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Shen Y, Yan L, Shao X, Zhao B, Bai J, Lu W, Wang DJ. Improved sensitivity of cellular MRI using phase-cycled balanced SSFP of ferumoxytol nanocomplex-labeled macrophages at ultrahigh field. Int J Nanomedicine 2018; 13:3839-3852. [PMID: 30013339 PMCID: PMC6039059 DOI: 10.2147/ijn.s169860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Purpose The purpose of this study was to investigate the feasibility and sensitivity of cellular magnetic resonance imaging (MRI) with ferumoxytol nanocomplex-labeled macrophages at ultrahigh magnetic field of 7 T. Materials and methods THP-1-induced macrophages were labeled using self-assembling heparin + protamine + ferumoxytol nanocomplexes which were injected into a gelatin phantom visible on both microscope and MRI. Susceptibility-weighted imaging (SWI) and balanced steady-state free precession (bSSFP) pulse sequences were applied at 3 and 7 T. The average, maximum intensity projection, and root mean square combined images were generated for phase-cycled bSSFP images. The signal-to-noise ratio and contrast-to-noise ratio (CNR) efficiencies were calculated. Ex vivo experiments were then performed using a formalin-fixed pig brain injected witĥ100 and ~1,000 labeled cells, respectively, at both 3 and 7 T. Results A high cell labeling efficiency (.90%) was achieved with heparin + protamine + ferumoxytol nanocomplexes. Less than 100 cells were detectable in the gelatin phantom at both 3 and 7 T. The 7 T data showed more than double CNR efficiency compared to the corresponding sequences at 3 T. The CNR efficiencies of phase-cycled bSSFP images were higher compared to those of SWI, and the root mean square combined bSSFP showed the highest CNR efficiency with minimal banding. Following co-registration of microscope and MR images, more cells (51/63) were detected by bSSFP at 7 T than at 3 T (36/63). On pig brain, botĥ100 and ~1,000 cells were detected at 3 and 7 T. While the cell size appeared larger due to blooming effects on SWI, bSSFP allowed better contrast to precisely identify the location of the cells with higher signal-to-noise ratio efficiency. Conclusion The proposed cellular MRI with ferumoxytol nanocomplex-labeled macrophages at 7 T has a high sensitivity to detect, 100 cells. The proposed method has great translational potential and may have broad clinical applications that involve cell types with a primary phagocytic phenotype.
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Affiliation(s)
- Yelong Shen
- Laboratory of FMRI Technology (LOFT), Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA, .,Shandong Medical Imaging Research Institute, School of Medicine, Shandong University, Jinan, Shangdong, China
| | - Lirong Yan
- Laboratory of FMRI Technology (LOFT), Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA,
| | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA,
| | - Bin Zhao
- Shandong Medical Imaging Research Institute, School of Medicine, Shandong University, Jinan, Shangdong, China
| | - Jinlun Bai
- Broad Center for Regenerative Medicine and Stem Cell Research, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA
| | - Wange Lu
- Broad Center for Regenerative Medicine and Stem Cell Research, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA
| | - Danny Jj Wang
- Laboratory of FMRI Technology (LOFT), Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA,
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Sun K, Xue R, Zhang P, Zuo Z, Chen Z, Wang B, Martin T, Wang Y, Chen L, He S, Wang DJJ. Integrated SSFP for functional brain mapping at 7T with reduced susceptibility artifact. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2017; 276:22-30. [PMID: 28092785 PMCID: PMC5336405 DOI: 10.1016/j.jmr.2016.12.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 12/21/2016] [Accepted: 12/22/2016] [Indexed: 06/06/2023]
Abstract
Balanced steady-state free precession (bSSFP) offers an alternative and potentially important tool to the standard gradient-echo echo-planar imaging (GE-EPI) for functional MRI (fMRI). Both passband and transition band based bSSFP have been proposed for fMRI. The applications of these methods, however, are limited by banding artifacts due to the sensitivity of bSSFP signal to off-resonance effects. In this article, a unique case of the SSFP-FID sequence, termed integrated-SSFP or iSSFP, was proposed to overcome the obstacle by compressing the SSFP profile into the width of a single voxel. The magnitude of the iSSFP signal was kept constant irrespective of frequency shift. Visual stimulation studies were performed to demonstrate the feasibility of fMRI using iSSFP at 7T with flip angles of 4° and 25°, compared to standard bSSFP and gradient echo (GRE) imaging. The signal changes for the complex iSSFP signal in activated voxels were 2.48±0.53 (%) and 2.96±0.87 (%) for flip angles (FA) of 4° and 25° respectively at the TR of 9.88ms. Simultaneous multi-slice acquisition (SMS) with the CAIPIRIHNA technique was carried out with iSSFP scanning to detect the anterior temporal lobe activation using a semantic processing task fMRI, compared with standard 2D GE-EPI. This study demonstrates the feasibility of iSSFP for fMRI with reduced susceptibility artifacts, while maintaining robust functional contrast at 7T.
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Affiliation(s)
- Kaibao Sun
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rong Xue
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Institute for Brain Disorders, Beijing 100053, China.
| | - Peng Zhang
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhongwei Chen
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bo Wang
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Thomas Martin
- Department of Neurology, University of California Los Angeles, Los Angeles 90095, United States
| | - Yi Wang
- Department of Neurology, University of California Los Angeles, Los Angeles 90095, United States
| | - Lin Chen
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, China.
| | - Sheng He
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Psychology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Danny J J Wang
- Department of Neurology, University of California Los Angeles, Los Angeles 90095, United States; Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States
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