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Qi W, Niu X, Zhan X, Ren Y, He J, Li J, Hou X, Li H. Multimodal magnetic resonance imaging studies on non-motor symptoms of Parkinson's disease. IBRO Neurosci Rep 2025; 18:180-190. [PMID: 39896716 PMCID: PMC11787613 DOI: 10.1016/j.ibneur.2025.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Accepted: 01/04/2025] [Indexed: 02/04/2025] Open
Abstract
Objective This study aims to investigate the diagnostic value of multi-modal magnetic resonance imaging (MRI) utilizing arterial spin labeling (ASL), quantitative susceptibility mapping (QSM), and 3D T1-weighted imaging (3DT1WI) in patients with Parkinson's disease (PD). Additionally, it evaluates the relationship between MRI findings and non-motor symptoms associated with PD. Methods ASL, QSM, and 3DT1WI scans were performed on 48 PD patients and 46 healthy controls (HC). We extracted and analyzed differences in regional cerebral blood flow (rCBF), magnetic susceptibility, and gray matter density parameters between the two groups. These MRI parameters were correlated with clinical scale scores assessing non-motor symptoms, including cognitive function, sleep quality, olfaction, autonomic function, anxiety, depression, and fatigue. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of each imaging modality in distinguishing PD from HC. Results The areas under the ROC curve (AUC) for rCBF, magnetic susceptibility, and gray matter density were 0.941, 0.979, and 0.624, respectively. In PD patients, a negative correlation was found between Unified Parkinson's Disease Rating Scale Part II (UPDRS II) scores and rCBF in the bilateral precuneus. The Pittsburgh Sleep Quality Index (PSQI) scores negatively correlated with rCBF in the left middle temporal gyrus and right middle occipital gyrus. Hamilton Depression Rating Scale (HAMD) scores positively correlated with QSM values in the right supplementary motor area, while scores on the Argentine Smell Identification Test (AHRS) negatively correlated with QSM values in the same area. Disease duration showed a positive correlation with QSM values in the right middle cingulate gyrus. Additionally, PSQI scores positively correlated with QSM values in the left middle cingulate gyrus, and fatigue severity scale (FSS) scores also positively correlated with QSM values in the left middle cingulate gyrus. Gray matter atrophy in the left inferior temporal gyrus was associated with cognitive impairment in PD. Conclusion Occipital hypoperfusion and cortical atrophy in the left inferior temporal gyrus may serve as novel imaging biomarkers for PD and are associated with sleep disturbances and cognitive impairment in PD patients. Extensive iron deposition in the bilateral cerebral cortex of PD patients may be a contributing factor to non-motor symptoms such as sleep disturbances and fatigue. Multimodal imaging techniques, including ASL, QSM, and 3DT1WI, can enhance the diagnostic accuracy for PD.
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Affiliation(s)
| | | | - Xiuping Zhan
- Neurology Department, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Yazhou Ren
- Neurology Department, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Jianhang He
- Neurology Department, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Jianxia Li
- Neurology Department, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Xiaolin Hou
- Neurology Department, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Haining Li
- Neurology Department, General Hospital of Ningxia Medical University, Yinchuan 750004, China
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Şişman M, Nguyen TD, Roberts AG, Romano DJ, Dimov AV, Kovanlikaya I, Spincemaille P, Wang Y. Microstructure-Informed Myelin Mapping (MIMM) from routine multi-echo gradient echo data using multiscale physics modeling of iron and myelin effects and QSM. Magn Reson Med 2025; 93:1499-1515. [PMID: 39552224 DOI: 10.1002/mrm.30369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 10/08/2024] [Accepted: 10/21/2024] [Indexed: 11/19/2024]
Abstract
PURPOSE Myelin quantification is used in the study of demyelination in neurodegenerative diseases. A novel noninvasive MRI method, Microstructure-Informed Myelin Mapping (MIMM), is proposed to quantify the myelin volume fraction (MVF) from a routine multi-gradient echo sequence (mGRE) using a multiscale biophysical signal model of the effects of microstructural myelin and iron. THEORY AND METHODS In MIMM, the effects of myelin are modeled based on the Hollow Cylinder Fiber Model accounting for anisotropy, while iron is considered as an isotropic paramagnetic point source. This model is used to create a dictionary of mGRE magnitude signal evolution and total voxel susceptibility using finite elements of size 0.2 μm. Next, voxel-by-voxel stochastic matching pursuit between acquired mGRE data (magnitude+QSM) and the pre-computed dictionary generates quantitative MVF and iron susceptibility maps. Dictionary matching was evaluated under three conditions: (1) without fiber orientation (basic), (2) with fiber orientation obtained using DTI, and (3) with fiber orientation obtained using an atlas (atlas). MIMM was compared with the three-pool complex fitting (3PCF) using T2-relaxometry myelin water fraction (MWF) map as reference. RESULTS The DTI MIMM and atlas MIMM approaches were equally effective in reducing the overestimation of MVF in certain white matter tracts observed in the basic MIMM approach, and they both showed good agreement with T2-relaxometry MWF. MIMM MVF reduced myelin overestimation of globus pallidus observed in 3PCF MWF. CONCLUSION MIMM processing of mGRE data can provide MVF maps from routine clinical scans without requiring special sequences.
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Affiliation(s)
- Mert Şişman
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornel Medicine, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornel Medicine, New York, New York, USA
| | - Alexandra G Roberts
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornel Medicine, New York, New York, USA
| | - Dominick J Romano
- Department of Radiology, Weill Cornel Medicine, New York, New York, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Alexey V Dimov
- Department of Radiology, Weill Cornel Medicine, New York, New York, USA
| | | | | | - Yi Wang
- Department of Radiology, Weill Cornel Medicine, New York, New York, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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Plähn NMJ, Safarkhanlo Y, Açikgöz BC, Mackowiak ALC, Radojewski P, Bonanno G, Peper ES, Heule R, Bastiaansen JAM. ORACLE: An analytical approach for T 1, T 2, proton density, and off-resonance mapping with phase-cycled balanced steady-state free precession. Magn Reson Med 2025; 93:1657-1673. [PMID: 39710877 DOI: 10.1002/mrm.30388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2024] [Revised: 11/08/2024] [Accepted: 11/09/2024] [Indexed: 12/24/2024]
Abstract
PURPOSE To develop and validate a novel analytical approach simplifyingT 1 $$ {T}_1 $$ ,T 2 $$ {T}_2 $$ , proton density (PD), and off-resonanceΔ f $$ \Delta f $$ quantifications from phase-cycled balanced steady-state free precession (bSSFP) data. Additionally, to introduce a method to correct aliasing effects in undersampled bSSFP profiles. THEORY AND METHODS Off-resonant-encoded analytical parameter quantification using complex linearized equations (ORACLE) provides analytical solutions for bSSFP profiles. which instantaneously quantifyT 1 $$ {T}_1 $$ ,T 2 $$ {T}_2 $$ , proton density (PD), andΔ f $$ \Delta f $$ . An aliasing correction formalism was derived to allow undersampling of bSSFP profiles. ORACLE was used to quantifyT 1 $$ {T}_1 $$ ,T 2 $$ {T}_2 $$ , PD,T 1 $$ {T}_1 $$ /T 2 $$ {T}_2 $$ , andΔ f $$ \Delta f $$ based on fully sampled (N = 20 $$ N=20 $$ ) bSSFP profiles from numerical simulations and 3T MRI experiments in phantom and 10 healthy subjects' brains. Obtained values were compared with reference scans in the same scan session. Aliasing correction was validated in subsampled (N = 4 $$ N=4 $$ ) bSSFP profiles in numerical simulations and human brains. RESULTS ORACLE quantifications agreed well with input values from simulations and phantom reference values (R2 = 0.99). In human brains,T 1 $$ {T}_1 $$ andT 2 $$ {T}_2 $$ quantifications when compared with reference methods showed coefficients of variation below 2.9% and 3.9%, biases of 182 and 16.6 ms, and mean white-matter values of 642 and 51 ms using ORACLE. TheΔ f $$ \Delta f $$ quantification differed less than 3 Hz between both methods. PD andT 1 $$ {T}_1 $$ maps had comparable histograms. TheΛ $$ \varLambda $$ maps effectively identified cerebrospinal fluid. Aliasing correction removed aliasing-related quantification errors in undersampled bSSFP profiles, significantly reducing scan time. CONCLUSION ORACLE enables simplified and rapid quantification ofT 1 $$ {T}_1 $$ ,T 2 $$ {T}_2 $$ , PD, andΔ f $$ \Delta f $$ from phase-cycled bSSFP profiles, reducing acquisition time and eliminating biomarker maps' coregistration issues.
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Affiliation(s)
- Nils M J Plähn
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences (GCB), University of Bern, Bern, Switzerland
| | - Yasaman Safarkhanlo
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences (GCB), University of Bern, Bern, Switzerland
- Department of Cardiology, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Berk C Açikgöz
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences (GCB), University of Bern, Bern, Switzerland
| | - Adèle L C Mackowiak
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Piotr Radojewski
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- University Institute of Diagnostic and Interventional Neuroradiology, Bern, Switzerland
| | - Gabriele Bonanno
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- University Institute of Diagnostic and Interventional Neuroradiology, Bern, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland
| | - Eva S Peper
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Rahel Heule
- Center for MR Research, University Children's Hospital, Zurich, Switzerland
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
- High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Jessica A M Bastiaansen
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
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de Vries E, Hagbohm C, Ouellette R, Granberg T. Clinical 7 Tesla magnetic resonance imaging: Impact and patient value in neurological disorders. J Intern Med 2025; 297:244-261. [PMID: 39775908 PMCID: PMC11846079 DOI: 10.1111/joim.20059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
Magnetic resonance imaging (MRI) is a cornerstone of non-invasive diagnostics and treatment monitoring, particularly for diseases of the central nervous system. Although 1.5- and 3 Tesla (T) field strengths remain the clinical standard, the advent of 7 T MRI represents a transformative step forward, offering superior spatial resolution, contrast, and sensitivity for visualizing neuroanatomy, metabolism, and function. Recent innovations, including parallel transmission and deep learning-based reconstruction, have resolved many prior technical challenges of 7 T MRI, enabling its routine clinical use. This review examines the diagnostic impact, patient value, and practical considerations of 7 T MRI, emphasizing its role in facilitating earlier diagnoses and improving care in conditions, such as amyotrophic lateral sclerosis (ALS), epilepsy, multiple sclerosis (MS), dementia, parkinsonism, tumors, and vascular diseases. Based on insights from over 1200 clinical scans with a second-generation 7 T system, the review highlights disease-specific biomarkers such as the motor band sign in ALS and the new diagnostic markers in MS, the central vein sign, and paramagnetic rim lesions. The unparalleled ability of 7 T MRI to study neurological diseases ex vivo at ultra-high resolution is also explored, offering new opportunities to understand pathophysiology and identify novel treatment targets. Additionally, the review provides a clinical perspective on patient handling and safety considerations, addressing challenges and practicalities associated with clinical 7 T MRI. By bridging research and clinical practice, 7 T MRI has the potential to redefine neuroimaging and advance the understanding and management of complex neurological disorders.
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Affiliation(s)
- Elisabeth de Vries
- Department of NeuroradiologyKarolinska University HospitalStockholmSweden
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | - Caroline Hagbohm
- Department of NeuroradiologyKarolinska University HospitalStockholmSweden
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | - Russell Ouellette
- Department of NeuroradiologyKarolinska University HospitalStockholmSweden
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | - Tobias Granberg
- Department of NeuroradiologyKarolinska University HospitalStockholmSweden
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
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Boğa Ç, Henning A. Bilateral orthogonality generative acquisitions method for homogeneous T 2 * images using parallel transmission at 7 T. Magn Reson Med 2025; 93:1043-1058. [PMID: 39375826 DOI: 10.1002/mrm.30329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 09/14/2024] [Accepted: 09/18/2024] [Indexed: 10/09/2024]
Abstract
PURPOSE The novel bilateral orthogonality generative acquisitions method has been developed for homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ images without the effects of transmit field inhomogeneity using a parallel-transmission (pTx) system at 7 T. THEORY AND METHODS A new method has been introduced using four low-angle gradient-echo (GRE) acquisitions to obtain homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ contrast by removing the effects of transmit field inhomogeneity in the pTx system. First, two input images are obtained in circularly polarized mode and another mode in which the first transmit channel or channel group have an additional transmit phase of π. The last two acquisitions are single-channel acquisitions for a dual-channel system or single-channel group acquisitions for more than two channels. The introduced method is demonstrated in dual-channel and eight-channel pTx systems using phantom and whole-brain in vivo experiments. Noise performance of the proposed method is also tested against the ratio of two GRE acquisitions and the TIAMO (time-interleaved acquisitions of modes) method. RESULTS Th new method results in more homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ contrast in the final images than the compared methods, particularly in the low-intensity regions of circularly polarized-mode images for the images obtained via ratio of the two GRE acquisitions. CONCLUSION The introduced method is easy to implement, robust, and provides homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ images of the whole brain using pTx systems with any number of channels, compared with the ratio of the two GRE images and the TIAMO method.
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Affiliation(s)
- Çelik Boğa
- UT Southwestern Medical Center, Dallas, Texas, USA
| | - Anke Henning
- UT Southwestern Medical Center, Dallas, Texas, USA
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Zhou Y, Zhao B, Moore J, Zong X. Automatic segmentation and diameter measurement of deep medullary veins. Magn Reson Med 2025; 93:1380-1393. [PMID: 39481043 DOI: 10.1002/mrm.30341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 09/26/2024] [Accepted: 09/29/2024] [Indexed: 11/02/2024]
Abstract
PURPOSE As one of the pathogenic factors of cerebral small vessel disease, venous collagenosis may result in the occlusion or stenosis of deep medullary veins (DMVs). Although numerous DMVs can be observed in susceptibility-weighted MRI images, their diameters are usually smaller than the MRI resolution, making it difficult to segment them and quantify their sizes. We aim to automatically segment DMVs and measure their diameters from gradient-echo images. METHODS A neural network model was trained for DMV segmentation based on the gradient-echo magnitude and phase images of 20 subjects at 7 T. The diameters of DMVs were obtained by fitting measured complex images with model images that accounted for the DMV-induced magnetic field and point spread function. A phantom study with graphite rods of different diameters was conducted to validate the proposed method. Simulation was carried out to evaluate the voxel-size dependence of measurement accuracy for a typical DMV size. RESULTS The automatically segmented DMV masks had Dice similarity coefficients of 0.68 ± 0.03 (voxel level) and 0.83 ± 0.04 (cluster level). The fitted graphite-rod diameters closely matched their true values. In simulation, the fitted diameters closely matched the true value when voxel size was ≤ 0.45 mm, and 92.2% of DMVs had diameters between 90 μm and 200 μm with a peak at about 120 μm, which agreed well with an earlier ex vivo report. CONCLUSION The proposed methods enabled efficient and quantitative study of DMVs, which may help illuminate the role of DMVs in the etiopathogenesis of cerebral small vessel disease.
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Affiliation(s)
- Yichen Zhou
- School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
| | - Bingbing Zhao
- School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
| | - Julia Moore
- Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Xiaopeng Zong
- School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
- Shanghai Clinical Research and Trial Center, Shanghai, China
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Sakurama A, Fushimi Y, Nakajima S, Sakata A, Okuchi S, Yamamoto T, Otani S, Wicaksono KP, Ikeda S, Ito S, Maki T, Liu W, Nakamoto Y. Comparison study of quantitative susceptibility mapping with GRAPPA and wave-CAIPI: reproducibility, consistency, and microbleeds detection. Jpn J Radiol 2025; 43:379-388. [PMID: 39467931 PMCID: PMC11868234 DOI: 10.1007/s11604-024-01683-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2024] [Accepted: 10/12/2024] [Indexed: 10/30/2024]
Abstract
PURPOSE We compared quantitative susceptibility mapping (QSM) with wave-CAIPI 9 × (QSM_WC9 ×) with reference standard QSM with GRAPPA 2 × (QSM_G2 ×) in two MR scanners. We also compared detectability of microbleeds in both QSMs to demonstrate clinical feasibility of both QSMs. MATERIALS AND METHODS This prospective study was approved by the institutional review board and written informed consent was obtained from each subject. Healthy subjects were recruited to evaluate intra-scanner reproducibility, inter-scanner consistency, and inter-sequence consistency of QSM_G2 × and QSM_WC9 × at 2 MR scanners. Susceptibility values measured with volume of interests (VOIs) were evaluated. Patients who were requested for susceptibility weighted imaging were also recruited in this study to measure microbleeds on QSM_G2 × and QSM_WC9 × . The number of microbleeds was compared between two QSMs. RESULTS Total 55 healthy subjects (male 34, female 21, 38.3 years [23-79]) were included in this study. We investigated reproducibility and consistency of QSM_WC9 × by comparing reference standard QSM_G2 × in two MR scanners in this study, and high correlation (ρ, 0.93-0.97) and high intraclass correlation coefficient (ICC) (0.97-0.99) were obtained. Sixty patients (male 30, female 30; age, 55.4 years [21-85]) were finally enrolled in this prospective study. The ICC of the detected number of microbleeds between QSM_G2 × and QSM_WC9 × was 0.99 (0.98-0.99). CONCLUSION QSM_WC9 × and reference standard QSM_G2 × in two MR scanners showed good reproducibility and consistency in estimating magnetic susceptibilities. QSM_WC9 × and QSM_G2 × were also comparable in terms of microbleeds detection with good agreement of raters and high ICC.
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Affiliation(s)
- Azusa Sakurama
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
| | - Satoshi Nakajima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Sachi Okuchi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Takayuki Yamamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Sayo Otani
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Krishna Pandu Wicaksono
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
- Department of Radiology, Faculty of Medicine, Universitas Indonesia-Dr. Cipto Mangunkusumo National Central General Hospital, Jakarta, Indonesia
| | - Satoshi Ikeda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Shuichi Ito
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Takakuni Maki
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
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Luyken AK, Lappe C, Viard R, Löhle M, Kleinlein HR, Kuchcinski G, Langner S, Wenzel AM, Walter M, Weber MA, Storch A, Devos D, Walter U. High correlation of quantitative susceptibility mapping and echo intensity measurements of nigral iron overload in Parkinson's disease. J Neural Transm (Vienna) 2025; 132:407-417. [PMID: 39485510 PMCID: PMC11870917 DOI: 10.1007/s00702-024-02856-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 10/22/2024] [Indexed: 11/03/2024]
Abstract
Quantitative susceptibility mapping (QSM) and transcranial sonography (TCS) offer proximal evaluations of iron load in the substantia nigra. Our prospective study aimed to investigate the relationship between QSM and TCS measurements of nigral iron content in patients with Parkinson's disease (PD). In secondary analyses, we wanted to explore the correlation of substantia nigra imaging data with clinical and laboratory findings. Eighteen magnetic resonance imaging and TCS examinations were performed in 15 PD patients at various disease stages. Susceptibility measures of substantia nigra were calculated from referenced QSM maps. Echogenicity of substantia nigra on TCS was measured planimetrically (echogenic area) and by digitized analysis (echo-intensity). Iron-related blood serum parameters were measured. Clinical assessments included the Unified PD Rating Scale and non-motor symptom scales. Substantia nigra susceptibility correlated with echogenic area (Pearson correlation, r = 0.53, p = 0.001) and echo-intensity (r = 0.78, p < 0.001). Individual asymmetry indices correlated between susceptibility and echogenic area measurements (r = 0.50, p = 0.042) and, more clearly, between susceptibility and echo-intensity measurements (r = 0.85, p < 0.001). Substantia nigra susceptibility (individual mean of bilateral measurements) correlated with serum transferrin saturation (Spearman test, r = 0.78, p < 0.001) and, by trend, with serum iron (r = 0.69, p = 0.004). Nigral echogenicity was not clearly related to serum values associated with iron metabolism. Susceptibility and echogenicity measurements were unrelated to PD duration, motor subtype, and severity of motor and non-motor symptoms. The present results support the assumption that iron accumulation is involved in the increase of nigral echogenicity in PD. Nigral echo-intensity probably reflects ferritin-bound iron, e.g. stored in microglia.
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Affiliation(s)
- Adrian Konstantin Luyken
- Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Chris Lappe
- Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
- German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Network of Centers of Excellence in Neurodegeneration (CoEN) Center Rostock, Rostock, Germany
| | - Romain Viard
- UAR 2014 - US 41 - PLBS - Plateformes Lilloises en Biologie & Santé, University of Lille, Lille, France
- INSERM, Centre Hospitalier Universitaire (CHU) de Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, University of Lille, Lille, France
| | - Matthias Löhle
- Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
- German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Network of Centers of Excellence in Neurodegeneration (CoEN) Center Rostock, Rostock, Germany
| | - Hanna Rebekka Kleinlein
- Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Grégory Kuchcinski
- UAR 2014 - US 41 - PLBS - Plateformes Lilloises en Biologie & Santé, University of Lille, Lille, France
- INSERM, Centre Hospitalier Universitaire (CHU) de Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, University of Lille, Lille, France
- Department of Neuroradiology, Centre Hospitalier Universitaire (CHU) de Lille, Lille, France
| | - Sönke Langner
- Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
| | - Anne-Marie Wenzel
- Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
- German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Network of Centers of Excellence in Neurodegeneration (CoEN) Center Rostock, Rostock, Germany
| | - Michael Walter
- Institute of Clinical Chemistry and Laboratory Medicine, Rostock University Medical Center, Rostock, Germany
| | - Marc-André Weber
- Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
| | - Alexander Storch
- Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
- German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Network of Centers of Excellence in Neurodegeneration (CoEN) Center Rostock, Rostock, Germany
- Center for Transdisciplinary Neurosciences Rostock (CTNR), University of Rostock, Rostock, Germany
| | - David Devos
- INSERM, Centre Hospitalier Universitaire (CHU) de Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, University of Lille, Lille, France
- Neurology and Movement Disorders Department, Reference Center for Parkinson's Disease, Lille Center of Excellence for Neurodegenerative Disorders (LiCEND), Network of Centers of Excellence in Neurodegeneration (CoEN) Center, Centre Hospitalier Universitaire (CHU) de Lille, Lille, France
- Department of Pharmacology, Centre Hospitalier Universitaire (CHU) de Lille, Lille, France
| | - Uwe Walter
- Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.
- German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Network of Centers of Excellence in Neurodegeneration (CoEN) Center Rostock, Rostock, Germany.
- Center for Transdisciplinary Neurosciences Rostock (CTNR), University of Rostock, Rostock, Germany.
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9
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Cherukara MT, Shmueli K. Comparing repeatability metrics for quantitative susceptibility mapping in the head and neck. MAGMA (NEW YORK, N.Y.) 2025:10.1007/s10334-025-01229-3. [PMID: 40024974 DOI: 10.1007/s10334-025-01229-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2024] [Revised: 01/09/2025] [Accepted: 01/21/2025] [Indexed: 03/04/2025]
Abstract
OBJECTIVE Quantitative susceptibility mapping (QSM) is a technique that has been demonstrated to be highly repeatable in the brain. As QSM is applied to other parts of the body, it is necessary to investigate metrics for quantifying repeatability, to enable optimization of repeatable QSM reconstruction pipelines beyond the brain. MATERIALS AND METHODS MRI data were acquired in the head and neck (HN) region in ten healthy volunteers, who underwent six acquisitions across two sessions. QSMs were reconstructed using six representative state-of-the-art techniques. Repeatability of the susceptibility values was compared using voxel-wise metrics (normalized root mean squared error and XSIM) and ROI-based metrics (within-subject and between-subject standard deviation, coefficient of variation (CV), intraclass correlation coefficient (ICC)). RESULTS Both within-subject and between-subject variations were smaller than the variation between QSM dipole inversion methods, in most ROIs. autoNDI produced the most repeatable susceptibility values, with ICC > 0.75 in three of six HN ROIs with an average ICC of 0.66 across all ROIs. Joint consideration of standard deviation and ICC offered the best metric of repeatability for comparisons between QSM methods, given typical distributions of positive and negative QSM values. DISCUSSION Repeatability of QSM in the HN region is highly dependent on the dipole inversion method chosen, but the most repeatable methods (autoNDI, QSMnet, TFI) are only moderately repeatable in most HN ROIs.
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Affiliation(s)
- Matthew T Cherukara
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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10
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Pishghadam M, Haizler-Cohen L, Ngwa JS, Yao W, Kapse K, Iqbal SN, Limperopoulos C, Andescavage NN. Placental quantitative susceptibility mapping and T2* characteristics for predicting birth weight in healthy and high-risk pregnancies. Eur Radiol Exp 2025; 9:18. [PMID: 39966316 PMCID: PMC11836258 DOI: 10.1186/s41747-025-00565-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Accepted: 01/24/2025] [Indexed: 02/20/2025] Open
Abstract
BACKGROUND The human placenta is critical in supporting fetal development, and placental dysfunction may compromise maternal-fetal health. Early detection of placental dysfunction remains challenging due to the lack of reliable biomarkers. This study compares placental quantitative susceptibility mapping and T2* values between healthy and high-risk pregnancies and investigates their association with maternal and fetal parameters and their ability to predict birth weight (BW). METHODS A total of 105 pregnant individuals were included: 68 healthy controls and 37 high-risk due to fetal growth restriction (FGR), chronic or gestational hypertension, and pre-eclampsia. Placental magnetic resonance imaging data were collected using a three-dimensional multi-echo radiofrequency-spoiled gradient-echo, and mean susceptibility and T2* values were calculated. To analyze associations and estimate BW, we employed linear regression and regression forest models. RESULTS No significant differences were found in susceptibility between high-risk pregnancies and controls (p = 0.928). T2* values were significantly lower in high-risk pregnancies (p = 0.013), particularly in pre-eclampsia and FGR, emerging as a predictor of BW. The regression forest model showed placental T2* as a promising mode for BW estimation. CONCLUSION Our findings underscore the potential of mean placental T2* as a more sensitive marker for detecting placental dysfunction in high-risk pregnancies than mean placental susceptibility. Moreover, the high-risk status emerged as a significant predictor of BW. These results call for further research with larger and more diverse populations to validate these findings and enhance prediction models for improved pregnancy management. RELEVANCE STATEMENT This study highlights the potential of placental T2* magnetic resonance imaging measurements as reliable indicators for detecting placental dysfunction in high-risk pregnancies, aiding in improved prenatal care and birth weight prediction. KEY POINTS Placental dysfunction in high-risk pregnancies is evaluated using MRI T2* values. Lower T2* values significantly correlate with pre-eclampsia and fetal growth restriction. T2* MRI may predict birth weight, enhancing prenatal care outcomes.
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Affiliation(s)
- Morteza Pishghadam
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA
| | - Lylach Haizler-Cohen
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, DC, USA
| | - Julius S Ngwa
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA
| | - Wu Yao
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA
| | - Kushal Kapse
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA
| | - Sara N Iqbal
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, DC, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA
- Department of Radiology, School of Medicine, and Health Sciences, George Washington University, Washington, DC, USA
- Department of Pediatrics, School of Medicine, and Health Sciences, George Washington University, Washington, DC, USA
| | - Nickie N Andescavage
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA.
- Division of Neonatology, Children's National Hospital, Washington, DC, USA.
- Department of Pediatrics, School of Medicine, and Health Sciences, George Washington University, Washington, DC, USA.
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11
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Wang J, Zhao R, Ma J, Qin J, Zhang H, Guo J, Chang X, Zhang W. Biallelic FDXR mutations induce ferroptosis in a rare mitochondrial disease with ataxia. Free Radic Biol Med 2025; 230:248-262. [PMID: 39954867 DOI: 10.1016/j.freeradbiomed.2025.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2025] [Revised: 02/06/2025] [Accepted: 02/09/2025] [Indexed: 02/17/2025]
Abstract
Biallelic mutations in the FDXR are known to cause rare mitochondrial diseases. However, the underlying pathogenic mechanisms remain elusive. This study investigated a patient affected by optic atrophy, ataxia, and peripheral neuropathy resulting from compound heterozygous mutations in FDXR. Structural abnormalities in mitochondria were observed in muscle and nerve tissues. Lymphoblastic cell lines (LCLs) and muscle samples from the patient exhibited signs of mitochondrial dysfunction, iron overload, oxidative stress, and lipid peroxidation. Dysregulation of the glutathione peroxidase-4 was noted in the LCLs. Furthermore, treatment with deferoxamine, N-acetyl-cysteine, and ferrostatin-1 effectively alleviated oxidative stress and cell death. Cortical neurons demonstrate that FDXR deficiency impacts the morphogenesis of neurites. Collectively, these findings suggest that ferroptosis plays a significant role in the pathogenesis of FDXR-associated diseases. Additionally, idebenone appeared to have protective effects against various cellular injuries induced by FDXR mutations, providing novel insights and therapeutic approaches for the treatment of FDXR-associated diseases.
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Affiliation(s)
- Juan Wang
- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Rongjuan Zhao
- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jing Ma
- First Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Jiangbo Qin
- Department of Radiology, First Hospital of Shanxi Medical University, China
| | - Huiqiu Zhang
- First Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Junhong Guo
- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xueli Chang
- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China.
| | - Wei Zhang
- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China.
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12
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Shin SH, Chae HD, Suprana A, Jerban S, Chang EY, Shi L, Sah RL, Pettus JH, Woods GN, Du J. UTE MRI technical developments and applications in osteoporosis: a review. Front Endocrinol (Lausanne) 2025; 16:1510010. [PMID: 39980853 PMCID: PMC11839439 DOI: 10.3389/fendo.2025.1510010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2024] [Accepted: 01/15/2025] [Indexed: 02/22/2025] Open
Abstract
Osteoporosis (OP) is a metabolic bone disease that affects more than 10 million people in the USA and leads to over two million fractures every year. The disease results in serious long-term disability and death in a large number of patients. Bone mineral density (BMD) measurement is the current standard in assessing fracture risk; however, the majority of fractures cannot be explained by BMD alone. Bone is a composite material of mineral, organic matrix, and water. While bone mineral provides stiffness and strength, collagen provides ductility and the ability to absorb energy before fracturing, and water provides viscoelasticity and poroelasticity. These bone components are arranged in a complex hierarchical structure. Both material composition and physical structure contribute to the unique strength of bone. The contribution of mineral to bone's mechanical properties has dominated scientific thinking for decades, partly because collagen and water are inaccessible using X-ray based techniques. Accurate evaluation of bone requires information about its components (mineral, collagen, water) and structure (cortical porosity, trabecular microstructure), which are all important in maintaining the mechanical integrity of bone. Magnetic resonance imaging (MRI) is routinely used to diagnose soft tissue diseases, but bone is "invisible" with clinical MRI due to its short transverse relaxation time. This review article discusses using ultrashort echo time (UTE) sequences to evaluate bone composition and structure. Both morphological and quantitative UTE MRI techniques are introduced. Their applications in osteoporosis are also briefly discussed. These UTE-MRI advancements hold great potential for improving the diagnosis and management of osteoporosis and other metabolic bone diseases by providing a more comprehensive assessment of bone quantity and quality.
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Affiliation(s)
- Soo Hyun Shin
- Department of Radiology, University of California, San Diego, San Diego, CA, United States
| | - Hee Dong Chae
- Department of Radiology, University of California, San Diego, San Diego, CA, United States
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Arya Suprana
- Department of Radiology, University of California, San Diego, San Diego, CA, United States
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
| | - Saeed Jerban
- Department of Radiology, University of California, San Diego, San Diego, CA, United States
| | - Eric Y. Chang
- Department of Radiology, University of California, San Diego, San Diego, CA, United States
- Radiology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Lingyan Shi
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
| | - Robert L. Sah
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
| | - Jeremy H. Pettus
- Department of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Gina N. Woods
- Department of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Jiang Du
- Department of Radiology, University of California, San Diego, San Diego, CA, United States
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
- Radiology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
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13
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Jang M, Dimov AV, Kapse K, Murnick J, Grinspan Z, Wu A, RoyChoudhury A, Wang Y, Spincemaille P, Nguyen TD, Limperopoulos C, Zun Z. Quantitative Susceptibility Mapping with Source Separation in Normal Brain Development of Newborns. AJNR Am J Neuroradiol 2025; 46:380-389. [PMID: 39231612 DOI: 10.3174/ajnr.a8488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 08/13/2024] [Indexed: 09/06/2024]
Abstract
BACKGROUND AND PURPOSE Quantitative susceptibility mapping is an emerging method for characterizing tissue composition and studying myelination and iron deposition. However, accurate assessment of myelin and iron content in the neonate brain using this method is challenging because these 2 susceptibility sources of opposite signs (myelin, negative; iron, positive) occupy the same voxel, with minimal and comparable content in both sources. In this study, susceptibilities were measured in the healthy neonate brain using susceptibility source separation. MATERIALS AND METHODS Sixty-nine healthy neonates without clinical indications were prospectively recruited for MRI. All neonates underwent gradient-echo imaging for quantitative susceptibility mapping. Positive (paramagnetic) and negative (diamagnetic) susceptibility sources were separated using additional information from R2* with linear modeling performed for the neonate brain. Average susceptibility maps were generated by normalizing all susceptibility maps to an atlas space. Mean regional susceptibility measurements were obtained in the cortical GM, WM, deep GM, caudate nucleus, putamen, globus pallidus, thalamus, and the 4 brain lobes. RESULTS A total of 65 healthy neonates (mean postmenstrual age, 42.8 [SD, 2.3] weeks; 34 females) were studied. The negative susceptibility maps visually demonstrated high signals in the thalamus, brainstem, and potentially myelinated WM regions, whereas the positive susceptibility maps depicted high signals in the GM compared with all WM regions, including both myelinated and unmyelinated WM. The WM exhibited significantly lower mean positive susceptibility and significantly higher mean negative susceptibility than cortical GM and deep GM. Within the deep GM, the thalamus showed a significantly lower mean negative susceptibility than the other nuclei, and the putamen and globus pallidus showed significant associations with neonate age in positive and/or negative susceptibility. Among the 4 brain lobes, the occipital lobe showed a significantly higher mean positive susceptibility and a significantly lower mean negative susceptibility than the frontal lobe. CONCLUSIONS This study demonstrates regional variations and temporal changes in positive and negative susceptibilities of the neonate brain, potentially associated with myelination and iron deposition patterns in normal brain development. It suggests that quantitative susceptibility mapping with source separation may be used for early identification of delayed myelination or iron deficiency.
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Affiliation(s)
- MinJung Jang
- From the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
| | - Alexey V Dimov
- From the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
| | - Kushal Kapse
- Institute for the Developing Brain (K.K., J.M., C.L.), Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC
| | - Jonathan Murnick
- Institute for the Developing Brain (K.K., J.M., C.L.), Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC
- Department of Pediatrics (J.M., C.L.), School of Medicine and Health Sciences, George Washington University, Washington, DC
- Department of Radiology, School of Medicine and Health Sciences (J.M., C.L.), George Washington University, Washington, DC
| | - Zachary Grinspan
- Department of Pediatrics (Z.G.), Weill Cornell Medicine, New York, New York
| | - Alan Wu
- Department of Population Health Sciences (A.W., A.R.), Weill Cornell Medicine, New York, New York
| | - Arindam RoyChoudhury
- Department of Population Health Sciences (A.W., A.R.), Weill Cornell Medicine, New York, New York
| | - Yi Wang
- From the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
| | - Pascal Spincemaille
- From the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
| | - Thanh D Nguyen
- From the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
| | - Catherine Limperopoulos
- Institute for the Developing Brain (K.K., J.M., C.L.), Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC
- Department of Pediatrics (J.M., C.L.), School of Medicine and Health Sciences, George Washington University, Washington, DC
- Department of Radiology, School of Medicine and Health Sciences (J.M., C.L.), George Washington University, Washington, DC
- Division of Fetal and Transitional Medicine (C.L.), Children's National Hospital, Washington, DC
| | - Zungho Zun
- From the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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14
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Kim M, Ji S, Kim J, Min K, Jeong H, Youn J, Kim T, Jang J, Bilgic B, Shin H, Lee J. χ-sepnet: Deep Neural Network for Magnetic Susceptibility Source Separation. Hum Brain Mapp 2025; 46:e70136. [PMID: 39835664 PMCID: PMC11748151 DOI: 10.1002/hbm.70136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 12/11/2024] [Accepted: 12/30/2024] [Indexed: 01/22/2025] Open
Abstract
Magnetic susceptibility source separation (χ-separation), an advanced quantitative susceptibility mapping (QSM) method, enables the separate estimation of paramagnetic and diamagnetic susceptibility source distributions in the brain. Similar to QSM, it requires solving the ill-conditioned problem of dipole inversion, suffering from so-called streaking artifacts. Additionally, the method utilizes reversible transverse relaxation (R 2 ' = R 2 * - R 2 $$ {R}_2^{\prime }={R}_2^{\ast }-{R}_2 $$ ) to complement frequency shift information for estimating susceptibility source concentrations, requiring time-consuming data acquisition forR 2 $$ {R}_2 $$ (e.g., multi-echo spin-echo) in addition to multi-echo GRE data forR 2 * $$ {R}_2^{\ast } $$ . To address these challenges, we develop a new deep learning network, χ-sepnet, and propose two deep learning-based susceptibility source separation pipelines, χ-sepnet-R 2 ' $$ {R}_2^{\prime } $$ for inputs with multi-echo GRE and multi-echo spin-echo (or turbo spin-echo) and χ-sepnet-R 2 * $$ {R}_2^{\ast } $$ for input with multi-echo GRE only. The neural network is trained using multiple head orientation data that provide streaking artifact-free labels, generating high-quality χ-separation maps. The evaluation of the pipelines encompasses both qualitative and quantitative assessments in healthy subjects, and visual inspection of lesion characteristics in multiple sclerosis patients. The susceptibility source-separated maps of the proposed pipelines delineate detailed brain structures with substantially reduced artifacts compared to those from the conventional regularization-based reconstruction methods. In quantitative analysis, χ-sepnet-R 2 ' $$ {R}_2^{\prime } $$ achieves the best outcomes followed by χ-sepnet-R 2 * $$ {R}_2^{\ast } $$ , outperforming the conventional methods. When the lesions of multiple sclerosis patients are classified into subtypes, most lesions are identified as the same subtype in the maps from χ-sepnet-R 2 ' $$ {R}_2^{\prime } $$ and χ-sepnet-R 2 * $$ {R}_2^{\ast } $$ (paramagnetic susceptibility: 99.6% and diamagnetic susceptibility: 98.4%; both out of 250 lesions). The χ-sepnet-R 2 * $$ {R}_2^{\ast } $$ pipeline, which only requires multi-echo GRE data, has demonstrated its potential to offer broad clinical and scientific applications, although further evaluations for various diseases and pathological conditions are necessary.
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Affiliation(s)
- Minjun Kim
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
| | - Sooyeon Ji
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
- Division of Computer EngineeringHankuk University of Foreign StudiesYonginRepublic of Korea
| | - Jiye Kim
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
| | - Kyeongseon Min
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
| | - Hwihun Jeong
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
| | - Jonghyo Youn
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
| | - Taechang Kim
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
| | - Jinhee Jang
- Department of RadiologySeoul St Mary's Hospital, College of Medicine, The Catholic University of KoreaSeoulRepublic of Korea
- Institute for Precision HealthUniversity of CaliforniaIrvineCaliforniaUSA
| | - Berkin Bilgic
- Massachusetts General Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Hyeong‐Geol Shin
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
- Russell H. Morgan Department of Radiology and Radiological ScienceThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National UniversitySeoulRepublic of Korea
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15
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Lin L, Ruan Z, Li Y, Qiu H, Deng C, Qian L, Cui W, Tang W, Yang Z, Cheng Y, Liang Y, Su S. Brain Iron Alteration in Pediatric Tourette Syndrome: A Quantitative Susceptibility Mapping Study. Eur J Neurol 2025; 32:e70054. [PMID: 39895224 PMCID: PMC11788536 DOI: 10.1111/ene.70054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 12/30/2024] [Accepted: 01/09/2025] [Indexed: 02/04/2025]
Abstract
BACKGROUND The cortico-striato-thalamo-cortical circuits play a crucial role in the pathogenesis of Tourette syndrome (TS). While iron deficiency has been reported in adult TS, the iron content in pediatric TS remains poorly understood. This study aims to quantitatively assess whole-brain iron deposition in pediatric TS compared to typically developing (TD) children using quantitative susceptibility mapping (QSM). METHODS In this prospective study, we recruited 50 children with a clinical diagnosis of TS and 50 age- and gender-matched TD controls. Whole-brain images were acquired using 3D T1 and multi-echo gradient-recalled echo sequences. QSM maps were generated using the STISuite toolbox. After normalizing the QSM maps to Montreal Neurological Institute space, voxel-based analysis was applied to compare between-group differences in iron content. Additionally, we evaluated the relationship between iron content and tic severity in TS children using the Pearson's correlation test. RESULTS Compared to TD children, those with TS exhibited iron deficiency in the right anterior cingulum (pFDR < 0.001). Conversely, increased QSM values were observed in the bilateral putamen of TS children (pFDR < 0.001). Notably, QSM values in the left putamen showed a significant negative correlation with tic severity (p = 0.044). CONCLUSIONS Our findings suggest that disturbed brain iron homeostasis in specific regions is associated with pediatric TS. These results reinforce the importance of the cortico-striato-thalamo-cortical circuits in TS pathogenesis and highlight the potential role of iron dysregulation. Furthermore, our study demonstrates that QSM could serve as a valuable auxiliary biomarker for diagnosing and potentially monitoring pediatric TS.
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Affiliation(s)
- Liping Lin
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Zhibin Ruan
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Yufen Li
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Huaqiong Qiu
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Chengfen Deng
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Long Qian
- Department of Biomedical Engineering, College of EngineeringPeking UniversityBeijingChina
| | - Wei Cui
- Department of Biomedical Engineering, College of EngineeringPeking UniversityBeijingChina
| | - Wen Tang
- Department of PediatricThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Zhiyun Yang
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Yanglei Cheng
- Department of EndocrineThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Yujian Liang
- Department of PediatricThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
| | - Shu Su
- Department of RadiologyThe First Affiliated Hospital, Sun Yat‐Sen UniversityGuangzhouChina
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16
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Deng X, Bu M, Liang J, Sun Y, Li L, Zheng H, Zeng Z, Jiang M, Chen BT. Relationship between cognitive impairment and hippocampal iron overload: A quantitative susceptibility mapping study of a rat model. Neuroimage 2025; 306:121006. [PMID: 39788338 DOI: 10.1016/j.neuroimage.2025.121006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 12/06/2024] [Accepted: 01/06/2025] [Indexed: 01/12/2025] Open
Abstract
BACKGROUND The aim of this study was to establish an iron overload rat model to simulate the elevated iron levels in patients with thalassemia and to investigate the potential association between hippocampal iron deposition and cognition. METHODS Two groups of iron overloaded rats and one group of control rats were used for this study. The Morris water maze (MWM) was used to test spatial reference memory indicated by escape latency time and number of MWM platform crossings. The magnetic susceptibility value of the hippocampal tissue, a measure of iron deposition, was assessed by quantitative susceptibility mapping (QSM) and was correlated with spatial reference memory performance. The iron content in hippocampal tissue sections of the rats were assessed using diaminobenzidine (DAB)-enhanced Perl's Prussian blue (PPB) staining. RESULTS The rat groups with iron overload including the Group H and Group L had higher hippocampal magnetic susceptibility values than the control rat group, i.e., Group D. In addition, the iron overloaded groups had longer MWM escape latency than the control group, and reduced number of MWM platform crossings. There was a positive correlation between the mean escape latency and the mean hippocampal magnetic susceptibility value, a negative correlation between the number of platform crossings and the mean hippocampal magnetic susceptibility value, and a negative correlation between the number of platform crossings and the latent escape time in Group H and Group L. CONCLUSION This rat model simulating iron overload in thalassemia showed hippocampal iron overload being associated with impairment of spatial reference memory. QSM could be used to quantify brain iron overload in vivo, highlighting its potential clinical application for assessing cognitive impairment in patients with thalassemia.
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Affiliation(s)
- Xi Deng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Meiru Bu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Jiali Liang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Yihao Sun
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Liyan Li
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Heishu Zheng
- Guangxi Key Laboratory of Oral Maxillofacial Rehabilitation Reconstruction, No.22 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Zisan Zeng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China
| | - Muliang Jiang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi 530021, PR China.
| | - Bihong T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, 1500 E Duarte, CA 91010, USA
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Ghaderi S, Mohammadi S, Fatehi F. Diamagnetic Signature of Beta-Amyloid (Aβ) and Tau (τ) Tangle Pathology in Alzheimer's Disease: A Review. Aging Med (Milton) 2025; 8:e70006. [PMID: 39949469 PMCID: PMC11817029 DOI: 10.1002/agm2.70006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2024] [Revised: 12/18/2024] [Accepted: 01/23/2025] [Indexed: 02/16/2025] Open
Abstract
The complex interplay between diamagnetic and paramagnetic substances within the brain, particularly in the context of Alzheimer's disease (AD), offers a rich landscape for investigation using advanced quantitative neuroimaging techniques. Although conventional approaches have focused on the paramagnetic properties of iron, emerging and promising research has highlighted the significance of diamagnetic signatures associated with beta-amyloid (Aβ) plaques and Tau (τ) protein aggregates. Quantitative susceptibility mapping (QSM) is a complex post-processing technique that visualizes and characterizes these subtle alterations in brain border tissue composition, such as the gray-white matter interface. Through voxel-wise separation of the contributions of diamagnetic and paramagnetic sources, QSM enabled the identification and quantification of Aβ and τ aggregates, even in the presence of iron. However, several challenges remain in utilizing diamagnetic signatures of Aβ and τ for clinical applications. These include the relatively small magnitude of the diamagnetic signal compared to paramagnetic iron, the need for high-resolution imaging and sophisticated analysis techniques, and the standardization of QSM acquisition and analysis protocols. Further research is necessary to refine QSM techniques, optimize acquisition parameters, and develop robust analysis pipelines to improve the sensitivity and specificity of detecting the diamagnetic nature of Aβ and τ aggregates. As our understanding of the diamagnetic properties of Aβ and τ continues to evolve, QSM is expected to play a pivotal role in advancing our knowledge of AD and other neurodegenerative diseases.
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Affiliation(s)
- Sadegh Ghaderi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
| | - Sana Mohammadi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
| | - Farzad Fatehi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
- Neurology DepartmentUniversity Hospitals of Leicester NHS TrustLeicesterUK
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18
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Xie Y, Zhang Y, Wu S, Zhang S, Zhu H, Zhu W, Wang Y. Atrophy-Independent and Dependent Iron and Myelin Changes in Deep Gray Matter of Multiple Sclerosis: A Longitudinal Study Using χ-Separation Imaging. Acad Radiol 2025; 32:988-999. [PMID: 39084936 DOI: 10.1016/j.acra.2024.07.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 07/15/2024] [Accepted: 07/16/2024] [Indexed: 08/02/2024]
Abstract
RATIONALE AND OBJECTIVES To investigate iron and myelin changes in deep gray matter (DGM) of relapsing-remitting multiple sclerosis (RRMS) patients and their relationship to atrophy by χ-separation imaging. MATERIALS AND METHODS 33 RRMS patients and 34 healthy controls (HC) were included in this study. The χ-separation map reconstructed from a 3D multi-echo gradient echo scan was used to measure the positive susceptibility (χpos) and negative susceptibility (χneg) of DGM. To take into account the effect of atrophy, susceptibility mass of DGM was calculated by multiplying volume by the mean bulk susceptibility. Differences in MRI metrics between baseline patients, follow-up patients, and HC were compared respectively. RESULTS Compared to HC, χpos of basal ganglia were significantly increased in follow-up patients (P < 0.05). The χpos of pallidum was significantly higher in follow-up patients than that in baseline patients (P = 0.006). The χneg of caudate, pallidum and hippocampus in baseline and follow-up patients was significantly higher than that in HC (P < 0.05). When taking into account the effect of atrophy, there was a significant decrease in χpos mass and a significant increase in χneg mass of thalamus, accumbens and amygdala in follow-up patients compared to HC (P < 0.05). The χpos mass of the thalamus was further decreased in follow-up patients compared to baseline patients (P = 0.006). CONCLUSION χ-separation imaging could generate independent information on iron and myelin changes in RRMS patients, showing atrophy-dependent iron increase in basal ganglia and atrophy-independent iron and myelin decrease in thalamus.
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Affiliation(s)
- Yan Xie
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaolong Wu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongquan Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA; Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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19
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Xiao Y, Liu Z, Wan X. Oxygen extraction fraction change in M1-M6 brain regions of patients with unilateral or bilateral middle cerebral artery occlusion. J Cereb Blood Flow Metab 2025; 45:319-327. [PMID: 39161251 PMCID: PMC11572168 DOI: 10.1177/0271678x241276386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 07/16/2024] [Accepted: 08/01/2024] [Indexed: 08/21/2024]
Abstract
Cerebral blood flow (CBF) and oxygen extraction fraction (OEF) can be measured using arterial spin labeling (ASL) and quantitative susceptibility mapping (QSM) sequences, respectively. ASL and QSM sequences were performed on 13 healthy participants and 46 patients with unilateral or bilateral Middle cerebral artery (MCA) occlusion. M1-M3 and M4-M6 correspond to anterior, lateral, and posterior MCA territories within the insular ribbon and centrum semiovale, respectively. In patients with unilateral MCA occlusion, significant decreases in CBF were observed in the lesions in M1, M3, M5 and M6 regions, as well as in the contralateral M3 and M5 regions. The OEF of the lesion in the M1-M4 and M6 regions, and the contralateral M1-M3 regions were significantly higher. Additionally, the cerebral metabolic rate of oxygen (CMRO2) in the lesions of the M3 and M6 regions, and the contralateral M3 region, were significantly lower compared to the corresponding regions of healthy participants. For patients with bilateral MCA occlusion, the CMRO2 in the left M5 region and the right M3 and M6 regions were significantly lower than that in the corresponding regions of healthy participants. In conclusion, abnormal hemodynamics occur in the contralateral hemisphere of patients with unilateral MCA occlusion.
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Affiliation(s)
- Yu Xiao
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University; Intelligent Medical Imaging of Jiangxi Key Laboratory, Nanchang city, China
| | - Zhenghua Liu
- The Department of Radiology, The Dongguan Maternal and Child Health Care Hospital, Guangdong, China
| | - Xinghua Wan
- The Department of Radiology, The People’s Hospital of Nanchang County, Nanchang city, China
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20
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Shin HG, Kim W, Lee JH, Lee HS, Nam Y, Kim J, Li X, van Zijl PCM, Calabresi PA, Lee J, Jang J. Association of iron deposition in MS lesion with remyelination capacity using susceptibility source separation MRI. Neuroimage Clin 2025; 45:103748. [PMID: 39904206 PMCID: PMC11847087 DOI: 10.1016/j.nicl.2025.103748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2024] [Revised: 01/21/2025] [Accepted: 01/29/2025] [Indexed: 02/06/2025]
Abstract
OBJECTIVES Susceptibility source-separation (χ-separation) MRI provides in-vivo proxy of myelin (diamagnetic susceptibility, χdia) and iron concentrations (paramagnetic susceptibility, χpara) in the central nervous system, potentially uncovering myelin- and iron-related pathology in multiple sclerosis (MS) lesions (e.g., demyelination, remyelination, and iron-laden microglia/macrophages formation). This study aims to monitor longitudinal changes in χpara and χdia signals within MS lesions using χ-separation and evaluate the association between lesional iron and remyelination capability. METHODS Fifty participants with MS (pwMS) were followed annually over a mean period of 3.3 years (SD = 1.8 years) with MRI, including χ-separation, and clinical assessments. To monitor lesions from their early stage (lesion age < 1 year), we identified newly-noted lesions (NNLs) and contrast-enhancing lesions (CELs), and tracked their longitudinal changes in χpara and χdia signals. RESULTS Twenty-three pwMS were detected with NNLs and/or CELs (38 NNLs, 31 CELs;7 overlapped). Among these lesions (62 lesions in total), 27 exhibited χpara hyperintensity, termed hyper-paramagnetic sign (HPS), indicating iron deposition "throughout" the lesion (not confined to rim sign). Early-stage HPS correlated with future remyelination failure detected by χdia myelin signals (P < 0.001). After adjustment, lesions with early HPS demonstrated an annual loss in myelin signal (-1.94 ppb/year), whereas those without early HPS exhibited annual recovery (+0.66 ppb/year). Participants with confirmed disability improvement (CDI) had fewer HPS-positive lesions at baseline than those without CDI (P < 0.001). CONCLUSION The presence of HPS is associated with impaired remyelination capacity and a lack of disease improvement in pwMS. Identifying HPS may help demarcate lesions more amenable to myelin repair therapies.
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Affiliation(s)
- Hyeong-Geol Shin
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD 21218, United States; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, United States
| | - Woojun Kim
- Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Jung Hwan Lee
- Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Hyun-Soo Lee
- MR Research Collaboration, Siemens Healthineers, Seoul 06620, Republic of Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin 17035, South Korea
| | - Jiwoong Kim
- Department of Mathematics and Statistics, University of South Florida, Tampa, FL 33620, United States
| | - Xu Li
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD 21218, United States; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, United States
| | - Peter C M van Zijl
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD 21218, United States; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, United States
| | - Peter A Calabresi
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21218, United States
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Jinhee Jang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea; Institute for Precision Health, University of California, Irvine, Irvine, CA 92697, United States.
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21
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Gillen KM, Nguyen TD, Dimov A, Kovanlikaya I, Luu HM, Demmon E, Markowitz DM, Bagnato F, Pitt D, Gauthier SA, Wang Y. Quantitative susceptibility mapping is more sensitive and specific than phase imaging in detecting chronic active multiple sclerosis lesion rims: pathological validation. Brain Commun 2025; 7:fcaf011. [PMID: 39916751 PMCID: PMC11800486 DOI: 10.1093/braincomms/fcaf011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 12/09/2024] [Accepted: 01/09/2025] [Indexed: 02/09/2025] Open
Abstract
Quantitative susceptibility mapping and phase imaging are used to identify multiple sclerosis lesions with paramagnetic rims that slowly expand over time and are associated with earlier progression to disability, decreased brain volume and increased frequency of clinical relapse. However, the presence of iron-laden microglia/macrophages at the lesion rim and demyelination within the lesion both contribute to phase and quantitative susceptibility mapping images. Therefore, simultaneous pathological validation is needed to assess accuracies in identifying iron-positive lesions. MRI was performed on 15 multiple sclerosis brain slabs; 32 lesions of interest were processed for myelin, iron and microglial markers. Three experienced readers classified lesions as rim positive or negative on quantitative susceptibility mapping and phase; these classifications were compared with Perls' stain as the gold standard. All 10 of the quantitative susceptibility mapping-positive lesions had iron-positive rims on histology. Of the 16 phase-positive lesions, only 10 had iron-positive rims on histology. Using Perls' stain as the ground truth, the positive predictive value was 100% for quantitative susceptibility mapping and 63% for phase; the negative predictive value was 95% for quantitative susceptibility mapping and 94% for phase. Post-mortem imaging results demonstrate that quantitative susceptibility mapping is a more reliable indicator of an iron-positive rim compared with phase imaging.
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Affiliation(s)
- Kelly M Gillen
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alexey Dimov
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ha Manh Luu
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Emily Demmon
- Department of Neurology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Daniel M Markowitz
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Francesca Bagnato
- Department of Neurology, Nashville VA Medical Center, Tennessee Valley Healthcare System, Nashville, TN 37212, USA
| | - David Pitt
- Department of Neurology, Yale School of Medicine, New Haven, CT 06511, USA
| | - Susan A Gauthier
- Department of Neurology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
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22
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Gao Y, Liang C, Zhang Q, Zhuang H, Sui C, Zhang N, Feng M, Xin H, Guo L, Wang Y. Brain iron deposition and cognitive decline in patients with cerebral small vessel disease : a quantitative susceptibility mapping study. Alzheimers Res Ther 2025; 17:17. [PMID: 39789638 PMCID: PMC11715900 DOI: 10.1186/s13195-024-01638-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Accepted: 12/03/2024] [Indexed: 01/12/2025]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) can study the susceptibility values of brain tissue which allows for noninvasive examination of local brain iron levels in both normal and pathological conditions. PURPOSE Our study compares brain iron deposition in gray matter (GM) nuclei between cerebral small vessel disease (CSVD) patients and healthy controls (HCs), exploring factors that affect iron deposition and cognitive function. MATERIALS AND METHODS A total of 321 subjects were enrolled in this study. All subjects had cognitive examination including the Stroop color word test (SCWT) and MRI including multiecho gradient echo (mGRE) sequence. The patients with CSVD were divided into mild to moderate group (CSVD-M, total CSVD score ≤ 1) and severe group (CSVD-S, total CSVD score > 1). Morphology-enabled dipole inversion with an automated uniform cerebrospinal fluid zero reference algorithm (MEDI + 0) was used to generate brain QSM maps from mGRE data. Deep gray regional susceptibility values and cognitive function were compared among three groups (CSVD-S, CSVD-M, and HC) using multiple linear regression analysis and mediation effect analysis. RESULTS There were significant differences in the SCWT scores and mean susceptibility values of the globus pallidus (GP), putamen (Put), and caudate nucleus (CN) among the three groups (P < 0.05, FDR correction). Age had a significant positive impact on the susceptibility values of GP (p = 0.018), Put (p < 0.001), and CN (p < 0.001). A history of diabetes had a significant positive influence on the susceptibility values of Put (p = 0.011) and CN (p < 0.001). A smoking history had a significant positive association with the susceptibility values of CN (p = 0.019). Mediation effect analysis demonstrated that iron deposition in the neostriatum partially mediated the relationship between hypertension and cognitive function. Age, diabetes, and smoking may increase iron deposition in the basal ganglia, associated with cognitive decline. The mean susceptibility values of the neostriatum played a mediating role in the association between hypertension and cognitive scores. CONCLUSIONS Age, diabetes, and smoking are associated with increased iron deposition in the basal ganglia and also linked to cognitive decline. This can help with understanding CSVD and its prevention and treatment.
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Affiliation(s)
- Yian Gao
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, China
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Changhu Liang
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, China
| | - Qihao Zhang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Hangwei Zhuang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA, Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Chaofan Sui
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, China
| | - Nan Zhang
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, China
| | - Mengmeng Feng
- Department of Radiology, Department of Radiology and Nuclear medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-chun St, Xicheng District, Beijing, China
| | - Haotian Xin
- Department of Radiology, Department of Radiology and Nuclear medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-chun St, Xicheng District, Beijing, China
| | - Lingfei Guo
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, China.
| | - Yi Wang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
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23
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Zachariou V, Pappas C, Bauer CE, Seago ER, Gold BT. Exploring the links among brain iron accumulation, cognitive performance, and dietary intake in older adults: A longitudinal MRI study. Neurobiol Aging 2025; 145:1-12. [PMID: 39447489 PMCID: PMC11578767 DOI: 10.1016/j.neurobiolaging.2024.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 10/09/2024] [Accepted: 10/17/2024] [Indexed: 10/26/2024]
Abstract
This study evaluated longitudinal brain iron accumulation in older adults, its association with cognition, and the role of specific nutrients in mitigating iron accumulation. MRI-based, quantitative susceptibility mapping estimates of brain iron concentration were acquired from seventy-two healthy older adults (47 women, ages 60-86) at a baseline timepoint (TP1) and a follow-up timepoint (TP2) 2.5-3.0 years later. Dietary intake was evaluated at baseline using a validated questionnaire. Cognitive performance was assessed at TP2 using the uniform data set (Version 3) neuropsychological tests of episodic memory (MEM) and executive function (EF). Voxel-wise, linear mixed-effects models, adjusted for longitudinal gray matter volume alterations, age, and several non-dietary lifestyle factors revealed brain iron accumulation in multiple subcortical and cortical brain regions, which was negatively associated with both MEM and EF performance at T2. However, consumption of specific dietary nutrients at TP1 was associated with reduced brain iron accumulation. Our study provides a map of brain regions showing iron accumulation in older adults over a short 2.5-year follow-up and indicates that certain dietary nutrients may slow brain iron accumulation.
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Affiliation(s)
- Valentinos Zachariou
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, USA.
| | - Colleen Pappas
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Christopher E Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Elayna R Seago
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Brian T Gold
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA; Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA; Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY, USA.
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24
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Yang A, Luan J, Xu M, Du L, Lv K, Hu P, Shu N, Yuan Z, Shmuel A, Ma G. Regional brain iron correlates with transcriptional and cellular signatures in Alzheimer's disease. Alzheimers Dement 2025; 21:e14459. [PMID: 39876820 PMCID: PMC11775454 DOI: 10.1002/alz.14459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Revised: 10/27/2024] [Accepted: 11/13/2024] [Indexed: 01/31/2025]
Abstract
INTRODUCTION The link between overload brain iron and transcriptional/cellular signatures in Alzheimer's disease (AD) remains inconclusive. METHODS Iron deposition in 41 cortical and subcortical regions of 30 AD patients and 26 healthy controls (HCs) was measured using quantitative susceptibility mapping (QSM). The expression of 15,633 genes was estimated in the same regions using transcriptomic data from the Allen Human Brain Atlas (AHBA). Partial least square (PLS) regression was used to identify the association between the healthy brain gene transcription and aberrant regional QSM signal in AD. The biological processes and cell types associated with the linked genes were evaluated. RESULTS Gene ontological analyses showed that the first PLS component (PLS1) genes were enriched for biological processes relating to the "protein phosphorylation" and "metal ion transport". Additionally, these genes were expressed in microglia (MG) and glutamatergic neurons (GLUs). DISCUSSION Our findings provide mechanistic insights from transcriptional and cellular signatures into regional iron accumulation measured by QSM in AD. HIGHLIGHTS Spatial patterns of iron deposition changes in AD correlate with cortical spatial expression genes in healthy subjects. The identified gene transcription profile underlies aberrant iron accumulation in AD was enriched for biological processes relating to "protein phosphorylation" and "metal ion transport". The related genes were predominantly expressed in MG and GLUs.
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Affiliation(s)
- Aocai Yang
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
- China‐Japan Friendship Hospital (Institute of Clinical Medical Sciences)Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
| | - Jixin Luan
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
- China‐Japan Friendship Hospital (Institute of Clinical Medical Sciences)Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
| | - Manxi Xu
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
| | - Lei Du
- Department of RadiologyKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education)Peking University Cancer Hospital & InstituteBeijingChina
| | - Kuan Lv
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
| | - Pianpian Hu
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
| | - Zhen Yuan
- Faculty of Health SciencesUniversity of MacauTaipaMacau SARChina
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaMacau SARChina
| | - Amir Shmuel
- McConnell Brain Imaging CentreMontreal Neurological InstituteMcGill UniversityMontrealCanada
- Departments of Neurology and NeurosurgeryPhysiology, and Biomedical EngineeringMcGill UniversityMontrealCanada
| | - Guolin Ma
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
- China‐Japan Friendship Hospital (Institute of Clinical Medical Sciences)Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
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25
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Buelo CJ, Velikina J, Mao L, Zhao R, Yuan Q, Ghasabeh MA, Ruschke S, Karampinos DC, Harris DT, Mattison RJ, Jeng MR, Pedrosa I, Kamel IR, Vasanawala S, Yokoo T, Reeder SB, Hernando D. Multicenter, multivendor validation of liver quantitative susceptibility mapping in patients with iron overload at 1.5 T and 3 T. Magn Reson Med 2025; 93:330-340. [PMID: 39238238 DOI: 10.1002/mrm.30251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/21/2024] [Accepted: 07/27/2024] [Indexed: 09/07/2024]
Abstract
PURPOSE To evaluate the repeatability and reproducibility of QSM of the liver via single breath-hold chemical shift-encoded MRI at both 1.5 T and 3 T in a multicenter, multivendor study in subjects with iron overload. METHODS This prospective study included four academic medical centers with three different MRI vendors at 1.5 T and 3 T. Subjects with known or suspected liver iron overload underwent multi-echo spoiled gradient-recalled-echo scans at each field strength. A subset received repeatability testing at either 1.5 T or 3 T. Susceptibility andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps were reconstructed from the multi-echo images and analyzed at a single center. QSM-measured susceptibility was compared withR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and a commercial R2-based liver iron concentration method across centers and field strengths using linear regression and F-tests on the intercept and slope. Field-strength reproducibility and test/retest repeatability were evaluated using Bland-Altman analysis. RESULTS A total of 155/80 data sets (test/retest) were available at 1.5 T, and 159/70 data sets (test/retest) were available at 3 T. Calibrations across sites were reproducible, with some variability (e.g., susceptibility slope with liver iron concentration ranged from 0.102 to 0.123 g/[mg· $$ \cdotp $$ ppm] across centers at 1.5 T). Field strength reproducibility was good (concordance correlation coefficient = 0.862), and test/retest repeatability was excellent (intraclass correlation coefficient = 0.951). CONCLUSION QSM as an imaging biomarker of liver iron overload is feasible and repeatable across centers and MR vendors. It may be complementary withR 2 * $$ {\mathrm{R}}_2^{\ast } $$ as they are obtained from the same acquisition. Although good reproducibility was observed, liver QSM may benefit from standardization of acquisition parameters. Overall, QSM is a promising method for liver iron quantification.
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Affiliation(s)
- Collin J Buelo
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Julia Velikina
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Lu Mao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ruiyang Zhao
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- GE Healthcare, Waukesha, Wisconsin, USA
| | - Qing Yuan
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | - Stefan Ruschke
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar and Health, Technical University of Munich, Munich, Germany
| | | | - David T Harris
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ryan J Mattison
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Michael R Jeng
- Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Ihab R Kamel
- Department of Radiology, The John Hopkins University, Baltimore, Maryland, USA
| | | | - Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Liu Y, Lu Y, Hu L, Xu J, Liu X, Yang N, Chen S, Zhang Z. Structural and iron content changes in subcortical vascular mild cognitive impairment: a combined voxel-based morphometry and quantitative susceptibility mapping study. Brain Res Bull 2025; 220:111160. [PMID: 39638098 DOI: 10.1016/j.brainresbull.2024.111160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Revised: 11/27/2024] [Accepted: 12/02/2024] [Indexed: 12/07/2024]
Abstract
BACKGROUND Further studies are necessary to investigate the neural mechanisms elemental of subcortical vascular mild cognitive impairment (svMCI), which is considered as precursor to vascular dementia (VaD). This objective of this research was to investigate the alterations in gray matter volume and brain iron deposition in patients with svMCI. METHODS This study involved 23 patients classified as health controls (HC) and 20 patients diagnosed with svMCI. All participants received cognitive assessments and magnetic resonance imaging (MRI). This research contains voxel-based morphometry (VBM), voxel-based quantitative susceptibility mapping (QSM) analysis, ROI-based QSM analysis, and correlation analysis. RESULTS svMCI patients showed more seriously cognitive impairment than HC patients. VBM analyses showed gray matter atrophy in the cingulate gyrus in the svMCI. Voxel-based QSM analyses showed increased susceptibilities in the right middle frontal gyrus, left paracentral lobule, as well as decreased susceptibility in the right postcentral gyrus in the svMCI. And ROI-based QSM analyses showed increased susceptibilities in left caudate nucleus and cerebellum in the svMCI. In addition, the susceptibility in left middle cingulate cortex and paracingulate gyrus was positively correlated associated with MoCA scores (r = 0.538 p < 0.001), and the susceptibility in the right middle frontal gyrus was negatively correlated with MoCA scores (r = -0.418 p < 0.007). CONCLUSIONS The results of our studies suggest that morphological alterations and iron burden in the brain may be related to cognitive dysfunction in svMCI patients, providing a new way to explore underlying neural mechanisms of cognitive dysfunction.
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Affiliation(s)
- Yushuang Liu
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China; Guangzhou Geriatric Hospital, Guangzhou 510000, China
| | - Yingqi Lu
- Department of Rehabilitation Medicine, The People's Hospital of Baoan Shenzhen, Shenzhen 518101, China; The Second Affiliated Hospital of Shenzhen University, Shenzhen 518101, China; Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Liyu Hu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Xingchen Liu
- Hospital of Traditional Chinese Medicine of Zhongshan, Zhongshan 528400, China
| | - Nan Yang
- Hospital of Traditional Chinese Medicine of Zhongshan, Zhongshan 528400, China.
| | - Shangjie Chen
- Department of Rehabilitation Medicine, The People's Hospital of Baoan Shenzhen, Shenzhen 518101, China; The Second Affiliated Hospital of Shenzhen University, Shenzhen 518101, China.
| | - Zhongling Zhang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
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Thompson GJ, Wang Z, Kim JY, Li H, Kim DH, Ye Q, Su MY. Histological Validation of Multi-Echo Gradient Echo (MGRE)-Derived Myelin Water Fraction (MWF) at 9.4 T and the Influence of Orientation on Quantification. NMR IN BIOMEDICINE 2025; 38:e5303. [PMID: 39701559 DOI: 10.1002/nbm.5303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Revised: 11/18/2024] [Accepted: 11/19/2024] [Indexed: 12/21/2024]
Abstract
Myelin is essential in the nervous system of mammals. As the location and degree of myelin loss can reflect varied pathophysiological status, noninvasive measurement of myelin is of high importance. The magnetic resonance imaging (MRI) technique of myelin water fraction (MWF) derived from multi-echo gradient echo (MGRE) sequence is a promising tool for the quantification of myelin content due to the low specific absorption rate (SAR) compared with the spin-echo sequence, time efficiency, and wide availability. Yet to our knowledge, MGRE-derived MWF has never been quantitatively validated with histology. The main objective of this study was to quantitatively validate the MRI findings by referencing the myelin histology using a rat model. As a second objective, we investigated how the orientation of white matter fibers with respect to the static B0 field impacted both the apparent transverse relaxation rate (R2* = 1/T2*) and the derived MWF. Moreover, MWF is known to change with age; thus, we compared rat brains of different ages. The orientation effect of MWF in a clinical setting was studied using 3 T human data. Twenty ex vivo rat brains with different ages and three healthy volunteers were scanned on a 9.4 T Bruker and 3.0 T Siemens systems, respectively. The 3D MGRE and diffusion tensor imaging (DTI) data were acquired. Our results showed a highly significant correlation between MGRE-derived MWF and histological stain of myelin, and susceptibility and diffusivity also demonstrated a significant association with myelin. Both MWF and R2* (R2* = 1/T2*) values changed as a function of orientation, and the function varied with age. Furthermore, MWF and R2* were more sensitive to age than DTI. In vivo 3 T human MWF also changed substantially with the orientation as well. Our results support that MGRE-derived MWF can be used to assess the myelin content quantitatively.
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Affiliation(s)
| | - Ziyi Wang
- Human Institute, ShanghaiTech University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jae-Yoon Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Hui Li
- Human Institute, ShanghaiTech University, Shanghai, China
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Qiong Ye
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, China
| | - Min-Ying Su
- Department of Radiological Sciences, University of California, Irvine, California, USA
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Milovic C, Tejos C, Silva J, Shmueli K, Irarrazaval P. XSIM: A structural similarity index measure optimized for MRI QSM. Magn Reson Med 2025; 93:411-421. [PMID: 39176438 DOI: 10.1002/mrm.30271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 07/03/2024] [Accepted: 08/06/2024] [Indexed: 08/24/2024]
Abstract
PURPOSE The structural similarity index measure (SSIM) has become a popular quality metric to evaluate QSM in a way that is closer to human perception than RMS error (RMSE). However, SSIM may overpenalize errors in diamagnetic tissues and underpenalize them in paramagnetic tissues, resulting in biasing. In addition, extreme artifacts may compress the dynamic range, resulting in unrealistically high SSIM scores (hacking). To overcome biasing and hacking, we propose XSIM: SSIM implemented in the native QSM range, and with internal parameters optimized for QSM. METHODS We used forward simulations from a COSMOS ground-truth brain susceptibility map included in the 2016 QSM Reconstruction Challenge to investigate the effect of QSM reconstruction errors on the SSIM, XSIM, and RMSE metrics. We also used these metrics to optimize QSM reconstructions of the in vivo challenge data set. We repeated this experiment with the QSM abdominal phantom. To validate the use of XSIM instead of SSIM for QSM quality assessment across a range of different reconstruction techniques/algorithms, we analyzed the reconstructions submitted to the 2019 QSM Reconstruction Challenge 2.0. RESULTS Our experiments confirmed the biasing and hacking effects on the SSIM metric applied to QSM. The XSIM metric was robust to those effects, penalizing the presence of streaking artifacts and reconstruction errors. Using XSIM to optimize QSM reconstruction regularization weights returned less overregularization than SSIM and RMSE. CONCLUSION XSIM is recommended over traditional SSIM to evaluate QSM reconstructions against a known ground truth, as it avoids biasing and hacking effects and provides a larger dynamic range of scores.
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Affiliation(s)
- Carlos Milovic
- School of Electrical Engineering, Pontificia Universidad Catolica de Valparaiso, Valparaiso, Chile
| | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH), Santiago, Chile
| | - Javier Silva
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Pablo Irarrazaval
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH), Santiago, Chile
- Institute for Biological and Medical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
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Kiersnowski OC, Fuchs P, Wastling SJ, Nassar J, Thornton JS, Shmueli K. Multiband accelerated 2D EPI for multi-echo brain QSM at 3 T. Magn Reson Med 2025; 93:183-198. [PMID: 39164832 DOI: 10.1002/mrm.30267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 06/26/2024] [Accepted: 08/05/2024] [Indexed: 08/22/2024]
Abstract
PURPOSE Data for QSM are typically acquired using multi-echo 3D gradient echo (GRE), but EPI can be used to accelerate QSM and provide shorter acquisition times. So far, EPI-QSM has been limited to single-echo acquisitions, which, for 3D GRE, are known to be less accurate than multi-echo sequences. Therefore, we compared single-echo and multi-echo EPI-QSM reconstructions across a range of parallel imaging and multiband acceleration factors. METHODS Using 2D single-shot EPI in the brain, we compared QSM from single-echo and multi-echo acquisitions across combined parallel-imaging and multiband acceleration factors ranging from 2 to 16, with volume pulse TRs from 21.7 to 3.2 s, respectively. For single-echo versus multi-echo reconstructions, we investigated the effect of acceleration factors on regional susceptibility values, temporal noise, and image quality. We introduce a novel masking method based on thresholding the magnitude of the local field gradients to improve brain masking in challenging regions. RESULTS At 1.6-mm isotropic resolution, high-quality QSM was achieved using multi-echo 2D EPI with a combined acceleration factor of 16 and a TR of 3.2 s, which enables functional applications. With these high acceleration factors, single-echo reconstructions are inaccurate and artefacted, rendering them unusable. Multi-echo acquisitions greatly improve QSM quality, particularly at higher acceleration factors, provide more consistent regional susceptibility values across acceleration factors, and decrease temporal noise compared with single-echo QSM reconstructions. CONCLUSION Multi-echo acquisition is more robust for EPI-QSM across parallel imaging and multiband acceleration factors than single-echo acquisition. Multi-echo EPI can be used for highly accelerated acquisition while preserving QSM accuracy and quality relative to gold-standard 3D-GRE QSM.
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Affiliation(s)
- Oliver C Kiersnowski
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Neuroradiology Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Patrick Fuchs
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Stephen J Wastling
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK
- Lysholm Department of Neuroradiology, London, UK
| | - Jannette Nassar
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK
- Lysholm Department of Neuroradiology, London, UK
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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30
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Meng Y, Allen JW, Sharghi VK, Qiu D. Motion and temporal B 0-shift corrections for QSM and R 2 * mapping using dual-echo spiral navigators and conjugate-phase reconstruction. Magn Reson Med 2025; 93:199-212. [PMID: 39233495 DOI: 10.1002/mrm.30266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 08/03/2024] [Accepted: 08/05/2024] [Indexed: 09/06/2024]
Abstract
PURPOSE To develop an efficient navigator-based motion and temporal B0-shift correction technique for 3D multi-echo gradient-echo (ME-GRE) MRI for quantitative susceptibility mapping (QSM) andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ mapping. THEORY AND METHODS A dual-echo 3D stack-of-spiral navigator was designed to interleave with the Cartesian multi-echo gradient-echo acquisitions, allowing the acquisition of both low-echo and high-echo time signals. We additionally designed a novel conjugate phase-based reconstruction method for the joint correction of motion and temporal B0 shifts. We performed numerical simulation, phantom scans, and in vivo human scans to assess the performance of the methods. RESULTS Numerical simulation and human brain scans demonstrated that the proposed technique successfully corrected artifacts induced by both head motions and temporal B0 changes. Efficient B0-change correction with conjugate-phase reconstruction can be performed on fewer than 10 clustered k-space segments. In vivo scans showed that combining temporal B0 correction with motion correction further reduced artifacts and improved image quality in bothR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM images. CONCLUSION Our proposed approach of using 3D spiral navigators and a novel conjugate-phase reconstruction method can improve susceptibility-related measurements using MR.
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Affiliation(s)
- Yuguang Meng
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Jason W Allen
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA
| | | | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA
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31
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Wu W, Su Y, Qin Z, Kang J, Xiang D, Liu D, Zheng C, Haacke EM, Wang L. Quantitative Assessment of Deep Gray Matter Susceptibility and Correlation With Cognition in Patients With Liver Cirrhosis. Brain Behav 2025; 15:e70240. [PMID: 39778978 PMCID: PMC11710887 DOI: 10.1002/brb3.70240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 09/23/2024] [Accepted: 12/14/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND AND OBJECTIVES Accumulation of metals quantified by quantitative susceptibility mapping (QSM) in deep gray matter (DGM) and their impact on cognition have not been studied in patients with liver cirrhosis. This study aims to use QSM to investigate the association between DGM susceptibility and cognition in cirrhotic patients. METHODS Thirty cirrhotic patients and 30 age-, gender-, and education-matched controls were imaged using a multiecho gradient-echo sequence for QSM analysis in a 3T scanner. The susceptibility values were determined for the caudate nucleus (CN), putamen (PU), globus pallidus (GP), thalamus (TH), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN). All subjects underwent number connection test A (NCT-A), digit substitution test (DST), and Montreal Cognitive Assessment (MoCA). Comparisons between the two groups and the correlation between the susceptibility values and neuropsychological scores were analyzed. RESULTS The susceptibility values of bilateral CN, TH, and RN were significantly lower in cirrhotic patients. Cirrhotic patients exhibited significantly prolonged NCT-A time and decreased DST and MoCA scores. The NCT-A, DST, MoCA, and sub-domain scores were correlated with susceptibility values of RN, DN, SN, and CN, respectively. The susceptibility value of the left RN was a predictor variable for the DST, MoCA, and visuospatial-executive scores; those of the right CN and left RN were predictor variables for the naming score, and that of the left SN was an independent predictor variable for the language score. CONCLUSIONS Altered susceptibility values of DGM measured by QSM are potential quantitative indicators of cognitive impairment in cirrhotic patients.
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Affiliation(s)
- Wenjun Wu
- Department of Radiology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Province Key Laboratory of Molecular ImagingWuhanChina
| | - Yu Su
- Department of Radiology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Ziji Qin
- Department of RadiologyThe People's Hospital of Guangxi Zhuang Autonomous RegionGuangxi Academy of Medical SciencesNanningChina
| | - Jiamin Kang
- Department of Radiology, Wuhan No. 1 Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Dongqiao Xiang
- Department of Radiology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Province Key Laboratory of Molecular ImagingWuhanChina
| | - Dingxi Liu
- Department of Radiology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Province Key Laboratory of Molecular ImagingWuhanChina
| | - Chuansheng Zheng
- Department of Radiology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Province Key Laboratory of Molecular ImagingWuhanChina
| | - E. Mark Haacke
- Magnetic Resonance InnovationsBingham FarmsMichiganUSA
- Department of RadiologyWayne State UniversityDetroitMichiganUSA
| | - Lixia Wang
- Department of Radiology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Province Key Laboratory of Molecular ImagingWuhanChina
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Yoshida A, Hikosaka O. Contribution of glutamatergic projections to neurons in the nonhuman primate lateral substantia nigra pars reticulata for the reactive inhibition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.25.630331. [PMID: 39763854 PMCID: PMC11703221 DOI: 10.1101/2024.12.25.630331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
The basal ganglia play a crucial role in action selection by facilitating desired movements and suppressing unwanted ones. The substantia nigra pars reticulata (SNr), a key output nucleus, facilitates movement through disinhibition of the superior colliculus (SC). However, its role in action suppression, particularly in primates, remains less clear. We investigated whether individual SNr neurons in three male macaque monkeys bidirectionally modulate their activity to both facilitate and suppress actions and examined the role of glutamatergic inputs in suppression. Monkeys performed a sequential choice task, selecting or rejecting visually presented targets. Electrophysiological recordings showed SNr neurons decreased firing rates during target selection and increased firing rates during rejection, demonstrating bidirectional modulation. Pharmacological blockade of glutamatergic inputs to the lateral SNr disrupted saccadic control and impaired suppression of reflexive saccades, providing causal evidence for the role of excitatory input in behavioral inhibition. These findings suggest that glutamatergic projections, most likely from the subthalamic nucleus, drive the increased SNr activity during action suppression. Our results highlight conserved basal ganglia mechanisms across species and offer insights into the neural substrates of action selection and suppression in primates, with implications for understanding disorders such as Parkinson's disease.
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Affiliation(s)
- Atsushi Yoshida
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Systems Neuroscience Laboratory, Department of Physiology, Hokkaido University Graduate School of Medicine, Sapporo, 060-8638, Hokkaido, Japan
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
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Dal-Bianco A, Oh J, Sati P, Absinta M. Chronic active lesions in multiple sclerosis: classification, terminology, and clinical significance. Ther Adv Neurol Disord 2024; 17:17562864241306684. [PMID: 39711984 PMCID: PMC11660293 DOI: 10.1177/17562864241306684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2024] [Accepted: 11/18/2024] [Indexed: 12/24/2024] Open
Abstract
In multiple sclerosis (MS), increasing disability is considered to occur due to persistent, chronic inflammation trapped within the central nervous system (CNS). This condition, known as smoldering neuroinflammation, is present across the clinical spectrum of MS and is currently understood to be relatively resistant to treatment with existing disease-modifying therapies. Chronic active white matter lesions represent a key component of smoldering neuroinflammation. Initially characterized in autopsy specimens, multiple approaches to visualize chronic active lesions (CALs) in vivo using advanced neuroimaging techniques and postprocessing methods are rapidly emerging. Among these in vivo imaging correlates of CALs, paramagnetic rim lesions (PRLs) are defined by the presence of a perilesional rim formed by iron-laden microglia and macrophages, whereas slowly expanding lesions are identified based on linear, concentric lesion expansion over time. In recent years, several longitudinal studies have linked the occurrence of in vivo detected CALs to a more aggressive disease course. PRLs are highly specific to MS and therefore have recently been incorporated into the MS diagnostic criteria. They also have prognostic potential as biomarkers to identify patients at risk of early and severe disease progression. These developments could significantly affect MS care and the evaluation of new treatments. This review describes the latest knowledge on CAL biology and imaging and the relevance of CALs to the natural history of MS. In addition, we outline considerations for current and future in vivo biomarkers of CALs, emphasizing the need for validation, standardization, and automation in their assessment.
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Affiliation(s)
- Assunta Dal-Bianco
- Department of Neurology, Medical University of Vienna, Währinger Gürtel 18–20, Vienna 1090, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Jiwon Oh
- Division of Neurology, Department of Medicine, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
| | - Pascal Sati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Martina Absinta
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
- Experimental Neuropathology Lab, Neuro Center, IRCCS Humanitas Research Hospital, Milan, Italy
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Orenstein S, Fang Z, Shin HG, van Zijl P, Li X, Sulam J. ProxiMO: Proximal Multi-operator Networks for Quantitative Susceptibility Mapping. MACHINE LEARNING IN CLINICAL NEUROIMAGING : 7TH INTERNATIONAL WORKSHOP, MLCN 2024, HELD IN CONJUNCTION WITH MICCAI 2024, MARRAKESH, MOROCCO, OCTOBER 10, 2024, PROCEEDINGS. MLCN (WORKSHOP) (7TH : 2024 : MARRAKESH, MOROCCO) 2024; 15266:13-23. [PMID: 39776602 PMCID: PMC11705005 DOI: 10.1007/978-3-031-78761-4_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
Quantitative Susceptibility Mapping (QSM) is a technique that derives tissue magnetic susceptibility distributions from phase measurements obtained through Magnetic Resonance (MR) imaging. This involves solving an ill-posed dipole inversion problem, however, and thus time-consuming and cumbersome data acquisition from several distinct head orientations becomes necessary to obtain an accurate solution. Most recent (supervised) deep learning methods for single-phase QSM require training data obtained via multiple orientations. In this work, we present an alternative unsupervised learning approach that can efficiently train on single-orientation measurement data alone, named ProxiMO (Proximal Multi-Operator), combining Learned Proximal Convolutional Neural Networks (LP-CNN) with multi-operator imaging (MOI). This integration enables LP-CNN training for QSM on single-phase data without ground truth reconstructions. We further introduce a semi-supervised variant, which further boosts the reconstruction performance, compared to the traditional supervised fashions. Extensive experiments on multicenter datasets illustrate the advantage of unsupervised training and the superiority of the proposed approach for QSM reconstruction. Code is available at https://github.com/shmuelor/ProxiMO.
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Affiliation(s)
- Shmuel Orenstein
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Zhenghan Fang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD 21218, USA
| | - Hyeong-Geol Shin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Peter van Zijl
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD 21218, USA
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Li J, Villar-Calle P, Chiu C, Reza M, Narula N, Li C, Zhang J, Nguyen TD, Wang Y, Zhang RS, Kim J, Weinsaft JW, Spincemaille P. Spiral cardiac quantitative susceptibility mapping for differential cardiac chamber oxygenation-Initial validation in relation to invasive blood sampling. Magn Reson Med 2024. [PMID: 39641910 DOI: 10.1002/mrm.30393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Revised: 10/18/2024] [Accepted: 11/18/2024] [Indexed: 12/07/2024]
Abstract
PURPOSE To develop a breath-hold cardiac quantitative susceptibility mapping (QSM) sequence for noninvasive measurement of differential cardiac chamber blood oxygen saturation (ΔSO2). METHODS A non-gated three-dimensional stack-of-spirals QSM sequence was implemented to continuously sample the data throughout the cardiac cycle. Measurements of ΔSO2 between the right and left heart chamber obtained by the proposed sequence and a previously validated navigator Cartesian QSM sequence were compared in three cohorts consisting of healthy volunteers, coronavirus disease 2019 survivors, and patients with pulmonary hypertension. In the pulmonary-hypertension cohort, Bland-Altman plots were used to assess the agreement of ΔSO2 values obtained by QSM and those obtained by invasive right heart catheterization (RHC). RESULTS Compared with navigator QSM (average acquisition time 419 ± 158 s), spiral QSM reduced the scan time on average by over 20-fold to a 20-s breath-hold. In all three cohorts, spiral QSM and navigator QSM yielded similar ΔSO2. Among healthy volunteers and coronavirus disease 2019 survivors, ΔSO2 was 17.41 ± 4.35% versus 17.67 ± 4.09% for spiral and navigator QSM, respectively. In pulmonary-hypertension patients, spiral QSM showed a slightly smaller ΔSO2 bias and narrower 95% limits of agreement than that obtained by navigator QSM (1.09% ± 6.47% vs. 2.79% ± 6.99%) when compared with right heart catheterization. CONCLUSION Breath-hold three-dimensional spiral cardiac QSM for measuring differential cardiac chamber blood oxygenation is feasible and provides values in good agreement with navigator cardiac QSM and with reference right heart catheterization.
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Affiliation(s)
- Jiahao Li
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | | | - Caitlin Chiu
- Department of Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Mahniz Reza
- Department of Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Nupoor Narula
- Department of Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Chao Li
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- School of Applied and Engineering Physics, Cornell University, Ithaca, New York, USA
| | - Jinwei Zhang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Yi Wang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Robert S Zhang
- Department of Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Jiwon Kim
- Department of Medicine, Weill Cornell Medicine, New York, New York, USA
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36
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Zachariou V, Bauer CE, Pappas C, Gold BT. A Review of the Association Between Dietary Intake and Brain Iron Levels in Older Adults: Preliminary Findings and Future Directions. Nutrients 2024; 16:4193. [PMID: 39683586 DOI: 10.3390/nu16234193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2024] [Revised: 11/20/2024] [Accepted: 11/27/2024] [Indexed: 12/18/2024] Open
Abstract
Background/Objectives: Non-heme iron is essential for critical neuronal functions such as ATP generation, synaptogenesis, neurotransmitter synthesis, and myelin formation. However, as non-heme iron accumulates with age, excessive levels can contribute to oxidative stress, potentially disrupting neuronal integrity and contributing to cognitive decline. Despite growing evidence linking high brain iron with poorer cognitive performance, there are currently no proven methods to reduce brain iron accumulation in aging or to protect cognitive function from iron's negative effects. Recent studies suggest that nutrition may influence brain iron levels, though the evidence remains limited and mixed. Methods: In this review, we explore recent findings, including our own cross-sectional and longitudinal studies, to evaluate the potential effectiveness of healthy diets and specific nutrients in mitigating brain iron accumulation during aging. We also briefly assess the roles of age and gender as factors in the relationship between dietary factors and brain iron load. Results: The limited findings in the literature indicate that dietary choices may impact brain iron levels. In particular, nutrients such as vitamins, antioxidants, iron-chelators, and polyunsaturated fatty acids may slow brain iron accumulation in older adults. Conclusions: Our review highlights the multiple gaps in current knowledge and underscores a critical need for additional research on this important topic.
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Affiliation(s)
- Valentinos Zachariou
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY 40536, USA
| | - Christopher E Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536, USA
| | - Colleen Pappas
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536, USA
| | - Brian T Gold
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536, USA
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536, USA
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY 40504, USA
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37
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Lu W, Song T, Zang Z, Li J, Zhang Y, Lu J. Relaxometry network based on MRI R 2⁎ mapping revealing brain iron accumulation patterns in Parkinson's disease. Neuroimage 2024; 303:120943. [PMID: 39571643 DOI: 10.1016/j.neuroimage.2024.120943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 10/12/2024] [Accepted: 11/18/2024] [Indexed: 11/27/2024] Open
Abstract
BACKGROUND Excessive iron accumulation in the brain has been implicated in Parkinson's disease (PD). However, the patterns and probable sequences of iron accumulation across the PD brain remain largely unknown. This study aimed to explore the sequence of iron accumulation across the PD brain using R2* mapping and a relaxometry covariance network (RCN) approach. METHODS R2* quantification maps were obtained from PD patients (n = 34) and healthy controls (n = 25). RCN was configured on R2* maps to identify covariance differences in iron levels between the two groups. Regions with excessive iron accumulation and large covariance changes in PD patients compared to controls were defined as propagators of iron. In the PD group, causal RCN analysis was performed on the R2* maps sequenced according to disease duration to investigate the dynamics of iron accumulations from the propagators. The associations between individual connections of the RCN and clinical information were analyzed in PD patients. RESULTS The left substantia nigra pars reticulata (SNpr), left substantia nigra pars compacta (SNpc), and lobule VII of the vermis (VER7) were identified as primary regions for iron accumulation and propagation (propagator). As the disease duration increased, iron accumulation in these three propagators demonstrated positive causal effects on the bilateral pallidum, bilateral gyrus rectus, right middle frontal gyrus, and medial and anterior orbitofrontal cortex (OFC). Furthermore, individual connections of VER7 with the left gyrus rectus and anterior OFC were positively associated with disease duration. CONCLUSIONS Our results indicate that the aberrant iron accumulation in PD involves several regions, mainly starts from the SN and cerebellum and extends to the pallidum and cortices. These findings provide preliminary information on sequences of iron accumulation in PD, which may advance our understanding of the disease.
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Affiliation(s)
- Weizhao Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Xuanwu Hospital, Beijing, 100053, China
| | - Tianbin Song
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Xuanwu Hospital, Beijing, 100053, China
| | - Zhenxiang Zang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jiping Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yuqing Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Xuanwu Hospital, Beijing, 100053, China.
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38
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Casula V, Kajabi AW. Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications. MAGMA (NEW YORK, N.Y.) 2024; 37:949-967. [PMID: 38904746 PMCID: PMC11582218 DOI: 10.1007/s10334-024-01174-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 05/04/2024] [Accepted: 05/30/2024] [Indexed: 06/22/2024]
Abstract
Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.
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Affiliation(s)
- Victor Casula
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
| | - Abdul Wahed Kajabi
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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39
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Huang Y, Guan X, Zhang X, Yoosefian G, Ho H, Huang LT, Lin HY, Anthony G, Lee HL, Bi X, Han F, Chan SF, Vora KP, Sharif B, Singh DP, Youssef K, Li D, Han H, Christodoulou AG, Dharmakumar R, Yang HJ. Accurate Intramyocardial Hemorrhage Assessment with Fast, Free-running, Cardiac Quantitative Susceptibility Mapping. Radiol Cardiothorac Imaging 2024; 6:e230376. [PMID: 39665631 DOI: 10.1148/ryct.230376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2024]
Abstract
Purpose To evaluate the performance of a high-dynamic-range quantitative susceptibility mapping (HDR-QSM) cardiac MRI technique to detect intramyocardial hemorrhage (IMH) and quantify iron content using phantom and canine models. Materials and Methods A free-running whole-heart HDR-QSM technique for IMH assessment was developed and evaluated in calibrated iron phantoms and 14 IMH female canine models. IMH detection and iron content quantification performance of this technique was compared with the conventional iron imaging approaches, R2*(1/T2*) maps, using measurements from ex vivo imaging as the reference standard. Results Phantom studies confirmed HDR-QSM's accurate iron content quantification and artifact mitigation ability by revealing a strong linear relationship between iron concentration and QSM values (R2, 0.98). In in vivo studies, HDR-QSM showed significantly improved image quality and susceptibility homogeneity in nonaffected myocardium by alleviating motion and off-resonance artifacts (HDR-QSM vs R2*: coefficient of variation, 0.31 ± 0.16 [SD] vs 0.73 ± 0.36 [P < .001]; image quality score [five-point Likert scale:], 3.58 ± 0.75 vs 2.87 ± 0.51 [P < .001]). Comparison between in vivo susceptibility maps and ex vivo measurements showed higher performance of HDR-QSM compared with R2* mapping for IMH detection (area under the receiver operating characteristic curve, 0.96 vs 0.75; P < .001) and iron content quantification (R2, 0.71 vs 0.14). Conclusion In a canine model of IMH, the fast and free-running cardiac QSM technique accurately detected IMH and quantified intramyocardial iron content of the entire heart within 5 minutes without requiring breath holding. Keywords: High-Dynamic-Range Quantitative Susceptibility Mapping, Myocardial Infarction, Intramyocardial Hemorrhage, MRI Supplemental material is available for this article. ©RSNA, 2024.
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Affiliation(s)
- Yuheng Huang
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Xingmin Guan
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Xinheng Zhang
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Ghazal Yoosefian
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Hao Ho
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Li-Ting Huang
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Hsin-Yao Lin
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Gregory Anthony
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Hsu-Lei Lee
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Xiaoming Bi
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Fei Han
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Shing Fai Chan
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Keyur P Vora
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Behzad Sharif
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Dhirendra P Singh
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Khalid Youssef
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Debiao Li
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Hui Han
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Anthony G Christodoulou
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Rohan Dharmakumar
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
| | - Hsin-Jung Yang
- From the Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Pacific Theatres Bldg, Ste 400, Los Angeles, CA 90048 (Y.H., L.T.H., H.L.L., D.L., H. Han, A.G.C., H.J.Y.); Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Ind (Y.H., X.G., X.Z., G.Y., G.A., S.F.C., K.P.V., B.S., D.P.S., K.Y., R.D.); Departments of Bioengineering (Y.H., X.Z., A.G.C.) and Statistics (H. Ho), University of California Los Angeles, Los Angeles, Calif; Academia Sinica, Institute of Statistical Science, Nankang, Taipei, Taiwan (H. Ho); Department of Surgery, Division of Neurosurgery, Mackay Memorial Hospital, Taipei, Taiwan (L.T.H.); Department of Medical Imaging, National Cheng Kung University Hospital, Tainan, Taiwan (H.Y.L.); Siemens Medical Solutions USA, Malvern, Pa (X.B., F.H.); and Department of Radiological Sciences, University of California Los Angeles David Geffen School of Medicine, Los Angeles, Calif (A.G.C.)
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Manasseh G, Hilbert T, Fartaria MJ, Deverdun J, Cuadra MB, Maréchal B, Kober T, Dunet V. Automated Quantitative Susceptibility and Morphometry MR Study: Feasibility and Interrelation Between Clinical Score, Lesion Load, Deep Grey Matter and Normal-Appearing White Matter in Multiple Sclerosis. Diagnostics (Basel) 2024; 14:2669. [PMID: 39682577 DOI: 10.3390/diagnostics14232669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Revised: 11/22/2024] [Accepted: 11/24/2024] [Indexed: 12/18/2024] Open
Abstract
INTRODUCTION Lesion load (LL), deep gray matter (DGM) and normal-appearing white matter (NAWM) susceptibility and morphometry may help in monitoring brain changes in multiple sclerosis (MS) patients. We aimed at evaluating the feasibility of a fully automated segmentation and the potential interrelation between these biomarkers and clinical disability. METHODS Sixty-six patients with brain MRIs and clinical evaluations (Expanded Disability Status Scale [EDSS]) were retrospectively included. Automated prototypes were used for the segmentation and morphometry of brain regions (MorphoBox) and MS lesions (LeManPV). Susceptibility maps were estimated using standard post-processing (RESHARP and TVSB). Spearman's rho was computed to evaluate the interrelation between biomarkers and EDSS. RESULTS We found (i) anticorrelations between the LL and right thalamus susceptibility (rho = -0.46, p < 0.001) and between the LL and NAWM susceptibility (rho = [-0.68 to -0.25], p ≤ 0.05); (ii) an anticorrelation between LL and DGM (rho = [-0.71 to -0.36], p < 0.04) and WM morphometry (rho = [-0.64 to -0.28], p ≤ 0.01); and (iii) a positive correlation between EDSS and LL (rho = [0.28 to 0.5], p ≤ 0.03) and anticorrelation between EDSS and NAWM susceptibility (rho = [-0.29 to -0.38], p < 0.014). CONCLUSIONS Fully automated brain morphometry and susceptibility monitoring is feasible in MS patients. The lesion load, thalamus and NAWM susceptibility values and trophicity are interrelated and correlate with disability.
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Affiliation(s)
- Gibran Manasseh
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Tom Hilbert
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, 1015 Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Mário João Fartaria
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, 1015 Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Jeremy Deverdun
- I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, 34295 Montpellier, France
| | - Meritxell Bach Cuadra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- CIBM Center of Biomedical Imaging, 1015 Lausanne, Switzerland
| | - Bénédicte Maréchal
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, 1015 Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Tobias Kober
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, 1015 Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Vincent Dunet
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
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Wu D, Li Y, Zhang S, Chen Q, Fang J, Cho J, Wang Y, Yan S, Zhu W, Lin J, Wang Z, Zhang Y. Trajectories and sex differences of brain structure, oxygenation and perfusion functions in normal aging. Neuroimage 2024; 302:120903. [PMID: 39461605 DOI: 10.1016/j.neuroimage.2024.120903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 10/07/2024] [Accepted: 10/23/2024] [Indexed: 10/29/2024] Open
Abstract
BACKGROUND Brain structure, oxygenation and perfusion are important factors in aging. Coupling between regional cerebral oxygen consumption and perfusion also reflects functions of neurovascular unit (NVU). Their trajectories and sex differences during normal aging important for clinical interpretation are still not well defined. In this study, we aim to investigate the relationship between brain structure, functions and age, and exam the sex disparities. METHOD A total of 137 healthy subjects between 20∼69 years old were enrolled with conventional MRI, structural three-dimensional T1-weighted imaging (3D-T1WI), 3D multi-echo gradient echo sequence (3D-mGRE), and 3D pseudo-continuous arterial spin labeling (3D-pCASL). Oxygen extraction fraction (OEF) and cerebral blood flow (CBF) were respectively reconstructed from 3D-mGRE and 3D-pCASL images. Cerebral metabolic rate of oxygen (CMRO2) were calculated as follows: CMRO2=CBF·OEF·[H]a, [H]a=7.377 μmol/mL. Brains were segmented into global gray matter (GM), global white matter (WM), and 148 cortical subregions. OEF, CBF, CMRO2, and volumes of GM/WM relative to intracranial volumes (rel_GM/rel_WM) were compared between males and females. Generalized additive models were used to evaluate the aging trajectories of brain structure and functions. The coupling between OEF and CBF was analyzed by correlation analysis. P or PFDR < 0.05 was considered statistically significant. RESULTS Females had larger rel_GM, higher CMRO2 and CBF of GM/WM than males (P < 0.05). With control of sex, CBF of GM significantly declined between 20 and 32 years, CMRO2 of GM declined subsequently from 33 to 41 years and rel_GM decreased significantly at all ages (R2 = 0.27, P < 0.001; R2 = 0.17, P < 0.001; R2 = 0.52, P < 0.001). In subregion analysis, CBF declined dispersedly while CMRO2 declined widely across most subregions of the cortex during aging. Robust negative coupling between OEF and CBF was found in most of the subregions (r range = -0.12∼-0.48, PFDR < 0.05). CONCLUSION The sex disparities, age trajectories of brain structure and functions as well as the coupling of NVU in healthy individuals provide insights into normal aging which are potential targets for study of pathological conditions.
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Affiliation(s)
- Di Wu
- Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
| | - Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiuyue Chen
- Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
| | - Jiayu Fang
- Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
| | - Junghun Cho
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY 14260, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA; Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junyu Lin
- Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
| | - Zhenxiong Wang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.
| | - Yaqin Zhang
- Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China.
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Otsuka FS, Otaduy MCG, Rodriguez RD, Langkammer C, Barbosa JHO, Salmon CEG. Biophysical contrast sources for magnetic susceptibility and R2* mapping: A combined 7 Tesla, mass spectrometry and electron paramagnetic resonance study. Neuroimage 2024; 302:120892. [PMID: 39433113 DOI: 10.1016/j.neuroimage.2024.120892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Accepted: 10/16/2024] [Indexed: 10/23/2024] Open
Abstract
Iron is the most abundant trace metal in the human brain and consistently shown elevated in prevalent neurological disorders. Because of its paramagnetism, brain iron can be assessed in vivo by quantitative MRI techniques such as R2* mapping and Quantitative Susceptibility Mapping (QSM). While Inductively Coupled Plasma Mass Spectrometry (ICP-MS) has demonstrated good correlations of the total iron content to MRI parameters in gray matter, the relationship to ferritin levels as assessed by Electron Paramagnetic Resonance (EPR) has not been systematically analyzed. Therefore, we included 15 postmortem subjects (age: 26-91 years) which underwent quantitative in-situ MRI at 7 Tesla within a post-mortem interval of 24 h after death. ICP-MS and EPR were used to measure the total iron and ferritin content in 8 selected gray matter (GM) structures and the correlations to R2* and QSM were calculated. We found that R2* and QSM in the iron rich basal ganglia and the red nucleus were highly correlated with iron (R² > 0.7) and ferritin (R² > 0.6), whereas those correlations were lost in cortical regions and the hippocampus. The neuromelanin-rich substantia nigra showed a different behavior with a correlation with total iron only (R² > 0.5) but not with ferritin. Although qualitative results were similar for both qMRI techniques the observed correlation was always stronger for QSM than R2*. This study demonstrated the quantitative correlations between R2*, QSM, total iron and ferritin levels in an in-situ MRI setup and therefore aids to understand how molecular forms of iron are responsible for MRI contrast generation.
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Affiliation(s)
- Fábio Seiji Otsuka
- InBrain, Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo USP, Avenida Bandeirantes 3900, Vila Monte Alegre, Ribeirão Preto, São Paulo CEP 14040-901, Brazil.
| | - Maria Concepción Garcia Otaduy
- LIM44, Instituto de Radiologia (InRad), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, São Paulo, Brazil
| | - Roberta Diehl Rodriguez
- LIM44, Instituto de Radiologia (InRad), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, São Paulo, Brazil
| | | | - Jeam Haroldo Oliveira Barbosa
- InBrain, Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo USP, Avenida Bandeirantes 3900, Vila Monte Alegre, Ribeirão Preto, São Paulo CEP 14040-901, Brazil; Setor de Radioterapia, Santa Casa de Misericórdia de Lavras, Minas Gerais, Brazil
| | - Carlos Ernesto Garrido Salmon
- InBrain, Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo USP, Avenida Bandeirantes 3900, Vila Monte Alegre, Ribeirão Preto, São Paulo CEP 14040-901, Brazil; Departamento de Imagens Médicas, Hematologia e Oncologia Clínica, Faculdade de Medicina de Ribeirão Preto (FMRP), Universidade de Sãoo Paulo, Ribeirão Preto, Brazil.
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Elanghovan P, Nguyen T, Spincemaille P, Gupta A, Wang Y, Cho J. Sensitivity assessment of QSM+qBOLD (or QQ) in detecting elevated oxygen extraction fraction (OEF) in physiological change. J Cereb Blood Flow Metab 2024:271678X241298584. [PMID: 39501700 DOI: 10.1177/0271678x241298584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/12/2025]
Abstract
The study investigated the sensitivity of a novel MRI-based OEF mapping, quantitative susceptibility mapping plus quantitative blood oxygen level-dependent imaging (QSM+qBOLD or QQ), to physiological changes, particularly increased oxygen extraction fraction (OEF) by using hyperventilation as a vasoconstrictive stimulus. While QQ's sensitivity to decreased OEF during hypercapnia has been demonstrated, its sensitivity to increased OEF levels, crucial for cerebrovascular disorders like vascular dementia and Parkinson's disease, remains unexplored. In comparison with a previous QSM-based OEF, we evaluated QQ's sensitivity to high OEF values. MRI data were obtained from 11 healthy subjects during resting state (RS) and hyperventilation state (HV) using a 3 T MRI with a three-dimensional multi-echo gradient echo sequence (mGRE) and arterial spin labeling (ASL). Region of interest (ROI) analysis and paired t-tests were used to compare OEF, CMRO2 and CBF between QQ and QSM. Similar to QSM, QQ showed higher OEF during HV compared to RS: in cortical gray matter, QQ-OEF and QSM-OEF was 36.4 ± 4.7% and 35.3 ± 12.5% at RS and 45.0 ± 11.6% and 45.0 ± 14.8% in HV, respectively. These findings demonstrate QQ's ability to detect physiological changes and suggest its potential in studying brain metabolism in neurological disorders.
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Affiliation(s)
- Praveena Elanghovan
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
| | - Thanh Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | | | - Ajay Gupta
- Department of Radiology, Columbia University, New York, NY, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Junghun Cho
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
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Mohammadi S, Ghaderi S, Fatehi F. Iron accumulation/overload and Alzheimer's disease risk factors in the precuneus region: A comprehensive narrative review. Aging Med (Milton) 2024; 7:649-667. [PMID: 39507230 PMCID: PMC11535174 DOI: 10.1002/agm2.12363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 09/25/2024] [Indexed: 11/08/2024] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease that is characterized by amyloid plaques, neurofibrillary tangles, and neuronal loss. Early cerebral and body iron dysregulation and accumulation interact with AD pathology, particularly in the precuneus, a crucial functional hub in cognitive functions. Quantitative susceptibility mapping (QSM), a novel post-processing approach, provides insights into tissue iron levels and cerebral oxygen metabolism and reveals abnormal iron accumulation early in AD. Increased iron deposition in the precuneus can lead to oxidative stress, neuroinflammation, and accelerated neurodegeneration. Metabolic disorders (diabetes, non-alcoholic fatty liver disease (NAFLD), and obesity), genetic factors, and small vessel pathology contribute to abnormal iron accumulation in the precuneus. Therefore, in line with the growing body of literature in the precuneus region of patients with AD, QSM as a neuroimaging method could serve as a non-invasive biomarker to track disease progression, complement other imaging modalities, and aid in early AD diagnosis and monitoring.
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Affiliation(s)
- Sana Mohammadi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
| | - Sadegh Ghaderi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
| | - Farzad Fatehi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
- Neurology DepartmentUniversity Hospitals of Leicester NHS TrustLeicesterUK
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Sollmann N, Dieckmeyer M, Carballido-Gamio J, Van AT, Karampinos DC, Feuerriegel GC, Foreman SC, Gersing AS, Krug R, Baum T, Kirschke JS. Magnetic Resonance Assessment of Bone Quality in Metabolic Bone Diseases. Semin Musculoskelet Radiol 2024; 28:576-593. [PMID: 39406221 DOI: 10.1055/s-0044-1788693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
Abstract
Metabolic bone diseases (MBDs) are a diverse group of diseases, affecting the mass or structure of bones and leading to reduced bone quality. Parameters representing different aspects of bone health can be obtained from various magnetic resonance imaging (MRI) methods such as proton MR spectroscopy, as well as chemical shift encoding-based water-fat imaging, that have been frequently applied to study bone marrow in particular. Furthermore, T2* mapping and high-resolution trabecular bone imaging have been implemented to study bone microstructure. In addition, quantitative susceptibility mapping and ultrashort echo time imaging are used for trabecular and cortical bone assessment. This review offers an overview of technical aspects, as well as major clinical applications and derived main findings, for MRI-based assessment of bone quality in MBDs. It focuses on osteoporosis as the most common MBD.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic, Interventional, and Pediatric Radiology, Inselspital, University of Bern, Bern, Switzerland
| | - Julio Carballido-Gamio
- Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Anh Tu Van
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Georg C Feuerriegel
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology, Balgrist University Hospital, Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Sarah C Foreman
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Neuroradiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Roland Krug
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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Aiello EN, Contarino VE, Conte G, Solca F, Curti B, Maranzano A, Torre S, Casale S, Doretti A, Colombo E, Verde F, Silani V, Liu C, Cinnante C, Triulzi FM, Morelli C, Poletti B, Ticozzi N. QSM-detected iron accumulation in the cerebellar gray matter is selectively associated with executive dysfunction in non-demented ALS patients. Front Neurol 2024; 15:1426841. [PMID: 39364420 PMCID: PMC11448125 DOI: 10.3389/fneur.2024.1426841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 08/20/2024] [Indexed: 10/05/2024] Open
Abstract
Background This study aimed to assess whether quantitative susceptibility imaging (QSM)-based measures of iron accumulation in the cerebellum predict cognitive and behavioral features in non-demented amyotrophic lateral sclerosis (ALS) patients. Methods A total of ALS patients underwent 3-T MRI and a clinical assessment using the ALS Functional Rating Scale-Revised (ALSFRS-R) and the Edinburgh Cognitive and Behavioural ALS Screen (ECAS). Regression models were applied to each subscale of the cognitive section of the ECAS and the ECAS-Carer Interview to examine the effect of QSM-based measures in white and gray matter (WM; GM) of the cerebellum, separately for right, left, and bilateral cerebellar regions of interest (ROIs). These effects were compared to those of cerebellar volumetrics in WM/GM, right and left hemispheres while controlling for demographics, disease status, and total intracranial volume. Results Higher QSM measures of the cerebellar GM on the left, right, and bilateral sides significantly predicted (ps ≤ 0.003) a greater number of errors on the executive functioning (EF) subscale of the ECAS (ECAS-EF). Moreover, higher GM-related, QSM measures of the cerebellum were associated with an increased probability of a below-cut-off performance on the ECAS-EF (ps ≤ 0.024). No significant effects were observed for QSM measures of the cerebellar WM or for volumetric measures on the ECAS-EF. Other ECAS measures showed no significant effects. Bilateral QSM measures of the cerebellar GM also selectively predicted performance on backward digit span and social cognition tasks. Discussion Iron accumulation within the cerebellar GM, particularly in the cerebellar cortices, may be associated with executive functioning deficits in non-demented ALS patients. Therefore, QSM-based measures could be useful for identifying the neural correlates of extra-motor cognitive deficits in ALS patients.
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Affiliation(s)
- Edoardo Nicolò Aiello
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Valeria Elisa Contarino
- Neuroradiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy
| | - Giorgio Conte
- Neuroradiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari" Center, Università degli Studi di Milano, Milano, Italy
| | - Federica Solca
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Beatrice Curti
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Alessio Maranzano
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Silvia Torre
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Silvia Casale
- Neuroradiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy
| | - Alberto Doretti
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Eleonora Colombo
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Federico Verde
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari" Center, Università degli Studi di Milano, Milano, Italy
| | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari" Center, Università degli Studi di Milano, Milano, Italy
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States
| | - Claudia Cinnante
- Department of Diagnostic Imaging, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Fabio Maria Triulzi
- Neuroradiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari" Center, Università degli Studi di Milano, Milano, Italy
| | - Claudia Morelli
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Barbara Poletti
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milano, Italy
| | - Nicola Ticozzi
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari" Center, Università degli Studi di Milano, Milano, Italy
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Andersson Forsman O, Sjöström H, Svenningsson P, Granberg T. Combined MR quantitative susceptibility mapping and multi-shell diffusion in Parkinson's disease. J Neuroimaging 2024; 34:603-611. [PMID: 39004781 DOI: 10.1111/jon.13222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 07/05/2024] [Accepted: 07/05/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND AND PURPOSE Quantitative susceptibility mapping (QSM), neurite orientation dispersion and density imaging (NODDI), and the g-ratio have separately shown differences between Parkinson's disease (PD) and healthy controls. The g-ratio has, however, not been studied in PD in the substantia nigra (SN) and the putamen. A combination of these methods could also potentially be a complementary imaging biomarker for PD. This study aimed to assess the diagnostic performance of QSM, NODDI, the g-ratio, and a combined QSM-NODDI imaging marker in the SN and putamen of PD patients. METHODS In this prospective study, the diagnostic performance of median region of interest values was compared in a cohort of 15 participants with PD and 14 healthy controls after manual segmentation. The diagnostic performance was assessed using the area under curve (AUC) for the receiving operator characteristic. RESULTS Median QSM in the contralateral SN identified PD with AUC 0.77, and median isotropic volume fraction identified PD in the ipsilateral SN with AUC 0.68. A combined NODDI-QSM marker improved diagnostic performance (AUC 0.80). No significant differences were found in the g-ratio. CONCLUSION A combination of median QSM and median isotropic volume fraction improves the differentiation of PD from healthy controls and is a potential biomarker in the diagnostics of PD. This confirms previously reported results indicating that combining QSM and NODDI modestly improves differentiation of PD.
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Affiliation(s)
| | - Henrik Sjöström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Neurology, Academic Specialist Center, Stockholm, Sweden
| | - Per Svenningsson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Neurology, Academic Specialist Center, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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Laissy JP, Boukobza M. Editorial for "Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping". J Magn Reson Imaging 2024; 60:1176-1177. [PMID: 38156433 DOI: 10.1002/jmri.29193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 12/30/2023] Open
Affiliation(s)
- Jean-Pierre Laissy
- Laboratory for Vascular Translational Science (LVTS), INSERM U1148, Paris, France
- DMU (DREAM) Diagnostic Radiologie Explorations fonctionnelles Anatomopathologie Médecine nucléaire, University de Paris, Paris, France
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T AR, K K, Paul JS. Unveiling metabolic patterns in dementia: Insights from high-resolution quantitative blood-oxygenation-level-dependent MRI. Med Phys 2024; 51:6002-6019. [PMID: 38888202 DOI: 10.1002/mp.17173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 04/12/2024] [Accepted: 05/08/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Oxygen extraction fraction (OEF) and deoxyhemoglobin (DoHb) levels reflect variations in cerebral oxygen metabolism in demented patients. PURPOSE Delineating the metabolic profiles evident throughout different phases of dementia necessitates an integrated analysis of OEF and DoHb levels. This is enabled by leveraging high-resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi-echo gradient-echo MRI (mGRE) scan performed on a 3.0 Tesla scanner. METHODS Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non-essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log-magnitude difference (L-MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log-difference qBOLD model undergoes refinement into a representative form, termed as r-qBOLD, particularly when applied to class-averaged L-MDif signals derived through k-means clustering of L-MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r-qBOLD for different cluster sizes is validated using Bland-Altman analysis, and the model's goodness-of-fit is evaluated using aχ 2 ${\chi ^2}$ -test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non-demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study. RESULTS Utilizing a cohort comprising 30 demented patients aged 65-83 years in stages 4-6 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age-matched non-demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r-qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1-regime), and OEF levels below the normal range (S2-regime). The S1-regime, accompanied by low DoHb levels, predominantly manifests in fronto-parietal and perivascular regions with increase in dementia severity. Conversely, the S2-regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial-orbital prefrontal cortex (MOPFC), hypothalamus, ventro-medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early-stage AD related functional abnormalities. CONCLUSIONS Integrated analysis of OEF and DoHb levels using r-qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.
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Affiliation(s)
- Arun Raj T
- Division of Medical Informatics, School of Informatics, Kerala University of Digital Sciences Innovation & Technology (DUK), Trivandrum, Kerala, India
| | - Karthik K
- Department of Neuroimaging & Interventional Radiology, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Joseph Suresh Paul
- Division of Medical Informatics, School of Informatics, Kerala University of Digital Sciences Innovation & Technology (DUK), Trivandrum, Kerala, India
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50
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Paluru N, Susan Mathew R, Yalavarthy PK. DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain. NMR IN BIOMEDICINE 2024; 37:e5163. [PMID: 38649140 DOI: 10.1002/nbm.5163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/22/2024] [Accepted: 03/11/2024] [Indexed: 04/25/2024]
Abstract
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susceptibility distribution from the measured local field obtained from the MR phase. Although existing deep learning based QSM methods can produce high-quality reconstruction, they are highly biased toward training data distribution with less scope for generalizability. This work proposes a hybrid two-step reconstruction approach to improve deep learning based QSM reconstruction. The susceptibility map prediction obtained from the deep learning methods has been refined in the framework developed in this work to ensure consistency with the measured local field. The developed method was validated on existing deep learning and model-based deep learning methods for susceptibility mapping of the brain. The developed method resulted in improved reconstruction for MRI volumes obtained with different acquisition settings, including deep learning models trained on constrained (limited) data settings.
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Affiliation(s)
- Naveen Paluru
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, India
| | - Raji Susan Mathew
- School of Data Science, Indian Institute of Science Education and Research, Thiruvananthapuram, Kerala, India
| | - Phaneendra K Yalavarthy
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, India
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