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Coolen BF. Editorial for "Black-Blood Magnetization Prepared 2 Rapid Acquisition Gradient Echoes: A Fast and Three-dimensional MR Black-blood T 1 Mapping Technique for Quantitative Assessment of Atherosclerosis and Venous Thrombosis". J Magn Reson Imaging 2024; 60:1163-1164. [PMID: 38014867 DOI: 10.1002/jmri.29154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 11/02/2023] [Accepted: 11/03/2023] [Indexed: 11/29/2023] Open
Affiliation(s)
- Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
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Nie Y, Lu N, Liao L, Liu Z, Gu A, Huang X, Tie C, Liu H, Huang Z, Xie G. Black-Blood Magnetization Prepared 2 Rapid Acquisition Gradient Echoes: A Fast and Three-Dimensional MR Black-Blood T 1 Mapping Technique for Quantitative Assessment of Atherosclerosis and Venous Thrombosis. J Magn Reson Imaging 2024; 60:1148-1162. [PMID: 38009385 DOI: 10.1002/jmri.29156] [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: 08/28/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 11/28/2023] Open
Abstract
BACKGROUND Blood flow signals may be a confounder in quantifying T1 values of plaque or thrombus and how to realize black-blood T1 mapping remains a challenge task. PURPOSE To develop a fast and three-dimensional black-blood T1 mapping technique for quantitative assessment of atherosclerosis and venous thrombosis. STUDY TYPE Sequence development and optimization via phantoms and volunteers as well as pilot prospective. PHANTOM AND SUBJECTS Numerical simulations, a standard phantom, 8 healthy volunteers (mean age, 22 ± 1 years; 5 males), and 19 patients (mean age, 57 ± 14 years; 13 males) with atherosclerosis or venous thrombosis. FIELD STRENGTH/SEQUENCE 3T/inversion recovery spin-echo sequence (IR-SE), magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE), and black-blood prepared MP2RAGE (BB-MP2RAGE). ASSESSMENT The black-blood preparation (i.e., delay alternating with nutation for tailored excitation, DANTE) was incorporated into MP2RAGE for black-blood T1 mapping. The BB-MP2RAGE was optimized numerically based on the Bloch equation, and then the phantom study was performed to verify the accuracy of T1 mapping by BB-MP2RAGE against IR-SE and MP2RAGE. Preliminary clinical validation was prospectively performed to assess the flow suppression effect and its potential application in plaque and thrombosis identification. STATISTICAL TESTS Pearson correlation test, Bland-Altman analysis, paired t-test, and intraclass correlation coefficient. A P value <0.05 indicates a statistically significant difference. RESULTS Phantom experiments showed comparable accuracy of T1 maps by BB-MP2RAGE with IR-SE and MP2RAGE (all r2 > 0.99); Compared to MP2RAGE, BB-MP2RAGE effectively nulled the blood flow signals, and had a significant improvement in contrast-to-noise ratio between static tissue and blood (250.5 ± 66.6 vs. 91.9 ± 35.9). BB-MP2RAGE can quantify plaque or thrombus T1 relaxation time with blood flow signal suppression. DATA CONCLUSION Accurate T1 mapping with sufficient blood flow suppression was achieved by BB-MP2RAGE. BB-MP2RAGE has the potential to quantitatively characterize atherosclerosis and venous thrombosis. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Yuhui Nie
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Na Lu
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Liping Liao
- Department of Radiology, The First People's Hospital of Qinzhou, Qinzhou, China
| | - Zeping Liu
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Anyan Gu
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xin Huang
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Changjun Tie
- Paul C. Lauterbur Imaging Center, Shenzhen Institutes Advanced Technology, Shenzhen, Guangdong, China
| | - Hongyan Liu
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Zehe Huang
- Department of Radiology, The First People's Hospital of Qinzhou, Qinzhou, China
| | - Guoxi Xie
- School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
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Gemmete JJ. Vessel Wall Characterization Using Quantitative MR Imaging. Neuroimaging Clin N Am 2024; 34:281-292. [PMID: 38604712 DOI: 10.1016/j.nic.2024.02.002] [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: 04/13/2024]
Abstract
MR imaging's exceptional capabilities in vascular imaging stem from its ability to visualize and quantify vessel wall features, such as plaque burden, composition, and biomechanical properties. The application of advanced MR imaging techniques, including two-dimensional and three-dimensional black-blood MR imaging, T1 and T2 relaxometry, diffusion-weighted imaging, and dynamic contrast-enhanced MR imaging, wall shear stress, and arterial stiffness, empowers clinicians and researchers to explore the intricacies of vascular diseases. This array of techniques provides comprehensive insights into the development and progression of vascular pathologies, facilitating earlier diagnosis, targeted treatment, and improved patient outcomes in the management of vascular health.
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Affiliation(s)
- Joseph J Gemmete
- Department of Radiology, Michigan Medicine, 1500 East Medican Center Drive, UH B1D 328, Ann Arbor, MI 48109.
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Wang Y, Liu X, Wang J, Wang Y, Qi H, Kong X, Liu D, Liu J, Zheng H, Xiong F, Zhang L, Fu X, Zhang X, Guo R, Qiao H, Chen Z, Si D, Chen H. Simultaneous T1, T2, and T2* Mapping of Carotid Plaque: The SIMPLE* Technique. Radiology 2023; 307:e222061. [PMID: 36853181 DOI: 10.1148/radiol.222061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Background Quantitative T1, T2, and T2* measurements of carotid atherosclerotic plaque are important in evaluating plaque vulnerability and monitoring its progression. Purpose To develop a sequence to simultaneously quantify T1, T2, and T2* of carotid plaque. Materials and Methods The simultaneous T1, T2, and T2* mapping of carotid plaque (SIMPLE*) sequence is composed of three modules with different T2 preparation pulses, inversion-recovery pulses, and acquisition schemas. Single-echo data were used for T1 and T2 quantification, while the multiecho (ME) data were used for T2* quantification. The quantitative accuracy of SIMPLE* was tested in a phantom study by comparing its measurements with those of reference standard sequences. In vivo feasibility of the technique was prospectively evaluated between November 2020 and February 2022 in healthy volunteers and participants with carotid atherosclerotic plaque. The Pearson or Spearman correlation test, Student t test, and Wilcoxon rank-sum test were used. Results T1, T2, and T2* estimated with SIMPLE* strongly correlated with inversion-recovery spin-echo (SE) (correlation coefficient [r] = 0.99), ME-SE (r = 0.99), and ME gradient-echo (r = 0.99) sequences in the phantom study. In five healthy volunteers (mean age, 25 years ± 3 [SD]; three women), measurements were similar between SIMPLE* and modified Look-Locker inversion recovery, or MOLLI (1151 msec ± 71 vs 1098 msec ± 64; P = .14), ME turbo SE (31 msec ± 1 vs 31 msec ± 1; P = .32), and ME turbo field echo (24 msec ± 2 vs 25 msec ± 2; P = .19). In 18 participants with carotid plaque (mean age, 65 years ± 9; 16 men), quantitative T1, T2, and T2* of plaque components were consistent with their signal characteristics on multicontrast images. Conclusion A quantitative technique for simultaneous T1, T2, and T2* mapping of carotid plaque with 100-mm3 coverage and 0.8-mm3 resolution was developed using the proposed SIMPLE* sequence and demonstrated high accuracy and in vivo feasibility. © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Yajie Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xiaoming Liu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Jing Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Yishi Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Haikun Qi
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xiangchuang Kong
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Dingxi Liu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Jia Liu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Hanpei Zheng
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Fu Xiong
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Lan Zhang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xiaona Fu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xinli Zhang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Rui Guo
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Huiyu Qiao
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Zhensen Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Dongyue Si
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Huijun Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
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Keegan J. Editorial for “Reliability and Usefulness of
3D
Sequential
QUantitative T
1
‐T
2
‐T
2
* Mappings (
SQUMA
)
MR Multi‐Parametric
Imaging in Characterizing Carotid Artery Atherosclerosis”. J Magn Reson Imaging 2022; 57:1390-1391. [PMID: 36382867 DOI: 10.1002/jmri.28443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 09/03/2022] [Indexed: 11/17/2022] Open
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Qiao H, Yang Q, Huo R, Han H, Ning Z, Shen R, Song X, Chen H, Chen S, Zhao X. Reliability and Value of 3D Sequential QUantitative T 1 -T 2 -T 2 * MAppings (SQUMA) MR Multi-Parametric Imaging in Characterizing Carotid Artery Atherosclerosis. J Magn Reson Imaging 2022; 57:1376-1389. [PMID: 36173363 DOI: 10.1002/jmri.28445] [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: 07/13/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND T1 , T2 , and T2 * mappings are seldom performed in a single examination, and their values in evaluating symptomatic atherosclerosis are lacking. PURPOSE To perform three-dimensional (3D) quantitative T1 , T2 , and T2 * mappings (SQUMA) multi-parametric imaging for carotid vessel wall and evaluate its reliability and value in assessing carotid atherosclerosis. STUDY TYPE Prospective. SUBJECTS Eight healthy subjects and 20 patients with symptomatic carotid atherosclerosis. FIELD STRENGTH/SEQUENCE 3 T, SQUMA imaging T1 -, T2 -, and T2 *-mapping, multi-contrast vessel wall imaging including T1 - and T2 -weighted, time-of-flight, and SNAP sequences. ASSESSMENT SQUMA was acquired in all subjects and multi-contrast images were acquired in healthy subjects. T1 , T2 , and T2 * values and lumen area (LA), wall area (WA), mean wall thickness (MeanWT), and normalized wall index (NWI) of carotid arteries were measured. SQUMA and multi-contrast measurements were compared in healthy subjects and differences in SQUMA measurements between healthy subjects and patients were assessed. The discriminative value of SQUMA measurements for symptomatic vessel was determined. STATISTICAL TESTS Paired t or Wilcoxon signed-rank test, independent t or Mann-Whitney U test, area under the receiver operating characteristic curve (AUC), intraclass correlation coefficients, and Bland-Altman plots. Statistically significant level, P < 0.05. RESULTS There were no significant differences in LA (P = 0.340), WA (P = 0.317), MeanWT (P = 0.088), and NWI (P = 0.091) of carotid arteries between SQUMA and multi-contrast vessel wall images. The values of T2 (50.9 ± 2.9 msec vs. 44.5 ± 4.2 msec), T2 * (28.2 ± 4.3 msec vs. 24.7 ± 2.6 msec), WA (23.7 ± 4.6 mm2 vs. 36.2 ± 7.7 mm2 ), MeanWT (0.99 ± 0.05 mm vs. 1.50 ± 0.28 mm), and NWI (40.7 ± 3.0% vs. 53.8 ± 5.4%) of carotid arteries in healthy subjects were significantly different from those in atherosclerotic patients. The combination of quantitative T1 , T2 , and T2 * values and MeanWT showed greatest AUC (0.81; 95% CI: 0.65-0.92) in discriminating symptomatic vessels. DATA CONCLUSION Carotid MR 3D quantitative multi-parametric imaging of SQUMA enables acquisition of T1 , T2 , and T2 * maps, reliably measuring carotid morphology and discriminating carotid symptomatic atherosclerosis. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Huiyu Qiao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China.,School of Medicine, Tsinghua University-Peking University Joint Center for Life Sciences, Beijing, China
| | - Qiansu Yang
- Center of Medicine Clinical Research, Department of Pharmacy, Medical Supplies Center of PLA General Hospital, Beijing, China
| | - Ran Huo
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Hualu Han
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China
| | - Zihan Ning
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China
| | - Rui Shen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China
| | - Xiaowei Song
- Department of Neurology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China
| | - Shuo Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China
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7
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Li Z, Xu X, Yang Y, Feng L. Repeatability and robustness of MP-GRASP T 1 mapping. Magn Reson Med 2022; 87:2271-2286. [PMID: 34971467 PMCID: PMC10061203 DOI: 10.1002/mrm.29131] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 12/03/2021] [Accepted: 12/06/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To demonstrate the repeatability of fast 3D T1 mapping using Magnetization-Prepared Golden-angle RAdial Sparse Parallel (MP-GRASP) MRI and its robustness to variation of imaging parameters including flip angle and spatial resolution in phantoms and the brain. THEORY AND METHODS Multiple imaging experiments were performed to (1) assess the robustness of MP-GRASP T1 mapping to B1 inhomogeneity using a single tube phantom filled with uniform MnCl2 liquid; (2) compare the repeatability of T1 mapping between MP-GRASP and inversion recovery-based spin-echo (IR-SE; over 12 scans), using a commercial T1MES phantom; (3) evaluate the longitudinal variation of T1 estimation using MP-GRASP with varying imaging parameters, including spatial resolution, flip angle, TR/TE, and acceleration rate, using the T1MES phantom (106 scans performed over a period of 12 months); and (4) evaluate the variation of T1 estimation using MP-GRASP with varying imaging parameters in the brain (24 scans in a single visit). In addition, the accuracy of MP-GRASP T1 mapping was also validated against IR-SE by performing linear correlation and calculating the Lin's concordance correlation coefficient (CCC). RESULTS MP-GRASP demonstrates good robustness to B1 inhomogeneity, with intra-slice variability below 1% in the single tube phantom experiment. The longitudinal variability is good both in the phantom (below 2.5%) and in the brain (below 2%) with varying imaging parameters. The T1 values estimated from MP-GRASP are accurate compared to that from the IR-SE imaging (R2 = 0.997, Lin's CCC = 0.996). CONCLUSION MP-GRASP shows excellent repeatability of T1 estimation over time, and it is also robust to variation of different imaging parameters evaluated in this study.
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Affiliation(s)
- Zhitao Li
- Department of Radiology, Stanford University, Palo Alto, California, United States
| | - Xiang Xu
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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8
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Kim SE, Parker DL, Roberts JA, Treiman GS, Alexander M, Baradaran H, de Havenon A, McNally JS. Differentiation of symptomatic and asymptomatic carotid intraplaque hemorrhage using 3D high-resolution diffusion-weighted stack of stars imaging. NMR IN BIOMEDICINE 2021; 34:e4582. [PMID: 34296793 DOI: 10.1002/nbm.4582] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 06/14/2021] [Accepted: 06/15/2021] [Indexed: 06/13/2023]
Abstract
Ischemic events related to carotid disease are far more strongly associated with plaque instability than stenosis. 3D high-resolution diffusion-weighted (DW) imaging can provide quantitative diffusion measurements on carotid atherosclerosis and may improve detection of vulnerable intraplaque hemorrhage (IPH). The 3D DW-stack of stars (SOS) sequence was implemented with 3D SOS acquisition combined with DW preparation. After simulation of signals created from 3D DW-SOS, phantom studies were performed. Three healthy subjects and 20 patients with carotid disease were recruited. Apparent diffusion coefficient (ADC) values were statistically analyzed on three subgroups by using a two-group comparison Wilcoxon-Mann-Whitney U test with p values less than 0.05: symptomatic versus asymptomatic; IPH-positive versus IPH-negative; and IPH-positive symptomatic versus asymptomatic plaques to determine the relationship with plaque vulnerability. ADC values calculated by 3D DW-SOS provided values similar to those calculated from other techniques. Mean ADC of symptomatic plaque was significantly lower than asymptomatic plaque (0.68 ± 0.18 vs. 0.98 ± 0.16 x 10-3 mm2 /s, p < 0.001). ADC was also significantly lower in IPH-positive versus IPH-negative plaque (0.68 ± 0.13 vs. 1.04 ± 0.11 x 10-3 mm2 /s, p < 0.001). Additionally, ADC was significantly lower in symptomatic versus asymptomatic IPH-positive plaque (0.57 ± 0.09 vs. 0.75 ± 0.11 x 10-3 mm2 /s, p < 0.001). Our results provide strong evidence that ADC measurements from 3D DW-SOS correlate with the symptomatic status of extracranial internal carotid artery plaque. Further, ADC improved discrimination of symptomatic plaque in IPH. These data suggest that diffusion characteristics may improve detection of destabilized plaque leading to elevated stroke risk.
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Affiliation(s)
- Seong-Eun Kim
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Dennis L Parker
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - John A Roberts
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Gerald S Treiman
- Department of Veterans Affairs, VASLCHCS, Salt Lake City, Utah, USA
| | - Matthew Alexander
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Hediyeh Baradaran
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Adam de Havenon
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - J Scott McNally
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
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9
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Coolen BF, Schoormans J, Gilbert G, Kooreman ES, de Winter N, Viessmann O, Zwanenburg JJM, Majoie CBLM, Strijkers GJ, Nederveen AJ, Siero JCW. Double delay alternating with nutation for tailored excitation facilitates banding-free isotropic high-resolution intracranial vessel wall imaging. NMR IN BIOMEDICINE 2021; 34:e4567. [PMID: 34076305 PMCID: PMC8459252 DOI: 10.1002/nbm.4567] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/26/2021] [Accepted: 05/15/2021] [Indexed: 06/12/2023]
Abstract
The purpose of this study was to evaluate the use of a double delay alternating with nutation for tailored excitation (D-DANTE)-prepared sequence for banding-free isotropic high-resolution intracranial vessel wall imaging (IC-VWI) and to compare its performance with regular DANTE in terms of signal-to-noise ratio (SNR) as well as cerebrospinal fluid (CSF) and blood suppression efficiency. To this end, a D-DANTE-prepared 3D turbo spin echo sequence was implemented by interleaving two separate DANTE pulse trains with different RF phase-cycling schemes, but keeping all other DANTE parameters unchanged, including the total number of pulses and total preparation time. This achieved a reduction of the banding distance compared with regular DANTE enabling banding-free imaging up to higher resolutions. Bloch simulations assuming static vessel wall and flowing CSF spins were performed to compare DANTE and D-DANTE in terms of SNR and vessel wall/CSF contrast. Similar image quality measures were assessed from measurements on 13 healthy middle-aged volunteers. Both simulation and in vivo results showed that D-DANTE had only slightly lower vessel wall/CSF and vessel wall/blood contrast-to-noise ratio values compared with regular DANTE, which originated from a 10%-15% reduction in vessel wall SNR but not from reduced CSF or blood suppression efficiency. As anticipated, IC-VWI acquisitions showed that D-DANTE can successfully remove banding artifacts compared with regular DANTE with equal scan time or DANTE preparation length. Moreover, application was demonstrated in a patient with an intracranial aneurysm, indicating improved robustness to slow flow artifacts compared with clinically available 3D turbo spin echo scans. In conclusion, D-DANTE provides banding artifact-free IC-VWI up to higher isotropic resolutions compared with regular DANTE. This allows for a more flexible choice of DANTE preparation parameters in high-resolution IC-VWI protocols.
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Affiliation(s)
- Bram F. Coolen
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | - Jasper Schoormans
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | | | - Ernst S. Kooreman
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
- Department of Radiation OncologyThe Netherlands Cancer InstituteAmsterdamThe Netherlands
| | - Naomi de Winter
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | - Olivia Viessmann
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical SchoolMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Jaco J. M. Zwanenburg
- Department of Radiology, University Medical Center UtrechtUtrecht UniversityUtrechtThe Netherlands
| | | | - Gustav J. Strijkers
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | - Aart J. Nederveen
- Department of Radiology & Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
| | - Jeroen C. W. Siero
- Department of Radiology, University Medical Center UtrechtUtrecht UniversityUtrechtThe Netherlands
- Spinoza Centre for NeuroimagingAmsterdamThe Netherlands
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10
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Li Z, Fu Z, Keerthivasan M, Bilgin A, Johnson K, Galons JP, Vedantham S, Martin DR, Altbach MI. Rapid high-resolution volumetric T 1 mapping using a highly accelerated stack-of-stars Look Locker technique. Magn Reson Imaging 2021; 79:28-37. [PMID: 33722634 PMCID: PMC8107135 DOI: 10.1016/j.mri.2021.03.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 03/03/2021] [Accepted: 03/03/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To develop a fast volumetric T1 mapping technique. MATERIALS AND METHODS A stack-of-stars (SOS) Look Locker technique based on the acquisition of undersampled radial data (>30× relative to Nyquist) and an efficient multi-slab excitation scheme is presented. A principal-component based reconstruction is used to reconstruct T1 maps. Computer simulations were performed to determine the best choice of partitions per slab and degree of undersampling. The technique was validated in phantoms against reference T1 values measured with a 2D Cartesian inversion-recovery spin-echo technique. The SOS Look Locker technique was tested in brain (n = 4) and prostate (n = 5). Brain T1 mapping was carried out with and without kz acceleration and results between the two approaches were compared. Prostate T1 mapping was compared to standard techniques. A reproducibility study was conducted in brain and prostate. Statistical analyses were performed using linear regression and Bland Altman analysis. RESULTS Phantom T1 values showed excellent correlations between SOS Look Locker and the inversion-recovery spin-echo reference (r2 = 0.9965; p < 0.0001) and between SOS Look Locker with slab-selective and non-slab selective inversion pulses (r2 = 0.9999; p < 0.0001). In vivo results showed that full brain T1 mapping (1 mm3) with kz acceleration is achieved in 4 min 21 s. Full prostate T1 mapping (0.9 × 0.9 × 4 mm3) is achieved in 2 min 43 s. T1 values for brain and prostate were in agreement with literature values. A reproducibility study showed coefficients of variation in the range of 0.18-0.2% (brain) and 0.15-0.18% (prostate). CONCLUSION A rapid volumetric T1 mapping technique was developed. The technique enables high-resolution T1 mapping with adequate anatomical coverage in a clinically acceptable time.
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Affiliation(s)
- Zhitao Li
- Department of Electrical and Computer Engineering, the University of Arizona, Tucson, AZ 85721, USA; Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | - Zhiyang Fu
- Department of Electrical and Computer Engineering, the University of Arizona, Tucson, AZ 85721, USA; Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | - Mahesh Keerthivasan
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA; Siemens Healthcare USA, Tucson, AZ 85724, USA
| | - Ali Bilgin
- Department of Electrical and Computer Engineering, the University of Arizona, Tucson, AZ 85721, USA; Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA; Department of Biomedical Engineering, the University of Arizona, Tucson, AZ 85721, USA
| | - Kevin Johnson
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | | | | | - Diego R Martin
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | - Maria I Altbach
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA; Department of Biomedical Engineering, the University of Arizona, Tucson, AZ 85721, USA.
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11
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Zhou Z, Chen S, Balu N, Chu B, Zhao X, Sun J, Mossa-Basha M, Hatsukami T, Börnert P, Yuan C. Neural network enhanced 3D turbo spin echo for MR intracranial vessel wall imaging. Magn Reson Imaging 2021; 78:7-17. [PMID: 33548457 DOI: 10.1016/j.mri.2021.01.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/28/2020] [Accepted: 01/31/2021] [Indexed: 11/17/2022]
Abstract
PURPOSE To improve the signal-to-noise ratio (SNR) and image sharpness for whole brain isotropic 0.5 mm three-dimensional (3D) T1 weighted (T1w) turbo spin echo (TSE) intracranial vessel wall imaging (IVWI) at 3 T. METHODS The variable flip angle (VFA) method enables useful optimization across scan efficiency, SNR and relaxation induced point spread function (PSF) for TSE imaging. A convolutional neural network (CNN) was developed to retrospectively enhance the acquired TSE image with PSF blurring. The previously developed VFA method to increase SNR at the expense of blur can be combined with the presented PSF correction to yield long echo train length (ETL) scan while the acquired image remains high SNR and sharp. The overall approach can enable an optimized solution for accelerated whole brain high-resolution 3D T1w TSE IVWI. Its performance was evaluated on healthy volunteers and patients. RESULTS The PSF blurred image acquired by a long ETL scan can be enhanced by CNN to restore similar sharpness as a short ETL scan, which outperforms the traditional linear PSF enhancement approach. For accelerated whole brain IVWI on volunteers, the optimized isotropic 0.5 mm 3D T1w TSE sequence with CNN based PSF enhancement provides sufficient flow suppression and improved image quality. Preliminary results on patients further demonstrated its improved delineation for intracranial vessel wall and plaque morphology. CONCLUSION The CNN enhanced VFA TSE imaging enables an overall image quality improvement for high-resolution 3D T1w IVWI, and may provide a better tradeoff across scan efficiency, SNR and PSF for 3D TSE acquisitions.
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Affiliation(s)
- Zechen Zhou
- Philips Research North America, Cambridge, MA 02141, United States.
| | - Shuo Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Niranjan Balu
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Baocheng Chu
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jie Sun
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Mahmud Mossa-Basha
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Thomas Hatsukami
- Department of Surgery, Division of Vascular Surgery, University of Washington, Seattle, WA 98104, United States
| | | | - Chun Yuan
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
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12
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Truong M, Lennartsson F, Bibic A, Sundius L, Persson A, Siemund R, In’t Zandt R, Goncalves I, Wassélius J. Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI. Eur J Radiol Open 2021; 8:100323. [PMID: 33532518 PMCID: PMC7822939 DOI: 10.1016/j.ejro.2021.100323] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND AND AIMS Histopathology is the gold standard for analysis of atherosclerotic plaques but has drawbacks due to the destructive nature of the method. Ex vivo MRI is a non-destructive method to image whole plaques. Our aim was to use quantitative high field ex vivo MRI to classify plaque components, with histology as gold standard. METHODS Surgically resected carotid plaques from 12 patients with recent TIA or stroke were imaged at 11.7 T MRI. Quantitative T1/T2* mapping sequences and qualitative T1/T2* gradient echo sequences with voxel size of 30 × 30 × 60 μm3 were obtained prior to histological preparation, sectioning and staining for lipids, inflammation, hemorrhage, and fibrous tissue. Regions of interest (ROI) were selected based on the histological staining at multiple levels matched between histology and MRI. The MRI parameters of each ROI were then analyzed with quadratic discriminant analysis (QDA) for classification. RESULTS A total of 965 ROIs, at 70 levels matched between histology and MRI, were registered based on histological staining. In the nine plaques where three or more plaque components were possible to co-localize with MRI, the mean degree of misclassification by QDA was 16.5 %. One of the plaques contained mostly fibrous tissue and lipids and had no misclassifications, and two plaques mostly contained fibrous tissue. QDA generally showed good classification for fibrous tissue and lipids, whereas plaques with hemorrhage and inflammation had more misclassifications. CONCLUSION 11.7 T ex vivo high field MRI shows good visual agreement with histology in carotid plaques. T1/T2* maps analyzed with QDA is a promising non-destructive method to classify plaque components, but with a higher degree of misclassifications in plaques with hemorrhage or inflammation.
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Key Words
- 11.7 T MRI
- 11.7T, 11.7 Tesla
- 3T, 3 Tesla
- Atherosclerosis
- BSA, bovine serum albumin
- CI, confidence interval
- CTA, computed tomography angiography
- Carotid plaque
- Classification
- FA, flip angle
- FOV, field of view
- GE3D, gradient echo three dimensional
- HRP, horse radish peroxidase
- ICA, internal carotid artery
- IPH, intra-plaque hemorrhage
- LRNC, lipid rich necrotic core
- MRI, magnetic resonance imaging
- OCT, optimal cutting temperature
- Plaque components
- RF, radio frequency
- ROI, region of interest
- SD, standard deviation
- T1 maps
- T1w, T1 weighted
- T2*maps
- T2*w, T2 star weighted
- TBS, tris-buffered saline
- TE, echo time
- TIA, transient ischemic attack
- TR, repetition time
- ms, millisecond
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Affiliation(s)
- My Truong
- Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Medical Imaging Department, Neuroradiology, 22185, Lund, Sweden
| | - Finn Lennartsson
- Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Medical Imaging Department, Neuroradiology, 22185, Lund, Sweden
| | - Adnan Bibic
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, F. M. Kirby Center, 707 North Broadway, Baltimore, MD, 21 205, USA
| | - Lena Sundius
- Clinical Sciences Malmö, Lund University, Jan Waldenströmsg 35, 91-12, Skåne University Hospital, 20502, Malmö, Sweden
| | - Ana Persson
- Clinical Sciences Malmö, Lund University, Jan Waldenströmsg 35, 91-12, Skåne University Hospital, 20502, Malmö, Sweden
| | - Roger Siemund
- Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Medical Imaging Department, Neuroradiology, 22185, Lund, Sweden
| | - René In’t Zandt
- Lund University Bioimaging Centre, Lund University, Klinikgatan 32, BMC D11, SE-221 84, Lund, Sweden
| | - Isabel Goncalves
- Cardiology, Skåne University Hospital, Sweden
- Clinical Sciences Malmö, Lund University, Jan Waldenströmsg 35, 91-12, Skåne University Hospital, 20502, Malmö, Sweden
| | - Johan Wassélius
- Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Medical Imaging Department, Neuroradiology, 22185, Lund, Sweden
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13
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Hajhosseiny R, Prieto C, Qi H, Phinikaridou A, Botnar RM. Thrombosis and Embolism. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00072-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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14
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Willemink MJ, Coolen BF, Dyvorne H, Robson PM, Bander I, Ishino S, Pruzan A, Sridhar A, Zhang B, Balchandani P, Mani V, Strijkers GJ, Nederveen AJ, Leiner T, Fayad ZA, Mulder WJM, Calcagno C. Ultra-high resolution, 3-dimensional magnetic resonance imaging of the atherosclerotic vessel wall at clinical 7T. PLoS One 2020; 15:e0241779. [PMID: 33315867 PMCID: PMC7735577 DOI: 10.1371/journal.pone.0241779] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 10/21/2020] [Indexed: 12/11/2022] Open
Abstract
Accurate quantification and characterization of atherosclerotic plaques with MRI requires high spatial resolution acquisitions with excellent image quality. The intrinsically better signal-to-noise ratio (SNR) at high-field clinical 7T compared to the widely employed lower field strengths of 1.5 and 3T may yield significant improvements to vascular MRI. However, 7T atherosclerosis imaging also presents specific challenges, related to local transmit coils and B1 field inhomogeneities, which may overshadow these theoretical gains. We present the development and evaluation of 3D, black-blood, ultra-high resolution vascular MRI on clinical high-field 7T in comparison lower-field 3T. These protocols were applied for in vivo imaging of atherosclerotic rabbits, which are often used for development, testing, and validation of translatable cardiovascular MR protocols. Eight atherosclerotic New Zealand White rabbits were imaged on clinical 7T and 3T MRI scanners using 3D, isotropic, high (0.63 mm3) and ultra-high (0.43 mm3) spatial resolution, black-blood MR sequences with extensive spatial coverage. Following imaging, rabbits were sacrificed for validation using fluorescence imaging and histology. Image quality parameters such as SNR and contrast-to-noise ratio (CNR), as well as morphological and functional plaque measurements (plaque area and permeability) were evaluated at both field strengths. Using the same or comparable imaging parameters, SNR and CNR were in general higher at 7T compared to 3T, with a median (interquartiles) SNR gain of +40.3 (35.3-80.1)%, and a median CNR gain of +68.1 (38.5-95.2)%. Morphological and functional parameters, such as vessel wall area and permeability, were reliably acquired at 7T and correlated significantly with corresponding, widely validated 3T vessel wall MRI measurements. In conclusion, we successfully developed 3D, black-blood, ultra-high spatial resolution vessel wall MRI protocols on a 7T clinical scanner. 7T imaging was in general superior to 3T with respect to image quality, and comparable in terms of plaque area and permeability measurements.
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Affiliation(s)
- Martin J. Willemink
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Radiology, Stanford University School of Medicine, Stanford, California, United States of America
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Hadrien Dyvorne
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Philip M. Robson
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ilda Bander
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Seigo Ishino
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Alison Pruzan
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Arthi Sridhar
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Bei Zhang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Priti Balchandani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Venkatesh Mani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Aart J. Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Zahi A. Fayad
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Willem J. M. Mulder
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Medical Biochemistry, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Claudia Calcagno
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- * E-mail:
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15
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Zi R, Zhu D, Qin Q. Quantitative T 2 mapping using accelerated 3D stack-of-spiral gradient echo readout. Magn Reson Imaging 2020; 73:138-147. [PMID: 32860871 PMCID: PMC7571618 DOI: 10.1016/j.mri.2020.08.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 08/18/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop a rapid T2 mapping protocol using optimized spiral acquisition, accelerated reconstruction, and model fitting. MATERIALS AND METHODS A T2-prepared stack-of-spiral gradient echo (GRE) pulse sequence was applied. A model-based approach joined with compressed sensing was compared with the two methods applied separately for accelerated reconstruction and T2 mapping. A 2-parameter-weighted fitting method was compared with 2- or 3-parameter models for accurate T2 estimation under the influences of noise and B1 inhomogeneity. The performance was evaluated using both digital phantoms and healthy volunteers. Mitigating partial voluming with cerebrospinal fluid (CSF) was also tested. RESULTS Simulations demonstrates that the 2-parameter-weighted fitting approach was robust to a large range of B1 scales and SNR levels. With an in-plane acceleration factor of 5, the model-based compressed sensing-incorporated method yielded around 8% normalized errors compared to references. The T2 estimation with and without CSF nulling was consistent with literature values. CONCLUSION This work demonstrated the feasibility of a T2 quantification technique with 3D high-resolution and whole-brain coverage in 2-3 min. The proposed iterative reconstruction method, which utilized the model consistency, data consistency and spatial sparsity jointly, provided reasonable T2 estimation. The technique also allowed mitigation of CSF partial volume effect.
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Affiliation(s)
- Ruoxun Zi
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dan Zhu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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16
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Kassem M, Florea A, Mottaghy FM, van Oostenbrugge R, Kooi ME. Magnetic resonance imaging of carotid plaques: current status and clinical perspectives. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:1266. [PMID: 33178798 PMCID: PMC7607136 DOI: 10.21037/atm-2020-cass-16] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Rupture of a vulnerable carotid plaque is one of the leading causes of stroke. Carotid magnetic resonance imaging (MRI) is able to visualize all the main hallmarks of plaque vulnerability. Various MRI sequences have been developed in the last two decades to quantify carotid plaque burden and composition. Often, a combination of multiple sequences is used. These MRI techniques have been extensively validated with histological analysis of carotid endarterectomy specimens. High agreement between the MRI and histological measures of plaque burden, intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), fibrous cap (FC) status, inflammation and neovascularization has been demonstrated. Novel MRI sequences allow to generate three-dimensional isotropic images with a large longitudinal coverage. Other new sequences can acquire multiple contrasts using a single sequence leading to a tremendous reduction in scan time. IPH can be easily identified as a hyperintense signal in the bulk of the plaque on strongly T1-weighted images, such as magnetization-prepared rapid acquisition gradient echo images, acquired within a few minutes with a standard neurovascular coil. Carotid MRI can also be used to evaluate treatment effects. Several meta-analyses have demonstrated a strong predictive value of IPH, LRNC, thinning or rupture of the FC for ischemic cerebrovascular events. Recently, in a large meta-analysis based on individual patient data of asymptomatic and symptomatic individuals with carotid artery stenosis, it was shown that IPH on MRI is an independent risk predictor for stroke, stronger than any known clinical risk parameter. Expert recommendations on carotid plaque MRI protocols have recently been described in a white paper. The present review provides an overview of the current status and applications of carotid plaque MR imaging and its future potential in daily clinical practice.
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Affiliation(s)
- Mohamed Kassem
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
| | - Alexandru Florea
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands.,Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
| | - Felix M Mottaghy
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands.,Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
| | - Robert van Oostenbrugge
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.,Department of Neurology, MUMC+, Maastricht, The Netherlands
| | - M Eline Kooi
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
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17
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Pruijssen JT, de Korte CL, Voss I, Hansen HHG. Vascular Shear Wave Elastography in Atherosclerotic Arteries: A Systematic Review. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:2145-2163. [PMID: 32620385 DOI: 10.1016/j.ultrasmedbio.2020.05.013] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/15/2020] [Accepted: 05/15/2020] [Indexed: 06/11/2023]
Abstract
Ischemic stroke is a leading cause of death and disability worldwide, so adequate prevention strategies are crucial. However, current stroke risk stratification is based on epidemiologic studies and is still suboptimal for individual patients. The aim of this systematic review was to provide a literature overview on the feasibility and diagnostic value of vascular shear wave elastography (SWE) using ultrasound (US) in (mimicked) human and non-human arteries affected by different stages of atherosclerotic diseases or diseases related to atherosclerosis. An online search was conducted on Pubmed, Embase, Web of Science and IEEE databases to identify studies using US SWE for the assessment of vascular elasticity. A quality assessment was performed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) checklist, and relevant data were extracted. A total of 19 studies were included: 10 with human patients and 9 with non-human subjects (i.e., [excised] animal arteries and polyvinyl alcohol phantoms). All studies revealed the feasibility of using US SWE to assess individually stiffness of the arterial wall and plaques. Quantitative elasticity values were highly variable between studies. However, within studies, SWE could detect statistically significant elasticity differences in patient/subject characteristics and could distinguish different plaque types with good reproducibility. US SWE, with its unique ability to assess the elasticity of the vessel wall and plaque throughout the cardiac cycle, might be a good candidate to improve stroke risk stratification. However, more clinical studies have to be performed to assess this technique's exact clinical value.
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Affiliation(s)
- Judith T Pruijssen
- Medical Ultrasound Imaging Centre (MUSIC), Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Chris L de Korte
- Medical Ultrasound Imaging Centre (MUSIC), Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; Physics of Fluid Group, MESA+ Institute for Nanotechnology, and MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Iona Voss
- Medical Ultrasound Imaging Centre (MUSIC), Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hendrik H G Hansen
- Medical Ultrasound Imaging Centre (MUSIC), Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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18
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Ziegler M, Good E, Engvall J, Warntjes M, de Muinck E, Dyverfeldt P. Towards Automated Quantification of Vessel Wall Composition Using MRI. J Magn Reson Imaging 2020; 52:710-719. [PMID: 32154973 DOI: 10.1002/jmri.27116] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 02/18/2020] [Accepted: 02/18/2020] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND MRI can be used to generate fat fraction (FF) and R2* data, which have been previously shown to characterize the plaque compositional features lipid-rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in the carotid arteries (CAs). Previously, these data were extracted from CA plaques using time-consuming manual analyses. PURPOSE To design and demonstrate a method for segmenting the CA and extracting data describing the composition of the vessel wall. STUDY TYPE Prospective. SUBJECTS 31 subjects from the Swedish CArdioPulmonary bioImage Study (SCAPIS). FIELD STRENGTH/SEQUENCES T1 -weighted (T1 W) quadruple inversion recovery, contrast-enhanced MR angiography (CE-MRA), and 4-point Dixon data were acquired at 3T. ASSESSMENT The vessel lumen of the CA was automatically segmented using support vector machines (SVM) with CE-MRA data, and the vessel wall region was subsequently delineated. Automatically generated segmentations were quantitatively measured and three observers visually compared the segmentations to manual segmentations performed on T1 w images. Dixon data were used to generate FF and R2* maps. Both manually and automatically generated segmentations of the CA and vessel wall were used to extract compositional data. STATISTICAL TESTS Two-tailed t-tests were used to examine differences between results generated using manual and automated analyses, and among different configurations of the automated method. Interobserver agreement was assessed with Fleiss' kappa. RESULTS Automated segmentation of the CA using SVM had a Dice score of 0.89 ± 0.02 and true-positive ratio 0.93 ± 0.03 when compared against ground truth, and median qualitative score of 4/5 when assessed visually by multiple observers. Vessel wall regions of 0.5 and 1 mm yielded compositional information similar to that gained from manual analyses. Using the 0.5 mm vessel wall region, the mean difference was 0.1 ± 2.5% considering FF and 1.1 ± 5.7[1/s] for R2*. LEVEL OF EVIDENCE 1. TECHNICAL EFFICACY STAGE 1. J. Magn. Reson. Imaging 2020;52:710-719.
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Affiliation(s)
- Magnus Ziegler
- Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Elin Good
- Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Department of Cardiology, Linköping University, Linköping, Sweden
| | - Jan Engvall
- Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Department of Clinical Physiology, Linköping University, Linköping, Sweden
| | - Marcel Warntjes
- Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Ebo de Muinck
- Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Department of Cardiology, Linköping University, Linköping, Sweden
| | - Petter Dyverfeldt
- Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
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19
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Wüst RCI, Calcagno C, Daal MRR, Nederveen AJ, Coolen BF, Strijkers GJ. Emerging Magnetic Resonance Imaging Techniques for Atherosclerosis Imaging. Arterioscler Thromb Vasc Biol 2020; 39:841-849. [PMID: 30917678 DOI: 10.1161/atvbaha.118.311756] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Atherosclerosis is a prevalent disease affecting a large portion of the population at one point in their lives. There is an unmet need for noninvasive diagnostics to identify and characterize at-risk plaque phenotypes noninvasively and in vivo, to improve the stratification of patients with cardiovascular disease, and for treatment evaluation. Magnetic resonance imaging is uniquely positioned to address these diagnostic needs. However, currently available magnetic resonance imaging methods for vessel wall imaging lack sufficient discriminative and predictive power to guide the individual patient needs. To address this challenge, physicists are pushing the boundaries of magnetic resonance atherosclerosis imaging to increase image resolution, provide improved quantitative evaluation of plaque constituents, and obtain readouts of disease activity such as inflammation. Here, we review some of these important developments, with specific focus on emerging applications using high-field magnetic resonance imaging, the use of quantitative relaxation parameter mapping for improved plaque characterization, and novel 19F magnetic resonance imaging technology to image plaque inflammation.
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Affiliation(s)
- Rob C I Wüst
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Claudia Calcagno
- Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York (C.C., G.J.S.)
| | - Mariah R R Daal
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Aart J Nederveen
- Radiology and Nuclear Medicine (A.J.N.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Bram F Coolen
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Gustav J Strijkers
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands.,Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York (C.C., G.J.S.)
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20
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Wang N, Gaddam S, Wang L, Xie Y, Fan Z, Yang W, Tuli R, Lo S, Hendifar A, Pandol S, Christodoulou AG, Li D. Six-dimensional quantitative DCE MR Multitasking of the entire abdomen: Method and application to pancreatic ductal adenocarcinoma. Magn Reson Med 2020; 84:928-948. [PMID: 31961967 DOI: 10.1002/mrm.28167] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 11/09/2019] [Accepted: 12/18/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a quantitative DCE MRI technique enabling entire-abdomen coverage, free-breathing acquisition, 1-second temporal resolution, and T1 -based quantification of contrast agent concentration and kinetic modeling for the characterization of pancreatic ductal adenocarcinoma (PDAC). METHODS Segmented FLASH readouts following saturation-recovery preparation with randomized 3D Cartesian undersampling was used for incoherent data acquisition. MR Multitasking was used to reconstruct 6-dimensional images with 3 spatial dimensions, 1 T1 recovery dimension for dynamic T1 quantification, 1 respiratory dimension to resolve respiratory motion, and 1 DCE time dimension to capture the contrast kinetics. Sixteen healthy subjects and 14 patients with pathologically confirmed PDAC were recruited for the in vivo studies, and kinetic parameters vp , Ktrans , ve , and Kep were evaluated for each subject. Intersession repeatability of Multitasking DCE was assessed in 8 repeat healthy subjects. One-way unbalanced analysis of variance was performed between control and patient groups. RESULTS In vivo studies demonstrated that vp , Ktrans , and Kep of PDAC were significantly lower compared with nontumoral regions in the patient group (P = .002, .003, .004, respectively) and normal pancreas in the control group (P = .011, <.001, <.001, respectively), while ve was significantly higher than nontumoral regions (P < .001) and healthy pancreas (P < .001). The kinetic parameters showed good in vivo repeatability (interclass correlation coefficient: vp , 0.95; Ktrans , 0.98; ve , 0.96; Kep , 0.99). CONCLUSION The proposed Multitasking DCE is promising for the quantification of vascular properties of PDAC. Quantitative DCE parameters were repeatable in vivo and showed significant differences between normal pancreas and both tumor and nontumoral regions in patients with PDAC.
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Affiliation(s)
- Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
| | - Srinivas Gaddam
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, California
| | - Lixia Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
| | - Wensha Yang
- Department of Clinical Radiation Oncology, University of Southern California, Los Angeles, California
| | - Richard Tuli
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Simon Lo
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, California
| | - Andrew Hendifar
- Department of Gastrointestinal Malignancies, Cedars-Sinai Medical Center, Los Angeles, California
| | - Stephen Pandol
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, California
| | | | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
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21
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Hajhosseiny R, Bahaei TS, Prieto C, Botnar RM. Molecular and Nonmolecular Magnetic Resonance Coronary and Carotid Imaging. Arterioscler Thromb Vasc Biol 2020; 39:569-582. [PMID: 30760017 DOI: 10.1161/atvbaha.118.311754] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Atherosclerosis is the leading cause of cardiovascular morbidity and mortality. Over the past 2 decades, increasing research attention is converging on the early detection and monitoring of atherosclerotic plaque. Among several invasive and noninvasive imaging modalities, magnetic resonance imaging (MRI) is emerging as a promising option. Advantages include its versatility, excellent soft tissue contrast for plaque characterization and lack of ionizing radiation. In this review, we will explore the recent advances in multicontrast and multiparametric imaging sequences that are bringing the aspiration of simultaneous arterial lumen, vessel wall, and plaque characterization closer to clinical feasibility. We also discuss the latest advances in molecular magnetic resonance and multimodal atherosclerosis imaging.
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Affiliation(s)
- Reza Hajhosseiny
- From the School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (R.H., T.S.B., C.P., R.M.B.).,National Heart and Lung Institute, Imperial College London, United Kingdom (R.H.)
| | - Tamanna S Bahaei
- From the School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (R.H., T.S.B., C.P., R.M.B.)
| | - Claudia Prieto
- From the School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (R.H., T.S.B., C.P., R.M.B.).,Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile (C.P., R.M.B.)
| | - René M Botnar
- From the School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (R.H., T.S.B., C.P., R.M.B.).,Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile (C.P., R.M.B.)
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22
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Keerthivasan MB, Saranathan M, Johnson K, Fu Z, Weinkauf CC, Martin DR, Bilgin A, Altbach MI. An efficient 3D stack-of-stars turbo spin echo pulse sequence for simultaneous T2-weighted imaging and T2 mapping. Magn Reson Med 2019; 82:326-341. [PMID: 30883879 DOI: 10.1002/mrm.27737] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 02/01/2019] [Accepted: 02/21/2019] [Indexed: 01/16/2023]
Abstract
PURPOSE To design a pulse sequence for efficient 3D T2-weighted imaging and T2 mapping. METHODS A stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles and a flexible pseudorandom view ordering is proposed for simultaneous T2-weighted imaging and T2 mapping. An analytical framework is introduced for the selection of refocusing flip angles to maximize relative tissue contrast while minimizing T2 estimation errors and maintaining low specific absorption rate. Images at different echo times are generated using a subspace constrained iterative reconstruction algorithm. T2 maps are obtained by modeling the signal evolution using the extended phase graph model. The technique is evaluated using phantoms and demonstrated in vivo for brain, knee, and carotid imaging. RESULTS Numerical simulations demonstrate an improved point spread function with the proposed pseudorandom view ordering compared to golden angle view ordering. Phantom experiments show that T2 values estimated from the stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles have good concordance with spin echo reference values. In vivo results show the proposed pulse sequence can generate qualitatively comparable T2-weighted images as conventional Cartesian 3D SPACE in addition to simultaneously generating 3D T2 maps. CONCLUSION The proposed stack-of-stars turbo spin echo pulse sequence with pseudorandom view ordering and variable refocusing flip angles allows high resolution isotropic T2 mapping in clinically acceptable scan times. The optimization framework for the selection of refocusing flip angles improves T2 estimation accuracy while generating T2-weighted contrast comparable to conventional Cartesian imaging.
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Affiliation(s)
- Mahesh Bharath Keerthivasan
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Manojkumar Saranathan
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Kevin Johnson
- Medical Imaging, University of Arizona, Tucson, Arizona
| | - Zhiyang Fu
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | | | | | - Ali Bilgin
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Biomedical Engineering, University of Arizona, Tucson, Arizona
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23
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Jiang D, Lu H, Parkinson C, Su P, Wei Z, Pan L, Tekes A, Huisman TAGM, Golden WC, Liu P. Vessel-specific quantification of neonatal cerebral venous oxygenation. Magn Reson Med 2019; 82:1129-1139. [PMID: 31066104 DOI: 10.1002/mrm.27788] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 03/25/2019] [Accepted: 04/08/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Noninvasive measurement of cerebral venous oxygenation (Yv ) in neonates is important in the assessment of brain oxygen extraction and consumption, and may be useful in characterizing brain development and neonatal brain diseases. This study aims to develop a rapid method for vessel-specific measurement of Yv in neonates. METHODS We developed a pulse sequence, named accelerated T2 -relaxation-under-phase-contrast (aTRUPC), which consists of velocity-encoding phase-contrast module to isolate pure blood signal, flow-insensitive T2 -preparation to quantify blood T2 , and turbo-field-echo (TFE) scheme for rapid image acquisition, which is critical for neonatal MRI. A series of studies were conducted. First, the pulse sequence was optimized in terms of TFE factor, velocity encoding (VENC), and slice thickness for best sensitivity. Second, to account for the influence of TFE acquisition on T2 quantification, simulation and experiments were conducted to establish the relationship between TFE-T2 and standard T2 . Finally, the complete aTRUPC sequence was applied on a group of healthy neonates and normative Yv values were determined. RESULTS Optimal parameters of aTRUPC in neonates were found to be a TFE factor of 15, VENC of 5 cm/s, and slice thickness of 10 mm. The TFE-T2 was on average 3.9% lower than standard T2 . These two measures were strongly correlated (R2 = 0.86); thus their difference can be accounted for by a correction equation, T2,standard = 1.2002 × T2,TFE - 10.6276. Neonatal Yv values in veins draining cortical brain and those draining central brain were 64.8 ± 2.9% and 70.2 ± 3.3%, respectively, with a significant difference (P =.02). CONCLUSION The aTRUPC MRI has the potential to provide vessel-specific quantification of cerebral Yv in neonates.
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Affiliation(s)
- Dengrong Jiang
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland
| | - Charlamaine Parkinson
- Neurosciences Intensive Care Nursery, Johns Hopkins School of Medicine, Baltimore, Maryland.,Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Pan Su
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Zhiliang Wei
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland
| | - Li Pan
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Siemens Healthineers, Baltimore, Maryland
| | - Aylin Tekes
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Neurosciences Intensive Care Nursery, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Thierry A G M Huisman
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Neurosciences Intensive Care Nursery, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - W Christopher Golden
- Neurosciences Intensive Care Nursery, Johns Hopkins School of Medicine, Baltimore, Maryland.,Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Peiying Liu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
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24
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Abstract
Background The quality of carotid wall MRI can benefit substantially from a dedicated RF coil that is tailored towards the human neck geometry and optimized for image signal-to-noise ratio (SNR), parallel imaging performance and RF penetration depth and coverage. In last decades, several of such dedicated carotid coils were introduced. However, a comparison of the more successful designs is still lacking. Objective To perform a head-to-head comparison over four dedicated MR carotid surface coils with 4, 6, 8 and 30 coil elements, respectively. Material and methods Ten volunteers were scanned on a 3T scanner. For each subject, multiple black-blood carotid vessel wall images were measured using the four coils with different parallel imaging settings. The performance of the coils was evaluated and compared in terms of image coverage, penetration depth and noise correlations between elements. Vessel wall of a common carotid section was delineated manually. Subsequently, images were assessed based on vessel wall morphology and image quality parameters. The morphological parameters consisted of the vessel wall area, thickness, and normalized wall index (wall area/total vessel area). Image quality parameters consisted of vessel wall SNR, wall-lumen contrast-to-noise ratio (CNR), the vessel g-factor, and CNRindex ((wall–lumen signal) / (wall+lumen signal)). Repeated measures analysis of variance (rmANOVA) was applied for each parameter for the averaged 10 slices for all volunteers to assess effect of coil and SENSE factor. If the rmANOVA was significant, post-hoc comparisons were conducted. Results No significant coil effect were found for vessel wall morphological parameters. SENSE acceleration affected some morphological parameters for 6- and 8-channel coils, but had no effect on the 30-channel coil. The 30-channel coil achieved high acceleration factors (10x) with significantly lower vessel g-factor values (ps ≤ 0.01), but lower vessel wall SNR and CNR values (ps ≤ 0.01). Conclusion All four coils were capable of high-quality carotid MRI. The 30-channel coil is recommended when rapid image acquisition acceleration is required for 3D measurements, whereas 6- and 8-channel coils demonstrated the highest SNR performance.
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Henningsson M, Zahr RA, Dyer A, Greil GF, Burkhardt B, Tandon A, Hussain T. Feasibility of 3D black-blood variable refocusing angle fast spin echo cardiovascular magnetic resonance for visualization of the whole heart and great vessels in congenital heart disease. J Cardiovasc Magn Reson 2018; 20:76. [PMID: 30474554 PMCID: PMC6260764 DOI: 10.1186/s12968-018-0508-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 11/14/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Volumetric black-blood cardiovascular magnetic resonance (CMR) has been hampered by long scan times and flow sensitivity. The purpose of this study was to assess the feasibility of black-blood, electrocardiogram (ECG)-triggered and respiratory-navigated 3D fast spin echo (3D FSE) for the visualization of the whole heart and great vessels. METHODS The implemented 3D FSE technique used slice-selective excitation and non-selective refocusing pulses with variable flip angles to achieve constant echo signal for tissue with T1 (880 ms) and T2 (40 ms) similar to the vessel wall. Ten healthy subjects and 21 patients with congenital heart disease (CHD) underwent 3D FSE and conventional 3D balanced steady-state free precession (bSSFP). The sequences were compared in terms of ability to perform segmental assessment, local signal-to-noise ratio (SNRl) and local contrast-to-noise ratio (CNRl). RESULTS In both healthy subjects and patients with CHD, 3D FSE showed superior pulmonary vein but inferior coronary artery origin visualisation compared to 3D bSFFP. However, in patients with CHD the combination of 3D bSSFP and 3D FSE whole-heart imaging improves the success rate of cardiac morphological diagnosis to 100% compared to either technique in isolation (3D FSE, 23.8% success rate, 3D bSSFP, 5% success rate). In the healthy subjects SNRl for 3D bSSFP was greater than for 3D FSE (30.1 ± 7.3 vs 20.9 ± 5.3; P = 0.002) whereas the CNRl was comparable (17.3 ± 5.6 vs 17.4 ± 4.9; P = 0.91) between the two scans. CONCLUSIONS The feasibility of 3D FSE for whole-heart black-blood CMR imaging has been demonstrated. Due to their high success rate for segmental assessment, the combination of 3D bSSFP and 3D FSE may be an attractive alternative to gadolinium contrast enhanced morphological CMR in patients with CHD.
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Affiliation(s)
- Markus Henningsson
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Riad Abou Zahr
- Departments of Pediatrics and Radiology, University of Texas Southwestern/Children’s Health, Dallas, TX USA
| | - Adrian Dyer
- Departments of Pediatrics and Radiology, University of Texas Southwestern/Children’s Health, Dallas, TX USA
| | - Gerald F. Greil
- Departments of Pediatrics and Radiology, University of Texas Southwestern/Children’s Health, Dallas, TX USA
| | - Barbara Burkhardt
- Departments of Pediatrics and Radiology, University of Texas Southwestern/Children’s Health, Dallas, TX USA
| | - Animesh Tandon
- Departments of Pediatrics and Radiology, University of Texas Southwestern/Children’s Health, Dallas, TX USA
| | - Tarique Hussain
- Departments of Pediatrics and Radiology, University of Texas Southwestern/Children’s Health, Dallas, TX USA
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Guyader JM, Huizinga W, Poot DHJ, van Kranenburg M, Uitterdijk A, Niessen WJ, Klein S. Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data. Sci Rep 2018; 8:13112. [PMID: 30166626 PMCID: PMC6117310 DOI: 10.1038/s41598-018-31474-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 08/20/2018] [Indexed: 02/07/2023] Open
Abstract
The most widespread technique used to register sets of medical images consists of selecting one image as fixed reference, to which all remaining images are successively registered. This pairwise scheme requires one optimization procedure per pair of images to register. Pairwise mutual information is a common dissimilarity measure applied to a large variety of datasets. Alternative methods, called groupwise registrations, have been presented to register two or more images in a single optimization procedure, without the need of a reference image. Given the success of mutual information in pairwise registration, we adapt one of its multivariate versions, called total correlation, in a groupwise context. We justify the choice of total correlation among other multivariate versions of mutual information, and provide full implementation details. The resulting total correlation measure is remarkably close to measures previously proposed by Huizinga et al. based on principal component analysis. Our experiments, performed on five quantitative imaging datasets and on a dynamic CT imaging dataset, show that total correlation yields registration results that are comparable to Huizinga's methods. Total correlation has the advantage of being theoretically justified, while the measures of Huizinga et al. were designed empirically. Additionally, total correlation offers an alternative to pairwise mutual information on quantitative imaging datasets.
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Affiliation(s)
- Jean-Marie Guyader
- Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands.
| | - Wyke Huizinga
- Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Dirk H J Poot
- Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Matthijs van Kranenburg
- Departments of Radiology, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Cardiology, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - André Uitterdijk
- Department of Cardiology, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Wiro J Niessen
- Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands
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Qi H, Sun J, Qiao H, Zhao X, Guo R, Balu N, Yuan C, Chen H. Simultaneous T 1 and T 2 mapping of the carotid plaque (SIMPLE) with T 2 and inversion recovery prepared 3D radial imaging. Magn Reson Med 2018; 80:2598-2608. [PMID: 29802629 DOI: 10.1002/mrm.27361] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 04/21/2018] [Accepted: 04/23/2018] [Indexed: 12/30/2022]
Abstract
PURPOSE To propose a technique that can produce different T1 and T2 contrasts in a single scan for simultaneous T1 and T2 mapping of the carotid plaque (SIMPLE). METHODS An interleaved 3D golden angle radial trajectory was used in conjunction with T2 preparation with variable duration (TEprep ) and inversion recovery pulses. Sliding window reconstruction was adopted to reconstruct images at different inversion delay time and TEprep for joint T1 and T2 fitting. In the fitting procedure, a rapid B1 correction method was presented. The accuracy of SIMPLE was investigated in phantom experiments. In vivo scans were performed on 5 healthy volunteers with 2 scans each, and on 5 patients with carotid atherosclerosis. RESULTS The phantom T1 and T2 estimations of SIMPLE agreed well with the standard methods with the percentage difference smaller than 7.1%. In vivo T1 and T2 for normal carotid vessel wall were 1213 ± 48.3 ms and 51.1 ± 1.7 ms, with good interscan repeatability. Alternations of T1 and T2 in plaque regions were in agreement with the conventional multicontrast imaging findings. CONCLUSION The proposed SIMPLE allows simultaneous T1 and T2 mapping of the carotid artery in less than 10 minutes, serving as a quantitative tool with good accuracy and reproducibility for plaque characterization.
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Affiliation(s)
- Haikun Qi
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Jie Sun
- Department of Radiology, University of Washington, Seattle, Washington
| | - Huiyu Qiao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Rui Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Niranjan Balu
- Department of Radiology, University of Washington, Seattle, Washington
| | - Chun Yuan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.,Department of Radiology, University of Washington, Seattle, Washington
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
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28
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Fujiwara Y, Maruyama H, Toyomaru K, Nishizaka Y, Fukamatsu M. Quantitative T 1 and T 2* carotid atherosclerotic plaque imaging using a three-dimensional multi-echo phase-sensitive inversion recovery sequence: a feasibility study. Radiol Phys Technol 2018; 11:156-164. [PMID: 29512056 DOI: 10.1007/s12194-018-0449-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 03/01/2018] [Accepted: 03/02/2018] [Indexed: 10/17/2022]
Abstract
Magnetic resonance imaging (MRI) is widely used to detect carotid atherosclerotic plaques. Although it is important to evaluate vulnerable carotid plaques containing lipids and intra-plaque hemorrhages (IPHs) using T1-weighted images, the image contrast changes depending on the imaging settings. Moreover, to distinguish between a thrombus and a hemorrhage, it is useful to evaluate the iron content of the plaque using both T1-weighted and T2*-weighted images. Therefore, a quantitative evaluation of carotid atherosclerotic plaques using T1 and T2* values may be necessary for the accurate evaluation of plaque components. The purpose of this study was to determine whether the multi-echo phase-sensitive inversion recovery (mPSIR) sequence can improve T1 contrast while simultaneously providing accurate T1 and T2* values of an IPH. T1 and T2* values measured using mPSIR were compared to values from conventional methods in phantom and in vivo studies. In the phantom study, the T1 and T2* values estimated using mPSIR were linearly correlated with those of conventional methods. In the in vivo study, mPSIR demonstrated higher T1 contrast between the IPH phantom and sternocleidomastoid muscle than the conventional method. Moreover, the T1 and T2* values of the blood vessel wall and sternocleidomastoid muscle estimated using mPSIR were correlated with values measured by conventional methods and with values reported previously. The mPSIR sequence improved T1 contrast while simultaneously providing accurate T1 and T2* values of the neck region. Although further study is required to evaluate the clinical utility, mPSIR may improve carotid atherosclerotic plaque detection and provide detailed information about plaque components.
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Affiliation(s)
- Yasuhiro Fujiwara
- Department of Medical Imaging, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Chuo-ku, Kumamoto, 862-0976, Japan.
| | - Hirotoshi Maruyama
- Radiological Center, National Hospital Organization Kumamoto Saisyunsou Hospital, Kumamoto, Japan
| | - Kanako Toyomaru
- Course of Radiological Science, School of Health Sciences, Kumamoto University, Kumamoto, Japan
| | - Yuri Nishizaka
- Course of Radiological Science, School of Health Sciences, Kumamoto University, Kumamoto, Japan
| | - Masahiro Fukamatsu
- Radiological Center, National Hospital Organization Kumamoto Medical Center, Kumamoto, Japan
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Yuan J, Patterson AJ, Ruetten PPR, Reid SA, Gillard JH, Graves MJ. A Comparison of Black-blood T 2 Mapping Sequences for Carotid Vessel Wall Imaging at 3T: An Assessment of Accuracy and Repeatability. Magn Reson Med Sci 2018. [PMID: 29515084 PMCID: PMC6326764 DOI: 10.2463/mrms.mp.2017-0141] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Purpose: This study is to compare the accuracy of four different black-blood T2 mapping sequences in carotid vessel wall. Methods: Four different black-blood T2 mapping sequences were developed and tested through phantom experiments and 17 healthy volunteers. The four sequences were: 1) double inversion-recovery (DIR) prepared 2D multi-echo spin-echo (MESE); 2) DIR-prepared 2D multi-echo fast spin-echo (MEFSE); 3) improved motion-sensitized driven-equilibrium (iMSDE) prepared 3D FSE and 4) iMSDE prepared 3D fast spoiled gradient echo (FSPGR). The concordance correlation coefficient and Bland–Altman statistics were used to compare the sequences with a gold-standard 2D MESE, without blood suppression in phantom studies. The volunteers were scanned twice to test the repeatability. Mean and standard deviation of vessel wall T2, signal-to-noise (SNR), the coefficient of variance and interclass coefficient (ICC) of the two scans were compared. Results: The phantom study demonstrated that T2 measurements had high concordance with respect to the gold-standard (all r values >0.9). In the volunteer study, the DIR 2D MEFSE had significantly higher T2 values than the other three sequences (P < 0.01). There was no difference in T2 measurements obtained using the other three sequences (P > 0.05). iMSDE 3D FSE had the highest SNR (P < 0.05) compared with the other three sequences. The 2D DIR MESE has the highest repeatability (ICC: 0.96, [95% CI: 0.88–0.99]). Conclusion: Although accurate T2 measurements can be achieved in phantom by the four sequences, in vivo vessel wall T2 quantification shows significant differences. The in vivo images can be influenced by multiple factors including black-blood preparation and acquisition method. Therefore, a careful choice of acquisition methods and analysis of the confounding factors are required for accurate in vivo carotid vessel wall T2 measurements. From the settings in this study, the iMSDE prepared 3D FSE is preferred for the future volunteer/patient scans.
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Affiliation(s)
- Jianmin Yuan
- Department of Radiology, University of Cambridge, Level 5, Box 218, Addenbrooke's Hospital
| | - Andrew J Patterson
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust
| | - Pascal P R Ruetten
- Department of Radiology, University of Cambridge, Level 5, Box 218, Addenbrooke's Hospital
| | | | - Jonathan H Gillard
- Department of Radiology, University of Cambridge, Level 5, Box 218, Addenbrooke's Hospital
| | - Martin J Graves
- Department of Radiology, University of Cambridge, Level 5, Box 218, Addenbrooke's Hospital.,Department of Radiology, Cambridge University Hospitals NHS Foundation Trust
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30
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Wang G, Zhang Y, Hegde SS, Bottomley PA. High-resolution and accelerated multi-parametric mapping with automated characterization of vessel disease using intravascular MRI. J Cardiovasc Magn Reson 2017; 19:89. [PMID: 29157260 PMCID: PMC5694914 DOI: 10.1186/s12968-017-0399-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 10/16/2017] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Atherosclerosis is prevalent in cardiovascular disease, but present imaging modalities have limited capabilities for characterizing lesion stage, progression and response to intervention. This study tests whether intravascular magnetic resonance imaging (IVMRI) measures of relaxation times (T1, T2) and proton density (PD) in a clinical 3 Tesla scanner could characterize vessel disease, and evaluates a practical strategy for accelerated quantification. METHODS IVMRI was performed in fresh human artery segments and swine vessels in vivo, using fast multi-parametric sequences, 1-2 mm diameter loopless antennae and 200-300 μm resolution. T1, T2 and PD data were used to train a machine learning classifier (support vector machine, SVM) to automatically classify normal vessel, and early or advanced disease, using histology for validation. Disease identification using the SVM was tested with receiver operating characteristic curves. To expedite acquisition of T1, T2 and PD data for vessel characterization, the linear algebraic method ('SLAM') was modified to accommodate the antenna's highly-nonuniform sensitivity, and used to provide average T1, T2 and PD measurements from compartments of normal and pathological tissue segmented from high-resolution images at acceleration factors of R ≤ 18-fold. The results were validated using compartment-average measures derived from the high-resolution scans. RESULTS The SVM accurately classified ~80% of samples into the three disease classes. The 'area-under-the-curve' was 0.96 for detecting disease in 248 samples, with T1 providing the best discrimination. SLAM T1, T2 and PD measures for R ≤ 10 were indistinguishable from the true means of segmented tissue compartments. CONCLUSION High-resolution IVMRI measures of T1, T2 and PD with a trained SVM can automatically classify normal, early and advanced atherosclerosis with high sensitivity and specificity. Replacing relaxometric MRI with SLAM yields good estimates of T1, T2 and PD an order-of-magnitude faster to facilitate IVMRI-based characterization of vessel disease.
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Affiliation(s)
- Guan Wang
- Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, MD USA
- Division of MR Research, Department of Radiology and Radiological Sciences, Johns Hopkins University, Park building 310, 600 N Wolfe Street, Baltimore, MD 21287 USA
| | - Yi Zhang
- Division of MR Research, Department of Radiology and Radiological Sciences, Johns Hopkins University, Park building 310, 600 N Wolfe Street, Baltimore, MD 21287 USA
| | - Shashank Sathyanarayana Hegde
- Division of MR Research, Department of Radiology and Radiological Sciences, Johns Hopkins University, Park building 310, 600 N Wolfe Street, Baltimore, MD 21287 USA
| | - Paul A. Bottomley
- Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, MD USA
- Division of MR Research, Department of Radiology and Radiological Sciences, Johns Hopkins University, Park building 310, 600 N Wolfe Street, Baltimore, MD 21287 USA
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31
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Qi H, Sun J, Qiao H, Chen S, Zhou Z, Pan X, Wang Y, Zhao X, Li R, Yuan C, Chen H. Carotid Intraplaque Hemorrhage Imaging with Quantitative Vessel Wall T1 Mapping: Technical Development and Initial Experience. Radiology 2017; 287:276-284. [PMID: 29117484 DOI: 10.1148/radiol.2017170526] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To develop a three-dimensional (3D) high-spatial-resolution time-efficient sequence for use in quantitative vessel wall T1 mapping. Materials and Methods A previously described sequence, simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) imaging, was extended by introducing 3D golden angle radial k-space sampling (GOAL-SNAP). Sliding window reconstruction was adopted to reconstruct images at different inversion delay times (different T1 contrasts) for voxelwise T1 fitting. Phantom studies were performed to test the accuracy of T1 mapping with GOAL-SNAP against a two-dimensional inversion recovery (IR) spin-echo (SE) sequence. In vivo studies were performed in six healthy volunteers (mean age, 27.8 years ± 3.0 [standard deviation]; age range, 24-32 years; five male) and five patients with atherosclerosis (mean age, 66.4 years ± 5.5; range, 60-73 years; five male) to compare T1 measurements between vessel wall sections (five per artery) with and without intraplaque hemorrhage (IPH). Statistical analyses included Pearson correlation coefficient, Bland-Altman analysis, and Wilcoxon rank-sum test with data permutation by subject. Results Phantom T1 measurements with GOAL-SNAP and IR SE sequences showed excellent correlation (R2 = 0.99), with a mean bias of -25.8 msec ± 43.6 and a mean percentage error of 4.3% ± 2.5. Minimum T1 was significantly different between sections with IPH and those without it (mean, 371 msec ± 93 vs 944 msec ± 120; P = .01). Estimated T1 of normal vessel wall and muscle were 1195 msec ± 136 and 1117 msec ± 153, respectively. Conclusion High-spatial-resolution (0.8 mm isotropic) time-efficient (5 minutes) vessel wall T1 mapping is achieved by using the GOAL-SNAP sequence. This sequence may yield more quantitative reproducible biomarkers with which to characterize IPH and monitor its progression. © RSNA, 2017.
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Affiliation(s)
- Haikun Qi
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Jie Sun
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Huiyu Qiao
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Shuo Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Zechen Zhou
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Xinlei Pan
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Yishi Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Xihai Zhao
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Rui Li
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Chun Yuan
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Huijun Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
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32
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Coolen BF, Calcagno C, van Ooij P, Fayad ZA, Strijkers GJ, Nederveen AJ. Vessel wall characterization using quantitative MRI: what's in a number? MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 31:201-222. [PMID: 28808823 PMCID: PMC5813061 DOI: 10.1007/s10334-017-0644-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 07/04/2017] [Accepted: 07/18/2017] [Indexed: 12/15/2022]
Abstract
The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.
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Affiliation(s)
- Bram F Coolen
- Department of Biomedical Engineering and Physics, Academic Medical Center, PO BOX 22660, 1100 DD, Amsterdam, The Netherlands. .,Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands.
| | - Claudia Calcagno
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pim van Ooij
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Zahi A Fayad
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Academic Medical Center, PO BOX 22660, 1100 DD, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
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Black-blood T2* mapping with delay alternating with nutation for tailored excitation. Magn Reson Imaging 2017; 40:91-97. [DOI: 10.1016/j.mri.2017.04.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2016] [Revised: 04/17/2017] [Accepted: 04/20/2017] [Indexed: 02/05/2023]
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34
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Qi H, Huang F, Zhou Z, Koken P, Balu N, Zhang B, Yuan C, Chen H. Large coverage black-bright blood interleaved imaging sequence (LaBBI) for 3D dynamic contrast-enhanced MRI of vessel wall. Magn Reson Med 2017. [PMID: 28626998 DOI: 10.1002/mrm.26786] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
PURPOSE To propose a large coverage black-bright blood interleaved imaging sequence (LaBBI) for 3D dynamic contrast-enhanced MRI (DCE-MRI) of the vessel wall. METHODS LaBBI consists of a 3D black-blood stack-of-stars golden angle radial acquisition with high spatial resolution for vessel wall imaging and a 2D bright-blood Cartesian acquisition with high temporal resolution for arterial input function estimation. The two acquisitions were performed in an interleaved fashion within a single scan. Simulations, phantom experiments, and in vivo tests in three patients were performed to investigate the feasibility and performance of the proposed LaBBI. RESULTS In simulation tests, the estimated Ktrans and vp by LaBBI were more accurate than conventional bright-blood DCE-MRI with lower root mean square error in all the tested conditions. In phantom test, no signal interference was found on the 2D scan in LaBBI. Pharmacokinetic analysis of the patients' data acquired by LaBBI showed that Ktrans was higher in fibrous tissue (0.0717 ± 0.0279 min-1 ), while lower in necrotic core (0.0206 ± 0.0040 min-1 ) and intraplaque hemorrhage (0.0078 ± 0.0007 min-1 ), compared with normal vessel wall (0.0273 ± 0.0052 min-1 ). CONCLUSION The proposed LaBBI sequence, with high spatial and temporal resolution, and large coverage blood suppression, was promising to probe the perfusion properties of vessel wall lesions. Magn Reson Med 79:1334-1344, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Haikun Qi
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | | | | | | | - Niranjan Balu
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | | | - Chun Yuan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.,Department of Radiology, University of Washington, Seattle, Washington, USA
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
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Manual versus Automated Carotid Artery Plaque Component Segmentation in High and Lower Quality 3.0 Tesla MRI Scans. PLoS One 2016; 11:e0164267. [PMID: 27930665 PMCID: PMC5145140 DOI: 10.1371/journal.pone.0164267] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 09/22/2016] [Indexed: 01/29/2023] Open
Abstract
PURPOSE To study the interscan reproducibility of manual versus automated segmentation of carotid artery plaque components, and the agreement between both methods, in high and lower quality MRI scans. METHODS 24 patients with 30-70% carotid artery stenosis were planned for 3T carotid MRI, followed by a rescan within 1 month. A multicontrast protocol (T1w,T2w, PDw and TOF sequences) was used. After co-registration and delineation of the lumen and outer wall, segmentation of plaque components (lipid-rich necrotic cores (LRNC) and calcifications) was performed both manually and automated. Scan quality was assessed using a visual quality scale. RESULTS Agreement for the detection of LRNC (Cohen's kappa (k) is 0.04) and calcification (k = 0.41) between both manual and automated segmentation methods was poor. In the high-quality scans (visual quality score ≥ 3), the agreement between manual and automated segmentation increased to k = 0.55 and k = 0.58 for, respectively, the detection of LRNC and calcification larger than 1 mm2. Both manual and automated analysis showed good interscan reproducibility for the quantification of LRNC (intraclass correlation coefficient (ICC) of 0.94 and 0.80 respectively) and calcified plaque area (ICC of 0.95 and 0.77, respectively). CONCLUSION Agreement between manual and automated segmentation of LRNC and calcifications was poor, despite a good interscan reproducibility of both methods. The agreement between both methods increased to moderate in high quality scans. These findings indicate that image quality is a critical determinant of the performance of both manual and automated segmentation of carotid artery plaque components.
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de Korte CL, Fekkes S, Nederveen AJ, Manniesing R, Hansen HRHG. Review: Mechanical Characterization of Carotid Arteries and Atherosclerotic Plaques. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2016; 63:1613-1623. [PMID: 27249826 DOI: 10.1109/tuffc.2016.2572260] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Cardiovascular disease (CVD) is a leading cause of death and is in the majority of cases due to the formation of atherosclerotic plaques in arteries. Initially, thickening of the inner layer of the arterial wall occurs. Continuation of this process leads to plaque formation. The risk of a plaque to rupture and thus to induce an ischemic event is directly related to its composition. Consequently, characterization of the plaque composition and its proneness to rupture are of crucial importance for risk assessment and treatment strategies. The carotid is an excellent artery to be imaged with ultrasound because of its superficial position. In this review, ultrasound-based methods for characterizing the mechanical properties of the carotid wall and atherosclerotic plaque are discussed. Using conventional echography, the intima media thickness (IMT) can be quantified. There is a wealth of studies describing the relation between IMT and the risk for myocardial infarction and stroke. Also the carotid distensibility can be quantified with ultrasound, providing a surrogate marker for the cross-sectional mechanical properties. Although all these parameters are associated with CVD, they do not easily translate to individual patient risk. Another technique is pulse wave velocity (PWV) assessment, which measures the propagation of the pressure pulse over the arterial bed. PWV has proven to be a marker for global arterial stiffness. Recently, an ultrasound-based method to estimate the local PWV has been introduced, but the clinical effectiveness still needs to be established. Other techniques focus on characterization of plaques. With ultrasound elastography, the strain in the plaque due to the pulsatile pressure can be quantified. This technique was initially developed using intravascular catheters to image coronaries, but recently noninvasive methods were successfully developed. A high correlation between the measured strain and the risk for rupture was established. Acoustic radiation force impulse (ARFI) imaging also provides characterization of local plaque components based on mechanical properties. However, both elastography and ARFI provide an indirect measure of the elastic modulus of tissue. With shear wave imaging, the elastic modulus can be quantified, although the carotid artery is one of the most challenging tissues for this technique due to its size and geometry. Prospective studies still have to establish the predictive value of these techniques for the individual patient. Validation of ultrasound-based mechanical characterization of arteries and plaques remains challenging. Magnetic resonance imaging is often used as the "gold" standard for plaque characterization, but its limited resolution renders only global characterization of the plaque. CT provides information on the vascular tree, the degree of stenosis, and the presence of calcified plaque, while soft plaque characterization remains limited. Histology still is the gold standard, but is available only if tissue is excised. In conclusion, elastographic ultrasound techniques are well suited to characterize the different stages of vascular disease.
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Revisiting the Potential of Alternating Repetition Time Balanced Steady-State Free Precession Imaging of the Abdomen at 3 T. Invest Radiol 2016; 51:560-8. [DOI: 10.1097/rli.0000000000000275] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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Koppal S, Warntjes M, Swann J, Dyverfeldt P, Kihlberg J, Moreno R, Magee D, Roberts N, Zachrisson H, Forssell C, Länne T, Treanor D, de Muinck ED. Quantitative fat and R2* mapping in vivo to measure lipid-rich necrotic core and intraplaque hemorrhage in carotid atherosclerosis. Magn Reson Med 2016; 78:285-296. [PMID: 27510300 DOI: 10.1002/mrm.26359] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 06/29/2016] [Accepted: 07/07/2016] [Indexed: 11/08/2022]
Abstract
PURPOSE The aim of this work was to quantify the extent of lipid-rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in atherosclerotic plaques. METHODS Patients scheduled for carotid endarterectomy underwent four-point Dixon and T1-weighted magnetic resonance imaging (MRI) at 3 Tesla. Fat and R2* maps were generated from the Dixon sequence at the acquired spatial resolution of 0.60 × 0.60 × 0.70 mm voxel size. MRI and three-dimensional (3D) histology volumes of plaques were registered. The registration matrix was applied to segmentations denoting LRNC and IPH in 3D histology to split plaque volumes in regions with and without LRNC and IPH. RESULTS Five patients were included. Regarding volumes of LRNC identified by 3D histology, the average fat fraction by MRI was significantly higher inside LRNC than outside: 12.64 ± 0.2737% versus 9.294 ± 0.1762% (mean ± standard error of the mean [SEM]; P < 0.001). The same was true for IPH identified by 3D histology, R2* inside versus outside IPH was: 71.81 ± 1.276 s-1 versus 56.94 ± 0.9095 s-1 (mean ± SEM; P < 0.001). There was a strong correlation between the cumulative fat and the volume of LRNC from 3D histology (R2 = 0.92) as well as between cumulative R2* and IPH (R2 = 0.94). CONCLUSION Quantitative mapping of fat and R2* from Dixon MRI reliably quantifies the extent of LRNC and IPH. Magn Reson Med 78:285-296, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Sandeep Koppal
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Marcel Warntjes
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.,SyntheticMR AB, Linköping, Sweden
| | - Jeremy Swann
- School of Computing, University of Leeds, Leeds, United Kingdom
| | - Petter Dyverfeldt
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Johan Kihlberg
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Department of Radiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Rodrigo Moreno
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,KTH, Royal Institute of Technology, Stockholm, Sweden
| | - Derek Magee
- School of Computing, University of Leeds, Leeds, United Kingdom
| | - Nicholas Roberts
- Division of Brain Sciences, Department of Medicine, Institute of Neurology, Imperial College, London, United Kingdom
| | - Helene Zachrisson
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Claes Forssell
- Department of Thoracic and Vascular Surgery, and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Toste Länne
- Department of Thoracic and Vascular Surgery, and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Darren Treanor
- Department of Pathology and Tumor Biology, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, United Kingdom.,Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Ebo D de Muinck
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
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Mazzoli V, Nederveen AJ, Oudeman J, Sprengers A, Nicolay K, Strijkers GJ, Verdonschot N. Water and fat separation in real-time MRI of joint movement with phase-sensitive bSSFP. Magn Reson Med 2016; 78:58-68. [DOI: 10.1002/mrm.26341] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2016] [Revised: 06/20/2016] [Accepted: 06/20/2016] [Indexed: 01/04/2023]
Affiliation(s)
- Valentina Mazzoli
- Biomedical NMR, Department of Biomedical Engineering; Eindhoven University of Technology; Eindhoven The Netherlands
- Department of Radiology; Academic Medical Center; Amsterdam The Netherlands
- Orthopaedic Research Lab; Radboud University Medical Center; Nijmegen The Netherlands
| | - Aart J. Nederveen
- Department of Radiology; Academic Medical Center; Amsterdam The Netherlands
| | - Jos Oudeman
- Department of Radiology; Academic Medical Center; Amsterdam The Netherlands
| | - Andre Sprengers
- Orthopaedic Research Lab; Radboud University Medical Center; Nijmegen The Netherlands
- Laboratory of Biomechanical Engineering; University of Twente; Enschede The Netherlands
| | - Klaas Nicolay
- Biomedical NMR, Department of Biomedical Engineering; Eindhoven University of Technology; Eindhoven The Netherlands
| | - Gustav J. Strijkers
- Biomedical NMR, Department of Biomedical Engineering; Eindhoven University of Technology; Eindhoven The Netherlands
- Biomedical Engineering and Physics; Academic Medical Center; Amsterdam The Netherlands
| | - Nico Verdonschot
- Orthopaedic Research Lab; Radboud University Medical Center; Nijmegen The Netherlands
- Laboratory of Biomechanical Engineering; University of Twente; Enschede The Netherlands
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Speelman L, Teng Z, Nederveen AJ, van der Lugt A, Gillard JH. MRI-based biomechanical parameters for carotid artery plaque vulnerability assessment. Thromb Haemost 2016; 115:493-500. [PMID: 26791734 DOI: 10.1160/th15-09-0712] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 12/13/2015] [Indexed: 12/18/2022]
Abstract
Carotid atherosclerotic plaques are a major cause of ischaemic stroke. The biomechanical environment to which the arterial wall and plaque is subjected to plays an important role in the initiation, progression and rupture of carotid plaques. MRI is frequently used to characterize the morphology of a carotid plaque, but new developments in MRI enable more functional assessment of carotid plaques. In this review, MRI based biomechanical parameters are evaluated on their current status, clinical applicability, and future developments. Blood flow related biomechanical parameters, including endothelial wall shear stress and oscillatory shear index, have been shown to be related to plaque formation. Deriving these parameters directly from MRI flow measurements is feasible and has great potential for future carotid plaque development prediction. Blood pressure induced stresses in a plaque may exceed the tissue strength, potentially leading to plaque rupture. Multi-contrast MRI based stress calculations in combination with tissue strength assessment based on MRI inflammation imaging may provide a plaque stress-strength balance that can be used to assess the plaque rupture risk potential. Direct plaque strain analysis based on dynamic MRI is already able to identify local plaque displacement during the cardiac cycle. However, clinical evidence linking MRI strain to plaque vulnerability is still lacking. MRI based biomechanical parameters may lead to improved assessment of carotid plaque development and rupture risk. However, better MRI systems and faster sequences are required to improve the spatial and temporal resolution, as well as increase the image contrast and signal-to-noise ratio.
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Affiliation(s)
- Lambert Speelman
- Dr. Lambert Speelman, Department of Biomedical Engineering, Ee 23.38B, P.O Box 2040, 3000 CA Rotterdam, the Netherlands, Tel.: +31 10 70 44039, Fax: +31 10 70 44720, E-mail:
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