Jingjia Chen
Nan-Jie Gong
Khallil Taverna Chaim
Maria Concepción García Otaduy
Chunlei Liu

PURPOSE: A method named DECOMPOSE-QSM is developed to decompose bulk susceptibility measured with QSM into sub-voxel paramagnetic and diamagnetic components based on a three-pool complex signal model. METHODS: Multi-echo gradient echo signal is modeled as a summation of three weighted exponentials corresponding to three types of susceptibility sources: reference susceptibility, diamagnetic and paramagnetic susceptibility relative to the reference. Paramagnetic component susceptibility (PCS) and diamagnetic component susceptibility (DCS) maps are constructed to represent the sub-voxel compartments by solving for linear and nonlinear parameters in the model. RESULTS: Numerical forward simulation and phantom validation confirmed the ability of DECOMPOSE-QSM to separate the mixture of paramagnetic and diamagnetic components. The PCS obtained from temperature-variant brainstem imaging follows the Curie's Law, which further validated the model and the solver. Initial in vivo investigation of human brain images showed the ability to extract sub-voxel PCS and DCS sources that produce visually enhanced contrast between brain structures comparing to threshold QSM.

YNIMG Journal 2021 Journal Article

MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping

Ruimin Feng
Jiayi Zhao
He Wang
Baofeng Yang
Jie Feng
Yuting Shi
Ming Zhang
Chunlei Liu

Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms ( χ 13, χ 23 and χ 33 ) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ 33 and phase induced by χ 13 and χ 23 terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications.

AAAI Conference 2021 Conference Paper

SA-BNN: State-Aware Binary Neural Network

Chunlei Liu
Peng Chen
Bohan Zhuang
Chunhua Shen
Baochang Zhang
Wenrui Ding

Binary Neural Networks (BNNs) have received significant attention due to the memory and computation efficiency recently. However, the considerable accuracy gap between BNNs and their full-precision counterparts hinders BNNs to be deployed to resource-constrained platforms. One of the main reasons for the performance gap can be attributed to the frequent weight flip, which is caused by the misleading weight update in BNNs. To address this issue, we propose a state-aware binary neural network (SA-BNN) equipped with the well designed stateaware gradient. Our SA-BNN is inspired by the observation that the frequent weight flip is more likely to occur, when the gradient magnitude for all quantization states {−1, 1} is identical. Accordingly, we propose to employ independent gradient coefficients for different states when updating the weights. Furthermore, we also analyze the effectiveness of the state-aware gradient on suppressing the frequent weight flip problem. Experiments on ImageNet show that the proposed SA-BNN outperforms the current state-of-the-arts (e. g. , Bi-Real Net) by more than 3% when using a ResNet architecture. Specifically, we achieve 61. 7%, 65. 5% and 68. 7% Top-1 accuracy with ResNet-18, ResNet-34 and ResNet-50 on ImageNet, respectively.

AAAI Conference 2021 Conference Paper

TRQ: Ternary Neural Networks With Residual Quantization

Yue Li
Wenrui Ding
Chunlei Liu
Baochang Zhang
Guodong Guo

Ternary neural networks (TNNs) are potential for network acceleration by reducing the full-precision weights in network to ternary ones, e. g. , {−1, 0, 1}. However, existing TNNs are mostly calculated based on rule-of-thumb quantization methods by simply thresholding operations, which causes a significant accuracy loss. In this paper, we introduce a stemresidual framework which provides new insight into ternary quantization, termed Ternary Residual Quantization (TRQ), to achieve more powerful TNNs. Rather than directly thresholding operations, TRQ recursively performs quantization on full-precision weights for a refined reconstruction by combining the binarized stem and residual parts. With such a unique quantization process, TRQ endows the quantizer with high flexibility and precision. Furthermore, our TRQ is generic, which can be easily extended to multiple bits through recursively encoded residual for a better recognition accuracy. Extensive experimental results demonstrate that the proposed method yields great recognition accuracy while being accelerated.

YNIMG Journal 2019 Journal Article

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

Nan-Jie Gong
Russell Dibb
Marjolein Bulk
Louise van der Weerd
Chunlei Liu

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

YNIMG Journal 2019 Journal Article

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

Hongjiang Wei
Steven Cao
Yuyao Zhang
Xiaojun Guan
Fuhua Yan
Kristen W. Yeom
Chunlei Liu

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.

YNIMG Journal 2019 Journal Article

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

Xu Li
Lin Chen
Kwame Kutten
Can Ceritoglu
Yue Li
Ningdong Kang
John T. Hsu
Ye Qiao

Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0. 77 ± 0. 09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0. 79 ± 0. 07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0. 79 ± 0. 08 to manual labels and 0. 89 ± 0. 04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0. 97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www. mricloud. org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

YNIMG Journal 2019 Journal Article

Neonate and infant brain development from birth to 2 years assessed using MRI-based quantitative susceptibility mapping

Yuyao Zhang
Jingjing Shi
Hongjiang Wei
Victor Han
Wen-Zhen Zhu
Chunlei Liu

The human brain rapidly develops during the first two years following birth. Quantitative susceptibility mapping (QSM) provides information of iron and myelin variations. It is considered to be a valuable tool for studying brain development in early life. In the present work, QSM is performed on neonates, 1-year and 2-year old infants, as well as a group of adults for the purpose of reference. Age-specific templates representing common brain structures are built for each age group. The neonate and infant QSM templates have shown some unique findings compared to conventional T1w and T2w imaging techniques. The contrast between the gray and white matters on the QSM images did not change through brain development from neonate to adult. A linear correlation was found between brain myelination determined in this study and the microscopic myelin degree determined by a previous autopsy study. Also, the magnetic susceptibility values of the cerebral spinal fluid (CSF) exhibit a gradually decreasing trend from birth to 2 years old and to adulthood. The findings suggest that the macromolecular content, myelin, and iron may play the most important contributing factors for the magnetic susceptibility of neonate and infant brain. QSM can be a powerful means to study early brain development and related pathologies that involve alterations in macromolecular content, iron, or brain myelination.

IJCAI Conference 2019 Conference Paper

Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs

Chunlei Liu
Wenrui Ding
Xin Xia
Yuan Hu
Baochang Zhang
Jianzhuang Liu
Bohan Zhuang
Guodong Guo

Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (DCNNs) for mobile and AI chips based applications. However, current BCNNs are not able to fully explore their corresponding full-precision models, causing a significant performance gap between them. In this paper, we propose rectified binary convolutional networks (RBCNs), towards optimized BCNNs, by combining full-precision kernels and feature maps to rectify the binarization process in a unified framework. In particular, we use a GAN to train the 1-bit binary network with the guidance of its corresponding full-precision model, which significantly improves the performance of BCNNs. The rectified convolutional layers are generic and flexible, and can be easily incorporated into existing DCNNs such as WideResNets and ResNets. Extensive experiments demonstrate the superior performance of the proposed RBCNs over state-of-the-art BCNNs. In particular, our method shows strong generalization on the object tracking task.

YNIMG Journal 2018 Journal Article

Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping

Yuyao Zhang
Hongjiang Wei
Matthew J. Cronin
Naying He
Fuhua Yan
Chunlei Liu

Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 1–83 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i. e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a “whole brain QSM parcellation map” by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases.

YNIMG Journal 2018 Journal Article

MRI gradient-echo phase contrast of the brain at ultra-short TE with off-resonance saturation

Hongjiang Wei
Peng Cao
Antje Bischof
Roland G. Henry
Peder E.Z. Larson
Chunlei Liu

Larmor-frequency shift or image phase measured by gradient-echo sequences has provided a new source of MRI contrast. This contrast is being used to study both the structure and function of the brain. So far, phase images of the brain have been largely obtained at long echo times as maximum phase signal-to-noise ratio (SNR) is achieved at TE = T2* (∼40 ms at 3T). The structures of the brain, however, are compartmentalized and complex with a wide range of signal relaxation times. At such long TE, the short-T2 components are largely attenuated and contribute minimally to phase contrast. The purpose of this study was to determine whether proton gradient-echo images of the brain exhibit phase contrast at ultra-short TE (UTE). Our data showed that UTE images acquired at 7 T without off-resonance saturation do not contain significant phase contrast between gray and white matter. However, UTE images of the brain can attain strong phase contrast even at a nominal TE of 106 μs by using off-resonance RF saturation pulses, which provide direct saturation of ultra-short-T2 components and indirect saturation of longer-T2 components via magnetization transfer. In addition, phase contrast between gray and white matter acquired at UTE with off-resonance saturation is reversed compared to that of the long-T2 signals acquired at long TEs. This finding opens up a potential new way to manipulate image phase contrast of the brain. By accessing short and ultra-short-T2 species, MRI phase images may further improve the characterization of tissue microstructure in the brain.

YNIMG Journal 2017 Journal Article

Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds

Matthew J. Cronin
Nian Wang
Kyle S. Decker
Hongjiang Wei
Wen-Zhen Zhu
Chunlei Liu

Quantitative susceptibility mapping (QSM) is increasingly used to measure variation in tissue composition both in the brain and in other areas of the body in a range of disease pathologies. Although QSM measurements were originally believed to be independent of the echo time (TE) used in the gradient-recalled echo (GRE) acquisition from which they are derived; recent literature (Sood et al. , 2016) has shown that these measurements can be highly TE-dependent in a number of brain regions. In this work we systematically investigate possible causes of this effect through analysis of apparent frequency and QSM measurements derived from data acquired at multiple TEs in vivo in healthy brain regions and in cerebral microbleeds (CMBs); QSM data acquired in a gadolinium-doped phantom; and in QSM data derived from idealized simulated phase data. Apparent frequency measurements in the optic radiations (OR) and central corpus callosum (CC) were compared to those predicted by a 3-pool white matter model, however the model failed to fully explain contrasting frequency profiles measured in the OR and CC. Our results show that TE-dependent QSM measurements can be caused by a failure of phase unwrapping algorithms in and around strong susceptibility sources such as CMBs; however, in healthy brain regions this behavior appears to result from intrinsic non-linear phase evolution in the MR signal. From these results we conclude that care must be taken when deriving frequency and QSM measurements in strong susceptibility sources due to the inherent limitations in phase unwrapping; and that while signal compartmentalization due to tissue microstructure and content is a plausible cause of TE-dependent frequency and QSM measurements in healthy brain regions, better sampling of the MR signal and more complex models of tissue are needed to fully exploit this relationship.

YNIMG Journal 2016 Journal Article

Imaging whole-brain cytoarchitecture of mouse with MRI-based quantitative susceptibility mapping

Hongjiang Wei
Luke Xie
Russell Dibb
Wei Li
Kyle Decker
Yuyao Zhang
G. Allan Johnson
Chunlei Liu

The proper microstructural arrangement of complex neural structures is essential for establishing the functional circuitry of the brain. We present an MRI method to resolve tissue microstructure and infer brain cytoarchitecture by mapping the magnetic susceptibility in the brain at high resolution. This is possible because of the heterogeneous magnetic susceptibility created by varying concentrations of lipids, proteins and irons from the cell membrane to cytoplasm. We demonstrate magnetic susceptibility maps at a nominal resolution of 10-μm isotropic, approaching the average cell size of a mouse brain. The maps reveal many detailed structures including the retina cell layers, olfactory sensory neurons, barrel cortex, cortical layers, axonal fibers in white and gray matter. Olfactory glomerulus density is calculated and structural connectivity is traced in the optic nerve, striatal neurons, and brainstem nerves. The method is robust and can be readily applied on MRI scanners at or above 7T.

YNIMG Journal 2016 Journal Article

Magnetic susceptibility of brain iron is associated with childhood spatial IQ

Kimberly L.H. Carpenter
Wei Li
Hongjiang Wei
Bing Wu
Xue Xiao
Chunlei Liu
Gordon Worley
Helen Link Egger

Iron is an essential micronutrient for healthy brain function and development. Because of the importance of iron in the brain, iron deficiency results in widespread and lasting effects on behavior and cognition. We measured iron in the basal ganglia of young children using a novel MRI method, quantitative susceptibility mapping, and examined the association of brain iron with age and cognitive performance. Participants were a community sample of 39 young children recruited from pediatric primary care who were participating in a 5-year longitudinal study of child brain development and anxiety disorders. The children were ages 7 to 11years old (mean age: 9. 5years old) at the time of the quantitative susceptibility mapping scan. The differential abilities scale was administered when the children were 6years old to provide a measure of general intelligence and verbal (receptive and expressive), non-verbal, and spatial performance. Magnetic susceptibility values, which are linearly related to iron concentration in iron-rich areas, were extracted from regions of interest within iron-rich deep gray matter nuclei from the basal ganglia, including the caudate, putamen, substantia nigra, globus pallidus, and thalamus. Controlling for scan age, there was a significant positive association between iron in the basal ganglia and spatial IQ, with this effect being driven by iron in the right caudate We also replicated previous findings of a significant positive association between iron in the bilateral basal ganglia and age. Our finding of a positive association between spatial IQ and mean iron in the basal ganglia, and in the caudate specifically, suggests that iron content in specific regions of the iron-rich deep nuclei of the basal ganglia influences spatial intelligence. This provides a potential neurobiological mechanism linking deficits in spatial abilities reported in children who were severely iron deficient as infants to decreased iron within the caudate.

YNIMG Journal 2016 Journal Article

Rapid multi-orientation quantitative susceptibility mapping

Berkin Bilgic
Luke Xie
Russell Dibb
Christian Langkammer
Aysegul Mutluay
Huihui Ye
Jonathan R. Polimeni
Jean Augustinack

Three-dimensional gradient echo (GRE) is the main workhorse sequence used for susceptibility weighted imaging (SWI), quantitative susceptibility mapping (QSM), and susceptibility tensor imaging (STI). Achieving optimal phase signal-to-noise ratio requires late echo times, thus necessitating a long repetition time (TR). Combined with the large encoding burden of whole-brain coverage with high resolution, this leads to increased scan time. Further, the dipole kernel relating the tissue phase to the underlying susceptibility distribution undersamples the frequency content of the susceptibility map. Scans at multiple head orientations along with calculation of susceptibility through multi-orientation sampling (COSMOS) are one way to effectively mitigate this issue. Additionally, STI requires a minimum of 6 head orientations to solve for the independent tensor elements in each voxel. The requirements of high-resolution imaging with long TR at multiple orientations substantially lengthen the acquisition of COSMOS and STI. The goal of this work is to dramatically speed up susceptibility mapping at multiple head orientations. We demonstrate highly efficient acquisition using 3D-GRE with Wave-CAIPI and dramatically reduce the acquisition time of these protocols. Using R=15-fold acceleration with Wave-CAIPI permits acquisition per head orientation in 90s at 1. 1mm isotropic resolution, and 5: 35min at 0. 5mm isotropic resolution. Since Wave-CAIPI fully harnesses the 3D spatial encoding capability of receive arrays, the maximum g-factor noise amplification remains below 1. 30 at 3T and 1. 12 at 7T. This allows a 30-min exam for STI with 12 orientations, thus paving the way to its clinical application.

YNIMG Journal 2015 Journal Article

A method for estimating and removing streaking artifacts in quantitative susceptibility mapping

Wei Li
Nian Wang
Fang Yu
Hui Han
Wei Cao
Rebecca Romero
Bundhit Tantiwongkosi
Timothy Q. Duong

Quantitative susceptibility mapping (QSM) is a novel MRI method for quantifying tissue magnetic property. In the brain, it reflects the molecular composition and microstructure of the local tissue. However, susceptibility maps reconstructed from single-orientation data still suffer from streaking artifacts which obscure structural details and small lesions. We propose and have developed a general method for estimating streaking artifacts and subtracting them from susceptibility maps. Specifically, this method uses a sparse linear equation and least-squares (LSQR)-algorithm-based method to derive an initial estimation of magnetic susceptibility, a fast quantitative susceptibility mapping method to estimate the susceptibility boundaries, and an iterative approach to estimate the susceptibility artifact from ill-conditioned k-space regions only. With a fixed set of parameters for the initial susceptibility estimation and subsequent streaking artifact estimation and removal, the method provides an unbiased estimate of tissue susceptibility with negligible streaking artifacts, as compared to multi-orientation QSM reconstruction. This method allows for improved delineation of white matter lesions in patients with multiple sclerosis and small structures of the human brain with excellent anatomical details. The proposed methodology can be extended to other existing QSM algorithms.

YNIMG Journal 2015 Journal Article

Association between increased magnetic susceptibility of deep gray matter nuclei and decreased motor function in healthy adults

Wei Li
Christian Langkammer
Ying-hui Chou
Katja Petrovic
Reinhold Schmidt
Allen W. Song
David J. Madden
Stefan Ropele

In the human brain, iron is more prevalent in gray matter than in white matter, and deep gray matter structures, particularly the globus pallidus, putamen, caudate nucleus, substantia nigra, red nucleus, and dentate nucleus, exhibit especially high iron content. Abnormally elevated iron levels have been found in various neurodegenerative diseases. Additionally, iron overload and related neurodegeneration may also occur during aging, but the functional consequences are not clear. In this study, we explored the correlation between magnetic susceptibility — a surrogate marker of brain iron — of these gray matter structures with behavioral measures of motor and cognitive abilities, in 132 healthy adults aged 40–83years. Latent variables corresponding to manual dexterity and executive functions were obtained using factor analysis. The factor scores for manual dexterity declined significantly with increasing age. Independent of gender, age, and global cognitive function, increasing magnetic susceptibility in the globus pallidus and red nuclei was associated with decreasing manual dexterity. This finding suggests the potential value of magnetic susceptibility, a non-invasive quantitative imaging marker of iron, for the study of iron-related brain function changes.

YNIMG Journal 2014 Journal Article

Prenatal alcohol exposure reduces magnetic susceptibility contrast and anisotropy in the white matter of mouse brains

Wei Cao
Wei Li
Hui Han
Shonagh K. O'Leary-Moore
Kathleen K. Sulik
G. Allan Johnson
Chunlei Liu

Prenatal alcohol exposure can result in long-term cognitive and behavioral deficits. Fetal alcohol spectrum disorder (FASD) refers to a range of permanent birth defects caused by prenatal alcohol exposure, and is the most common neurodevelopmental disorder in the US. Studies by autopsy and conventional structural MRI indicate that the midline structures of the brain are particularly vulnerable to prenatal alcohol exposure. Diffusion tensor imaging (DTI) has shown that abnormalities in brain white matter especially the corpus callosum are very common in FASD. Quantitative susceptibility mapping (QSM) is a novel technique that measures tissue's magnetic property. Such magnetic property is affected by tissue microstructure and molecular composition including that of myelin in the white matter. In this work, we studied three major white matter fiber bundles of a mouse model of FASD and compared it to control mice using both QSM and DTI. QSM revealed clear and significant abnormalities in anterior commissure, corpus callosum, and hippocampal commissure, which were likely due to reduced myelination. Our data also suggested that QSM may be even more sensitive than DTI for examining changes due to prenatal alcohol exposure. Although this is a preclinical study, the technique of QSM is readily translatable to human brain.

YNIMG Journal 2014 Journal Article

Quantitative magnetic susceptibility of the developing mouse brain reveals microstructural changes in the white matter

Ioannis Argyridis
Wei Li
G. Allan Johnson
Chunlei Liu

Cerebral development involves a complex cascade of events which are difficult to visualize and quantify in vivo. In this study we combine information from Diffusion Tensor Imaging (DTI) and Quantitative Susceptibility Mapping (QSM) to analyze developing mouse brains at five stages up to 56days postnatal. Susceptibility maps were calculated using frequency shifts in gradient echo MR images acquired at 9. 4T. The mean apparent magnetic susceptibility and magnetic susceptibility anisotropy of major white matter tracts were evaluated as a function of age. During the first two weeks, susceptibility of white matter appeared paramagnetic relative to surrounding gray matter; it then gradually became more diamagnetic. While diffusion anisotropy was already apparent and high at postnatal day 2, susceptibility anisotropy only became significant during the third week. This mismatch indicated different microstructural underpinnings for diffusion anisotropy and susceptibility anisotropy. Histological exams were also performed to evaluate myelin and iron content. It is confirmed that the main source of susceptibility contrast in WM is the myelin content. The ability to quantify the magnetic properties of white matter will provide valuable information on the architecture of the brain during development and potentially a more specific indicator for myelin degenerative diseases.

YNIMG Journal 2013 Journal Article

Imaging neural architecture of the brain based on its multipole magnetic response

Chunlei Liu
Wei Li

Although magnetic fields interact weakly with biological tissues, at high fields, this interaction is sufficiently strong to cause measurable shifts in the Larmor frequency among various tissue types. While measuring frequency shift and its anisotropy has enabled NMR spectroscopy to determine structures of large molecules, MRI has not been able to fully utilize the vast information existing in the frequency to elucidate tissue microstructure. Using a multipole analysis of the complex MRI signal in the Fourier spectral space, we developed a fast and high-resolution method that enables the quantification of tissue's magnetic response with a set of magnetic susceptibility tensors of various ranks. The Fourier spectral space, termed p-space, can be generated by applying field gradients or equivalently by shifting the k-space data in various directions. Measuring these tensors allows the visualization and quantification of tissue architecture. We performed 3D whole-brain multipole susceptibility tensor imaging in simulation, on intact mouse brains ex vivo and on human brains in vivo. We showed that these multipole susceptibility tensors can be used to image orientations of ordered white matter fibers. These experiments demonstrate that multipole tensor analysis may enable practical mapping of tissue microstructure in vivo without rotating subject or magnetic field.

YNIMG Journal 2012 Journal Article

3D fiber tractography with susceptibility tensor imaging

Chunlei Liu
Wei Li
Bing Wu
Yi Jiang
G. Allan Johnson

Gradient-echo MRI has revealed anisotropic magnetic susceptibility in the brain white matter. This magnetic susceptibility anisotropy can be measured and characterized with susceptibility tensor imaging (STI). In this study, a method of fiber tractography based on STI is proposed and demonstrated in the mouse brain. STI experiments of perfusion-fixed mouse brains were conducted at 7. 0T. The magnetic susceptibility tensor was calculated for each voxel with regularization and decomposed into its eigensystem. The major eigenvector is found to be aligned with the underlying fiber orientation. Following the orientation of the major eigenvector, we are able to map distinctive fiber pathways in 3D. As a comparison, diffusion tensor imaging (DTI) and DTI fiber tractography were also conducted on the same specimens. The relationship between STI and DTI fiber tracts was explored with similarities and differences identified. It is anticipated that the proposed method of STI tractography may provide a new way to study white matter fiber architecture. As STI tractography is based on physical principles that are fundamentally different from DTI, it may also be valuable for the ongoing validation of DTI tractography.

YNIMG Journal 2012 Journal Article

Fast and tissue-optimized mapping of magnetic susceptibility and T2* with multi-echo and multi-shot spirals

Bing Wu
Wei Li
Alexandru Vlad Avram
Sung-Min Gho
Chunlei Liu

Gradient-echo MRI of resonance-frequency shift and T2* values exhibit unique tissue contrast and offer relevant physiological information. However, acquiring 3D-phase images and T2* maps with the standard spoiled gradient echo (SPGR) sequence is lengthy for routine imaging at high-spatial resolution and whole-brain coverage. In addition, with the standard SPGR sequence, optimal signal-to-noise ratio (SNR) cannot be achieved for every tissue type given their distributed resonance frequency and T2* value. To address these two issues, a SNR optimized multi-echo sequence with a stack-of-spiral acquisition is proposed and implemented for achieving fast and simultaneous acquisition of image phase and T2* maps. The analytical behavior of the phase SNR is derived as a function of resonance frequency, T2* and echo time. This relationship is utilized to achieve tissue optimized SNR by combining phase images with different echo times. Simulations and in vivo experiments were designed to verify the theoretical predictions. Using the multi-echo spiral acquisition, whole-brain coverage with 1mm isotropic resolution can be achieved within 2. 5min, shortening the scan time by a factor of 8. The resulting multi-echo phase map shows similar SNR to that of the standard SPGR. The acquisition can be further accelerated with non-Cartesian parallel imaging. The technique can be readily extended to other multi-shot readout trajectories besides spiral. It may provide a practical acquisition strategy for high resolution and simultaneous 3D mapping of magnetic susceptibility and T2*.

YNIMG Journal 2012 Journal Article

Magnetic susceptibility anisotropy of human brain in vivo and its molecular underpinnings

Wei Li
Bing Wu
Alexandru V. Avram
Chunlei Liu

Frequency shift of gradient-echo MRI provides valuable information for assessing brain tissues. Recent studies suggest that the frequency and susceptibility contrast depend on white matter fiber orientation. However, the molecular underpinning of the orientation dependence is unclear. In this study, we investigated the orientation dependence of susceptibility of human brain in vivo and mouse brains ex vivo. The source of susceptibility anisotropy in white matter is likely to be myelin as evidenced by the loss of anisotropy in the dysmyelinating shiverer mouse brain. A biophysical model is developed to investigate the effect of the molecular susceptibility anisotropy of myelin components, especially myelin lipids, on the bulk anisotropy observed by MRI. This model provides a consistent interpretation of the orientation dependence of macroscopic magnetic susceptibility in normal mouse brain ex vivo and human brain in vivo and the microscopic origin of anisotropic susceptibility. It is predicted by the theoretical model and illustrated by the experimental data that the magnetic susceptibility of the white matter is least diamagnetic along the fiber direction. This relationship allows an efficient extraction of fiber orientation using susceptibility tensor imaging. These results suggest that anisotropy on the molecular level can be observed on the macroscopic level when the molecules are aligned in a highly ordered manner. Similar to the utilization of magnetic susceptibility anisotropy in elucidating molecular structures, imaging magnetic susceptibility anisotropy may also provide a useful tool for elucidating the microstructure of ordered biological tissues.

YNIMG Journal 2011 Journal Article

High-field (9.4T) MRI of brain dysmyelination by quantitative mapping of magnetic susceptibility

Chunlei Liu
Wei Li
G. Allan Johnson
Bing Wu

The multilayered myelin sheath wrapping around nerve axons is essential for proper functioning of the central nervous system. Abnormal myelination leads to a wide range of neurological diseases and developmental disorders. Non-invasive imaging of myelin content is of great clinical importance. The present work demonstrated that loss of myelin in the central nervous system of the shiverer mouse results in a dramatic reduction of magnetic susceptibility in white matter axons. The reduction resulted in a near extinction of susceptibility contrast between gray and white matter. Quantitative magnetic susceptibility imaging and diffusion tensor imaging were conducted on a group of control and shiverer mice at 9. 4T. We measured the resonance frequency distribution of the whole brain for each mouse. Magnetic susceptibility maps were computed and compared between the two groups. It was shown that the susceptibility contrast between gray and white matter was reduced by 96% in the shiverer compared to the controls. Diffusion measurements further confirmed intact fiber pathways in the shiverer mice, ruling out the possibility of axonal injury and its potential contribution to the altered susceptibility. As an autosomal recessive mutation, shiverer is characterized by an almost total lack of central nervous system myelin. Our data provide new evidences indicating that myelin is the predominant source of susceptibility differences between deep gray and white matter observed in magnetic resonance imaging. More importantly, the present study suggests that quantitative magnetic susceptibility is a potential endogenous biomarker for myelination.

YNIMG Journal 2011 Journal Article

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

Wei Li
Bing Wu
Chunlei Liu

Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter micro-architectures.