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Mohammadi S, Ghaderi S. Parkinson's disease and Parkinsonism syndromes: Evaluating iron deposition in the putamen using magnetic susceptibility MRI techniques - A systematic review and literature analysis. Heliyon 2024; 10:e27950. [PMID: 38689949 PMCID: PMC11059419 DOI: 10.1016/j.heliyon.2024.e27950] [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: 12/10/2023] [Revised: 02/29/2024] [Accepted: 03/08/2024] [Indexed: 05/02/2024] Open
Abstract
Magnetic resonance imaging (MRI) techniques, such as quantitative susceptibility mapping (QSM) and susceptibility-weighted imaging (SWI), can detect iron deposition in the brain. Iron accumulation in the putamen (PUT) can contribute to the pathogenesis of Parkinson's disease (PD) and atypical Parkinsonian disorders. This systematic review aimed to synthesize evidence on iron deposition in the PUT assessed by MRI susceptibility techniques in PD and Parkinsonism syndromes. The PubMed and Scopus databases were searched for relevant studies. Thirty-four studies from January 2007 to October 2023 that used QSM, SWI, or other MRI susceptibility methods to measure putaminal iron in PD, progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and healthy controls (HCs) were included. Most studies have found increased putaminal iron levels in PD patients versus HCs based on higher quantitative susceptibility. Putaminal iron accumulation correlates with worse motor scores and cognitive decline in patients with PD. Evidence regarding differences in susceptibility between PD and atypical Parkinsonism is emerging, with several studies showing greater putaminal iron deposition in PSP and MSA than in PD patients. Alterations in putaminal iron levels help to distinguish these disorders from PD. Increased putaminal iron levels appear to be associated with increased disease severity and progression. Thus, magnetic susceptibility MRI techniques can detect abnormal iron accumulation in the PUT of patients with Parkinsonism. Moreover, quantifying putaminal susceptibility may serve as an MRI biomarker to monitor motor and cognitive changes in PD and aid in the differential diagnosis of Parkinsonian disorders.
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Affiliation(s)
- Sana Mohammadi
- Department of Medical Sciences, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Merenstein JL, Zhao J, Overson DK, Truong TK, Johnson KG, Song AW, Madden DJ. Depth- and curvature-based quantitative susceptibility mapping analyses of cortical iron in Alzheimer's disease. Cereb Cortex 2024; 34:bhad525. [PMID: 38185996 PMCID: PMC10839848 DOI: 10.1093/cercor/bhad525] [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: 09/20/2023] [Revised: 11/21/2023] [Accepted: 12/15/2023] [Indexed: 01/09/2024] Open
Abstract
In addition to amyloid beta plaques and neurofibrillary tangles, Alzheimer's disease (AD) has been associated with elevated iron in deep gray matter nuclei using quantitative susceptibility mapping (QSM). However, only a few studies have examined cortical iron, using more macroscopic approaches that cannot assess layer-specific differences. Here, we conducted column-based QSM analyses to assess whether AD-related increases in cortical iron vary in relation to layer-specific differences in the type and density of neurons. We obtained global and regional measures of positive (iron) and negative (myelin, protein aggregation) susceptibility from 22 adults with AD and 22 demographically matched healthy controls. Depth-wise analyses indicated that global susceptibility increased from the pial surface to the gray/white matter boundary, with a larger slope for positive susceptibility in the left hemisphere for adults with AD than controls. Curvature-based analyses indicated larger global susceptibility for adults with AD versus controls; the right hemisphere versus left; and gyri versus sulci. Region-of-interest analyses identified similar depth- and curvature-specific group differences, especially for temporo-parietal regions. Finding that iron accumulates in a topographically heterogenous manner across the cortical mantle may help explain the profound cognitive deterioration that differentiates AD from the slowing of general motor processes in healthy aging.
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Affiliation(s)
- Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
| | - Jiayi Zhao
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
| | - Devon K Overson
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - Kim G Johnson
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
- Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, United States
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Perera Molligoda Arachchige AS, Garner AK. Seven Tesla MRI in Alzheimer's disease research: State of the art and future directions: A narrative review. AIMS Neurosci 2023; 10:401-422. [PMID: 38188012 PMCID: PMC10767068 DOI: 10.3934/neuroscience.2023030] [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: 07/27/2023] [Revised: 11/29/2023] [Accepted: 12/04/2023] [Indexed: 01/09/2024] Open
Abstract
Seven tesla magnetic resonance imaging (7T MRI) is known to offer a superior spatial resolution and a signal-to-noise ratio relative to any other non-invasive imaging technique and provides the possibility for neuroimaging researchers to observe disease-related structural changes, which were previously only apparent on post-mortem tissue analyses. Alzheimer's disease is a natural and widely used subject for this technology since the 7T MRI allows for the anticipation of disease progression, the evaluation of secondary prevention measures thought to modify the disease trajectory, and the identification of surrogate markers for treatment outcome. In this editorial, we discuss the various neuroimaging biomarkers for Alzheimer's disease that have been studied using 7T MRI, which include morphological alterations, molecular characterization of cerebral T2*-weighted hypointensities, the evaluation of cerebral microbleeds and microinfarcts, biochemical changes studied with MR spectroscopy, as well as some other approaches. Finally, we discuss the limitations of the 7T MRI regarding imaging Alzheimer's disease and we provide our outlook for the future.
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Wang F, Zhang M, Li Y, Li Y, Gong H, Li J, Zhang Y, Zhang C, Yan F, Sun B, He N, Wei H. Alterations in brain iron deposition with progression of late-life depression measured by magnetic resonance imaging (MRI)-based quantitative susceptibility mapping. Quant Imaging Med Surg 2022; 12:3873-3888. [PMID: 35782236 PMCID: PMC9246724 DOI: 10.21037/qims-21-1137] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 04/19/2022] [Indexed: 08/27/2023]
Abstract
BACKGROUND Previous studies have revealed abnormality of iron deposition in the brain of patients with depression. The progression of iron deposition associated with depression remains to be elucidated. METHODS This is a longitudinal study. We explored brain iron deposition with disease progression in 20 patients older than 55 years with depression and on antidepressants, using magnetic resonance imaging (MRI)-based quantitative susceptibility mapping (QSM). Magnetic susceptibility values of the whole brain were compared between baseline and approximately one-year follow-up scans using permutation testing. Furthermore, we examined the relationship of changes between the susceptibility values and disease improvement using Spearman's partial correlation analysis, controlling for age, gender, and the visit interval. RESULTS Compared to the initial scan, increased magnetic susceptibility values were found in the medial prefrontal cortex (mPFC), dorsal anterior cingulate cortex (dACC), occipital areas, habenula, brainstem, and cerebellum (P<0.05, corrected). The susceptibility values decreased in the dorsal part of the mPFC, middle and posterior cingulate cortex (MCC and PCC), right postcentral gyrus, right inferior parietal lobule, right precuneus, right supramarginal gyrus, left lingual gyrus, left dorsal striatum, and right thalamus (P<0.05, corrected). Notably, the increase in susceptibility values at the mPFC and dACC negatively correlated with the changes in depression scores, as calculated using the Hamilton Depression Scale (HAMD) (r=-0.613, P=0.009), and the increase in susceptibility values at the cerebellum and habenula negatively correlated with the changes in cognitive scores, which were calculated using the Mini-Mental State Examination (MMSE) (cerebellum: r=-0.500, P=0.041; habenula: r=-0.588, P=0.013). Additionally, the decreased susceptibility values at the white matter near the mPFC (anterior corona radiata) also correlated with the changes in depression scores (r=-0.541, P=0.025), and the decreased susceptibility values at the left lingual gyrus correlated with the changes in cognitive scores (r=-0.613, P=0.009). CONCLUSIONS Our study identified brain areas where iron deposition changed with the progression of depression while on antidepressants. The linear relationship of changes in the magnetic susceptibility values in the mPFC, dACC, and some subcortical areas with changes in depression symptoms and cognitive functions of patients is highlighted. Our results strengthen the understanding of the alterations of brain iron levels associated with disease progression in patients with late-life depression.
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Affiliation(s)
- Fang Wang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ming Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufei Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hengfen Gong
- Department of Psychiatry, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China
| | - Jun Li
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Yuyao Zhang
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Chencheng Zhang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Ding Y, Chu Y, Liu M, Ling Z, Wang S, Li X, Li Y. Fully automated discrimination of Alzheimer's disease using resting-state electroencephalography signals. Quant Imaging Med Surg 2022; 12:1063-1078. [PMID: 35111605 DOI: 10.21037/qims-21-430] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 08/24/2021] [Indexed: 12/29/2022]
Abstract
Background The Alzheimer's disease (AD) population increases worldwide, placing a heavy burden on the economy and society. Presently, there is no cure for AD. Developing a convenient method of screening for AD and mild cognitive impairment (MCI) could enable early intervention, thus slowing down the progress of the disease and enabling better overall disease management. Methods In the current study, resting-state electroencephalography (EEG) data were acquired from 113 normal cognition (NC) subjects, 116 amnestic MCI patients, and 72 probable AD patients. After preprocessing by an automatic algorithm, features including spectral power, complexity, and functional connectivity were extracted, and machine-learning classifiers were built to differentiate among the 3 groups. The classification performance was evaluated from multiple perspectives, including accuracy, specificity, sensitivity, area under the curve (AUC) with 95% confidence intervals, and compared to the empirical chance level by permutation tests. Results The analysis of variance results (P<0.05 with false discovery rate correction) confirmed the tendency to slow brain activity, reduced complexity, and connectivity with AD progress. By combining the features, the ability of the machine-learning classifiers, especially the ensemble trees, to differentiate among the 3 groups, was significantly better than that of the empirical chance level of the permutation test. The AUC of the classifier with the best performance was 80.08% for AD vs. NC, 70.82% for AD vs. MCI, and 63.95% for MCI vs. NC. Conclusions The current study presented a fully automatic procedure that could significantly distinguish NC, MCI, and AD subjects via resting-state EEG signals. The study was based on a large data set with evidence-based medical diagnosis and provided further evidence that resting-state EEG data could assist in the discrimination of AD patients.
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Affiliation(s)
- Yue Ding
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,iFLYTEK Research, iFLYTEK CO., LTD., Hefei, China
| | - Yinxue Chu
- iFLYTEK Research, iFLYTEK CO., LTD., Hefei, China
| | - Meng Liu
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhenhua Ling
- National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, China
| | - Shijin Wang
- iFLYTEK Research, iFLYTEK CO., LTD., Hefei, China.,State Key Laboratory of Cognitive Intelligence, Hefei, China
| | - Xin Li
- iFLYTEK Research, iFLYTEK CO., LTD., Hefei, China.,National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, China
| | - Yunxia Li
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
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Probst J, Rohner M, Zahn M, Piccirelli M, Pangalu A, Luft A, Deistung A, Klohs J, Wegener S. Quantitative susceptibility mapping in ischemic stroke patients after successful recanalization. Sci Rep 2021; 11:16038. [PMID: 34362957 PMCID: PMC8346586 DOI: 10.1038/s41598-021-95265-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 07/22/2021] [Indexed: 11/09/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is a novel processing method for gradient-echo magnetic resonance imaging (MRI). Higher magnetic susceptibility in cortical veins have been observed on susceptibility maps in the ischemic hemisphere of stroke patients, indicating an increased oxygen extraction fraction (OEF). Our goal was to investigate susceptibility in veins of stroke patients after successful recanalization in order to analyze the value of QSM in predicting tissue prognosis and clinical outcome. We analyzed MR images of 23 patients with stroke due to unilateral middle cerebral artery (MCA)-M1/M2 occlusion acquired 24–72 h after successful thrombectomy. The susceptibilities of veins were obtained from QSM and compared between the stroke territory, the ipsilateral non-ischemic MCA territory and the contralateral MCA territory. As outcome variables, early infarct size and functional disability (modified Rankin Scale, mRS) after 3–5 months was used. The median susceptibility value of cortical veins in the ischemic core was 41% lower compared to the ipsilateral non-ischemic MCA territory and 38% lower than on the contralateral MCA territory. Strikingly, in none of the patients prominent vessels with high susceptibility signal were found after recanalization. Venous susceptibility values within the infarct did not correlate with infarct volume or functional disability after 3–5 months. Low venous susceptibility within the infarct core after successful recanalization of the occluded vessel likely indicates poor oxygen extraction arising from tissue damage. We did not identify peri-infarct tissue with increased susceptibility values as potential surrogate of former penumbral areas. We found no correlation of QSM parameters with infarct size or outcome.
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Affiliation(s)
- Jasmin Probst
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Marco Rohner
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Malin Zahn
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| | - Andreas Luft
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland.,Cereneo Center for Neurology and Rehabilitation, Vitznau, Switzerland
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, University Hospital Halle (Saale), Halle, Germany
| | - Jan Klohs
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Susanne Wegener
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland.
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