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Malhi BS, Moazamian D, Shin SH, Athertya JS, Silva L, Jerban S, Jang H, Chang E, Ma Y, Carl M, Du J. Bi-Exponential 3D UTE-T1ρ Relaxation Mapping of Ex Vivo Human Knee Patellar Tendon at 3T. Bioengineering (Basel) 2024; 11:66. [PMID: 38247943 PMCID: PMC10813751 DOI: 10.3390/bioengineering11010066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/30/2023] [Accepted: 01/03/2024] [Indexed: 01/23/2024] Open
Abstract
Introduction: The objective of this study was to assess the bi-exponential relaxation times and fractions of the short and long components of the human patellar tendon ex vivo using three-dimensional ultrashort echo time T1ρ (3D UTE-T1ρ) imaging. Materials and Methods: Five cadaveric human knee specimens were scanned using a 3D UTE-T1ρ imaging sequence on a 3T MR scanner. A series of 3D UTE-T1ρ images were acquired and fitted using single-component and bi-component models. Single-component exponential fitting was performed to measure the UTE-T1ρ value of the patellar tendon. Bi-component analysis was performed to measure the short and long UTE-T1ρ values and fractions. Results: The single-component analysis showed a mean single-component UTE-T1ρ value of 8.4 ± 1.7 ms for the five knee patellar tendon samples. Improved fitting was achieved with bi-component analysis, which showed a mean short UTE-T1ρ value of 5.5 ± 0.8 ms with a fraction of 77.6 ± 4.8%, and a mean long UTE-T1ρ value of 27.4 ± 3.8 ms with a fraction of 22.4 ± 4.8%. Conclusion: The 3D UTE-T1ρ sequence can detect the single- and bi-exponential decay in the patellar tendon. Bi-component fitting was superior to single-component fitting.
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Affiliation(s)
- Bhavsimran Singh Malhi
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Dina Moazamian
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Soo Hyun Shin
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Jiyo S. Athertya
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Livia Silva
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Saeed Jerban
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Hyungseok Jang
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Eric Chang
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
- Radiology Service, Veterans Affairs San Diego Healthcare System, La Jolla, San Diego, CA 92161, USA
| | - Yajun Ma
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
| | - Michael Carl
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
- General Electric Health Care, San Diego, CA 92037, USA
| | - Jiang Du
- Department of Radiology, University of California, La Jolla, San Diego, CA 92037, USA; (B.S.M.); (D.M.); (S.H.S.); (J.S.A.); (L.S.); (S.J.); (H.J.); (E.C.); (Y.M.); (M.C.)
- Radiology Service, Veterans Affairs San Diego Healthcare System, La Jolla, San Diego, CA 92161, USA
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Deng W, Wang Z, Jia Z, Liu F, Wu J, Yang J, An S, Yu Y, Han Y, Zhao R, Li X. Cardiac T1ρ Mapping Values Affected by Age and Sex in a Healthy Chinese Cohort. J Magn Reson Imaging 2024. [PMID: 38168067 DOI: 10.1002/jmri.29196] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/04/2023] [Accepted: 12/05/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND To facilitate the clinical use of cardiac T1ρ, it is important to understand the impact of age and sex on T1ρ values of the myocardium. PURPOSE To investigate the impact of age and gender on myocardial T1ρ values. STUDY TYPE Cross-sectional. POPULATION Two hundred ten healthy Han Chinese volunteers without cardiovascular risk factors (85 males, mean age 34.4 ± 12.5 years; 125 females, mean age 37.9 ± 14.8 years). FIELD STRENGTH/SEQUENCE 1.5 T; T1ρ-prepared steady-state free precession (T1ρ mapping) sequence. ASSESSMENT Basal, mid, and apical short-axis left ventricular T1ρ maps were acquired. T1ρ maps acquired with spin-lock frequencies of 5 and 400 Hz were subtracted to create a myocardial fibrosis index (mFI) map. T1ρ and mFI values across different age decades, sex, and slice locations were compared. STATISTICAL TESTS Shapiro-Wilk test, Student's t test, Mann-Whitney U test, linear regression analysis, one-way analysis of variance and intraclass correlation coefficient. SIGNIFICANCE P value <0.05. RESULTS Women had significantly higher T1ρ and mFI values than men (50.3 ± 2.0 msec vs. 47.7 ± 2.4 msec and 4.7 ± 1.0 msec vs. 4.3 ± 1.1 msec, respectively). Additionally, in males and females combined, there was a significant positive but weak correlation between T1ρ values and age (r = 0.27), while no correlation was observed between the mFI values and age (P = 0.969). DATA CONCLUSION We report potential reference values for cardiac T1ρ by sex, age distribution, and slice location in a Chinese population. T1ρ was significantly correlated with age and sex, while mFI was only associated with sex. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Wei Deng
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Zhen Wang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Zhuoran Jia
- Department of Cardiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Fang Liu
- Department of Cardiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jian Wu
- Department of Cardiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jinxiu Yang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Shutian An
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Yuchi Han
- Cardiovascular Division, Wexner Medical Center, College of Medicine, The Ohio State University Medical Center, Columbus, Ohio, USA
| | - Ren Zhao
- Department of Cardiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xiaohu Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
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Reynolds LA, Morris SR, Vavasour IM, Barlow L, Laule C, MacKay AL, Michal CA. Nonaqueous magnetization following adiabatic and selective pulses in brain: T1 and cross-relaxation dynamics. NMR IN BIOMEDICINE 2023:e4936. [PMID: 36973767 DOI: 10.1002/nbm.4936] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 03/03/2023] [Accepted: 03/20/2023] [Indexed: 06/18/2023]
Abstract
Inversion pulses are commonly employed in MRI for T 1 $$ {T}_1 $$ -weighted contrast and relaxation measurements. In the brain, it is often assumed that adiabatic pulses saturate the nonaqueous magnetization. We investigated this assumption using solid-state NMR to monitor the nonaqueous signal directly following adiabatic inversion and compared this with signals following hard and soft inversion pulses. The effects of the different preparations on relaxation dynamics were explored. Inversion recovery experiments were performed on ex vivo bovine and porcine brains using 360-MHz (8.4 T) and 200-MHz (4.7 T) NMR spectrometers, respectively, using broadband rectangular, adiabatic, and sinc inversion pulses as well as a long rectangular saturation pulse. Analogous human brain MRI experiments were performed at 3 T using single-slice echo-planar imaging. Relaxation data were fitted by mono- and biexponential decay models. Further fitting analysis was performed using only two inversion delay times. Adiabatic and sinc inversion left much of the nonaqueous magnetization along B 0 $$ {B}_0 $$ and resulted in biexponential relaxation. Saturation of both aqueous and nonaqueous magnetization components led to effectively monoexponential T 1 $$ {T}_1 $$ relaxation. Typical adiabatic inversion pulses do not, as has been widely assumed, saturate the nonaqueous proton magnetization in white matter. Unequal magnetization states in aqueous and nonaqueous 1 H reservoirs prepared by soft and adiabatic pulses result in biexponential T 1 $$ {T}_1 $$ relaxation. Both pools must be prepared in the same magnetization state (e.g., saturated or inverted) in order to observe consistent monoexponential relaxation.
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Affiliation(s)
- Luke A Reynolds
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Sarah R Morris
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, Blusson Spinal Cord Centre, University of British Columbia, Vancouver, BC, Canada
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, Blusson Spinal Cord Centre, University of British Columbia, Vancouver, BC, Canada
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Laura Barlow
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, Blusson Spinal Cord Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Alex L MacKay
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Carl A Michal
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
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Menon RG, Sharafi A, Muccio M, Smith T, Kister I, Ge Y, Regatte RR. Three-dimensional multi-parameter brain mapping using MR fingerprinting. RESEARCH SQUARE 2023:rs.3.rs-2675278. [PMID: 36993561 PMCID: PMC10055680 DOI: 10.21203/rs.3.rs-2675278/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imaging technique capable of quantifying T1, T2 and T1ρ was used. The imaging sequence was tested in standardized phantoms and 3D-MRF brain imaging with multiple shots (1, 2 and 4) in healthy human volunteers and MS patients. Quantitative parametric maps for T1, T2, T1ρ, were generated. Mean gray matter (GM) and white matter (WM) ROIs were compared for each mapping technique, Bland-Altman plots and intra-class correlation coefficient (ICC) were used to assess repeatability and Student T-tests were used to compare results in MS patients. Standardized phantom studies demonstrated excellent agreement with reference T1/T2/T1ρ mapping techniques. This study demonstrates that the 3D-MRF technique is able to simultaneously quantify T1, T2 and T1ρ for tissue property characterization in a clinically feasible scan time. This multi-parametric approach offers increased potential to detect and differentiate brain lesions and to better test imaging biomarker hypotheses for several neurological diseases, including MS.
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Affiliation(s)
| | | | | | - Tyler Smith
- New York University Grossman School of Medicine
| | - Ilya Kister
- New York University Grossman School of Medicine
| | - Yulin Ge
- New York University Grossman School of Medicine
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Menon RG, Zibetti MVW, Regatte RR. Data-driven optimization of sampling patterns for MR brain T 1ρ mapping. Magn Reson Med 2023; 89:205-216. [PMID: 36129110 PMCID: PMC10022748 DOI: 10.1002/mrm.29445] [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: 10/19/2021] [Revised: 08/09/2022] [Accepted: 08/17/2022] [Indexed: 02/05/2023]
Abstract
PURPOSE The goal of this study was to apply a fast data-driven optimization algorithm, called bias-accelerated subset selection, for MR brain T1ρ mapping to generate optimized sampling patterns (SPs) for compressed sensing reconstruction of brain 3D-T1ρ MRI. METHODS Five healthy volunteers were recruited, and fully sampled Cartesian 3D-T1ρ MRIs were obtained. Variable density (VD) and Poisson disc (PD) undersampling was used as the input to SP optimization process. The reconstruction used 3 compressed sensing methods: spatiotemporal finite differences, low-rank plus sparse with spatial finite differences, and low rank. The performance of images and T1ρ maps using PD-SP and VD-SP and their optimized sampling patterns (PD-OSP and VD-OSP) were compared to the fully sampled reference using normalized root mean square error (NRMSE). RESULTS The VD-OSP with spatiotemporal finite differences reconstruction (NRMSE = 0.078) and the PD-OSP with spatiotemporal finite differences reconstruction (NRMSE = 0.079) at the highest acceleration factors (AF = 30) showed the largest improvement compared to the respective nonoptimized SPs (VD NRMSE = 0.087 and PD NRMSE = 0.149). Prospective undersampling was tested at AF = 4, with VD-OSP NRMSE = 0.057 versus PD-OSP NRMSE = 0.060, with optimized sampling performing better that input PD or VD sampling. For brain T1ρ mapping, the VD-OSP with low rank reconstruction for AFs <10 and VD-OSP with spatiotemporal finite differences for AFs >10 perform better. CONCLUSIONS The study demonstrated that the appropriate use of data-driven optimized sampling and suitable compressed sensing reconstruction technique can be employed to potentially accelerate 3D T1ρ mapping for brain imaging applications.
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Affiliation(s)
- Rajiv G Menon
- Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
| | - Marcelo V W Zibetti
- Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
| | - Ravinder R Regatte
- Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
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Normal Values of Magnetic Resonance T
1
ρ
Relaxation Times in the Adult Heart at 1.5 T
MRI. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.28506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/14/2022] [Accepted: 10/14/2022] [Indexed: 11/27/2022] Open
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Menon RG, Raghavan P, Regatte RR. Pilot study quantifying muscle glycosaminoglycan using bi-exponential T 1ρ mapping in patients with muscle stiffness after stroke. Sci Rep 2021; 11:13951. [PMID: 34230600 PMCID: PMC8260636 DOI: 10.1038/s41598-021-93304-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 06/16/2021] [Indexed: 01/14/2023] Open
Abstract
Post stroke muscle stiffness is a common problem, which left untreated can lead to disabling muscle contractures. The purpose of this pilot study was to evaluate the feasibility of bi-exponential T1ρ mapping in patients with arm muscle stiffness after stroke and its ability to measure treatment related changes in muscle glycosaminoglycans (GAGs). Five patients with muscle stiffness after stroke and 5 healthy controls were recruited for imaging of the upper arm with 3D-T1ρ mapping. Patients were scanned before and after treatment with hyaluronidase injections, whereas the controls were scanned once. Wilcoxon Mann-Whitney tests compared patients vs. controls and patients pre-treatment vs. post-treatment. With bi-exponential modeling, the long component, T1ρl was significantly longer in the patients (biceps P = 0.01; triceps P = 0.004) compared to controls. There was also a significant difference in the signal fractions of the long and short components (biceps P = 0.03, triceps P = 0.04). The results suggest that muscle stiffness is characterized by increased muscle free water and GAG content. Post-treatment, the T1ρ parameters shifted toward control values. This pilot study demonstrates the application of bi-exponential T1ρ mapping as a marker for GAG content in muscle and as a potential treatment monitoring tool for patients with muscle stiffness after stroke.
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Affiliation(s)
- Rajiv G Menon
- Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 1st Ave, 4th Floor, New York, NY, 10016, USA.
| | - Preeti Raghavan
- Deparments of Physical Medicine and Rehabilitation and Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Ravinder R Regatte
- Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 1st Ave, 4th Floor, New York, NY, 10016, USA
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Zhu Y, Liu Y, Ying L, Qiu Z, Liu Q, Jia S, Wang H, Peng X, Liu X, Zheng H, Liang D. A 4-minute solution for submillimeter whole-brain T 1ρ quantification. Magn Reson Med 2021; 85:3299-3307. [PMID: 33421224 DOI: 10.1002/mrm.28656] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 12/02/2020] [Accepted: 12/04/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To develop a robust, accurate, and accelerated T1ρ quantification solution for submillimeter in vivo whole-brain imaging. METHODS A multislice T1ρ mapping solution (MS-T1ρ ) was developed based on a two-acquisition scheme using turbo spin echo with RF cycling to allow for whole-brain coverage with 0.8-mm in-plane resolution. A compressed sensing-based fast imaging method, SCOPE, was used to accelerate the MS-T1ρ acquisition time to a total scan time of 3 minutes 31 seconds. A phantom experiment was conducted to assess the accuracy of MS-T1ρ by comparing the T1ρ value obtained using MS-T1ρ with the reference value obtained using the standard single-slice T1ρ mapping method. In vivo scans of 13 volunteers were acquired prospectively to validate the robustness of MS-T1ρ . RESULTS In the phantom study, the T1ρ values obtained with MS-T1ρ were in good agreement with the reference T1ρ values (R2 = 0.9991) and showed high consistency throughout all slices (coefficient of variation = 2.2 ± 2.43%). In the in vivo experiments, T1ρ maps were successfully acquired for all volunteers with no visually noticeable artifacts. There was no significant difference in T1ρ values between MS-T1ρ acquisitions and fully sampled acquisitions for all brain tissues (p-value > .05). In the intraclass correlation coefficient and Bland-Altman analyses, the accelerated T1ρ measurements show moderate to good agreement to the fully sampled reference values. CONCLUSION The proposed MS-T1ρ solution allows for high-resolution whole-brain T1ρ mapping within 4 minutes and may provide a potential tool for investigating neural diseases.
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Affiliation(s)
- Yanjie Zhu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Yuanyuan Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China.,University of Chinese Academy of Sciences, Beijing, 100049, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Leslie Ying
- Department of Biomedical Engineering and Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, New York, 14260, USA
| | - Zhilang Qiu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China.,University of Chinese Academy of Sciences, Beijing, 100049, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Qiegen Liu
- Department of Electronic Information Engineering, Nanchang University, Nanchang, Jiangxi, 330031, China
| | - Sen Jia
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Haifeng Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Xi Peng
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, 55905, USA
| | - Xin Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Dong Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
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Menon RG, Zibetti MVW, Jain R, Ge Y, Regatte RR. Performance Comparison of Compressed Sensing Algorithms for Accelerating T 1ρ Mapping of Human Brain. J Magn Reson Imaging 2020; 53:1130-1139. [PMID: 33190362 DOI: 10.1002/jmri.27421] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 10/15/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND 3D-T1ρ mapping is useful to quantify various neurologic disorders, but data are currently time-consuming to acquire. PURPOSE To compare the performance of five compressed sensing (CS) algorithms-spatiotemporal finite differences (STFD), exponential dictionary (EXP), 3D-wavelet transform (WAV), low-rank (LOW) and low-rank plus sparse model with spatial finite differences (L + S SFD)-for 3D-T1ρ mapping of the human brain with acceleration factors (AFs) of 2, 5, and 10. STUDY TYPE Retrospective. SUBJECTS Eight healthy volunteers underwent T1ρ imaging of the whole brain. FIELD STRENGTH/SEQUENCE The sequence was fully sampled 3D Cartesian ultrafast gradient echo sequence with a customized T1ρ preparation module on a clinical 3T scanner. ASSESSMENT The fully sampled data was undersampled by factors of 2, 5, and 10 and reconstructed with the five CS algorithms. Image reconstruction quality was evaluated and compared to the SENSE reconstruction of the fully sampled data (reference) and T1ρ estimation errors were assessed as a function of AF. STATISTICAL TESTS Normalized root mean squared errors (nRMSE) and median normalized absolute deviation (MNAD) errors were calculated to compare image reconstruction errors and T1ρ estimation errors, respectively. Linear regression plots, Bland-Altman plots, and Pearson correlation coefficients (CC) are shown. RESULTS For image reconstruction quality, at AF = 2, EXP transforms had the lowest mRMSE (1.56%). At higher AF values, STFD performed better, with the smallest errors (3.16% at AF = 5, 4.32% at AF = 10). For whole-brain quantitative T1ρ mapping, at AF = 2, EXP performed best (MNAD error = 1.62%). At higher AF values (AF = 5, 10), the STFD technique had the least errors (2.96% at AF = 5, 4.24% at AF = 10) and the smallest variance from the reference T1ρ estimates. DATA CONCLUSION This study demonstrates the use of different CS algorithms that may be useful in reducing the scan time required to perform volumetric T1ρ mapping of the brain. LEVEL OF EVIDENCE 2. TECHNICAL EFFICACY STAGE 1.
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Affiliation(s)
- Rajiv G Menon
- Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York, USA
| | - Marcelo V W Zibetti
- Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York, USA
| | - Rajan Jain
- Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Department of Neurosurgery, New York University Grossman School of Medicine, New York, New York, USA
| | - Yulin Ge
- Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York, USA
| | - Ravinder R Regatte
- Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York, USA
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Gram M, Seethaler M, Gensler D, Oberberger J, Jakob PM, Nordbeck P. Balanced spin-lock preparation for B 1 -insensitive and B 0 -insensitive quantification of the rotating frame relaxation time T 1ρ. Magn Reson Med 2020; 85:2771-2780. [PMID: 33166009 DOI: 10.1002/mrm.28585] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 09/04/2020] [Accepted: 10/13/2020] [Indexed: 01/04/2023]
Abstract
PURPOSE Accurate and artifact-free T1ρ quantification is still a major challenge due to a susceptibility of the spin-locking module to B0 and/or B1 field inhomogeneities. In this study, we present a novel spin-lock preparation module (B-SL) that enables an almost full compensation of both types of inhomogeneities. METHODS The new B-SL module contains a second 180° refocusing pulse to compensate each pulse in the preparation block by a corresponding pulse with opposite phase. For evaluation and validation of B-SL, extensive simulations as well as phantom measurements were performed. Furthermore, the new module was compared to three common established compensation methods. RESULTS Both simulations and measurements demonstrate a much lower susceptibility to artifacts for the B-SL module, therefore providing an improved accuracy in T1ρ quantification. In the presence of field inhomogeneities, measurements revealed an increased banding compensation by 79% compared with the frequently used composite module. The goodness of the mono-exponential T1ρ fitting procedure was improved by 58%. CONCLUSION The B-SL preparation enables the generation of accurate relaxation maps with significantly reduced artifacts, even in the case of large field imperfections. Therefore, the B-SL module is suggested to be highly beneficial for in vivo T1ρ quantification.
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Affiliation(s)
- Maximilian Gram
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany.,Experimental Physics 5, University of Würzburg, Würzburg, Germany
| | - Michael Seethaler
- Experimental Physics 5, University of Würzburg, Würzburg, Germany.,Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
| | - Daniel Gensler
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany.,Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
| | - Johannes Oberberger
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Peter M Jakob
- Experimental Physics 5, University of Würzburg, Würzburg, Germany
| | - Peter Nordbeck
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany.,Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
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11
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Wang Q, Xiao H, Yu X, Lin H, Yang B, Zhang Y, Feng D, Yan F, Wang H. R1ρ at high spin-lock frequency could be a complementary imaging biomarker for liver iron overload quantification. Magn Reson Imaging 2020; 75:141-148. [PMID: 33129937 DOI: 10.1016/j.mri.2020.10.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 10/25/2020] [Accepted: 10/26/2020] [Indexed: 01/16/2023]
Abstract
PURPOSE To compare the correlations among the R1ρ, R2, and R2* relaxation rates with liver iron concentration (LIC) in the assessment of rat liver iron content and explore the application potential of R1ρ in assessing liver iron content. METHODS Iron dextran (dosage of 0, 25, 50, 100, and 200 mg/kg body weight) was injected into 35 male rats to increase the amount of iron storage in the liver. After one week, all rats were euthanized with isoflurane. A portion of the largest hepatic lobe was extracted to quantify the LIC by inductively coupled plasma, and the remaining liver tissue was stored in 4% buffered paraformaldehyde for 24 h before MRI. Spin-lock preparation with a RARE (rapid acquisition with relaxation enhancement) readout (9 different spin-lock times and 7 different spin-lock frequencies (FSLs)) and multi-echo UTE (ultrashort TE) pulses were developed to quantify R1ρ and R2 * on a Bruker 11.7 T MR system. For comparisons with R1ρ and R2*, R2 was acquired using the CPMG sequence. RESULTS Mean R1ρ values displayed dispersion, with decrease in R1ρ at higher FSLs. Spearman's correlation analysis (two-tailed) indicated that the R1ρ values were significantly associated with LIC at FSL = 2000, 2500, and 3000 Hz (r = 0.365 and P = 0.031, r = 0.608 and P < 0.001, and r = 0.764 and P < 0.001, respectively), and were not significantly associated with LIC at FSL = 500, 1000, 1250, and 1500 Hz (all P > 0.05). R2 and R2* showed significant linear correlations with LIC (r = 0.787 and P < 0.001, and r = 0.859 and P < 0.001, respectively). Correlation analysis across R1ρ, R2, and R* also suggested that the correlation strength between R1ρ and R2 and between R1ρ and R* showed an increasing trend with increase in FSL. CONCLUSION In this study, a strong association was observed between R1ρ and LIC at high FSLs further confirming previous findings. The results demonstrated that R1ρ at high FSL might serve as a complementary imaging biomarker for liver iron overload quantification.
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Affiliation(s)
- Qianfeng Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Hong Xiao
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuchen Yu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Huimin Lin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Baofeng Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yuwen Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Danyang Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.
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12
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Ma S, Wang N, Fan Z, Kaisey M, Sicotte NL, Christodoulou AG, Li D. Three-dimensional whole-brain simultaneous T1, T2, and T1ρ quantification using MR Multitasking: Method and initial clinical experience in tissue characterization of multiple sclerosis. Magn Reson Med 2020; 85:1938-1952. [PMID: 33107126 DOI: 10.1002/mrm.28553] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 09/22/2020] [Accepted: 09/23/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a 3D whole-brain simultaneous T1/T2/T1ρ quantification method with MR Multitasking that provides high quality, co-registered multiparametric maps in 9 min. METHODS MR Multitasking conceptualizes T1/T2/T1ρ relaxations as different time dimensions, simultaneously resolving all three dimensions with a low-rank tensor image model. The proposed method was validated on a phantom and in healthy volunteers, comparing quantitative measurements against corresponding reference methods and evaluating the scan-rescan repeatability. Initial clinical validation was performed in age-matched relapsing-remitting multiple sclerosis (RRMS) patients to examine the feasibility of quantitative tissue characterization and to compare with the healthy control cohort. The feasibility of synthesizing six contrast-weighted images was also examined. RESULTS Our framework produced high quality, co-registered T1/T2/T1ρ maps that closely resemble the reference maps. Multitasking T1/T2/T1ρ measurements showed substantial agreement with reference measurements on the phantom and in healthy controls. Bland-Altman analysis indicated good in vivo repeatability of all three parameters. In RRMS patients, lesions were conspicuously delineated on all three maps and on four synthetic weighted images (T2-weighted, T2-FLAIR, double inversion recovery, and a novel "T1ρ-FLAIR" contrast). T1 and T2 showed significant differences for normal appearing white matter between patients and controls, while T1ρ showed significant differences for normal appearing white matter, cortical gray matter, and deep gray matter. The combination of three parameters significantly improved the differentiation between RRMS patients and healthy controls, compared to using any single parameter alone. CONCLUSION MR Multitasking simultaneously quantifies whole-brain T1/T2/T1ρ and is clinically promising for quantitative tissue characterization of neurological diseases, such as MS.
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Affiliation(s)
- Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Marwa Kaisey
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Anthony G Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
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13
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Johnson CP, Thedens DR, Kruger SJ, Magnotta VA. Three-Dimensional GRE T 1ρ mapping of the brain using tailored variable flip-angle scheduling. Magn Reson Med 2020; 84:1235-1249. [PMID: 32052489 DOI: 10.1002/mrm.28198] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 01/07/2020] [Accepted: 01/13/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE To introduce a new approach called tailored variable flip-angle (VFA) scheduling for SNR-efficient 3D T1ρ mapping of the brain using a magnetization-prepared gradient-echo sequence. METHODS Simulations were used to assess the relative SNR efficiency, quantitative accuracy, and spatial blurring of tailored VFA scheduling for T1ρ mapping of brain tissue compared with magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS), a state-of-the-art technique for accurate 3D gradient-echo T1ρ mapping. Simulations were also used to calculate optimal imaging parameters for tailored VFA scheduling versus MAPSS, without and with nulling of CSF. Four participants were imaged at 3T MRI to demonstrate the feasibility of tailored VFA scheduling for T1ρ mapping of the brain. Using MAPSS as a reference standard, in vivo data were used to validate the relative SNR efficiency and quantitative accuracy of the new approach. RESULTS Tailored VFA scheduling can provide a 2-fold to 4-fold gain in the SNR of the resulting T1ρ map as compared with MAPSS when using identical sequence parameters while limiting T1ρ quantification errors to 2% or less. In vivo whole-brain 3D T1ρ maps acquired with tailored VFA scheduling had superior SNR efficiency than is achievable with MAPSS, and the SNR efficiency improved with a greater number of views per segment. CONCLUSIONS Tailored VFA scheduling is an SNR-efficient GRE technique for 3D T1ρ mapping of the brain that provides increased flexibility in choice of imaging parameters compared with MAPSS, which may benefit a variety of applications.
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Affiliation(s)
- Casey P Johnson
- Veterinary Clinical Sciences Department, University of Minnesota, Saint Paul, MN, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Vincent A Magnotta
- Department of Radiology, University of Iowa, Iowa City, IA, USA.,Department of Psychiatry, University of Iowa, Iowa City, IA, USA.,Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
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14
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Zou L, Zheng H, Liang D, Wang H, Zhu Y, Liu Y, Cheng J, Jia S, Shi C, Su S, Liu X. T1rho Fractional-order Relaxation of Human Articular Cartilage. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:4496-4499. [PMID: 31946864 DOI: 10.1109/embc.2019.8857231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
T1rho imaging is a promising non-invasive diagnostic tool for early detection of articular cartilage degeneration. A mono-exponential model is normally used to describe the T1rho relaxation process. However, mono-exponentials may not adequately to describe NMR relaxation in complex, heterogeneous, and anisotropic materials, such as articular cartilage. Fractional-order models have been used successfully to describe complex relaxation phenomena in the laboratory frame in cartilage matrix components. In this paper, we develop a time-fractional order (T-FACT) model for T1rho fitting in human articular cartilage. Representative results demonstrate that the proposed method is able to fit the experimental data with smaller root mean squared error than the one from conventional mono-exponential relaxation model in human articular cartilage.
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15
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Zhu Y, Liu Y, Ying L, Liu X, Zheng H, Liang D. Bio-SCOPE: fast biexponential T 1ρ mapping of the brain using signal-compensated low-rank plus sparse matrix decomposition. Magn Reson Med 2019; 83:2092-2106. [PMID: 31762102 DOI: 10.1002/mrm.28067] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 09/28/2019] [Accepted: 10/14/2019] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop and evaluate a fast imaging method based on signal-compensated low-rank plus sparse matrix decomposition to accelerate data acquisition for biexponential brain T1ρ mapping (Bio-SCOPE). METHODS Two novel strategies were proposed to improve reconstruction performance. A variable-rate undersampling scheme was used with a varied acceleration factor for each k-space along the spin-lock time direction, and a modified nonlinear thresholding scheme combined with a feature descriptor was used for Bio-SCOPE reconstruction. In vivo brain T1ρ mappings were acquired from 4 volunteers. The fully sampled k-space data acquired from 3 volunteers were retrospectively undersampled by net acceleration rates (R) of 4.6 and 6.1. Reference values were obtained from the fully sampled data. The agreement between the accelerated T1ρ measurements and reference values was assessed with Bland-Altman analyses. Prospectively undersampled data with R = 4.6 and R = 6.1 were acquired from 1 volunteer. RESULTS T1ρ -weighted images were successfully reconstructed using Bio-SCOPE for R = 4.6 and 6.1 with signal-to-noise ratio variations <1 dB and normalized root mean square errors <4%. Accelerated and reference T1ρ measurements were in good agreement for R = 4.6 (T1ρ s : 18.6651 ± 1.7786 ms; T1ρ l : 88.9603 ± 1.7331 ms) and R = 6.1 (T1ρ s : 17.8403 ± 3.3302 ms; T1ρ l : 88.0275 ± 4.9606 ms) in the Bland-Altman analyses. T1ρ parameter maps from prospectively undersampled data also show reasonable image quality using the Bio-SCOPE method. CONCLUSION Bio-SCOPE achieves a high net acceleration rate for biexponential T1ρ mapping and improves reconstruction quality by using a variable-rate undersampling data acquisition scheme and a modified soft-thresholding algorithm in image reconstruction.
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Affiliation(s)
- Yanjie Zhu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yuanyuan Liu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Leslie Ying
- Department of Biomedical Engineering and Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, New York
| | - Xin Liu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Dong Liang
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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