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Cao X, Liao C, Zhou Z, Zhong Z, Li Z, Dai E, Iyer SS, Hannum AJ, Yurt M, Schauman S, Chen Q, Wang N, Wei J, Yan Y, He H, Skare S, Zhong J, Kerr A, Setsompop K. DTI-MR fingerprinting for rapid high-resolution whole-brain T 1 , T 2 , proton density, ADC, and fractional anisotropy mapping. Magn Reson Med 2024; 91:987-1001. [PMID: 37936313 PMCID: PMC11068310 DOI: 10.1002/mrm.29916] [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: 07/14/2023] [Revised: 10/17/2023] [Accepted: 10/18/2023] [Indexed: 11/09/2023]
Abstract
PURPOSE This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1 , T2 , proton density (PD), ADC, and fractional anisotropy (FA). The proposed method is intended for pushing routine clinical brain imaging from weighted imaging to quantitative imaging and can also be particularly useful for diffusion-relaxometry studies, which typically suffer from lengthy acquisition time. METHODS To address challenges associated with diffusion weighting, such as shot-to-shot phase variation and low SNR, we integrated several innovative data acquisition and reconstruction techniques. Specifically, we used M1-compensated diffusion gradients, cardiac gating, and navigators to mitigate phase variations caused by cardiac motion. We also introduced a data-driven pre-pulse gradient to cancel out eddy currents induced by diffusion gradients. Additionally, to enhance image quality within a limited acquisition time, we proposed a data-sharing joint reconstruction approach coupled with a corresponding sequence design. RESULTS The phantom and in vivo studies indicated that the T1 and T2 values measured by the proposed method are consistent with a conventional MR fingerprinting sequence and the diffusion results (including diffusivity, ADC, and FA) are consistent with the spin-echo EPI DWI sequence. CONCLUSION The proposed method can achieve whole-brain T1 , T2 , diffusivity, ADC, and FA maps at 1-mm isotropic resolution within 10 min, providing a powerful tool for investigating the microstructural properties of brain tissue, with potential applications in clinical and research settings.
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Affiliation(s)
- Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zihan Zhou
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Zheng Zhong
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Zhitao Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Erpeng Dai
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Siddharth Srinivasan Iyer
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts, USA
| | - Ariel J Hannum
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Mahmut Yurt
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Sophie Schauman
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Quan Chen
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Nan Wang
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Jintao Wei
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yifan Yan
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, Zhejiang, China
- School of Physics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Jianhui Zhong
- Department of Imaging Sciences, University of Rochester, NY, USA
| | - Adam Kerr
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
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Monga A, Singh D, de Moura HL, Zhang X, Zibetti MVW, Regatte RR. Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review. Bioengineering (Basel) 2024; 11:236. [PMID: 38534511 DOI: 10.3390/bioengineering11030236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/28/2024] Open
Abstract
Magnetic resonance imaging (MRI) stands as a vital medical imaging technique, renowned for its ability to offer high-resolution images of the human body with remarkable soft-tissue contrast. This enables healthcare professionals to gain valuable insights into various aspects of the human body, including morphology, structural integrity, and physiological processes. Quantitative imaging provides compositional measurements of the human body, but, currently, either it takes a long scan time or is limited to low spatial resolutions. Undersampled k-space data acquisitions have significantly helped to reduce MRI scan time, while compressed sensing (CS) and deep learning (DL) reconstructions have mitigated the associated undersampling artifacts. Alternatively, magnetic resonance fingerprinting (MRF) provides an efficient and versatile framework to acquire and quantify multiple tissue properties simultaneously from a single fast MRI scan. The MRF framework involves four key aspects: (1) pulse sequence design; (2) rapid (undersampled) data acquisition; (3) encoding of tissue properties in MR signal evolutions or fingerprints; and (4) simultaneous recovery of multiple quantitative spatial maps. This paper provides an extensive literature review of the MRF framework, addressing the trends associated with these four key aspects. There are specific challenges in MRF for all ranges of magnetic field strengths and all body parts, which can present opportunities for further investigation. We aim to review the best practices in each key aspect of MRF, as well as for different applications, such as cardiac, brain, and musculoskeletal imaging, among others. A comprehensive review of these applications will enable us to assess future trends and their implications for the translation of MRF into these biomedical imaging applications.
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Affiliation(s)
- Anmol Monga
- Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Dilbag Singh
- Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Hector L de Moura
- Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Xiaoxia Zhang
- Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Marcelo V W Zibetti
- Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ravinder R Regatte
- Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
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Tourais J, Ploem T, van Zadelhoff TA, van de Steeg-Henzen C, Oei EHG, Weingartner S. Rapid Whole-Knee Quantification of Cartilage Using T 1, T 2*, and T RAFF2 Mapping With Magnetic Resonance Fingerprinting. IEEE Trans Biomed Eng 2023; 70:3197-3205. [PMID: 37227911 DOI: 10.1109/tbme.2023.3280115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
OBJECTIVE Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T1, T2*, and TRAFF2 with whole-knee coverage. METHODS A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference ( TRAFF2) along with T1 and T2*. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T1, T2*, and TRAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed. RESULTS Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T1, T2*, and TRAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning ( R2 ≥ 0.94) and with repositioning ( R2 ≥ 0.57) for T1, T2*, and TRAFF2. SIGNIFICANCE The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.
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Bustin A, Witschey WRT, van Heeswijk RB, Cochet H, Stuber M. Magnetic resonance myocardial T1ρ mapping : Technical overview, challenges, emerging developments, and clinical applications. J Cardiovasc Magn Reson 2023; 25:34. [PMID: 37331930 DOI: 10.1186/s12968-023-00940-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 05/15/2023] [Indexed: 06/20/2023] Open
Abstract
The potential of cardiac magnetic resonance to improve cardiovascular care and patient management is considerable. Myocardial T1-rho (T1ρ) mapping, in particular, has emerged as a promising biomarker for quantifying myocardial injuries without exogenous contrast agents. Its potential as a contrast-agent-free ("needle-free") and cost-effective diagnostic marker promises high impact both in terms of clinical outcomes and patient comfort. However, myocardial T1ρ mapping is still at a nascent stage of development and the evidence supporting its diagnostic performance and clinical effectiveness is scant, though likely to change with technological improvements. The present review aims at providing a primer on the essentials of myocardial T1ρ mapping, and to describe the current range of clinical applications of the technique to detect and quantify myocardial injuries. We also delineate the important limitations and challenges for clinical deployment, including the urgent need for standardization, the evaluation of bias, and the critical importance of clinical testing. We conclude by outlining technical developments to be expected in the future. If needle-free myocardial T1ρ mapping is shown to improve patient diagnosis and prognosis, and can be effectively integrated in cardiovascular practice, it will fulfill its potential as an essential component of a cardiac magnetic resonance examination.
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Affiliation(s)
- Aurelien Bustin
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Avenue du Haut Lévêque, 33604, Pessac, France.
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France.
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | | | - Ruud B van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Hubert Cochet
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France
| | - Matthias Stuber
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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Gram M, Gensler D, Albertova P, Gutjahr FT, Lau K, Arias-Loza PA, Jakob PM, Nordbeck P. Quantification correction for free-breathing myocardial T 1ρ mapping in mice using a recursively derived description of a T 1ρ* relaxation pathway. J Cardiovasc Magn Reson 2022; 24:30. [PMID: 35534901 PMCID: PMC9082875 DOI: 10.1186/s12968-022-00864-2] [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: 12/01/2021] [Accepted: 04/07/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Fast and accurate T1ρ mapping in myocardium is still a major challenge, particularly in small animal models. The complex sequence design owing to electrocardiogram and respiratory gating leads to quantification errors in in vivo experiments, due to variations of the T1ρ relaxation pathway. In this study, we present an improved quantification method for T1ρ using a newly derived formalism of a T1ρ* relaxation pathway. METHODS The new signal equation was derived by solving a recursion problem for spin-lock prepared fast gradient echo readouts. Based on Bloch simulations, we compared quantification errors using the common monoexponential model and our corrected model. The method was validated in phantom experiments and tested in vivo for myocardial T1ρ mapping in mice. Here, the impact of the breath dependent spin recovery time Trec on the quantification results was examined in detail. RESULTS Simulations indicate that a correction is necessary, since systematically underestimated values are measured under in vivo conditions. In the phantom study, the mean quantification error could be reduced from - 7.4% to - 0.97%. In vivo, a correlation of uncorrected T1ρ with the respiratory cycle was observed. Using the newly derived correction method, this correlation was significantly reduced from r = 0.708 (p < 0.001) to r = 0.204 and the standard deviation of left ventricular T1ρ values in different animals was reduced by at least 39%. CONCLUSION The suggested quantification formalism enables fast and precise myocardial T1ρ quantification for small animals during free breathing and can improve the comparability of study results. Our new technique offers a reasonable tool for assessing myocardial diseases, since pathologies that cause a change in heart or breathing rates do not lead to systematic misinterpretations. Besides, the derived signal equation can be used for sequence optimization or for subsequent correction of prior study results.
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Affiliation(s)
- Maximilian Gram
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
- Experimental Physics 5, University of Würzburg, Würzburg, Germany
| | - Daniel Gensler
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center (CHFC), University Hospital Würzburg, Würzburg, Germany
| | - Petra Albertova
- Experimental Physics 5, University of Würzburg, Würzburg, Germany
| | - Fabian Tobias Gutjahr
- Experimental Physics 5, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center (CHFC), University Hospital Würzburg, Würzburg, Germany
| | - Kolja Lau
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Paula-Anahi Arias-Loza
- Comprehensive Heart Failure Center (CHFC), University Hospital Würzburg, Würzburg, Germany
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | | | - Peter Nordbeck
- Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany.
- Comprehensive Heart Failure Center (CHFC), University Hospital Würzburg, Würzburg, Germany.
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Velasco C, Cruz G, Lavin B, Hua A, Fotaki A, Botnar RM, Prieto C. Simultaneous T 1 , T 2 , and T 1ρ cardiac magnetic resonance fingerprinting for contrast agent-free myocardial tissue characterization. Magn Reson Med 2021; 87:1992-2002. [PMID: 34799854 DOI: 10.1002/mrm.29091] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 10/28/2021] [Accepted: 11/01/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop a simultaneous T1 , T2 , and T1ρ cardiac magnetic resonance fingerprinting (MRF) approach to enable comprehensive contrast agent-free myocardial tissue characterization in a single breath-hold scan. METHODS A 2D gradient-echo electrocardiogram-triggered cardiac MRF sequence with low flip angles, varying magnetization preparation, and spiral trajectory was acquired at 1.5 T to encode T1 , T2 , and T1⍴ simultaneously. The MRF images were reconstructed using low-rank inversion, regularized with a multicontrast patch-based higher-order reconstruction. Parametric maps were generated and matched in the singular value domain to extended phase graph-based dictionaries. The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional methods in terms of coefficients of determination and best fits for the phantom study, and in terms of Bland-Altman agreement, average values and coefficient of variation of T1 , T2 , and T1⍴ for the healthy subjects study. RESULTS The T1 , T2 , and T1⍴ MRF values showed excellent correlation with conventional spin-echo and clinical mapping methods in phantom studies (r2 > 0.97). Measured MRF values in myocardial tissue (mean ± SD) were 1133 ± 33 ms, 38.8 ± 3.5 ms, and 52.0 ± 4.0 ms for T1 , T2 and T1⍴ , respectively, against 1053 ± 47 ms, 50.4 ± 3.9 ms, and 55.9 ± 3.3 ms for T1 modified Look-Locker inversion imaging, T2 gradient and spin echo, and T1⍴ turbo field echo, respectively. CONCLUSION A cardiac MRF approach for simultaneous quantification of myocardial T1 , T2 , and T1ρ in a single breath-hold MR scan of about 16 seconds has been proposed. The approach has been investigated in phantoms and healthy subjects showing good agreement with reference spin echo measurements and conventional clinical maps.
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Affiliation(s)
- Carlos Velasco
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gastão Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Begoña Lavin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Department of Biochemistry and Molecular Biology, School of Chemistry, Complutense University of Madrid, Madrid, Spain
| | - Alina Hua
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Anastasia Fotaki
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
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Velasco C, Cruz G, Jaubert O, Lavin B, Botnar RM, Prieto C. Simultaneous comprehensive liver T 1 , T 2 , T 2 ∗ , T 1ρ , and fat fraction characterization with MR fingerprinting. Magn Reson Med 2021; 87:1980-1991. [PMID: 34792212 DOI: 10.1002/mrm.29089] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 10/18/2021] [Accepted: 10/29/2021] [Indexed: 12/23/2022]
Abstract
PURPOSE To develop a novel simultaneous co-registered T1 , T2 , T 2 ∗ , T1ρ , and fat fraction abdominal MR fingerprinting (MRF) approach for fully comprehensive liver-tissue characterization in a single breath-hold scan. METHODS A gradient-echo liver MRF sequence with low fixed flip angle, multi-echo radial readout, and varying magnetization preparation pulses for multiparametric encoding is performed at 1.5 T. The T 2 ∗ and fat fraction are estimated from a graph/cut water/fat separation method using a six-peak fat model. Water/fat singular images obtained are then matched to an MRF dictionary, estimating water-specific T1 , T2 , and T1ρ . The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional sequences. RESULTS For the phantom studies, linear fits show excellent coefficients of determination (r2 > 0.9) for every parametric map. For in vivo studies, the average values measured within regions of interest drawn on liver, spleen, muscle, and fat are statistically different from the reference scans (p < 0.05) for T1 , T2 , and T1⍴ but not for T 2 ∗ and fat fraction, whereas correlation between MRF and reference scans is excellent for each parameter (r2 > 0.92 for every parameter). CONCLUSION The proposed multi-echo inversion-recovery, T2 , and T1⍴ prepared liver MRF sequence presented in this work allows for quantitative T1 , T2 , T 2 ∗ , T1⍴ , and fat fraction liver-tissue characterization in a single breath-hold scan of 18 seconds. The approach showed good agreement and correlation with respect to reference clinical maps.
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Affiliation(s)
- Carlos Velasco
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gastão Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Olivier Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Begoña Lavin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Department of Biochemistry and Molecular Biology, School of Chemistry, Complutense University of Madrid, Madrid, Spain
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
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Chen Y, Lu L, Zhu T, Ma D. Technical overview of magnetic resonance fingerprinting and its applications in radiation therapy. Med Phys 2021; 49:2846-2860. [PMID: 34633687 DOI: 10.1002/mp.15254] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 08/23/2021] [Accepted: 09/17/2021] [Indexed: 11/07/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is an emerging imaging technique for rapid and simultaneous quantification of multiple tissue properties. The technique has been developed for quantitative imaging of different organs. The obtained quantitative measures have the potential to improve multiple steps of a typical radiotherapy workflow and potentially further improve integration of magnetic resonance imaging guided clinical decision making. In this review paper, we first provide a technical overview of the MRF method from data acquisition to postprocessing, along with recent development in advanced reconstruction methods. We further discuss critical aspects that could influence its usage in radiation therapy, such as accuracy and precision, repeatability and reproducibility, geometric distortion, and motion robustness. Finally, future directions for MRF application in radiation therapy are discussed.
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Affiliation(s)
- Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Lan Lu
- Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, USA
| | - Tong Zhu
- Radiation Oncology, Washington University in St Louis, St Louis, Missouri, USA
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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Zou L, Liang D, Ye H, Su S, Zhu Y, Liu X, Zheng H, Wang H. Quantitative MR relaxation using MR fingerprinting with fractional-order signal evolution. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 330:107042. [PMID: 34333244 DOI: 10.1016/j.jmr.2021.107042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 06/19/2021] [Accepted: 07/19/2021] [Indexed: 06/13/2023]
Abstract
The fractional-order Bloch equations have been shown to describe a wider range of experimental situations involving heterogeneous, porous, or composite materials. This paper introduces a novel dictionary of quantitative MR fingerprinting generated by signal evolution model with fractional-order Bloch equations to describe magnetic resonance (MR) relaxation. Here, the fractional-order relaxation models are implemented into Bloch equations through phase transitions using EPG simulation. In the phantom experiments, the fractional-order analysis showed smaller root mean squared error (T1: RMSE = 5.21%, T2: RMSE=3.75%) using the proposed method compared to using conventional method. Among the in vivo experiments of human brains, the estimated T1 and T2 values (mean ± SD) were 843 ± 46.3 ms and 70 ± 4.7 ms in white matter, 1323 ± 28.5 ms and 95 ± 3.8 ms in gray matter. So the proposed method can provide well extensions of current MR fingerprinting and has shown potential to apply into the phantom experiments and the in vivo applications to approach the standard methods for quantitative imaging.
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Affiliation(s)
- Lixian Zou
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Dong Liang
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China; Research Centre for Medical AI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Huihui Ye
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shi Su
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Yanjie Zhu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Xin Liu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China.
| | - Haifeng Wang
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China.
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Lu Y, Wang Q, Zhang T, Li J, Liu H, Yao D, Hou L, Tu B, Wang D. Staging Liver Fibrosis: Comparison of Native T1 Mapping, T2 Mapping, and T1ρ: An Experimental Study in Rats With Bile Duct Ligation and Carbon Tetrachloride at 11.7 T MRI. J Magn Reson Imaging 2021; 55:507-517. [PMID: 34254388 DOI: 10.1002/jmri.27822] [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: 04/17/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND T1, T2, and T1ρ might be potential biomarkers for assessing liver fibrosis. However, few studies reported the value of them in different animal models. PURPOSE To investigate and compare the performances of T1, T2, and T1ρ for noninvasively staging liver fibrosis in bile duct ligation (BDL) or carbon tetrachloride (CCl4 ) model. STUDY TYPE Prospective animal model. SUBJECTS Liver fibrosis was induced by BDL or injection of CCl4 in 120 rats. FIELD STRENGTH/SEQUENCE 11.7 T, T1 mapping with 10 repetition times, T2 mapping with 32 echo times, and T1ρ with 10 spin-lock times. ASSESSMENT T1, T2, and T1ρ were measured and correlated with liver fibrosis stages, as well as the degree of inflammation, steatosis, iron deposition, and the expression of cytokeratin 19. The discriminative performance of T1, T2, and T1ρ for staging liver fibrosis was compared. STATISTICAL TESTS One-way analysis of variance (ANOVA), Spearman's correlation analysis, factorial design ANOVA, and receiver operating characteristic curves (P < 0.05 was considered statistically significant). RESULTS T1, T2, and T1ρ (BDL: rho = 0.73, 0.85, 0.68; CCl4 : rho = 0.80, 0.29, 0.61) were significantly correlated with liver fibrosis stages, while there was no significant difference in T2 among stage F0-F4 in the CCl4 model (P = 0.204). The area under the curves (AUCs) range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.76-0.95, 0.89-0.98, and 0.80-0.94 in the CCl4 model. For the CCl4 model, the AUCs range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.83-0.95, 0.61-0.74, and 0.73-0.89, respectively. T2 had significantly higher AUC in the BDL model than CCl4 model for diagnosing liver fibrosis. DATA CONCLUSION The most sensitive and accurate method for staging liver fibrosis appeared to be T1 in our animal models followed by T1ρ. T2 may not be suitable for evaluating liver fibrosis. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Yimei Lu
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qianfeng Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Tingting Zhang
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinning Li
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huanhuan Liu
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Defan Yao
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liang Hou
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Beiwu Tu
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dengbin Wang
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Sharafi A, Medina K, Zibetti MWV, Rao S, Cloos MA, Brown R, Regatte RR. Simultaneous T 1 , T 2 , and T 1ρ relaxation mapping of the lower leg muscle with MR fingerprinting. Magn Reson Med 2021; 86:372-381. [PMID: 33554369 DOI: 10.1002/mrm.28704] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 12/31/2020] [Accepted: 01/09/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE To develop a novel MR-fingerprinting (MRF) pulse sequence that is insensitive to B 1 + and B0 imperfections for simultaneous T1 , T2 , and T1ρ relaxation mapping. METHODS We implemented a totally balanced spin-lock (TB-SL) module to encode T1ρ relaxation into an existing MRF framework that encoded T1 and T2 . The spin-lock module used two 180° pulses with compensatory phases to reduce T1ρ sensitivity to B1 and B0 inhomogeneities. We compared T1ρ measured using TB-SL MRF in Bloch simulations, model agar phantoms, and in vivo experiments to those with a self-compensated spin-lock preparation module (SC-SL). The TB-SL MRF repeatability was evaluated in maps acquired in the lower leg skeletal muscle of 12 diabetic peripheral neuropathy patients, scanned two times each during visits separated by about 30 days. RESULTS The phantom relaxation times measured with TB-SL and SC-SL MRF were in good agreement with reference values in regions with low B1 inhomogeneities. Compared with SC-SL, TB-SL MRF showed in experiments greater robustness against severe B1 inhomogeneities and in Bloch simulations greater robustness against B1 and B0 . We measured with TB-SL MRF an average T1 = 950.1 ± 28.7 ms, T2 = 26.0 ± 1.2 ms, and T1ρ = 31.7 ± 3.2 ms in skeletal muscle across patients. Bland-Altman analysis demonstrated low bias between TB-SL and SC-SL MRF and between TB-SL MRF maps acquired in two visits. The coefficient of variation was less than 3% for all measurements. CONCLUSION The proposed TB-SL MRF sequence is fast and insensitive to B 1 + and B0 imperfections. It can simultaneously map T1 , T2 , T1ρ , and B 1 + in a single scan and can potentially be used to study muscle composition.
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Affiliation(s)
- Azadeh Sharafi
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Katherine Medina
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Marcelo W V Zibetti
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Smita Rao
- Department of Physical Therapy, New York University, New York, New York, USA
| | - Martijn A Cloos
- Center of Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Ryan Brown
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.,Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, New York, USA
| | - Ravinder R Regatte
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.,Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, New York, USA
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12
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Eck BL, Flamm SD, Kwon DH, Tang WHW, Vasquez CP, Seiberlich N. Cardiac magnetic resonance fingerprinting: Trends in technical development and potential clinical applications. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2021; 122:11-22. [PMID: 33632415 PMCID: PMC8366914 DOI: 10.1016/j.pnmrs.2020.10.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 10/23/2020] [Accepted: 10/29/2020] [Indexed: 05/02/2023]
Abstract
Quantitative cardiac magnetic resonance has emerged in recent years as an approach for evaluating a range of cardiovascular conditions, with T1 and T2 mapping at the forefront of these developments. Cardiac Magnetic Resonance Fingerprinting (cMRF) provides a rapid and robust framework for simultaneous quantification of myocardial T1 and T2 in addition to other tissue properties. Since the advent of cMRF, a number of technical developments and clinical validation studies have been reported. This review provides an overview of cMRF, recent technical developments, healthy subject and patient studies, anticipated technical improvements, and potential clinical applications. Recent technical developments include slice profile and pulse efficiency corrections, improvements in image reconstruction, simultaneous multislice imaging, 3D whole-ventricle imaging, motion-resolved imaging, fat-water separation, and machine learning for rapid dictionary generation. Future technical developments in cMRF, such as B0 and B1 field mapping, acceleration of acquisition and reconstruction, imaging of patients with implanted devices, and quantification of additional tissue properties are also described. Potential clinical applications include characterization of infiltrative, inflammatory, and ischemic cardiomyopathies, tissue characterization in the left atrium and right ventricle, post-cardiac transplantation assessment, reduction of contrast material, pre-procedural planning for electrophysiology interventions, and imaging of patients with implanted devices.
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Affiliation(s)
- Brendan L Eck
- Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
| | - Scott D Flamm
- Heart and Vascular Institute and Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
| | - Deborah H Kwon
- Heart and Vascular Institute and Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
| | - W H Wilson Tang
- Heart and Vascular Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
| | - Claudia Prieto Vasquez
- School of Biomedical Engineering and Imaging Sciences, King's College London, Westminster Bridge Road, London, UK.
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, 1150 West Medical Center Drive, Ann Arbor, MI 48109, USA.
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13
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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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14
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Serrao EM, Kessler DA, Carmo B, Beer L, Brindle KM, Buonincontri G, Gallagher FA, Gilbert FJ, Godfrey E, Graves MJ, McLean MA, Sala E, Schulte RF, Kaggie JD. Magnetic resonance fingerprinting of the pancreas at 1.5 T and 3.0 T. Sci Rep 2020; 10:17563. [PMID: 33067515 PMCID: PMC7567885 DOI: 10.1038/s41598-020-74462-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 09/29/2020] [Indexed: 12/18/2022] Open
Abstract
Magnetic resonance imaging of the pancreas is increasingly used as an important diagnostic modality for characterisation of pancreatic lesions. Pancreatic MRI protocols are mostly qualitative due to time constraints and motion sensitivity. MR Fingerprinting is an innovative acquisition technique that provides qualitative data and quantitative parameter maps from a single free-breathing acquisition with the potential to reduce exam times. This work investigates the feasibility of MRF parameter mapping for pancreatic imaging in the presence of free-breathing exam. Sixteen healthy participants were prospectively imaged using MRF framework. Regions-of-interest were drawn in multiple solid organs including the pancreas and T1 and T2 values determined. MRF T1 and T2 mapping was performed successfully in all participants (acquisition time:2.4-3.6 min). Mean pancreatic T1 values were 37-43% lower than those of the muscle, spleen, and kidney at both 1.5 and 3.0 T. For these organs, the mean pancreatic T2 values were nearly 40% at 1.5 T and < 12% at 3.0 T. The feasibility of MRF at 1.5 T and 3 T was demonstrated in the pancreas. By enabling fast and free-breathing quantitation, MRF has the potential to add value during the clinical characterisation and grading of pathological conditions, such as pancreatitis or cancer.
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Affiliation(s)
- Eva M Serrao
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Cancer Research UK, Cambridge, UK
| | - Dimitri A Kessler
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Bruno Carmo
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lucian Beer
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | | | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Cancer Research UK, Cambridge, UK
| | - Fiona J Gilbert
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Cancer Research UK, Cambridge, UK
| | - Edmund Godfrey
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Martin J Graves
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Mary A McLean
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Cancer Research UK, Cambridge, UK
| | - Evis Sala
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Cancer Research UK, Cambridge, UK
| | | | - Joshua D Kaggie
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK.
- Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
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