Pengcheng Wang1,2, Jiayu Xiao2, Qingle Kong2, Jingxiang Zhang1,2, William Mack3, Nasim Sheikh-Bahaei2, Zhaoyang Fan 1,2
1Department of Biomedical Engineering, University of Southern California, Los Angeles, United States of America
2Department of Radiology, University of Southern California, Los Angeles, United States of America
3Department of Neurological Surgery, University of Southern California, Los Angeles, United States of America
Presenting Author: Zhaoyang Fan
Synopsis
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1. Mandell D, Mossa-Basha M, Qiao Y, Hess C, Hui F, Matouk C, et al. Intracranial vessel wall MRI: principles and expert consensus recommendations of the American Society of Neuroradiology. American Journal of Neuroradiology. 2017; 38:218-29. DOI: 10.3174/ajnr.A4893 [doi]
2. Mattay RR, Saucedo JF, Lehman VT, Xiao J, Obusez EC, Raymond SB, et al. Current clinical applications of intracranial vessel wall MR imaging. Seminars in Ultrasound, CT and MRI; 2021: Elsevier. DOI: 10.1053/j.sult.2021.07.004 [doi]
3. Alexander MD, Yuan C, Rutman A, Tirschwell DL, Palagallo G, Gandhi D, et al. High-resolution intracranial vessel wall imaging: imaging beyond the lumen. Journal of Neurology, Neurosurgery & Psychiatry. 2016; 87:589-97. DOI: 10.1136/jnnp-2015-312020 [doi]
4. Fan Z, Yang Q, Deng Z, Li Y, Bi X, Song S, et al. Whole‐brain intracranial vessel wall imaging at 3 T esla using cerebrospinal fluid–attenuated T1‐weighted 3 D turbo spin echo. Magnetic resonance in medicine. 2017; 77:1142-50. DOI: 10.1002/mrm.26201 [doi]
5. Qiao Y, Steinman DA, Qin Q, Etesami M, Schär M, Astor BC, et al. Intracranial arterial wall imaging using three‐dimensional high isotropic resolution black blood MRI at 3.0 Tesla. Journal of Magnetic Resonance Imaging. 2011; 34:22-30. DOI: 10.1002/jmri.22592 [doi]
6. Yang Q, Deng Z, Bi X, Song SS, Schlick KH, Gonzalez NR, et al. Whole‐brain vessel wall MRI: a parameter tune‐up solution to improve the scan efficiency of three‐dimensional variable flip‐angle turbo spin‐echo. Journal of Magnetic Resonance Imaging. 2017; 46:751-7. DOI: 10.1002/jmri.25611 [doi]
7. Zhang L, Zhang N, Wu J, Zhang L, Huang Y, Liu X, et al. High resolution three dimensional intracranial arterial wall imaging at 3 T using T1 weighted SPACE. Magnetic resonance imaging. 2015; 33:1026-34. DOI: 10.1016/j.mri.2015.06.006 [doi]
8. Qiao Y, Guallar E, Suri FK, Liu L, Zhang Y, Anwar Z, et al. MR imaging measures of intracranial atherosclerosis in a population-based study. Radiology. 2016; 280:860-8. DOI: 10.1148/radiol.2016151124 [doi]
9. Bathla G, Messina SA, Black DF, Benson JC, Kollasch P, Nickel MD, et al. Deep Learning–Based Reconstruction of 3D T1 SPACE Vessel Wall Imaging Provides Improved Image Quality with Reduced Scan Times: A Preliminary Study. American Journal of Neuroradiology. 2024. DOI: 10.3174/ajnr.A8382 [doi]
10. Kharaji M, Canton G, Guo Y, Mosi MH, Zhou Z, Balu N, et al. DANTE-CAIPI Accelerated Contrast-Enhanced 3D T1: Deep learning-based image quality improvement for Vessel Wall MR. American Journal of Neuroradiology. 2024. DOI: 10.3174/ajnr.A8424 [doi]
11. Seo M, Jung W, Jeong G, Yang S, Shin I, Lee JY, et al. Deep learning improves quality of intracranial vessel wall MRI for better characterization of potentially culprit plaques. Scientific Reports. 2024; 14:18983. DOI: 10.1038/s41598-024-69750-4 [doi]
12. BART Toolbox for Computational Magnetic Resonance Imaging2016: Available from: https://doi.org/10.5281/zenodo.592960. [doi]
13. Huang J, Fang Y, Wu Y, Wu H, Gao Z, Li Y, et al. Swin transformer for fast MRI. Neurocomputing. 2022; 493:281-304. https://doi.org/10.1016/j.neucom.2022.04.051 [doi]
14. Liang J, Cao J, Sun G, Zhang K, Van Gool L, Timofte R. Swinir: Image restoration using swin transformer. Proceedings of the IEEE/CVF international conference on computer vision; 2021. DOI: 10.1109/ICCVW54120.2021.00210 [doi]
15. Wang P, Chen J, Wang Z, Yang Q, Cen SY, Cui S, Mack W, Sheikh-Bahaei N, Fan Z. Vessel Wall Imaging-dedicated Rapid Acquisition Package (VWI-RAP): Toward a 5-min robust MR protocol. ISMRM; 2025.
16. Billot B, Greve DN, Puonti O, Thielscher A, Van Leemput K, Fischl B, et al. SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining. Medical image analysis. 2023; 86:102789. DOI: 10.1016/j.media.2023.102789 [doi]
17. Uecker M, Lai P, Murphy MJ, Virtue P, Elad M, Pauly JM, et al. ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magnetic resonance in medicine. 2014; 71:990-1001. DOI: 10.1002/mrm.24751 [doi]