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Guimarães J, de Almeida J, Mendes PL, Ferreira MJ, Gonçalves L. Advancements in non-invasive imaging of atherosclerosis: Future perspectives. J Clin Lipidol 2024; 18:e142-e152. [PMID: 38142178 DOI: 10.1016/j.jacl.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 11/11/2023] [Accepted: 11/14/2023] [Indexed: 12/25/2023]
Abstract
Atherosclerosis is a chronic inflammatory disease characterized by the buildup of plaques in arterial walls, leading to cardiovascular diseases and high morbidity and mortality rates worldwide. Non-invasive imaging techniques play a crucial role in evaluating patients with suspected or established atherosclerosis. However, there is a growing body of evidence suggesting the need to visualize the underlying processes of plaque progression and rupture to enhance risk stratification. This review explores recent advancements in non-invasive assessment of atherosclerosis, focusing on computed tomography, magnetic resonance imaging, and nuclear imaging. These advancements provide valuable insights into the assessment and management of atherosclerosis, potentially leading to better risk stratification and improved patient outcomes.
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Affiliation(s)
- Joana Guimarães
- Cardiology Department, Coimbra's Hospital and University Center, Praceta Mota Pinto, 3000-561 Coimbra, Portugal.
| | - José de Almeida
- Cardiology Department, Coimbra's Hospital and University Center, Praceta Mota Pinto, 3000-561 Coimbra, Portugal
| | - Paulo Lázaro Mendes
- Cardiology Department, Coimbra's Hospital and University Center, Praceta Mota Pinto, 3000-561 Coimbra, Portugal
| | - Maria João Ferreira
- Cardiology Department, Coimbra's Hospital and University Center, Praceta Mota Pinto, 3000-561 Coimbra, Portugal; Faculty of Medicine, Coimbra's University, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal
| | - Lino Gonçalves
- Cardiology Department, Coimbra's Hospital and University Center, Praceta Mota Pinto, 3000-561 Coimbra, Portugal; Faculty of Medicine, Coimbra's University, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal
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Peng P, Yue X, Tang L, Wu X, Deng Q, Wu T, Cai L, Liu Q, Xu J, Huang X, Chen Y, Diao K, Sun J. Feasibility of Free-Breathing, Non-ECG-Gated, Black-Blood Cine Magnetic Resonance Images With Multitasking in Measuring Left Ventricular Function Indices. Korean J Radiol 2023; 24:1221-1231. [PMID: 38016681 DOI: 10.3348/kjr.2023.0377] [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: 01/18/2023] [Revised: 09/21/2023] [Accepted: 09/25/2023] [Indexed: 11/30/2023] Open
Abstract
OBJECTIVE To clinically validate the feasibility and accuracy of cine images acquired through the multitasking method, with no electrocardiogram gating and free-breathing, in measuring left ventricular (LV) function indices by comparing them with those acquired through the balanced steady-state free precession (bSSFP) method, with multiple breath-holds and electrocardiogram gating. MATERIALS AND METHODS Forty-three healthy volunteers (female:male, 30:13; mean age, 23.1 ± 2.3 years) and 36 patients requiring an assessment of LV function for various clinical indications (female:male, 22:14; 57.8 ± 11.3 years) were enrolled in this prospective study. Each participant underwent cardiac magnetic resonance imaging (MRI) using the multiple breath-hold bSSFP method and free-breathing multitasking method. LV function parameters were measured for both MRI methods. Image quality was assessed through subjective image quality scores (1 to 5) and calculation of the contrast-to-noise ratio (CNR) between the myocardium and blood pool. Differences between the two MRI methods were analyzed using the Bland-Altman plot, paired t-test, or Wilcoxon signed-rank test, as appropriate. RESULTS LV ejection fraction (LVEF) was not significantly different between the two MRI methods (P = 0.222 in healthy volunteers and P = 0.343 in patients). LV end-diastolic mass was slightly overestimated with multitasking in both healthy volunteers (multitasking vs. bSSFP, 60.5 ± 10.7 g vs. 58.0 ± 10.4 g, respectively; P < 0.001) and patients (69.4 ± 18.1 g vs. 66.8 ± 18.0 g, respectively; P = 0.003). Acceptable and comparable image quality was achieved for both MRI methods (multitasking vs. bSSFP, 4.5 ± 0.7 vs. 4.6 ± 0.6, respectively; P = 0.203). The CNR between the myocardium and blood pool showed no significant differences between the two MRI methods (18.89 ± 6.65 vs. 18.19 ± 5.83, respectively; P = 0.480). CONCLUSION Multitasking-derived cine images obtained without electrocardiogram gating and breath-holding achieved similar image quality and accurate quantification of LVEF in healthy volunteers and patients.
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Affiliation(s)
- Pengfei Peng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xun Yue
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lu Tang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xi Wu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiao Deng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tao Wu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lei Cai
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qi Liu
- UIH America, Inc., Houston, TX, USA
| | - Jian Xu
- UIH America, Inc., Houston, TX, USA
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Yucheng Chen
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kaiyue Diao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Jiayu Sun
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Zhou A, Leach JR, Zhu C, Dong H, Jiang F, Lee YJ, Iannuzzi J, Gasper W, Saloner D, Hope MD, Mitsouras D. Dynamic Contrast-Enhanced MRI in Abdominal Aortic Aneurysms as a Potential Marker for Disease Progression. J Magn Reson Imaging 2023; 58:1258-1267. [PMID: 36747321 DOI: 10.1002/jmri.28640] [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: 05/20/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Abdominal aortic aneurysms (AAAs) may rupture before reaching maximum diameter (Dmax ) thresholds for repair. Aortic wall microvasculature has been associated with elastin content and rupture sites in specimens, but its relation to progression is unknown. PURPOSE To investigate whether dynamic contrast-enhanced (DCE) MRI of AAA is associated with Dmax or growth. STUDY TYPE Prospective. POPULATION A total of 27 male patients with infrarenal AAA (mean age ± standard deviation = 75 ± 5 years) under surveillance with DCE MRI and 2 years of prior follow-up intervals with computed tomography (CT) or MRI. FIELD STRENGTH/SEQUENCE A 3-T, dynamic three-dimensional (3D) fast gradient-echo stack-of-stars volumetric interpolated breath-hold examination (Star-VIBE). ASSESSMENT Wall voxels were manually segmented in two consecutive slices at the level of Dmax . We measured slope to 1-minute and area under the curve (AUC) to 1 minute and 4 minutes of the signal intensity change postcontrast relative to that precontrast arrival, and, Ktrans , a measure of microvascular permeability, using the Patlak model. These were averaged over all wall voxels for association to Dmax and growth rate, and, over left/right and anterior/posterior quadrants for testing circumferential homogeneity. Dmax was measured orthogonal to the aortic centerline and growth rate was calculated by linear fit of Dmax measurements. STATISTICAL TESTS Pearson correlation and linear mixed effects models. A P value <0.05 was considered statistically significant. RESULTS In 44 DCE MRIs, mean Dmax was 45 ± 7 mm and growth rate in 1.5 ± 0.4 years of prior follow-up was 1.7 ± 1.2 mm per year. DCE measurements correlated with each other (Pearson r = 0.39-0.99) and significantly differed between anterior/posterior versus left/right quadrants. DCE measurements were not significantly associated with Dmax (P = 0.084, 0.289, 0.054 and 0.255 for slope, AUC at 1 minute and 4 minutes, and Ktrans , respectively). Slope and 4 minutes AUC significantly associated with growth rate after controlling for Dmax . CONCLUSION Contrast uptake may be increased in lateral aspects of the AAA. Contrast enhancement 1-minute slope and 4-minutes AUC may be associated with a period of recent AAA growth that is independent of Dmax . EVIDENCE LEVEL 3. TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Ang Zhou
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Joseph R Leach
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Chengcheng Zhu
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | - Huiming Dong
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Fei Jiang
- Department of Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Yoo Jin Lee
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - James Iannuzzi
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
- Department of Surgery, University of California San Francisco, San Francisco, California, USA
| | - Warren Gasper
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
- Department of Surgery, University of California San Francisco, San Francisco, California, USA
| | - David Saloner
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Michael D Hope
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Dimitrios Mitsouras
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
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Wu C, Wang N, Gaddam S, Wang L, Han H, Sung K, Christodoulou AG, Xie Y, Pandol S, Li D. Retrospective quantification of clinical abdominal DCE-MRI using pharmacokinetics-informed deep learning: a proof-of-concept study. FRONTIERS IN RADIOLOGY 2023; 3:1168901. [PMID: 37731600 PMCID: PMC10507354 DOI: 10.3389/fradi.2023.1168901] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/24/2023] [Indexed: 09/22/2023]
Abstract
Introduction Dynamic contrast-enhanced (DCE) MRI has important clinical value for early detection, accurate staging, and therapeutic monitoring of cancers. However, conventional multi-phasic abdominal DCE-MRI has limited temporal resolution and provides qualitative or semi-quantitative assessments of tissue vascularity. In this study, the feasibility of retrospectively quantifying multi-phasic abdominal DCE-MRI by using pharmacokinetics-informed deep learning to improve temporal resolution was investigated. Method Forty-five subjects consisting of healthy controls, pancreatic ductal adenocarcinoma (PDAC), and chronic pancreatitis (CP) were imaged with a 2-s temporal-resolution quantitative DCE sequence, from which 30-s temporal-resolution multi-phasic DCE-MRI was synthesized based on clinical protocol. A pharmacokinetics-informed neural network was trained to improve the temporal resolution of the multi-phasic DCE before the quantification of pharmacokinetic parameters. Through ten-fold cross-validation, the agreement between pharmacokinetic parameters estimated from synthesized multi-phasic DCE after deep learning inference was assessed against reference parameters from the corresponding quantitative DCE-MRI images. The ability of the deep learning estimated parameters to differentiate abnormal from normal tissues was assessed as well. Results The pharmacokinetic parameters estimated after deep learning have a high level of agreement with the reference values. In the cross-validation, all three pharmacokinetic parameters (transfer constant K trans , fractional extravascular extracellular volume v e , and rate constant k ep ) achieved intraclass correlation coefficient and R2 between 0.84-0.94, and low coefficients of variation (10.1%, 12.3%, and 5.6%, respectively) relative to the reference values. Significant differences were found between healthy pancreas, PDAC tumor and non-tumor, and CP pancreas. Discussion Retrospective quantification (RoQ) of clinical multi-phasic DCE-MRI is possible by deep learning. This technique has the potential to derive quantitative pharmacokinetic parameters from clinical multi-phasic DCE data for a more objective and precise assessment of cancer.
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Affiliation(s)
- Chaowei Wu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Radiology Department, Stanford University, Stanford, CA, United States
| | - Srinivas Gaddam
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Lixia Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Kyunghyun Sung
- Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Stephen Pandol
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States
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Wang N, Gaddam S, Xie Y, Christodoulou AG, Wu C, Ma S, Fan Z, Wang L, Lo S, Hendifar AE, Pandol SJ, Li D. Multitasking dynamic contrast enhanced magnetic resonance imaging can accurately differentiate chronic pancreatitis from pancreatic ductal adenocarcinoma. Front Oncol 2023; 12:1007134. [PMID: 36686811 PMCID: PMC9853434 DOI: 10.3389/fonc.2022.1007134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 11/16/2022] [Indexed: 01/08/2023] Open
Abstract
Background and aims Accurate differentiation of chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) is an area of unmet clinical need. In this study, a novel Multitasking dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) technique was used to quantitatively evaluate the microcirculation properties of pancreas in CP and PDAC and differentiate between them. Methods The Multitasking DCE technique was able to acquire one 3D image per second during the passage of MRI contrast agent, allowing the quantitative estimation of microcirculation properties of tissue, including blood flow Fp, plasma volume fraction vp, transfer constant Ktrans, and extravascular extracellular volume fraction ve. Receiver operating characteristic (ROC) analysis was performed to differentiate the CP pancreas, PDAC pancreas, normal control pancreas, PDAC tumor, PDAC upstream, and PDAC downstream. ROCs from quantitative analysis and conventional analysis were compared. Results Fourteen PDAC patients, 8 CP patients and 20 healthy subjects were prospectively recruited. The combination of Fp, vp, Ktrans, and ve can differentiate CP versus PDAC pancreas with good AUC (AUC [95% CI] = 0.821 [0.654 - 0.988]), CP versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), PDAC pancreas versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC tumor with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC downstream with excellent AUC (0.917 [0.795 - 1.000]), and CP versus PDAC upstream with fair AUC (0.722 [0.465 - 0.980]). This quantitative analysis outperformed conventional analysis in differentiation of each pair. Conclusion Multitasking DCE MRI is a promising clinical tool that is capable of unbiased quantitative differentiation between CP from PDAC.
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Affiliation(s)
- Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Srinivas Gaddam
- The Karsh Division of Gastroenterology and Hepatology, Cedars Sinai Medical Center, Los Angeles, CA, United States
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States,Bioengineering Department, University of California, Los Angeles, Los Angeles, CA, United States
| | - Chaowei Wu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States,Bioengineering Department, University of California, Los Angeles, Los Angeles, CA, United States
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States,Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, Los Angeles, CA, United States
| | - Lixia Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Simon Lo
- The Karsh Division of Gastroenterology and Hepatology, Cedars Sinai Medical Center, Los Angeles, CA, United States
| | - Andrew E. Hendifar
- Samuel Oschin Comprehensive Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Stephen J. Pandol
- The Karsh Division of Gastroenterology and Hepatology, Cedars Sinai Medical Center, Los Angeles, CA, United States
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States,Bioengineering Department, University of California, Los Angeles, Los Angeles, CA, United States,*Correspondence: Debiao Li,
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Calcagno C, David JA, Motaal AG, Coolen BF, Beldman T, Corbin A, Kak A, Ramachandran S, Pruzan A, Sridhar A, Soler R, Faries CM, Fayad ZA, Mulder WJM, Strijkers GJ. Self-gated, dynamic contrast-enhanced magnetic resonance imaging with compressed-sensing reconstruction for evaluating endothelial permeability in the aortic root of atherosclerotic mice. NMR IN BIOMEDICINE 2023; 36:e4823. [PMID: 36031706 PMCID: PMC10078106 DOI: 10.1002/nbm.4823] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 08/01/2022] [Accepted: 08/21/2022] [Indexed: 05/16/2023]
Abstract
High-risk atherosclerotic plaques are characterized by active inflammation and abundant leaky microvessels. We present a self-gated, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition with compressed sensing reconstruction and apply it to assess longitudinal changes in endothelial permeability in the aortic root of Apoe-/- atherosclerotic mice during natural disease progression. Twenty-four, 8-week-old, female Apoe-/- mice were divided into four groups (n = 6 each) and imaged with self-gated DCE-MRI at 4, 8, 12, and 16 weeks after high-fat diet initiation, and then euthanized for CD68 immunohistochemistry for macrophages. Eight additional mice were kept on a high-fat diet and imaged longitudinally at the same time points. Aortic-root pseudo-concentration curves were analyzed using a validated piecewise linear model. Contrast agent wash-in and washout slopes (b1 and b2 ) were measured as surrogates of aortic root endothelial permeability and compared with macrophage density by immunohistochemistry. b2 , indicating contrast agent washout, was significantly higher in mice kept on an high-fat diet for longer periods of time (p = 0.03). Group comparison revealed significant differences between mice on a high-fat diet for 4 versus 16 weeks (p = 0.03). Macrophage density also significantly increased with diet duration (p = 0.009). Spearman correlation between b2 from DCE-MRI and macrophage density indicated a weak relationship between the two parameters (r = 0.28, p = 0.20). Validated piecewise linear modeling of the DCE-MRI data showed that the aortic root contrast agent washout rate is significantly different during disease progression. Further development of this technique from a single-slice to a 3D acquisition may enable better investigation of the relationship between in vivo imaging of endothelial permeability and atherosclerotic plaques' genetic, molecular, and cellular makeup in this important model of disease.
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Affiliation(s)
- Claudia Calcagno
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - John A. David
- Amsterdam University Medical Centers, Department of Medical Biochemistry, Amsterdam Cardiovascular SciencesUniversity of AmsterdamAmsterdamThe Netherlands
| | - Abdallah G. Motaal
- Siemens Healthineers, Cardiovascular Care Group, Advanced Therapies BusinessErlangenGermany
| | - Bram F. Coolen
- Amsterdam University Medical Centers, Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular SciencesUniversity of AmsterdamAmsterdamThe Netherlands
| | - Thijs Beldman
- Department of Internal MedicineRadboud University Medical CenterNijmegenThe Netherlands
- Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Alexandra Corbin
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Arnav Kak
- University of Texas Southwestern Medical CenterDallasTXUSA
| | - Sarayu Ramachandran
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Alison Pruzan
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Arthi Sridhar
- Department of Hematology/OncologyUTHealth McGovern Medical SchoolHoustonTXUSA
| | - Raphael Soler
- CNRS, CRMBMMarseilleFrance
- Department of Vascular and Endovascular SurgeryHôpital Universitaire de la Timone, APHMMarseilleFrance
| | - Christopher M. Faries
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Zahi A. Fayad
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Willem J. M. Mulder
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Internal MedicineRadboud University Medical CenterNijmegenThe Netherlands
- Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Gustav J. Strijkers
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Amsterdam University Medical Centers, Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular SciencesUniversity of AmsterdamAmsterdamThe Netherlands
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Hu Z, Christodoulou AG, Wang N, Xie Y, Shiroishi MS, Yang W, Zada G, Chow FE, Margol AS, Tamrazi B, Chang EL, Li D, Fan Z. MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE): Simultaneous quantification of permeability and leakage-insensitive perfusion by dynamic T 1 / T 2 * mapping. Magn Reson Med 2023; 89:161-176. [PMID: 36128892 PMCID: PMC9826278 DOI: 10.1002/mrm.29431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 07/16/2022] [Accepted: 08/10/2022] [Indexed: 01/26/2023]
Abstract
PURPOSE To develop an MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) technique for simultaneous quantification of permeability and leakage-insensitive perfusion with a single-dose contrast injection. METHODS MT-DICE builds on a saturation-recovery prepared multi-echo fast low-angle shot sequence. The k-space is randomly sampled for 7.6 min, with single-dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole-brain coverage, a saturation-recovery time dimension, and a TE dimension for dynamicT 1 $$ {\mathrm{T}}_1 $$ andT 2 * $$ {\mathrm{T}}_2^{\ast } $$ quantification, respectively, and a contrast dynamics dimension for capturing contrast kinetics. The derived pixel-wiseT 1 / T 2 * $$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ time series are converted into contrast concentration-time curves for calculation of kinetic metrics. The technique was assessed for its agreement with reference methods inT 1 $$ {\mathrm{T}}_1 $$ andT 2 * $$ {\mathrm{T}}_2^{\ast } $$ measurements in eight healthy subjects and, in three of them, inter-session repeatability of permeability and leakage-insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors. RESULTS MT-DICET 1 / T 2 * $$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter ). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range. CONCLUSION Based on dynamicT 1 / T 2 * $$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ mapping, MT-DICE allows for simultaneous quantification of permeability and leakage-insensitive perfusion metrics with a single-dose contrast injection.
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Affiliation(s)
- Zhehao Hu
- Department of RadiologyUniversity of Southern California
Los AngelesCaliforniaUSA
- Biomedical Imaging Research InstituteCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
- Department of BioengineeringUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Anthony G. Christodoulou
- Biomedical Imaging Research InstituteCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
- Department of BioengineeringUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Nan Wang
- Biomedical Imaging Research InstituteCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Yibin Xie
- Biomedical Imaging Research InstituteCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Mark S. Shiroishi
- Department of RadiologyUniversity of Southern California
Los AngelesCaliforniaUSA
| | - Wensha Yang
- Department of Radiation OncologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Gabriel Zada
- Department of NeurosurgeryUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Frances E. Chow
- Department of NeurosurgeryUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Ashley S. Margol
- Department of Neuro‐oncologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Benita Tamrazi
- Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Eric L. Chang
- Department of Radiation OncologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Debiao Li
- Biomedical Imaging Research InstituteCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
- Department of BioengineeringUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Zhaoyang Fan
- Department of RadiologyUniversity of Southern California
Los AngelesCaliforniaUSA
- Biomedical Imaging Research InstituteCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
- Department of Radiation OncologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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8
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Wang Y, Liu X, Wang Y, Qi H, Liu X, Kong X, Zhang Q, Dou J, Wang J, Chen H. Optimization of the Contrast Agent Injection Protocol for Carotid Artery Dynamic Contrast-Enhanced Magnetic Resonance Imaging. J Magn Reson Imaging 2022; 56:1372-1381. [PMID: 35324034 DOI: 10.1002/jmri.28175] [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: 02/11/2022] [Accepted: 03/11/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The injection protocol used in previous carotid artery dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies varied. PURPOSE To investigate the effect of contrast injection protocol and optimize this protocol for carotid artery DCE-MRI. STUDY TYPE Prospective. SUBJECTS Digital phantom and seven patients with carotid atherosclerosis. FIELD STRENGTH/SEQUENCE 3 T, spoiled gradient recalled echo sequence. ASSESSMENT Different injection doses (0.01-0.3 mmol/kg) and effective injection rates (0.01-1 mmol/sec) were tested using a digital carotid plaque phantom considering the contrast pharmacokinetics, DCE-MRI imaging, contrast variation and flow-related imaging artifacts, random time delay between the contrast injection and image acquisition, and pharmacokinetic analysis process. For each injection protocol, combining the root mean square relative error (RMSRE) of the measured K trans and v P maps within the adventitial vasa vasorum from 10 tested time delays by the root mean square produced RMSREoverall-vv which was used to measure the overall accuracy of the pharmacokinetic parameters. In vivo validation was performed on seven patients with carotid atherosclerosis by imaging them twice using the traditional commonly used protocol and the recommended protocol found by simulation. STATISTICAL TEST Student's t-test, chi-square test, and paired t-test, P < 0.05 was considered statistically significant. RESULTS A low region of RMSREoverall-vv with the combination of medium injection dose and low effective injection rate was found. The protocol with injection dose of 0.07 mmol/kg and effective injection rate of 0.06 mmol/sec achieved the minimal RMSREoverall-vv (4.29%), thus was recommended, which showed more accurate arterial input function. Coinciding with the simulation results, this recommended protocol in in vivo experiments produced significantly fewer image artifacts, lower K trans and v P (P all <0.05) than traditional protocol which overestimated these parameters in simulation. DATA CONCLUSION The contrast injection protocol influenced the accuracy of the pharmacokinetics parameter estimation in carotid artery DCE-MRI. The injection protocol with injection dose of 0.07 mmol/kg and effective injection rate of 0.06 mmol/sec was recommended. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yajie Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaoming Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei, China
| | | | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Xian Liu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiangchuang Kong
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei, China
| | - Qiang Zhang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Jiaqi Dou
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Jing Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
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9
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Ma L, Wu J, Yang Q, Zhou Z, He H, Bao J, Bao L, Wang X, Zhang P, Zhong J, Cai C, Cai S, Chen Z. Single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MOLED) imaging. Neuroimage 2022; 263:119645. [PMID: 36155244 DOI: 10.1016/j.neuroimage.2022.119645] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 09/21/2022] [Accepted: 09/21/2022] [Indexed: 11/29/2022] Open
Abstract
Multi-parametric quantitative magnetic resonance imaging (mqMRI) allows the characterization of multiple tissue properties non-invasively and has shown great potential to enhance the sensitivity of MRI measurements. However, real-time mqMRI during dynamic physiological processes or general motions remains challenging. To overcome this bottleneck, we propose a novel mqMRI technique based on multiple overlapping-echo detachment (MOLED) imaging, termed MQMOLED, to enable mqMRI in a single shot. In the data acquisition of MQMOLED, multiple MR echo signals with different multi-parametric weightings and phase modulations are generated and acquired in the same k-space. The k-space data is Fourier transformed and fed into a well-trained neural network for the reconstruction of multi-parametric maps. We demonstrated the accuracy and repeatability of MQMOLED in simultaneous mapping apparent proton density (APD) and any two parameters among T2, T2*, and apparent diffusion coefficient (ADC) in 130-170 ms. The abundant information delivered by the multiple overlapping-echo signals in MQMOLED makes the technique potentially robust to system imperfections, such as inhomogeneity of static magnetic field or radiofrequency field. Benefitting from the single-shot feature, MQMOLED exhibits a strong motion tolerance to the continuous movements of subjects. For the first time, it captured the synchronous changes of ADC, T2, and T1-weighted APD in contrast-enhanced perfusion imaging on patients with brain tumors, providing additional information about vascular density to the hemodynamic parametric maps. We expect that MQMOLED would promote the development of mqMRI technology and greatly benefit the applications of mqMRI, including therapeutics and analysis of metabolic/functional processes.
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Affiliation(s)
- Lingceng Ma
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jian Wu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Qinqin Yang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Zihan Zhou
- The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China
| | - Hongjian He
- The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China
| | - Jianfeng Bao
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Lijun Bao
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Xiaoyin Wang
- The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China
| | - Pujie Zhang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jianhui Zhong
- The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China; Department of Imaging Sciences, University of Rochester, Rochester, NY 14642, USA
| | - Congbo Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
| | - Zhong Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
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10
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Cao T, Ma S, Wang N, Gharabaghi S, Xie Y, Fan Z, Hogg E, Wu C, Han F, Tagliati M, Haacke EM, Christodoulou AG, Li D. Three-dimensional simultaneous brain mapping of T1, T2, T2∗ and magnetic susceptibility with MR Multitasking. Magn Reson Med 2022; 87:1375-1389. [PMID: 34708438 PMCID: PMC8776611 DOI: 10.1002/mrm.29059] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 09/08/2021] [Accepted: 10/07/2021] [Indexed: 01/24/2023]
Abstract
PURPOSE To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T 2 ∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan. METHODS The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T 2 ∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined. RESULTS High quality, co-registered T1 , T2 , and T 2 ∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T 2 ∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images. CONCLUSION The MR Multitasking-based 3D brain mapping of T1 , T2 , T 2 ∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.
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Affiliation(s)
- Tianle Cao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Sara Gharabaghi
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Elliot Hogg
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Chaowei Wu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Fei Han
- Siemens Medical Solutions USA, Inc., Los Angeles, California, USA
| | - Michele Tagliati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - E. Mark Haacke
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA
- The MRI Institute for Biomedical Research, Bingham Farms, MI, 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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11
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Malmberg MA, Odéen H, Parker DL. Effects of T 2 * on accuracy and precision of dynamic T 1 measurements using the single reference variable flip angle method - a simulation study. Med Phys 2022; 49:2396-2412. [PMID: 35066898 PMCID: PMC9007881 DOI: 10.1002/mp.15476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 01/05/2021] [Accepted: 01/07/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To study in simulation and in theory the accuracy and precision of dynamic T1 measurements obtained using the previously published single-reference variable flip angle (SR-VFA) technique, with a focus on the effects of dynamic changes in T2 * on the calculation. METHODS Monte Carlo simulations were performed over 1000 noisy iterations for the VFA method, the SR-VFA method, and a proposed method, SR-VFA with a T2 * correction (SR-VFA-T2 *). Dynamic T1 estimates were calculated analytically for each method, with signals modeled by the steady-state spoiled gradient echo equation. The mean and standard deviation of these estimates were calculated and compared to truth, while varying repetition time (TR), baseline and dynamic T1 , echo time (TE), baseline and dynamic T2 *, flip angles, and the number of averages on baseline scans. Additionally, the variance of T1 in the SR-VFA and SR-VFA-T2 * methods was derived analytically based on the theory of propagation of errors. This equation was used to produce an inverse-variance weighted linear combination to improve T1 mapping precision in the SR-VFA-T2 * method. Flip angle sensitivity of dynamic T1 precision in the SR-VFA and SR-VFA-T2 * methods was also performed. RESULTS Substantial bias can be produced by the SR-VFA method when the ratio of the T2 * decay of the dynamic signal versus that of the baseline signals deviates from 1, with a 0.01 deviation leading to approximately a 1% bias in cases of high SNR and TR ≫ T1 . This bias can be corrected by estimating the baseline and dynamic T2 * values in this ratio via multi-echo measurements. The bias and precision of the SR-VFA-T2 * method, when normalized to scan time, is found to rival and sometimes improve upon the two flip angle VFA method when an inverse variance weighted linear combination is applied across its multi-echo T1 maps. The analytic variance equation presented is found to be accurate within 1% relative to the Monte Carlo simulations over a broad parameter space. Flip angle ranges that maximize SR-VFA and SR-VFA-T2 * T1 precision over a broad parameter space are given, and each is defined relative to TR and T1 . CONCLUSIONS Multi-echo SR-VFA-T2 * T1 mapping is found in simulation and theory to be a promising alternative to the VFA method that maintains speed of the SR-VFA method with accuracy and precision similar to the VFA method. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Michael A Malmberg
- Department of Bioengineering, University of Utah, Salt Lake City, UT, USA.,Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Henrik Odéen
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Dennis L Parker
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
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12
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Ma S, Wang N, Xie Y, Fan Z, Li D, Christodoulou AG. Motion-robust quantitative multiparametric brain MRI with motion-resolved MR multitasking. Magn Reson Med 2022; 87:102-119. [PMID: 34398991 PMCID: PMC8616852 DOI: 10.1002/mrm.28959] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 06/30/2021] [Accepted: 07/20/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE To address head motion in brain MRI with a novel motion-resolved imaging framework, with application to motion-robust quantitative multiparametric mapping. METHODS MR multitasking conceptualizes the underlying multiparametric image in the presence of motion as a multidimensional low-rank tensor. By incorporating a motion-state dimension into the parameter dimensions and introducing unsupervised motion-state binning and outlier motion reweighting mechanisms, the brain motion can be readily resolved for motion-robust quantitative imaging. A numerical motion phantom was used to simulate different discrete and periodic motion patterns under various translational and rotational scenarios, as well as investigate the sensitivity to exceptionally small and large displacements. In vivo brain MRI was performed to also evaluate different real discrete and periodic motion patterns. The effectiveness of motion-resolved imaging for simultaneous T1 /T2 /T1ρ mapping in the brain was investigated. RESULTS For all 14 simulation scenarios of small, intermediate, and large motion displacements, the motion-resolved approach produced T1 /T2 /T1ρ maps with less absolute difference errors against the ground truth, lower RMSE, and higher structural similarity index measure of T1 /T2 /T1ρ measurements compared to motion removal, and no motion handling. For in vivo experiments, the motion-resolved approach produced T1 /T2 /T1ρ maps with the best image quality free from motion artifacts under random discrete motion, tremor, periodic shaking, and nodding patterns compared to motion removal and no motion handling. The proposed method also yielded T1 /T2 /T1ρ measurement distributions closest to the motion-free reference, with minimal measurement bias and variance. CONCLUSION Motion-resolved quantitative brain imaging is achieved with multitasking, which is generalizable to various head motion patterns without explicit need for registration-based motion correction.
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Affiliation(s)
- Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA,Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA,Corresponding author: Anthony G. Christodoulou, 8700 Beverly Blvd, PACT 400, Los Angeles, CA 90048, , phone: 3104236754
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13
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Pelled G, Salas MM, Han P, Gill HE, Lautenschlager KA, Lai TT, Shawver CM, Hoch MB, Goff BJ, Betts AM, Zhou Z, Lynch C, Schroeder G, Bez M, Maya MM, Bresee C, Gazit Z, McCallin JP, Gazit D, Li D. Intradiscal quantitative chemical exchange saturation transfer MRI signal correlates with discogenic pain in human patients. Sci Rep 2021; 11:19195. [PMID: 34584114 PMCID: PMC8478892 DOI: 10.1038/s41598-021-97672-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 08/22/2021] [Indexed: 12/13/2022] Open
Abstract
Low back pain (LBP) is often a result of a degenerative process in the intervertebral disc. The precise origin of discogenic pain is diagnosed by the invasive procedure of provocative discography (PD). Previously, we developed quantitative chemical exchange saturation transfer (qCEST) magnetic resonance imaging (MRI) to detect pH as a biomarker for discogenic pain. Based on these findings we initiated a clinical study with the goal to evaluate the correlation between qCEST values and PD results in LBP patients. Twenty five volunteers with chronic low back pain were subjected to T2-weighted (T2w) and qCEST MRI scans followed by PD. A total of 72 discs were analyzed. The average qCEST signal value of painful discs was significantly higher than non-painful discs (p = 0.012). The ratio between qCEST and normalized T2w was found to be significantly higher in painful discs compared to non-painful discs (p = 0.0022). A receiver operating characteristics (ROC) analysis indicated that qCEST/T2w ratio could be used to differentiate between painful and non-painful discs with 78% sensitivity and 81% specificity. The results of the study suggest that qCEST could be used for the diagnosis of discogenic pain, in conjunction with the commonly used T2w scan.
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Affiliation(s)
- Gadi Pelled
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
- Department of Orthopedics, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
| | - Margaux M Salas
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- 59th Medical Wing Air Force, San Antonio, TX, 78236, USA
| | - Pei Han
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Biomedical Research Imaging Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Howard E Gill
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Karl A Lautenschlager
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Tristan T Lai
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Cameron M Shawver
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Matthew B Hoch
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Brandon J Goff
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Aaron M Betts
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Zhengwei Zhou
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Biomedical Research Imaging Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Cody Lynch
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Biomedical Research Imaging Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Grant Schroeder
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Maxim Bez
- Medical Corps, Israel Defense Forces, Tel HaShomer, Israel
| | - Marcel M Maya
- Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Catherine Bresee
- Biostatistics and Bioinformatics Research Center, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Zulma Gazit
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Department of Orthopedics, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - John P McCallin
- Division of Pain Management, Department of Rehabilitation Medicine, Brooke Army Medical Center, San Antonio, TX, 78234, USA
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Dan Gazit
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Department of Orthopedics, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Faculty of Dental Medicine, Hebrew University, 91120, Jerusalem, Israel
| | - Debiao Li
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Biomedical Research Imaging Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, 90095, USA
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14
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Han P, Zhang R, Wagner S, Xie Y, Cingolani E, Marban E, Christodoulou AG, Li D. Electrocardiogram-less, free-breathing myocardial extracellular volume fraction mapping in small animals at high heart rates using motion-resolved cardiovascular magnetic reesonance multitasking: a feasibility study in a heart failure with preserved ejection fraction rat model. J Cardiovasc Magn Reson 2021; 23:8. [PMID: 33568177 PMCID: PMC7877086 DOI: 10.1186/s12968-020-00699-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Accepted: 12/10/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Extracellular volume fraction (ECV) quantification with cardiovascular magnetic resonance (CMR) T1 mapping is a powerful tool for the characterization of focal or diffuse myocardial fibrosis. However, it is technically challenging to acquire high-quality T1 and ECV maps in small animals for preclinical research because of high heart rates and high respiration rates. In this work, we developed an electrocardiogram (ECG)-less, free-breathing ECV mapping method using motion-resolved CMR Multitasking on a 9.4 T small animal CMR system. The feasibility of characterizing diffuse myocardial fibrosis was tested in a rat heart failure model with preserved ejection fraction (HFpEF). METHODS High-salt fed rats diagnosed with HFpEF (n = 9) and control rats (n = 9) were imaged with the proposed ECV Multitasking technique. A 25-min exam, including two 4-min T1 Multitasking scans before and after gadolinium injection, were performed on each rat. It allows a cardiac temporal resolution of 20 ms for a heart rate of ~ 300 bpm. Myocardial ECV was calculated from the hematocrit (HCT) and fitted T1 values of the myocardium and the blood pool. Masson's trichrome stain was used to measure the extent of fibrosis. Welch's t-test was performed between control and HFpEF groups. RESULTS ECV was significantly higher in the HFpEF group (22.4% ± 2.5% vs. 18.0% ± 2.1%, P = 0.0010). A moderate correlation between the ECV and the extent of fibrosis was found (R = 0.59, P = 0.0098). CONCLUSIONS Motion-resolved ECV Multitasking CMR can quantify ECV in the rat myocardium at high heart rates without ECG triggering or respiratory gating. Elevated ECV found in the HFpEF group is consistent with previous human studies and well correlated with histological data. This technique has the potential to be a viable imaging tool for myocardial tissue characterization in small animal models.
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Affiliation(s)
- Pei Han
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA USA
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Rui Zhang
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
- Department of Cardiology, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shawn Wagner
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Eugenio Cingolani
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Eduardo Marban
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Anthony G. Christodoulou
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA USA
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Debiao Li
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA USA
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
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15
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Wang N, Xie Y, Fan Z, Ma S, Saouaf R, Guo Y, Shiao SL, Christodoulou AG, Li D. Five-dimensional quantitative low-dose Multitasking dynamic contrast- enhanced MRI: Preliminary study on breast cancer. Magn Reson Med 2021; 85:3096-3111. [PMID: 33427334 DOI: 10.1002/mrm.28633] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 10/17/2020] [Accepted: 11/13/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To develop a low-dose Multitasking DCE technique (LD-MT-DCE) for breast imaging, enabling dynamic T1 mapping-based quantitative characterization of tumor blood flow and vascular properties with whole-breast coverage, a spatial resolution of 0.9 × 0.9 × 1.1 mm3 , and a temporal resolution of 1.4 seconds using a 20% gadolinium dose (0.02 mmol/kg). METHODS Magnetic resonance Multitasking was used to reconstruct 5D images with three spatial dimensions, one T1 recovery dimension for dynamic T1 quantification, and one DCE dimension for contrast kinetics. Kinetic parameters F p , v p , K trans , and v e were estimated from dynamic T1 maps using the two-compartment exchange model. The LD-MT-DCE repeatability and agreement against standard-dose MT-DCE were evaluated in 20 healthy subjects. In 7 patients with triple-negative breast cancer, LD-MT-DCE image quality and diagnostic results were compared with that of standard-dose clinical DCE in the same imaging session. One-way unbalanced analysis of variance with Tukey test was performed to evaluate the statistical significance of the kinetic parameters between control and patient groups. RESULTS The LD-MT-DCE technique was repeatable, agreed with standard-dose MT-DCE, and showed excellent image quality. The diagnosis using LD-MT-DCE matched well with clinical results. The values of F p , v p , and K trans were significantly different between malignant tumors and normal breast tissue (P < .001, < .001, and < .001, respectively), and between malignant and benign tumors (P = .020, .003, and < .001, respectively). CONCLUSION The LD-MT-DCE technique was repeatable and showed excellent image quality and equivalent diagnosis compared with standard-dose clinical DCE. The estimated kinetic parameters were capable of differentiating between normal breast tissue and benign and malignant tumors.
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Affiliation(s)
- Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 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
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Rola Saouaf
- Department of Imaging, Cedars Sinai Medical Center, Los Angeles, California, USA
| | - Yu Guo
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - Stephen L Shiao
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Biomedical Sciences, Division of Immunology, 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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16
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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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17
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Qiao H, Li D, Cao J, Qi H, Han Y, Han H, Xu H, Wang T, Chen S, Chen H, Wang Y, Zhao X. Quantitative evaluation of carotid atherosclerotic vulnerable plaques using in vivo T1 mapping cardiovascular magnetic resonaonce: validation by histology. J Cardiovasc Magn Reson 2020; 22:38. [PMID: 32434582 PMCID: PMC7240932 DOI: 10.1186/s12968-020-00624-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 04/07/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND It has been proved that multi-contrast cardiovascular magnetic resonance (CMR) vessel wall imaging could be used to characterize carotid vulnerable plaque components according to the signal intensity on different contrast images. The signal intensity of plaque components is mainly dependent on the values of T1 and T2 relaxation. T1 mapping recently showed a potential in identifying plaque components but it is not well validated by histology. This study aimed to validate the usefulness of in vivo T1 mapping in assessing carotid vulnerable plaque components by histology. METHODS Thirty-four subjects (mean age, 64.0 ± 8.9 years; 26 males) with carotid plaques referred to carotid endarterectomy were prospectively enrolled and underwent 3 T CMR imaging from May 2017 to October 2017. The T1 values of intraplaque hemorrhage (IPH), necrotic core (NC) and loose matrix (LM) which were identified on multi-contrast vessel wall images or histology were measured on in-vivo T1 mapping. The IPHs were divided into two types based on the proportion of the area of fresh hemorrhage on histology. The T1 values of different plaque components were compared using Mann-Whitney U test and the agreement between T1 mapping and histology in identifying and quantifying IPH was analyzed with Cohen's Kappa and intraclass correlation coefficient (ICC). RESULTS Of 34 subjects, 19 had histological specimens matched with CMR imaging. The mean T1 values of IPH (651 ± 253 ms), NC (1161 ± 182 ms) and LM (1447 ± 310 ms) identified by histology were significantly different. The T1 values of Type 1 IPH were significantly shorter than that of Type 2 IPH (456 ± 193 ms vs. 775 ± 205 ms, p < 0.001). Moderate to excellent agreement was found in identification (kappa = 0.51, p < 0.001), classification (kappa = 0.40, p = 0.028) and segmentation (ICC = 0.816, 95% CI 0.679-0.894) of IPHs between T1 mapping and histology. CONCLUSIONS The T1 values of carotid plaque components, particularly for intraplaque hemorrhage, are differentiable, and the stage of intraplaque hemorrhage can be classified according to T1 values, suggesting the potential capability of assessment of vulnerable plaque components by T1 mapping.
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Affiliation(s)
- Huiyu Qiao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China
| | - Dongye Li
- Department of Radiology, Sun Yat-sen Memorial hospital, Sun Yat-sen University, Guangzhou, China
| | - Jingli Cao
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Haikun Qi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Yongjun Han
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China
| | - Hualu Han
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China
| | - Huimin Xu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Tao Wang
- Department of Neurosurgery, Peking University Third Hospital, Beijing, China
| | - Shuo Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China
| | - Yajie Wang
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China.
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18
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Hu Z, Christodoulou AG, Wang N, Shaw JL, Song SS, Maya MM, Ishimori ML, Forbess LJ, Xiao J, Bi X, Han F, Li D, Fan Z. Magnetic resonance multitasking for multidimensional assessment of cardiovascular system: Development and feasibility study on the thoracic aorta. Magn Reson Med 2020; 84:2376-2388. [PMID: 32301164 DOI: 10.1002/mrm.28275] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 03/15/2020] [Accepted: 03/16/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE To develop an MR multitasking-based multidimensional assessment of cardiovascular system (MT-MACS) with electrocardiography-free and navigator-free data acquisition for a comprehensive evaluation of thoracic aortic diseases. METHODS The MT-MACS technique adopts a low-rank tensor image model with a cardiac time dimension for phase-resolved cine imaging and a T2 -prepared inversion-recovery dimension for multicontrast assessment. Twelve healthy subjects and 2 patients with thoracic aortic diseases were recruited for the study at 3 T, and both qualitative (image quality score) and quantitative (contrast-to-noise ratio between lumen and wall, lumen and wall area, and aortic strain index) analyses were performed in all healthy subjects. The overall image quality was scored based on a 4-point scale: 3, excellent; 2, good; 1, fair; and 0, poor. Statistical analysis was used to test the measurement agreement between MT-MACS and its corresponding 2D references. RESULTS The MT-MACS images reconstructed from acquisitions as short as 6 minutes demonstrated good or excellent image quality for bright-blood (2.58 ± 0.46), dark-blood (2.58 ± 0.50), and gray-blood (2.17 ± 0.53) contrast weightings, respectively. The contrast-to-noise ratios for the three weightings were 49.2 ± 12.8, 20.0 ± 5.8 and 2.8 ± 1.8, respectively. There were good agreements in the lumen and wall area (intraclass correlation coefficient = 0.993, P < .001 for lumen; intraclass correlation coefficient = 0.969, P < .001 for wall area) and strain (intraclass correlation coefficient = 0.947, P < .001) between MT-MACS and conventional 2D sequences. CONCLUSION The MT-MACS technique provides high-quality, multidimensional images for a comprehensive assessment of the thoracic aorta. Technical feasibility was demonstrated in healthy subjects and patients with thoracic aortic diseases. Further clinical validation is warranted.
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Affiliation(s)
- Zhehao Hu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
| | - Anthony G Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Medicine, University of California, Los Angeles, California
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
| | - Jaime L Shaw
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Shlee S Song
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California
| | - Marcel M Maya
- Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California
| | - Mariko L Ishimori
- Department of Rheumatology, Cedars-Sinai Medical Center, Los Angeles, California
| | - Lindsy J Forbess
- Department of Rheumatology, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jiayu Xiao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | | | - Fei Han
- Siemens Healthcare, 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.,Department of Medicine, University of California, 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.,Department of Medicine, University of California, Los Angeles, California
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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: 6.8] [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: 3.8] [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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Ma S, Nguyen CT, Han F, Wang N, Deng Z, Binesh N, Moser FG, Christodoulou AG, Li D. Three-dimensional simultaneous brain T 1 , T 2 , and ADC mapping with MR Multitasking. Magn Reson Med 2019; 84:72-88. [PMID: 31765496 DOI: 10.1002/mrm.28092] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 10/01/2019] [Accepted: 10/31/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a simultaneous T1 , T2 , and ADC mapping method that provides co-registered, distortion-free images and enables multiparametric quantification of 3D brain coverage in a clinically feasible scan time with the MR Multitasking framework. METHODS The T1 /T2 /diffusion weighting was generated by a series of T2 preparations and diffusion preparations. The underlying multidimensional image containing 3 spatial dimensions, 1 T1 weighting dimension, 1 T2 -preparation duration dimension, 1 b-value dimension, and 1 diffusion direction dimension was modeled as a 5-way low-rank tensor. A separate real-time low-rank model incorporating time-resolved phase correction was also used to compensate for both inter-shot and intra-shot phase inconsistency induced by physiological motion. The proposed method was validated on both phantom and 16 healthy subjects. The quantification of T1 /T2 /ADC was evaluated for each case. Three post-surgery brain tumor patients were scanned for demonstration of clinical feasibility. RESULTS Multitasking T1 /T2 /ADC maps were perfectly co-registered and free from image distortion. Phantom studies showed substantial quantitative agreement ( R 2 = 0.999 ) with reference protocols for T1 /T2 /ADC. In vivo studies showed nonsignificant T1 (P = .248), T2 (P = .97), ADC (P = .328) differences among the frontal, parietal, and occipital regions. Although Multitasking showed significant differences of T1 (P = .03), T2 (P < .001), and ADC (P = .001) biases against the references, the mean bias estimates were small (ΔT1 % < 5%, ΔT2 % < 7%, ΔADC% < 5%), with all intraclass correlation coefficients greater than 0.82 indicating "excellent" agreement. Patient studies showed that Multitasking T1 /T2 /ADC maps were consistent with the clinical qualitative images. CONCLUSION The Multitasking approach simultaneously quantifies T1 /T2 /ADC with substantial agreement with the references and is promising for clinical applications.
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Affiliation(s)
- Sen Ma
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Christopher T Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Fei Han
- Siemens Healthcare, Los Angeles, California
| | - Nan Wang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Zixin Deng
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Nader Binesh
- S. Mark Taper Foundation Imaging Center, Cedars-Sinai Medical Center, Los Angeles, California
| | - Franklin G Moser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California
| | | | - Debiao Li
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
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22
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Feng L, Wen Q, Huang C, Tong A, Liu F, Chandarana H. GRASP-Pro: imProving GRASP DCE-MRI through self-calibrating subspace-modeling and contrast phase automation. Magn Reson Med 2019; 83:94-108. [PMID: 31400028 DOI: 10.1002/mrm.27903] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Accepted: 06/25/2019] [Indexed: 12/19/2022]
Abstract
PURPOSE To propose a highly accelerated, high-resolution dynamic contrast-enhanced MRI (DCE-MRI) technique called GRASP-Pro (golden-angle radial sparse parallel imaging with imProved performance) through a joint sparsity and self-calibrating subspace constraint with automated selection of contrast phases. METHODS GRASP-Pro reconstruction enforces a combination of an explicit low-rank subspace-constraint and a temporal sparsity constraint. The temporal basis used to construct the subspace is learned from an intermediate reconstruction step using the low-resolution portion of radial k-space, which eliminates the need for generating the basis using auxiliary data or a physical signal model. A convolutional neural network was trained to generate the contrast enhancement curve in the artery, from which clinically relevant contrast phases are automatically selected for evaluation. The performance of GRASP-Pro was demonstrated for high spatiotemporal resolution DCE-MRI of the prostate and was compared against standard GRASP in terms of overall image quality, image sharpness, and residual streaks and/or noise level. RESULTS Compared to GRASP, GRASP-Pro reconstructed dynamic images with enhanced sharpness, less residual streaks and/or noise, and finer delineation of the prostate without prolonging reconstruction time. The image quality improvement reached statistical significance (P < 0.05) in all the assessment categories. The neural network successfully generated contrast enhancement curves in the artery, and corresponding peak enhancement indexes correlated well with that from the manual selection. CONCLUSION GRASP-Pro is a promising method for rapid and continuous DCE-MRI. It enables superior reconstruction performance over standard GRASP and allows reliable generation of artery enhancement curve to guide the selection of desired contrast phases for improving the efficiency of GRASP MRI workflow.
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Affiliation(s)
- Li Feng
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana
| | - Chenchan Huang
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Angela Tong
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Fang Liu
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Hersh Chandarana
- Department of Radiology, New York University School of Medicine, New York, New York.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York
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