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Qian M, Wang J, Gao Y, Chen M, Liu Y, Zhou D, Lu HD, Zhang X, Hu JM, Roe AW. Multiple loci for foveolar vision in macaque monkey visual cortex. Nat Neurosci 2025; 28:137-149. [PMID: 39639181 PMCID: PMC11706779 DOI: 10.1038/s41593-024-01810-4] [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: 06/13/2023] [Accepted: 10/14/2024] [Indexed: 12/07/2024]
Abstract
In humans and nonhuman primates, the central 1° of vision is processed by the foveola, a retinal structure that comprises a high density of photoreceptors and is crucial for primate-specific high-acuity vision, color vision and gaze-directed visual attention. Here, we developed high-spatial-resolution ultrahigh-field 7T functional magnetic resonance imaging methods for functional mapping of the foveolar visual cortex in awake monkeys. In the ventral pathway (visual areas V1-V4 and the posterior inferior temporal cortex), viewing of a small foveolar spot elicits a ring of multiple (eight) foveolar representations per hemisphere. This ring surrounds an area called the 'foveolar core', which is populated by millimeter-scale functional domains sensitive to fine stimuli and high spatial frequencies, consistent with foveolar visual acuity, color and achromatic information and motion. Thus, this elaborate rerepresentation of central vision coupled with a previously unknown foveolar core area signifies a cortical specialization for primate foveation behaviors.
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Affiliation(s)
- Meizhen Qian
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China
| | - Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yang Gao
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- College of Electrical Engineering, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Ming Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yin Liu
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Dengfeng Zhou
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiaotong Zhang
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China.
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China.
- College of Electrical Engineering, Zhejiang University, Hangzhou, China.
| | - Jia Ming Hu
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China.
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China.
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China.
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China.
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
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Wang J, Du X, Yao S, Li L, Tanigawa H, Zhang X, Roe AW. Mesoscale organization of ventral and dorsal visual pathways in macaque monkey revealed by 7T fMRI. Prog Neurobiol 2024; 234:102584. [PMID: 38309458 DOI: 10.1016/j.pneurobio.2024.102584] [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: 08/17/2023] [Revised: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
In human and nonhuman primate brains, columnar (mesoscale) organization has been demonstrated to underlie both lower and higher order aspects of visual information processing. Previous studies have focused on identifying functional preferences of mesoscale domains in specific areas; but there has been little understanding of how mesoscale domains may cooperatively respond to single visual stimuli across dorsal and ventral pathways. Here, we have developed ultrahigh-field 7 T fMRI methods to enable simultaneous mapping, in individual macaque monkeys, of response in both dorsal and ventral pathways to single simple color and motion stimuli. We provide the first evidence that anatomical V2 cytochrome oxidase-stained stripes are well aligned with fMRI maps of V2 stripes, settling a long-standing controversy. In the ventral pathway, a systematic array of paired color and luminance processing domains across V4 was revealed, suggesting a novel organization for surface information processing. In the dorsal pathway, in addition to high quality motion direction maps of MT, MST and V3A, alternating color and motion direction domains in V3 are revealed. As well, submillimeter motion domains were observed in peripheral LIPd and LIPv. In sum, our study provides a novel global snapshot of how mesoscale networks in the ventral and dorsal visual pathways form the organizational basis of visual objection recognition and vision for action.
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Affiliation(s)
- Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Xiao Du
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Songping Yao
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Lihui Li
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Hisashi Tanigawa
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Xiaotong Zhang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China.
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Qu S, Shi S, Quan Z, Gao Y, Wang M, Wang Y, Pan G, Lai HY, Roe AW, Zhang X. Design and application of a multimodality-compatible 1Tx/6Rx RF coil for monkey brain MRI at 7T. Neuroimage 2023; 276:120185. [PMID: 37244320 DOI: 10.1016/j.neuroimage.2023.120185] [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: 04/11/2023] [Revised: 05/09/2023] [Accepted: 05/22/2023] [Indexed: 05/29/2023] Open
Abstract
OBJECTIVE Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales. APPROACH In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted. MAIN RESULTS The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images. SIGNIFICANCE This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.
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Affiliation(s)
- Shuxian Qu
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Sunhang Shi
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Zhiyan Quan
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Yang Gao
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China
| | - Minmin Wang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China
| | - Yueming Wang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China; State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China
| | - Gang Pan
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China.
| | - Hsin-Yi Lai
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
| | - Anna Wang Roe
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
| | - Xiaotong Zhang
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
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Lou F, Tang X, Quan Z, Qian M, Wang J, Qu S, Gao Y, Wang Y, Pan G, Lai HY, Roe AW, Zhang X. A 16-channel loop array for in vivo macaque whole-brain imaging at 7 T. Magn Reson Imaging 2023:S0730-725X(23)00110-8. [PMID: 37356599 DOI: 10.1016/j.mri.2023.06.014] [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: 03/01/2023] [Revised: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 06/27/2023]
Abstract
Combining multimodal approaches with functional magnetic resonance imaging (fMRI) has catapulted the research on brain circuitries of non-human primates (NHPs) into a new era. However, many studies are constrained by a lack of appropriate RF coils. In this study,a single loop transmit and 16-channel receive array coil was constructed for brain imaging of macaques at 7 Tesla (7 T). The 16 receive channels were mounted on a 3D-printed helmet-shaped form closely fiting the macaque head, with fourteen openings arranged for multimodal devices around the cortical regions. Coil performance was evaluated by quantifying and comparing signal-to-noise ratio (SNR) maps, noise correlations, g-factor maps and flip-angle maps with a 28-channel commercial knee coil. The in vivo results suggested that the macaque coil has higher SNR in cortical regions and better acceleration ability in parallel imaging, which may benefit revealing mesoscale organizations in the brain.
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Affiliation(s)
- Feiyang Lou
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Xiaocui Tang
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Zhiyan Quan
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Meizhen Qian
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jianbao Wang
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Shuxian Qu
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yang Gao
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yueming Wang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China; State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China
| | - Gang Pan
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Hsin-Yi Lai
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Anna Wang Roe
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaotong Zhang
- The Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
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Du F, Li N, Yang X, Zhang B, Zhang X, Li Y. Design and construction of an 8-channel transceiver coil array for rat imaging at 9.4 T. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 351:107302. [PMID: 37116433 DOI: 10.1016/j.jmr.2022.107302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/27/2022] [Accepted: 09/11/2022] [Indexed: 05/29/2023]
Abstract
Ultra-high field (UHF) small animal magnetic resonance imaging (MRI) is a crucial tool permitting investigation of metabolic diseases and identification of imaging biomarkers suitable for clinical diagnosis and translation. Radiofrequency (RF) coils are critical components in enabling acquisition of high-quality rat abdomen MRI data. However, efficient RF coils with high-channel count, capable of sensitive and accelerated rat abdomen imaging at 9.4 T, are not available commercially. The SNR of the commonly-used 9.4 T birdcage coil is relatively weak, particularly in the peripheral area of the subject. In addition, the birdcage is not readily to perform parallel imaging due to unavailability of the required multiple channels. Consequently, the extended scanning duration may cause unnecessary hazards to the rat. In this work, an 8-channel transceiver coil array was designed and constructed to provide good image quality and large coverage for rat abdomen imaging at 9.4 T. The structure and the performance of the developed array was optimized and evaluated by numerical electromagnetic simulations and bench tests, respectively. The MR imaging experiments in phantoms and rat models were also performed on a Bruker 9.4 T preclinical MRI system to validate the feasibility of the proposed design. The coil array supports a one-dimensional acceleration factor up to R = 4, providing good parallel imaging capabilities. These results demonstrated that the proposed 8-channel transceiver coil array for rat imaging has the ability to obtain high spatial resolution of rat abdomen anatomical structure images at 9.4 T.
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Affiliation(s)
- Feng Du
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen 518055, Guang Dong, China
| | - Nan Li
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen 518055, Guang Dong, China
| | - Xing Yang
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen 518055, Guang Dong, China
| | - Baogui Zhang
- State Key Laboratory of Brain and Cognitive Sciences, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiaoliang Zhang
- Department of Biomedical Engineering, State University of New York at Buffalo, NY, United States., Buffalo, NY, United States
| | - Ye Li
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen 518055, Guang Dong, China.
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Zheng M, Gao Y, Quan Z, Zhang X. The design and evaluation of single-channel loopole coils at 7T MRI. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac8fdf] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 09/06/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective. Improving the local uniformity of
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field for awake monkey brain magnetic resonance imaging (MRI) at ultra-high fields while facilitating convenient placement and fixation of MRI-compatible multimodal devices for neuroscience study, can eventually advance our understanding of the primate’s brain organization. Approach. A group of single-channel RF coils including conventional loop coils and loopole coils sharing the same size and shape were designed for comparison; their performance as the transmit coil was quantitatively evaluated through a series of numerical electromagnetic (EM) simulations, and further verified by using 7T MRI over a saline phantom and a monkey in vivo. Main results. Compared to conventional loop coils, the optimized loopole coil brought up to 23.5%
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uniformity improvement for monkey brain imaging in EM simulations, and this performance was further verified over monkey brain imaging at 7T in vivo. Importantly, we have systematically explored the underlying mechanism regarding the relationship between loopole coils’ current density distribution and
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uniformity, observing that it can be approximated as a sinusoidal curve. Significance. The proposed loopole coil design can improve the imaging quality in awake and behaving monkeys, thus benefiting advanced brain research at UHF.
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The Value of Nuclear Magnetic Resonance in Liver Nodular Lesions. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:8165950. [PMID: 36017027 PMCID: PMC9388286 DOI: 10.1155/2022/8165950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/19/2022] [Accepted: 07/26/2022] [Indexed: 11/30/2022]
Abstract
In order to analyze the value of contrast-enhanced ultrasound (CEUS) combined with functional magnetic resonance imaging (fMRI) in the early differential diagnosis of liver nodular lesions, the authors studied the value of MRI in liver nodular lesions. A total of 82 patients with liver nodular lesions admitted to the hospital were selected for retrospective analysis; all of them underwent CEUS and fMRI examinations, and taking a biopsy or postoperative pathological examination results as the gold standard, the diagnostic value of CEUS, fMRI single item, and the two combined examinations for liver nodular lesions was analyzed by four-table. The biopsy or postoperative pathological examination results showed that a total of 88 lesions were detected in 82 patients, including 51 patients with benign lesions, with 54 lesions, and 31 patients with malignant lesions, with 34 lesions. Taking biopsy or pathological examination results as the gold standard, the four-table analysis CEUS had a sensitivity of 79.63%, a specificity of 82.35%, an accuracy of 80.68%, and a Kappa value of 0.603 for diagnosing benign and malignant liver nodular lesions. The sensitivity of fMRI in diagnosing benign and malignant liver nodular lesions was 83.33%, the specificity was 85.29%, the accuracy was 84.09%, and the Kappa value was 0.672; the combined sensitivity of the two in the diagnosis of benign and malignant liver nodular lesions was 94.44%, the specificity was 91.18%, the accuracy was 93.18%, and the Kappa value was 0.856, both of which were superior to single detection, and the difference in accuracy was statistically significant (χ2 = 5.683, P < 0.05). CEUS and fMRI have a certain value in the differential diagnosis of liver nodular lesions; the combination of the two can improve the diagnostic sensitivity and accuracy, and has more clinical application value.
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Ultra-high-field MRI studies of brain structure and function in humans and nonhuman primates: A collaborative approach to precision medicine. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021. [DOI: 10.1016/j.cobme.2021.100320] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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