101
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Coronado R, Cruz G, Castillo-Passi C, Tejos C, Uribe S, Prieto C, Irarrazaval P. A Spatial Off-Resonance Correction in Spirals for Magnetic Resonance Fingerprinting. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3832-3842. [PMID: 34310296 DOI: 10.1109/tmi.2021.3100293] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
In MR Fingerprinting (MRF), balanced Steady-State Free Precession (bSSFP) has advantages over unbalanced SSFP because it retains the spin history achieving a higher signal-to-noise ratio (SNR) and scan efficiency. However, bSSFP-MRF is not frequently used because it is sensitive to off-resonance, producing artifacts and blurring, and affecting the parametric map quality. Here we propose a novel Spatial Off-resonance Correction (SOC) approach for reducing these artifacts in bSSFP-MRF with spiral trajectories. SOC-MRF uses each pixel's Point Spread Function to create system matrices that encode both off-resonance and gridding effects. We iteratively compute the inverse of these matrices to reduce the artifacts. We evaluated the proposed method using brain simulations and actual MRF acquisitions of a standardized T1/T2 phantom and five healthy subjects. The results show that the off-resonance distortions in T1/T2 maps were considerably reduced using SOC-MRF. For T2, the Normalized Root Mean Square Error (NRMSE) was reduced from 17.3 to 8.3% (simulations) and from 35.1 to 14.9% (phantom). For T1, the NRMS was reduced from 14.7 to 7.7% (simulations) and from 17.7 to 6.7% (phantom). For in-vivo, the mean and standard deviation in different ROI in white and gray matter were significantly improved. For example, SOC-MRF estimated an average T2 for white matter of 77ms (the ground truth was 74ms) versus 50 ms of MRF. For the same example the standard deviation was reduced from 18 ms to 6ms. The corrections achieved with the proposed SOC-MRF may expand the potential applications of bSSFP-MRF, taking advantage of its better SNR property.
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102
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Ben-Eliezer N, Raya JG, Babb JS, Youm T, Sodickson DK, Lattanzi R. A New Method for Cartilage Evaluation in Femoroacetabular Impingement Using Quantitative T2 Magnetic Resonance Imaging: Preliminary Validation against Arthroscopic Findings. Cartilage 2021; 13:1315S-1323S. [PMID: 31455091 PMCID: PMC8808928 DOI: 10.1177/1947603519870852] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE The outcome of arthroscopic treatment for femoroacetabular impingement (FAI) depends on the preoperative status of the hip cartilage. Quantitative T2 can detect early biochemical cartilage changes, but its routine implementation is challenging. Furthermore, intrinsic T2 variability between patients makes it difficult to define a threshold to identify cartilage lesions. To address this, we propose a normalized T2-index as a new method to evaluate cartilage in FAI. DESIGN We retrospectively analyzed magnetic resonance imaging (MRI) data of 18 FAI patients with arthroscopically confirmed cartilage defects. Cartilage T2 maps were reconstructed from multi-spin-echo 3-T data using the echo-modulation-curve (EMC) model-based technique. The central femoral cartilage, assumed healthy in early-stage FAI, was used as the normalization reference to define a T2-index. We investigated the ability of the T2-index to detect surgically confirmed cartilage lesions. RESULTS The average T2-index was 1.14 ± 0.1 and 1.13 ± 0.1 for 2 separated segmentations. Using T2-index >1 as the threshold for damaged cartilage, accuracy was 88% and 100% for the 2 segmentations. We found moderate intraobserver repeatability, although separate segmentations yielded comparable accuracy. Damaged cartilage could not be identified using nonnormalized average T2 values. CONCLUSIONS This preliminary study confirms the importance of normalizing T2 values to account for interpatient variability and suggests that the T2-index is a promising biomarker for the detection of cartilage lesions in FAI. Future work is needed to confirm that combining T2-index with morphologic MRI and other quantitative biomarkers could improve cartilage assessment in FAI.
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Affiliation(s)
- Noam Ben-Eliezer
- Center for Advanced Imaging Innovation
and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging,
Department of Radiology, New York University School of Medicine, New York, NY,
USA
| | - José G. Raya
- Center for Advanced Imaging Innovation
and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging,
Department of Radiology, New York University School of Medicine, New York, NY,
USA,The Sackler Institute of Graduate
Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - James S. Babb
- Center for Advanced Imaging Innovation
and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging,
Department of Radiology, New York University School of Medicine, New York, NY,
USA
| | - Thomas Youm
- Department of Orthopedic Surgery, New
York University Hospital for Joint Diseases, New York, NY, USA
| | - Daniel K. Sodickson
- Center for Advanced Imaging Innovation
and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging,
Department of Radiology, New York University School of Medicine, New York, NY,
USA,The Sackler Institute of Graduate
Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Riccardo Lattanzi
- Center for Advanced Imaging Innovation
and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging,
Department of Radiology, New York University School of Medicine, New York, NY,
USA,The Sackler Institute of Graduate
Biomedical Sciences, New York University School of Medicine, New York, NY, USA,Riccardo Lattanzi, The Bernard and Irene
Schwartz Center for Biomedical Imaging, New York University Langone Health, 660
First Avenue Room 203, New York, NY 10016, USA.
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103
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Delgado PR, Kuehne A, Aravina M, Millward JM, Vázquez A, Starke L, Waiczies H, Pohlmann A, Niendorf T, Waiczies S. B 1 inhomogeneity correction of RARE MRI at low SNR: Quantitative in vivo 19 F MRI of mouse neuroinflammation with a cryogenically-cooled transceive surface radiofrequency probe. Magn Reson Med 2021; 87:1952-1970. [PMID: 34812528 DOI: 10.1002/mrm.29094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 11/03/2021] [Accepted: 11/04/2021] [Indexed: 12/26/2022]
Abstract
PURPOSE Low SNR in fluorine-19 (19 F) MRI benefits from cryogenically-cooled transceive surface RF probes (CRPs), but strong B1 inhomogeneities hinder quantification. Rapid acquisition with refocused echoes (RARE) is an SNR-efficient method for MRI of neuroinflammation with perfluorinated compounds but lacks an analytical signal intensity equation to retrospectively correct B1 inhomogeneity. Here, a workflow was proposed and validated to correct and quantify 19 F-MR signals from the inflamed mouse brain using a 19 F-CRP. METHODS In vivo 19 F-MR images were acquired in a neuroinflammation mouse model with a quadrature 19 F-CRP using an imaging setup including 3D-printed components to acquire co-localized anatomical and 19 F images. Model-based corrections were validated on a uniform 19 F phantom and in the neuroinflammatory model. Corrected 19 F-MR images were benchmarked against reference images and overlaid on in vivo 1 H-MR images. Computed concentration uncertainty maps using Monte Carlo simulations served as a measure of performance of the B1 corrections. RESULTS Our study reports on the first quantitative in vivo 19 F-MR images of an inflamed mouse brain using a 19 F-CRP, including in vivo T1 calculations for 19 F-nanoparticles during pathology and B1 corrections for 19 F-signal quantification. Model-based corrections markedly improved 19 F-signal quantification from errors > 50% to < 10% in a uniform phantom (p < 0.001). Concentration uncertainty maps ex vivo and in vivo yielded uncertainties that were generally < 25%. Monte Carlo simulations prescribed SNR ≥ 10.1 to reduce uncertainties < 10%, and SNR ≥ 4.25 to achieve uncertainties < 25%. CONCLUSION Our model-based correction method facilitated 19 F signal quantification in the inflamed mouse brain when using the SNR-boosting 19 F-CRP technology, paving the way for future low-SNR 19 F-MRI applications in vivo.
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Affiliation(s)
- Paula Ramos Delgado
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany.,Experimental and Clinical Research Center, a cooperation between the Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association and the Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Mariya Aravina
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | - Jason M Millward
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | | | - Ludger Starke
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | | | - Andreas Pohlmann
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | - Thoralf Niendorf
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany.,Experimental and Clinical Research Center, a cooperation between the Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association and the Charité-Universitätsmedizin Berlin, Berlin, Germany.,MRI.TOOLS, Berlin, Germany
| | - Sonia Waiczies
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
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104
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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: 15] [Impact Index Per Article: 5.0] [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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105
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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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106
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Soustelle L, Troalen T, Hertanu A, Mchinda S, Ranjeva JP, Guye M, Varma G, Alsop DC, Duhamel G, Girard OM. A strategy to reduce the sensitivity of inhomogeneous magnetization transfer (ihMT) imaging to radiofrequency transmit field variations at 3 T. Magn Reson Med 2021; 87:1346-1359. [PMID: 34779020 DOI: 10.1002/mrm.29055] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/17/2021] [Accepted: 10/05/2021] [Indexed: 02/05/2023]
Abstract
PURPOSE To minimize the sensitivity of inhomogeneous magnetization transfer gradient-echo (ihMT-GRE) imaging to radiofrequency (RF) transmit field ( B 1 + ) inhomogeneities at 3 T. METHODS The ihMT-GRE sequence was optimized by varying the concentration of the RF saturation energy over time, obtained by increasing the saturation pulse power while extending the sequence repetition time (TR). Different protocols were tested using numerical simulations and human in vivo experiments in the brain white matter (WM) of healthy subjects at 3 T. The sensitivity of the ihMT ratio (ihMTR) to B 1 + variations was investigated by comparing measurements obtained at nominal transmitter adjustments and following a 20% global B 1 + drop. The resulting relative variations (δihMTR ) were evaluated voxelwise as a function of the local B 1 + distribution. The reproducibility of the protocol providing minimal B 1 + bias was assessed in a test-retest experiment. RESULTS In line with simulations, ihMT-GRE experiments conducted at high concentration of the RF energy over time demonstrated strong reduction of the B 1 + inhomogeneity effects in the human WM. Under the optimal conditions of 350-ms TR and 3-µT root mean square (RMS) saturation power, 73% of all WM voxels presented δihMTR below 10%. Reproducibility analysis yielded a close-to-zero systematic bias (ΔihMTR = -0.081%) and a high correlation (ρ² = 0.977) between test and retest experiments. CONCLUSION Concentrating RF saturation energy in ihMT-GRE sequences mitigates the sensitivity of the ihMTR to B 1 + variations and allows for clinical-ready ihMT imaging at 3 T. This feature is of particular interest for high and ultra-high field applications.
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Affiliation(s)
- Lucas Soustelle
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | | | - Andreea Hertanu
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Samira Mchinda
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Gopal Varma
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Alsop
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Guillaume Duhamel
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Olivier M Girard
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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107
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Iyyakkunnel S, Weigel M, Ganter C, Bieri O. Complex B 1 + mapping with Carr-Purcell spin echoes and its application to electrical properties tomography. Magn Reson Med 2021; 87:1250-1260. [PMID: 34752636 PMCID: PMC9298742 DOI: 10.1002/mrm.29020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 08/12/2021] [Accepted: 09/05/2021] [Indexed: 11/09/2022]
Abstract
Purpose To present a new complex‐valued B1+ mapping method for electrical properties tomography using Carr‐Purcell spin echoes. Methods A Carr‐Purcell (CP) echo train generates pronounced flip‐angle dependent oscillations that can be used to estimate the magnitude of B1+. To this end, a dictionary is used that takes into account the slice profile as well as T2 relaxation along the echo train. For validation, the retrieved B1+ map is compared with the actual flip angle imaging (AFI) method in a phantom (79 ε0, 0.34 S/m). Moreover, the phase of the first echo reflects the transceive phase. Overall, the CP echo train yields an estimate of the complex‐valued B1+, allowing electrical properties tomography with both permittivity and conductivity. The presented method is evaluated in phantom scans as well as for in vivo brain at 3 T. Results In the phantom, the obtained magnitude B1+ maps retrieved from the CP echo train and the AFI method show excellent agreement, and both the reconstructed estimated permittivity (79 ± 3) ε0 and conductivity (0.35 ± 0.04) S/m values are in accordance with expectations. In the brain, the obtained electrical properties are also close to expectations. In addition to the retrieved complex B1+ information, the decay of the CP echo trains also yields an estimate for T2. Conclusion The CP sequence can be used to simultaneously provide both B1+ magnitude and phase estimations, and therefore allows for full reconstruction of the electrical properties.
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Affiliation(s)
- Santhosh Iyyakkunnel
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Carl Ganter
- Department of Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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108
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Guenthner C, Amthor T, Doneva M, Kozerke S. A unifying view on extended phase graphs and Bloch simulations for quantitative MRI. Sci Rep 2021; 11:21289. [PMID: 34711847 PMCID: PMC8553818 DOI: 10.1038/s41598-021-00233-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 10/05/2021] [Indexed: 12/16/2022] Open
Abstract
Quantitative MRI methods and learning-based algorithms require exact forward simulations. One critical factor to correctly describe magnetization dynamics is the effect of slice-selective RF pulses. While contemporary simulation techniques correctly capture their influence, they only provide final magnetization distributions, require to be run for each parameter set separately, and make it hard to derive general theoretical conclusions and to generate a fundamental understanding of echo formation in the presence of slice-profile effects. This work aims to provide a mathematically exact framework, which is equally intuitive as extended phase graphs (EPGs), but also considers slice-profiles through their natural spatial representation. We show, through an analytical, hybrid Bloch-EPG formalism, that the spatially-resolved EPG approach allows to exactly predict the signal dependency on off-resonance, spoiling moment, microscopic dephasing, and echo time. We also demonstrate that our formalism allows to use the same phase graph to simulate both gradient-spoiled and balanced SSFP-based MR sequences. We present a derivation of the formalism and identify the connection to existing methods, i.e. slice-selective Bloch, slice-selective EPG, and the partitioned EPG. As a use case, the proposed hybrid Bloch-EPG framework is applied to MR Fingerprinting.
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Affiliation(s)
- Christian Guenthner
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
- Philips Research, Hamburg, Germany.
| | | | | | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
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109
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Lee AM, Stait-Gardner T, Price WS. Explicit phenomenological solutions for magnetization exposed to an arbitrary NMR diffusion steady state pulse sequence. J Chem Phys 2021; 155:144204. [PMID: 34654301 DOI: 10.1063/5.0062190] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Explicit phenomenological solutions to recurrence relations for the bulk transverse and longitudinal magnetization found using the Torrey-Bloch equations with relaxation effects are used to investigate nuclear magnetic resonance (NMR) diffusion measurements. Of particular interest are steady state NMR (self-)diffusion measurements that reduce experimental time that can extend the techniques to quickly reacting systems. The solutions for bulk transverse and longitudinal magnetization presented here are used to investigate the average behavior of the transverse and longitudinal magnetization in forming a steady state and are used to derive new expressions for the steady state longitudinal magnetization. These solutions can be applied to a noninteracting spin 1/2 ensemble undergoing free diffusion exposed to an arbitrary NMR pulse sequence containing arbitrary magnetic field gradient waveforms. The closed algebraic form method presented here has an advantage over iterative procedures for calculating transverse and longitudinal magnetization for the analysis and development of steady state pulse sequences. Previous theoretical results for steady state diffusion measurements are also reproduced. The Mathematica code for these solutions is provided in the supplementary material.
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Affiliation(s)
- Anthony M Lee
- Nanoscale Organisation and Dynamics Group, Western Sydney University, Penrith, NSW 2751, Australia
| | - Timothy Stait-Gardner
- Nanoscale Organisation and Dynamics Group, Western Sydney University, Penrith, NSW 2751, Australia
| | - William S Price
- Nanoscale Organisation and Dynamics Group, Western Sydney University, Penrith, NSW 2751, Australia
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110
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Cruz G, Qi H, Jaubert O, Kuestner T, Schneider T, Botnar RM, Prieto C. Generalized low-rank nonrigid motion-corrected reconstruction for MR fingerprinting. Magn Reson Med 2021; 87:746-763. [PMID: 34601737 DOI: 10.1002/mrm.29027] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/12/2021] [Accepted: 09/09/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE Develop a novel low-rank motion-corrected (LRMC) reconstruction for nonrigid motion-corrected MR fingerprinting (MRF). METHODS Generalized motion-corrected (MC) reconstructions have been developed for steady-state imaging. Here we extend this framework to enable nonrigid MC for transient imaging applications with varying contrast, such as MRF. This is achieved by integrating low-rank dictionary-based compression into the generalized MC model to reconstruct MC singular images, reducing motion artifacts in the resulting parametric maps. The proposed LRMC reconstruction was applied for cardiac motion correction in 2D myocardial MRF (T1 and T2 ) with extended cardiac acquisition window (~450 ms) and for respiratory MC in free-breathing 3D myocardial and 3D liver MRF. Experiments were performed in phantom and 22 healthy subjects. The proposed approach was compared with reference spin echo (phantom) and with 2D electrocardiogram-triggered/breath-hold MOLLI and T2 gradient-and-spin echo conventional maps (in vivo 2D and 3D myocardial MRF). RESULTS Phantom results were in general agreement with reference spin-echo measurements, presenting relative errors of approximately 5.4% and 5.5% for T1 and short T2 (<100 ms), respectively. The proposed LRMC MRF reduced residual blurring artifacts with respect to no MC for cardiac or respiratory motion in all cases (2D and 3D myocardial, 3D abdominal). In 2D myocardial MRF, left-ventricle T1 values were 1150 ± 41 ms for LRMC MRF and 1010 ± 56 ms for MOLLI; T2 values were 43.8 ± 2.3 ms for LRMC MRF and 49.5 ± 4.5 ms for T2 gradient and spin echo. Corresponding measurements for 3D myocardial MRF were 1085 ± 30 ms and 1062 ± 29 ms for T1 , and 43.5 ± 1.9 ms and 51.7 ± 1.7 ms for T2 . For 3D liver, LRMC MRF measured liver T1 at 565 ± 44 ms and liver T2 at 35.4 ± 2.4 ms. CONCLUSION The proposed LRMC reconstruction enabled generalized (nonrigid) MC for 2D and 3D MRF, both for cardiac and respiratory motion. The proposed approach reduced motion artifacts in the MRF maps with respect to no motion compensation and achieved good agreement with reference measurements.
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Affiliation(s)
- Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Haikun Qi
- 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
| | - Thomas Kuestner
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | | | - Rene Michael Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Ding H, Velasco C, Ye H, Lindner T, Grech-Sollars M, O’Callaghan J, Hiley C, Chouhan MD, Niendorf T, Koh DM, Prieto C, Adeleke S. Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer. Cancers (Basel) 2021; 13:4742. [PMID: 34638229 PMCID: PMC8507535 DOI: 10.3390/cancers13194742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/08/2021] [Accepted: 09/16/2021] [Indexed: 11/25/2022] Open
Abstract
Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians' judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment.
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Affiliation(s)
- Hao Ding
- Imperial College School of Medicine, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK;
| | - Carlos Velasco
- School of Biomedical Engineering and Imaging Sciences, St Thomas’ Hospital, King’s College London, London SE1 7EH, UK; (C.V.); (C.P.)
| | - Huihui Ye
- State Key Laboratory of Modern Optical instrumentation, Zhejiang University, Hangzhou 310027, China;
| | - Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg Eppendorf, 20246 Hamburg, Germany;
| | - Matthew Grech-Sollars
- Department of Medical Physics, Royal Surrey NHS Foundation Trust, Surrey GU2 7XX, UK;
- Department of Surgery & Cancer, Imperial College London, London SW7 2AZ, UK
| | - James O’Callaghan
- UCL Centre for Medical Imaging, Division of Medicine, University College London, London W1W 7TS, UK; (J.O.); (M.D.C.)
| | - Crispin Hiley
- Cancer Research UK, Lung Cancer Centre of Excellence, University College London Cancer Institute, London WC1E 6DD, UK;
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Manil D. Chouhan
- UCL Centre for Medical Imaging, Division of Medicine, University College London, London W1W 7TS, UK; (J.O.); (M.D.C.)
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrueck, Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany;
| | - Dow-Mu Koh
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London SM2 5NG, UK;
- Department of Radiology, Royal Marsden Hospital, London SW3 6JJ, UK
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, St Thomas’ Hospital, King’s College London, London SE1 7EH, UK; (C.V.); (C.P.)
| | - Sola Adeleke
- High Dimensional Neurology Group, Queen’s Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Oncology, Guy’s & St Thomas’ Hospital, London SE1 9RT, UK
- School of Cancer & Pharmaceutical Sciences, King’s College London, London WC2R 2LS, UK
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Stout JN, Liao C, Gagoski B, Turk EA, Feldman HA, Bibbo C, Barth WH, Shainker SA, Wald LL, Grant PE, Adalsteinsson E. Quantitative T 1 and T 2 mapping by magnetic resonance fingerprinting (MRF) of the placenta before and after maternal hyperoxia. Placenta 2021; 114:124-132. [PMID: 34537569 DOI: 10.1016/j.placenta.2021.08.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 06/16/2021] [Accepted: 08/05/2021] [Indexed: 11/13/2022]
Abstract
INTRODUCTION MR relaxometry has been used to assess placental exchange function, but methods to date are not sufficiently fast to be robust to placental motion. Magnetic resonance fingerprinting (MRF) permits rapid, voxel-wise, intrinsically co-registered T1 and T2 mapping. After characterizing measurement error, we scanned pregnant women during air and oxygen breathing to demonstrate MRF's ability to detect placental oxygenation changes. METHODS The accuracy of FISP-based, sliding-window reconstructed MRF was tested on phantoms. MRF scans in 9-s breath holds were acquired at 3T in 31 pregnant women during air and oxygen breathing. A mixed effects model was used to test for changes in placenta relaxation times between physiological states, to assess the dependency on gestational age (GA), and the impact of placental motion. RESULTS MRF estimates of known phantom relaxation times resulted in mean absolute errors for T1 of 92 ms (4.8%), but T2 was less accurate at 16 ms (13.6%). During normoxia, placental T1 = 1825 ± 141 ms (avg ± standard deviation) and T2 = 60 ± 16 ms (gestational age range 24.3-36.7, median 32.6 weeks). In the statistical model, placental T2 rose and T1 remained contant after hyperoxia, and no GA dependency was observed for T1 or T2. DISCUSSION Well-characterized, motion-robust MRF was used to acquire T1 and T2 maps of the placenta. Changes with hyperoxia are consistent with a net increase in oxygen saturation. Toward the goal of whole-placenta quantitative oxygenation imaging over time, we aim to implement 3D MRF with integrated motion correction to improve T2 accuracy.
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Affiliation(s)
- Jeffrey N Stout
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA.
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Borjan Gagoski
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Esra Abaci Turk
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Henry A Feldman
- Centers for Clinical and Translational Research, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Carolina Bibbo
- Brigham and Women's Hospital, Division of Maternal-Fetal Medicine, Boston, MA, 02115, USA
| | - William H Barth
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Scott A Shainker
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Boston, MA, 02115, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, 02129, USA
| | - P Ellen Grant
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Elfar Adalsteinsson
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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Accuracy and repeatability of QRAPMASTER and MRF-vFA. Magn Reson Imaging 2021; 83:196-207. [PMID: 34506911 DOI: 10.1016/j.mri.2021.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 09/03/2021] [Accepted: 09/05/2021] [Indexed: 11/23/2022]
Abstract
Our purpose is to evaluate bias and repeatability of the quantitative MRI sequences QRAPMASTER, based on steady-state imaging, and variable Flip Angle MRF (MRF-VFA), based on the transient response. Both techniques are assessed with a standardized phantom and five volunteers on 1.5 T and 3 T clinical scanners. All scans were repeated eight times in consecutive weeks. In the phantom, the mean bias±95% confidence interval for T1 values with QRAPMASTER was 10 ± 10% on 1.5 T and 4 ± 13% on 3.0 T. The mean bias for T1 values with MRF-vFA was 21 ± 17% on 1.5 T and 9 ± 9% on 3.0 T. For T2 values the mean bias with QRAPMASTER was 12 ± 3% on 1.5 T and 23 ± 1% on 3.0 T. For T2 values the mean bias with MRF-vFA was 17 ± 1% on 1.5 T and 19 ± 2% on 3.0 T. QRAPMASTER estimated lower T1 and T2 values than MRF-vFA. Repeatability was good with low coefficients of variation (CoV). Mean CoV ± 95% confidence interval for T1 were 3.2 ± 0.4% on 1.5 T and 4.5 ± 0.8% on 3.0 T with QRAPMASTER and 2.7% ± 0.2% on 1.5 T and 2.5 ± 0.2% on 3.0 T with MRF-vFA. For T2 were 3.3 ± 1.9% on 1.5 T and 3.2 ± 0.6% on 3.0 T with QRAPMASTER and 2.0 ± 0.4% on 1.5 T and 5.7 ± 1.0% on 3.0 T with MRF-vFA. The in-vivo T1 and T2 are in the range of values previously reported by other authors. The in-vivo mean CoV ± 95% confidence interval in gray matter were for T1 1.7 ± 0.2% using QRAPMASTER and 0.7 ± 0.5% using MRF-vFA and for T2 were 0.9 ± 0.4% using QRAPMASTER and 2.4 ± 0.5% using MRF-vFA. In white matter were for T1 0.9 ± 0.3% using QRAPMASTER and 1.3 ± 1.1% using MRF-vFA and for T2 were 0.7 ± 0.4% using QRAPMASTER and 2.4 ± 0.4% using MRF-vFA. A GLM analysis showed that the variations in T1 and T2 mainly depend on the field strength and the subject, but not on the follow-up repetition in different days. This confirms the high repeatability of QRAPMASTER and MRF-vFA. In summary, QRAPMASTER and MRF-vFA on both systems were highly repeatable with moderate accuracy, providing results comparable to standard references. While repeatability was similar for both methods, QRAPMASTER was more accurate. QRAPMASTER is a tested commercial product but MRF-vFA is 4.77 times faster, which would ease the inclusion of quantitative relaxometry.
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Mickevicius NJ, Kim JP, Zhao J, Morris ZS, Hurst NJ, Glide-Hurst CK. Toward magnetic resonance fingerprinting for low-field MR-guided radiation therapy. Med Phys 2021; 48:6930-6940. [PMID: 34487357 DOI: 10.1002/mp.15202] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 08/17/2021] [Accepted: 08/25/2021] [Indexed: 12/14/2022] Open
Abstract
PURPOSE The acquisition of multiparametric quantitative magnetic resonance imaging (qMRI) is becoming increasingly important for functional characterization of cancer prior to- and throughout the course of radiation therapy. The feasibility of a qMRI method known as magnetic resonance fingerprinting (MRF) for rapid T1 and T2 mapping was assessed on a low-field MR-linac system. METHODS A three-dimensional MRF sequence was implemented on a 0.35T MR-guided radiotherapy system. MRF-derived measurements of T1 and T2 were compared to those obtained with gold standard single spin echo methods, and the impacts of the radiofrequency field homogeneity and scan times ranging between 6 and 48 min were analyzed by acquiring between 1 and 8 spokes per time point in a standard quantitative system phantom. The short-term repeatability of MRF was assessed over three measurements taken over a 10-h period. To evaluate transferability, MRF measurements were acquired on two additional MR-guided radiotherapy systems. Preliminary human volunteer studies were performed. RESULTS The phantom benchmarking studies showed that MRF is capable of mapping T1 and T2 values within 8% and 10% of gold standard measures, respectively, at 0.35T. The coefficient of variation of T1 and T2 estimates over three repeated scans was < 5% over a broad range of relaxation times. The T1 and T2 times derived using a single-spoke MRF acquisition across three scanners were near unity and mean percent errors in T1 and T2 estimates using the same phantom were < 3%. The mean percent differences in T1 and T2 as a result of truncating the scan time to 6 min over the large range of relaxation times in the system phantom were 0.65% and 4.05%, respectively. CONCLUSIONS The technical feasibility and accuracy of MRF on a low-field MR-guided radiation therapy device has been demonstrated. MRF can be used to measure accurate T1 and T2 maps in three dimensions from a brief 6-min scan, offering strong potential for efficient and reproducible qMRI for future clinical trials in functional plan adaptation and tumor/normal tissue response assessment.
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Affiliation(s)
- Nikolai J Mickevicius
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Joshua P Kim
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan, USA
| | - Jiwei Zhao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Zachary S Morris
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Newton J Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Wang M, Perucho JAU, Cao P, Vardhanabhuti V, Cui D, Wang Y, Khong PL, Hui ES, Lee EYP. Repeatability of MR fingerprinting in normal cervix and utility in cervical carcinoma. Quant Imaging Med Surg 2021; 11:3990-4003. [PMID: 34476184 DOI: 10.21037/qims-20-1382] [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: 12/21/2020] [Accepted: 04/08/2021] [Indexed: 11/06/2022]
Abstract
Background Magnetic resonance fingerprinting (MRF) is a fast-imaging acquisition technique that generates quantitative and co-registered parametric maps. The aim of this feasibility study was to evaluate the agreement between MRF and phantom reference values, scan-rescan repeatability of MRF in normal cervix, and its ability to distinguish cervical carcinoma (CC) from normal cervical tissues. Methods An International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) phantom was scanned using MRF 15 times over 65 days. Agreement between MRF and phantom reference T1 and T2 values was assessed by linear regression. Healthy volunteers and patients with suspected CC were prospectively recruited. MRF was repeated twice for healthy volunteers (MRF1 and MRF2). Volumes of interest of normal cervical tissues and CC were delineated on T1 and T2 maps. MRF scan-rescan repeatability was evaluated by Bland-Altman plots, within-subject coefficients of variation (wCV), and intraclass correlation coefficients (ICC). T1 and T2 values were compared between CC and normal cervical tissues using Mann-Whitney U test. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic efficiency. Results Strong correlations were observed between MRF and phantom (R2=0.999 for T1, 0.981 for T2). Twelve healthy volunteers (28.7±5.1 years) and 28 patients with CC (54.6±15.2 years) were recruited for the in-vivo experiments. Repeatability of MRF parameters were wCV <3% for T1, <5% for T2 and ICC ≥0.92 for T1, ≥0.94 for T2. T1 value of CC (1,529±112 ms) was higher than normal mucosa [MRF1: 1,430±129 ms, MRF2: 1,440±130 ms; P=0.031, area under the curve (AUC) ≥0.717] and normal stroma (MRF1: 1,258±101 ms, MRF2: 1,276±105 ms; P<0.001, AUC ≥0.946). T2 value of CC (69±9 ms) was lower than normal mucosa (MRF1: 88±16 ms, MRF2: 87±13 ms; P<0.001, AUC ≥0.854), but was not different from normal stroma (P=0.919). Conclusions Excellent agreement was observed between MRF and phantom reference values. MRF exhibited excellent scan-rescan repeatability in normal cervix with potential value in differentiating CC from normal cervical tissues.
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Affiliation(s)
- Mandi Wang
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Jose A U Perucho
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Peng Cao
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Varut Vardhanabhuti
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Di Cui
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Yiang Wang
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Pek-Lan Khong
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Edward S Hui
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Elaine Y P Lee
- Department of Diagnostic Radiology, Queen Mary Hospital, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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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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Freitas AC, Gaspar AS, Sousa I, Teixeira RPAG, Hajnal JV, Nunes RG. Improving B 1 + parametric estimation in the brain from multispin-echo sequences using a fusion bootstrap moves solver. Magn Reson Med 2021; 86:2426-2440. [PMID: 34231250 DOI: 10.1002/mrm.28878] [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: 12/11/2020] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE To simultaneously estimate the B 1 + field (along with the T2 ) in the brain with multispin-echo (MSE) sequences and dictionary matching. METHODS T2 mapping provides clinically relevant information such as in the assessment of brain degenerative diseases. It is commonly obtained with MSE sequences, and accuracy can be further improved by matching the MSE signal to a precomputed dictionary of echo-modulation curves. For additional T1 quantification, transmit B 1 + field knowledge is also required. Preliminary work has shown that although simultaneous brain B 1 + estimation along with T2 is possible, it presents a bimodal distribution with the main peak coinciding with the true value. By taking advantage of this, the B 1 + maps are expected to be spatially smooth by applying an iterative method that takes into account each pixel neighborhood known as the fusion bootstrap moves solver (FBMS). The effect of the FBMS on B 1 + accuracy and piecewise smoothness is investigated and different spatial regularization levels are compared. Total variation regularization was used for both B 1 + and T2 simultaneous estimation because of its simplicity as an initial proof-of-concept; future work could explore non edge-preserving regularization independently for B 1 + . RESULTS Improvements in B 1 + accuracy (up to 45.37% and 16.81% B 1 + error decrease) and recovery of spatially homogeneous maps are shown in simulations and in vivo 3.0T brain data, respectively. CONCLUSION Accurate B 1 + estimated values can be obtained from widely available MSE sequences while jointly estimating T2 maps with the use of echo-modulation curve matching and FBMS at no further cost.
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Affiliation(s)
- Andreia C Freitas
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Andreia S Gaspar
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Inês Sousa
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Rui P A G Teixeira
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Rita G Nunes
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
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Liu H, van der Heide O, van den Berg CAT, Sbrizzi A. Fast and accurate modeling of transient-state, gradient-spoiled sequences by recurrent neural networks. NMR IN BIOMEDICINE 2021; 34:e4527. [PMID: 33949718 PMCID: PMC8244023 DOI: 10.1002/nbm.4527] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 03/26/2021] [Indexed: 05/11/2023]
Abstract
Fast and accurate modeling of MR signal responses are typically required for various quantitative MRI applications, such as MR fingerprinting. This work uses a new extended phase graph (EPG)-Bloch model for accurate simulation of transient-state, gradient-spoiled MR sequences, and proposes a recurrent neural network (RNN) as a fast surrogate of the EPG-Bloch model for computing large-scale MR signals and derivatives. The computational efficiency of the RNN model is demonstrated by comparisons with other existing models, showing one to three orders of acceleration compared with the latest GPU-accelerated, open-source EPG package. By using numerical and in vivo brain data, two used cases, namely, MRF dictionary generation and optimal experimental design, are also provided. Results show that the RNN surrogate model can be efficiently used for computing large-scale dictionaries of transient-state signals and derivatives within tens of seconds, resulting in several orders of magnitude acceleration with respect to state-of-the-art implementations. The practical application of transient-state quantitative techniques can therefore be substantially facilitated.
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Affiliation(s)
- Hongyan Liu
- Center for Image SciencesUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Oscar van der Heide
- Center for Image SciencesUniversity Medical Center UtrechtUtrechtthe Netherlands
| | | | - Alessandro Sbrizzi
- Center for Image SciencesUniversity Medical Center UtrechtUtrechtthe Netherlands
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Qi H, Cruz G, Botnar R, Prieto C. Synergistic multi-contrast cardiac magnetic resonance image reconstruction. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200197. [PMID: 33966456 DOI: 10.1098/rsta.2020.0197] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Cardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matching. Furthermore, extra efforts to deal with respiratory and cardiac motion by triggering and gating further increase the scan time. Several techniques have been developed to speed up CMR acquisitions, which usually acquire less data than that required by the Nyquist-Shannon sampling theorem, followed by regularized reconstruction to mitigate undersampling artefacts. Recent advances in CMR parametric mapping speed up CMR by synergistically exploiting spatial-temporal and contrast redundancies. In this article, we will review the recent developments in multi-contrast CMR image reconstruction for parametric mapping with special focus on low-rank and model-based reconstructions. Deep learning-based multi-contrast reconstruction has recently been proposed in other magnetic resonance applications. These developments will be covered to introduce the general methodology. Current technical limitations and potential future directions are discussed. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
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Affiliation(s)
- Haikun Qi
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - René Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Cui D, Hui ES, Cao P. A multi-inversion-recovery magnetic resonance fingerprinting for multi-compartment water mapping. Magn Reson Imaging 2021; 81:82-87. [PMID: 34146651 DOI: 10.1016/j.mri.2021.06.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 06/11/2021] [Accepted: 06/15/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE This study aimed at introducing short-T1/T2 compartment to MR fingerprinting (MRF) at 3 T. Water that is bound to myelin macromolecules have significantly shorter T1 and T2 than free water and can be distinguished from free water by multi-compartment analysis. METHODS We developed a new multi-inversion-recovery (mIR) water mapping-MRF based on an unbalanced steady-state coherent sequence (FISP). mIR pulses with an interval of 400 or 500 repetition times (TRs) were inserted into the conventional FISP MRF sequence. Data from our proposed mIR MRF was used to quantify different compartments, including myelin water, gray matter free water, and white matter free water, of brain water by virtue of the iterative non-negative least square (NNLS) with reweighting. Three healthy volunteers were scanned with mIR MRF on a clinical 3 T MRI. RESULTS Using an extended phase graph simulation, we found that our proposed mIR scheme with four IR pulses allowed differentiation between short and long T1/T2 components. For in vivo experiments, we achieved the quantification of myelin water, gray matter water, and white matter water at an image resolution of 1.17 × 1.17 × 5 mm3/pixel. As compared to the conventional MRF technique with single IR, our proposed mIR improved the detection of myelin water content. In addition, mIR MRF using spiral-in/out trajectory provided a higher signal level compared with that with spiral-out trajectory. Myelin water quantification using mIR MRF with 4 IR and 5 IR pulses were qualitatively similar. Meanwhile, 5 IR MRF showed fewer artifacts in myelin water detection. CONCLUSION We developed a new mIR MRF sequence for the rapid quantification of brain water compartments.
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Affiliation(s)
- Di Cui
- Department of Diagnostic Radiology, The University of Hong Kong, HKSAR, China
| | - Edward S Hui
- Department of Rehabilitation Science, The Hong Kong Polytechnic University, Hong Kong, HKSAR, China
| | - Peng Cao
- Department of Diagnostic Radiology, The University of Hong Kong, HKSAR, China.
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Zhu X, Tan F, Johnson K, Larson P. Optimizing trajectory ordering for fast radial ultra-short TE (UTE) acquisitions. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 327:106977. [PMID: 33873091 PMCID: PMC8164474 DOI: 10.1016/j.jmr.2021.106977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 03/26/2021] [Accepted: 03/30/2021] [Indexed: 06/12/2023]
Abstract
PURPOSE Additional spoiler gradients are required in 3D UTE sequences with random view ordering to suppress magnetization refocusing. By leveraging the encoding gradient induced spoiling effect, the spoiler gradients could potentially be reduced or removed to shorten the TR and increase encoding efficiency. An analysis framework is built that models the gradient spoiling effects and a new ordering scheme is proposed for fast 3D UTE acquisition. THEORY AND METHODS UTE signal evolution and spatial encoding gradient induced spoiling effect are derived from the Bloch equations. And the concept is validated in 2D radial UTE simulation. Then an optimized ordering scheme, named reordered 2D golden angle (r2DGA) scheme, for 3D UTE acquisition is proposed. The r2DGA scheme is compared to the sequential and 3D golden angle schemes in both phantom and volunteer studies. RESULTS The proposed r2DGA ordering scheme was applied to two applications, single breath-holding and free breathing 3D lung MRI. With r2DGA ordering scheme, breath-holding lung MRI scan increased 60% scan efficiency by removing the spoiler gradients and the free breathing scan reduced 20% scan time compared to the 3D golden angle scheme by reducing the spoiler gradients. CONCLUSIONS The proposed r2DGA ordering scheme UTE acquisition reduces the need of spoiler gradients and increases the encoding efficiency, and shows improvements in both breath-holding and free breathing lung MRI applications.
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Affiliation(s)
- Xucheng Zhu
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, CA, United States; Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States; GE Healthcare, Menlo Park, CA, United States
| | - Fei Tan
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, CA, United States; Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States
| | - Kevin Johnson
- Medical Physics, University of Wisconsin, Madison, WI, United States; Radiology, University of Wisconsin, Madison, WI, United States
| | - Peder Larson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, CA, United States; Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States.
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Naarding KJ, Keene KR, Sardjoe Mishre ASD, Veeger TTJ, van de Velde NM, Prins AJ, Burakiewicz J, Verschuuren JJGM, van der Holst M, Niks EH, Kan HE. Preserved thenar muscles in non-ambulant Duchenne muscular dystrophy patients. J Cachexia Sarcopenia Muscle 2021; 12:694-703. [PMID: 33963807 PMCID: PMC8200430 DOI: 10.1002/jcsm.12711] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/10/2021] [Accepted: 03/29/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Clinical trials in Duchenne muscular dystrophy (DMD) focus primarily on ambulant patients. Results cannot be extrapolated to later disease stages due to a decline in targeted muscle tissue. In non-ambulant DMD patients, hand function is relatively preserved and crucial for daily-life activities. We used quantitative MRI (qMRI) to establish whether the thenar muscles could be valuable to monitor treatment effects in non-ambulant DMD patients. METHODS Seventeen non-ambulant DMD patients (range 10.2-24.1 years) and 13 healthy controls (range 9.5-25.4 years) underwent qMRI of the right hand at 3 T at baseline. Thenar fat fraction (FF), total volume (TV), and contractile volume (CV) were determined using 4-point Dixon, and T2water was determined using multiecho spin-echo. Clinical assessments at baseline (n = 17) and 12 months (n = 13) included pinch strength (kg), performance of the upper limb (PUL) 2.0, DMD upper limb patient reported outcome measure (PROM), and playing a video game for 10 min using a game controller. Group differences and correlations were assessed with non-parametric tests. RESULTS Total volume was lower in patients compared with healthy controls (6.9 cm3 , 5.3-9.0 cm3 vs. 13.0 cm3 , 7.6-15.8 cm3 , P = 0.010). CV was also lower in patients (6.3 cm3 , 4.6-8.3 cm3 vs. 11.9 cm3 , 6.9-14.6 cm3 , P = 0.010). FF was slightly elevated (9.7%, 7.3-11.4% vs. 7.7%, 6.6-8.4%, P = 0.043), while T2water was higher (31.5 ms, 30.0-32.6 ms vs. 28.1 ms, 27.8-29.4 ms, P < 0.001). Pinch strength and PUL decreased over 12 months (2.857 kg, 2.137-4.010 to 2.243 kg, 1.930-3.339 kg, and 29 points, 20-36 to 23 points, 17-30, both P < 0.001), while PROM did not (49 points, 36-57 to 44 points, 30-54, P = 0.041). All patients were able to play for 10 min at baseline or follow-up, but some did not comply with the study procedures regarding this endpoint. Pinch strength correlated with TV and CV in patients (rho = 0.72 and rho = 0.68) and controls (both rho = 0.89). PUL correlated with TV, CV, and T2water (rho = 0.57, rho = 0.51, and rho = -0.59). CONCLUSIONS Low thenar FF, increased T2water , correlation of muscle size with strength and function, and the decrease in strength and function over 1 year indicate that the thenar muscles are a valuable and quantifiable target for therapy in later stages of DMD. Further studies are needed to relate these data to the loss of a clinically meaningful milestone.
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Affiliation(s)
- Karin J Naarding
- Department of Neurology, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Duchenne Center, Leiden, Netherlands
| | - Kevin R Keene
- Department of Neurology, Leiden University Medical Center (LUMC), Leiden, Netherlands.,C.J. Gorter Center for High Field MRI, Department of Radiology, LUMC, Leiden, Netherlands
| | | | - Thom T J Veeger
- C.J. Gorter Center for High Field MRI, Department of Radiology, LUMC, Leiden, Netherlands
| | - Nienke M van de Velde
- Department of Neurology, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Duchenne Center, Leiden, Netherlands
| | - Arina J Prins
- Department of Neurology, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Duchenne Center, Leiden, Netherlands
| | - Jedrzej Burakiewicz
- C.J. Gorter Center for High Field MRI, Department of Radiology, LUMC, Leiden, Netherlands
| | - Jan J G M Verschuuren
- Department of Neurology, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Duchenne Center, Leiden, Netherlands
| | - Menno van der Holst
- Duchenne Center, Leiden, Netherlands.,Department of Orthopedics, Rehabilitation and Physiotherapy, Leiden University Medical Center, Leiden, Netherlands
| | - Erik H Niks
- Department of Neurology, Leiden University Medical Center (LUMC), Leiden, Netherlands.,Duchenne Center, Leiden, Netherlands
| | - Hermien E Kan
- Duchenne Center, Leiden, Netherlands.,C.J. Gorter Center for High Field MRI, Department of Radiology, LUMC, Leiden, Netherlands
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Non-contrast MRI of synovitis in the knee using quantitative DESS. Eur Radiol 2021; 31:9369-9379. [PMID: 33993332 DOI: 10.1007/s00330-021-08025-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 03/22/2021] [Accepted: 04/28/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVES To determine whether synovitis graded by radiologists using hybrid quantitative double-echo in steady-state (qDESS) images can be utilized as a non-contrast approach to assess synovitis in the knee, compared against the reference standard of contrast-enhanced MRI (CE-MRI). METHODS Twenty-two knees (11 subjects) with moderate to severe osteoarthritis (OA) were scanned using CE-MRI, qDESS with a high diffusion weighting (qDESSHigh), and qDESS with a low diffusion weighting (qDESSLow). Four radiologists graded the overall impression of synovitis, their diagnostic confidence, and regional grading of synovitis severity at four sites (suprapatellar pouch, intercondylar notch, and medial and lateral peripatellar recesses) in the knee using a 4-point scale. Agreement between CE-MRI and qDESS, inter-rater agreement, and intra-rater agreement were assessed using a linearly weighted Gwet's AC2. RESULTS Good agreement was seen between CE-MRI and both qDESSLow (AC2 = 0.74) and qDESSHigh (AC2 = 0.66) for the overall impression of synovitis, but both qDESS sequences tended to underestimate the severity of synovitis compared to CE-MRI. Good inter-rater agreement was seen for both qDESS sequences (AC2 = 0.74 for qDESSLow, AC2 = 0.64 for qDESSHigh), and good intra-rater agreement was seen for both sequences as well (qDESSLow AC2 = 0.78, qDESSHigh AC2 = 0.80). Diagnostic confidence was moderate to high for qDESSLow (mean = 2.36) and slightly less than moderate for qDESSHigh (mean = 1.86), compared to mostly high confidence for CE-MRI (mean = 2.73). CONCLUSIONS qDESS shows potential as an alternative MRI technique for assessing the severity of synovitis without the use of a gadolinium-based contrast agent. KEY POINTS The use of the quantitative double-echo in steady-state (qDESS) sequence for synovitis assessment does not require the use of a gadolinium-based contrast agent. Preliminary results found that low diffusion-weighted qDESS (qDESSLow) shows good agreement to contrast-enhanced MRI for characterization of the severity of synovitis, with a relative bias towards underestimation of severity. Preliminary results also found that qDESSLow shows good inter- and intra-rater agreement for the depiction of synovitis, particularly for readers experienced with the sequence.
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Liu D, Li W, Xu F, Zhu D, Shin T, Qin Q. Ensuring both velocity and spatial responses robust to B0/B1+ field inhomogeneities for velocity-selective arterial spin labeling through dynamic phase-cycling. Magn Reson Med 2021; 85:2723-2734. [PMID: 33349968 PMCID: PMC7962600 DOI: 10.1002/mrm.28622] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/15/2020] [Accepted: 11/09/2020] [Indexed: 01/22/2023]
Abstract
PURPOSE To evaluate both velocity and spatial responses of velocity-selective arterial spin labeling (VS-ASL), using velocity-insensitive and velocity-compensated waveforms for control modules, as well as a novel dynamic phase-cycling approach, at different B0 / B 1 + field inhomogeneities. METHODS In the presence of imperfect refocusing, the mechanism of phase-cycling the refocusing pulses through four dynamics was first theoretically analyzed with the conventional velocity-selective saturation (VSS) pulse train. Numerical simulations were then deployed to compare the performance of the Fourier-transform based velocity-selective inversion (FT-VSI) with these three different schemes in terms of both velocity and spatial responses under various B0 / B 1 + conditions. Phantom and human brain scans were performed to evaluate the three methods at B 1 + scales of 0.8, 1.0, and 1.2. RESULTS The simulations of FT-VSI showed that, under nonuniform B0 / B 1 + conditions, the scheme with velocity-insensitive control was susceptible to DC bias of the static spins as systematic error, while the scheme with velocity-compensated control had deteriorated velocity-selective labeling profiles and, thus, reduced labeling efficiency. Through numerical simulation, phantom scans, and brain perfusion measurements, the dynamic phase-cycling method demonstrated considerable improvements over these issues. CONCLUSION The proposed dynamic phase-cycling approach was demonstrated for the velocity-selective label and control modules with both velocity and spatial responses robust to a wide range of B0 and B 1 + field inhomogeneities.
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Affiliation(s)
- Dapeng Liu
- Department of Radiology; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Wenbo Li
- Department of Radiology; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Feng Xu
- Department of Radiology; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Dan Zhu
- Department of Biomedical Engineering; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Taehoon Shin
- Division of Mechanical and Biomedical Engineering, Ewha Womans University, Seoul, South Korea
- Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Qin Qin
- Department of Radiology; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Li T, Cui D, Ren G, Hui ES, Cai J. Investigation of the effect of acquisition schemes on time-resolved magnetic resonance fingerprinting. Phys Med Biol 2021; 66. [PMID: 33823496 DOI: 10.1088/1361-6560/abf51f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 04/06/2021] [Indexed: 01/27/2023]
Abstract
Purpose.This study aims to investigate the feasibility of different acquisition methods for time-resolved magnetic resonance fingerprinting (TR-MRF) in computer simulation.Methods.An extended cardiac-torso (XCAT) phantom is used to generate abdominal T1, T2, and proton density maps for MRF simulation. The simulated MRF technique consists of an IR-FISP MRF sequence with spiral trajectory acquisition. MRF maps were simulated with different numbers of repetitions from 1 to 15. Three different methods were used to generate TR-MRF maps: (1) continuous acquisition without delay between MRF repetitions; (2) continuous acquisition with 5 s delay between MRF repetitions; (3) triggered acquisition with variable delay between MRF repetitions to allow the next acquisition to start at different respiration phase. After the generation of TR-MRF maps, the image quality indexes including the absolute T1 and T2 values, signal-to-noise-ratio (SNR), tumor-to-liver contrast-to-noise ratio, error in the amplitude of diaphragm motion and tumor volume error were used to evaluate the reconstructed parameter maps. Three volunteers were recruited to test the feasibility of the selected acquisition method.Results.Dynamic MR parametric maps using three different acquisition methods were estimated. The overall and liver T1 value error, liver SNR in T1 and T2 maps, and tumor SNR from T1 maps from triggered method is statistically significantly better than the other two methods (p-value < 0.05). The other image quality indexes have no significant difference between the triggered method and the other two continuous acquisition methods. All image quality indexes exhibit no significant difference between the acquisition methods with 0 s and 5 s delay. The triggered method was successfully performed in three healthy volunteers.Conclusion.TR-MRF technique was investigated using three different acquisition methods in computer simulation where the triggered method showed better performance than the other two methods. The triggered method has been tested successfully in healthy volunteers.
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Affiliation(s)
- Tian Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | - Di Cui
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong
| | - Ge Ren
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | - Edward S Hui
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
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Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging. Neuroradiology 2021; 63:1831-1851. [PMID: 33835238 PMCID: PMC8528802 DOI: 10.1007/s00234-021-02703-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 03/28/2021] [Indexed: 12/04/2022]
Abstract
Purpose Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values. Methods To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II–IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue. Results The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm3 voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm3 FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency. Conclusion 3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints.
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Hucker P, Dacko M, Zaitsev M. Combining prospective and retrospective motion correction based on a model for fast continuous motion. Magn Reson Med 2021; 86:1284-1298. [PMID: 33829538 DOI: 10.1002/mrm.28783] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 03/05/2021] [Accepted: 03/06/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE Prospective motion correction (PMC) and retrospective motion correction (RMC) have different advantages and limitations. The present work aims to combine the advantages of both for rigid body motion, aiming at correcting for faster motions than was previously achievable. Additionally, it provides insights into the effects of motion on pulse sequences and MR signals with a goal of further improving motion correction in the future. METHODS The effective encoding trajectory and a global phase offset in a moving object are calculated based on complete gradient waveforms of an arbitrary sequence and a continuous motion model. These data are used to feed the forward signal model, which is then used in iterative image reconstruction to suppress the artifacts still present after the PMC. RESULTS Verification experiments with a rotation phantom and in vivo were performed. Predictions of simulated motion artifacts for PMC based on sequence waveforms are very accurate. The performance at combined PMC+RMC is limited by Nyquist violations in the sampled k-space and can be compensated by oversampling. CONCLUSION The combined correction results in better images than pure PMC in the presence of fast motion. The predictions of artifacts are very accurate, allowing for comparing sequences or protocols in simulations. The observed artifacts due to Nyquist violations are expected to be corrected by utilizing parallel imaging.
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Affiliation(s)
- Patrick Hucker
- Center for Diagnostic and Therapeutic Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Dacko
- Center for Diagnostic and Therapeutic Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Maxim Zaitsev
- Center for Diagnostic and Therapeutic Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
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128
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Savini G, Asteggiano C, Paoletti M, Parravicini S, Pezzotti E, Solazzo F, Muzic SI, Santini F, Deligianni X, Gardani A, Germani G, Farina LM, Bergsland N, Gandini Wheeler-Kingshott CAM, Berardinelli A, Bastianello S, Pichiecchio A. Pilot Study on Quantitative Cervical Cord and Muscular MRI in Spinal Muscular Atrophy: Promising Biomarkers of Disease Evolution and Treatment? Front Neurol 2021; 12:613834. [PMID: 33854470 PMCID: PMC8039452 DOI: 10.3389/fneur.2021.613834] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 02/15/2021] [Indexed: 12/11/2022] Open
Abstract
Introduction: Nusinersen is a recent promising therapy approved for the treatment of spinal muscular atrophy (SMA), a rare disease characterized by the degeneration of alpha motor neurons (αMN) in the spinal cord (SC) leading to progressive muscle atrophy and dysfunction. Muscle and cervical SC quantitative magnetic resonance imaging (qMRI) has never been used to monitor drug treatment in SMA. The aim of this pilot study is to investigate whether qMRI can provide useful biomarkers for monitoring treatment efficacy in SMA. Methods: Three adult SMA 3a patients under treatment with nusinersen underwent longitudinal clinical and qMRI examinations every 4 months from baseline to 21-month follow-up. The qMRI protocol aimed to quantify thigh muscle fat fraction (FF) and water-T2 (w-T2) and to characterize SC volumes and microstructure. Eleven healthy controls underwent the same SC protocol (single time point). We evaluated clinical and imaging outcomes of SMA patients longitudinally and compared SC data between groups transversally. Results: Patient motor function was stable, with only Patient 2 showing moderate improvements. Average muscle FF was already high at baseline (50%) and progressed over time (57%). w-T2 was also slightly higher than previously published data at baseline and slightly decreased over time. Cross-sectional area of the whole SC, gray matter (GM), and ventral horns (VHs) of Patients 1 and 3 were reduced compared to controls and remained stable over time, while GM and VHs areas of Patient 2 slightly increased. We found altered diffusion and magnetization transfer parameters in SC structures of SMA patients compared to controls, thus suggesting changes in tissue microstructure and myelin content. Conclusion: In this pilot study, we found a progression of FF in thigh muscles of SMA 3a patients during nusinersen therapy and a concurrent slight reduction of w-T2 over time. The SC qMRI analysis confirmed previous imaging and histopathological studies suggesting degeneration of αMN of the VHs, resulting in GM atrophy and demyelination. Our longitudinal data suggest that qMRI could represent a feasible technique for capturing microstructural changes induced by SMA in vivo and a candidate methodology for monitoring the effects of treatment, once replicated on a larger cohort.
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Affiliation(s)
- Giovanni Savini
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Carlo Asteggiano
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Matteo Paoletti
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Stefano Parravicini
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Elena Pezzotti
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Francesca Solazzo
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Shaun I. Muzic
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Francesco Santini
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Xeni Deligianni
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Alice Gardani
- Child Neuropsychiatry Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Giancarlo Germani
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Lisa M. Farina
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, Russell Square, London, United Kingdom
- Brain Connectivity Research Unit, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Stefano Bastianello
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Anna Pichiecchio
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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Marriott A, Bowen C, Rioux J, Brewer K. Simultaneous quantification of SPIO and gadolinium contrast agents using MR fingerprinting. Magn Reson Imaging 2021; 79:121-129. [PMID: 33774098 DOI: 10.1016/j.mri.2021.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 03/22/2021] [Accepted: 03/22/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Develop a magnetic resonance fingerprinting (MRF) methodology with R2∗ quantification, intended for use with simultaneous contrast agent concentration mapping, particularly gadolinium (Gd) and iron labelled CD8+ T cells. METHODS Variable-density spiral SSFP MRF was used, modified to allow variable TE, and with an exp.(-TE·R2∗) dictionary modulation. In vitro phantoms containing SPIO labelled cells and/or gadolinium were used to validate parameter maps, probe undersampling capacity, and verify dual quantification capabilities. A C57BL/6 mouse was imaged using MRF to demonstrate acceptable in vivo resolution and signal at 8× undersampling necessary for a 25-min scan. RESULTS Strong agreement was found between conventional and MRF-derived values for R1, R2, and R2∗. Expanded MRF allowed quantification of iron-loaded CD8+ T cells. Results were robust to 8× undersampling and enabled recreation of relaxation profiles for both a Gd agent and iron labelled cells simultaneously. In vivo data demonstrated sufficient SNR in undersampled data for parameter mapping to visualise key features. CONCLUSION MRF can be expanded to include R1, R2, and R2∗ mapping required for simultaneous quantification of gadolinium and SPIO in vitro, allowing for potential implementation of a variety of future in vivo studies using dual MR contrast agents, including molecular imaging of labelled cells.
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Affiliation(s)
- Anna Marriott
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada
| | - Chris Bowen
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada
| | - James Rioux
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada
| | - Kimberly Brewer
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada.
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130
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Gao X, Hucker P, Hennig J, Zaitsev M. Strategies to improve intratrain prospective motion correction for turbo spin-echo sequences with constant flip angles. Magn Reson Med 2021; 86:852-865. [PMID: 33724546 DOI: 10.1002/mrm.28763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 02/12/2021] [Accepted: 02/12/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE To investigate the effects of prospective motion correction on turbo spin echo sequences and optimize motion correction approaches, mitigating signal dropout artifacts caused by the imperfections of motion tracking data. METHODS Signal dropout artifacts caused by undesired phase deviations introduced by tracking errors are analyzed theoretically. To reduce the adverse effect of such deviations, two approaches are proposed: (1) freezing the correction for example, for even-numbered or higher number of echoes and (2) shifting the correction event prior to the left crusher gradient preceding the refocusing pulse. A comprehensive analysis is presented, including both signal simulations and experimental verifications in phantoms and in vivo. Performance of the proposed approach is validated in two healthy volunteers imaged under two types of motion conditions simulating inadvertent fast motions associated with discomfort and continuous large motions. RESULTS The results show that the proposed optimization is able to efficiently correct for the motion artifacts and at the same time avoid signal dropout artifacts. Specifically, performing correction every 4th echo prior to the left crusher gradient was shown to improve image quality. CONCLUSION An optimization approach is proposed to exploit the potential of external tracking for intra-echo-train motion artifact correction for turbo spin echo sequences.
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Affiliation(s)
- Xiang Gao
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Patrick Hucker
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Maxim Zaitsev
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
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131
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Metzner S, Wuebbeler G, Flassbeck S, Gatefait C, Kolbitsch C, Elster C. Bayesian uncertainty quantification for magnetic resonance fingerprinting. Phys Med Biol 2021; 66. [PMID: 33647894 DOI: 10.1088/1361-6560/abeae7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 03/01/2021] [Indexed: 11/11/2022]
Abstract
Magnetic Resonance Fingerprinting (MRF) is a promising technique for fast quantitative imaging of human tissue. In general, MRF is based on a sequence of highly undersampled MR images which are analyzed with a pre-computed dictionary. MRF provides valuable diagnostic parameters such as the $T_1$ and $T_2$ MR relaxation times. However, uncertainty characterization of dictionary-based MRF estimates for $T_1$ and $T_2$ has not been achieved so far, which makes it challenging to assess if observed differences in these estimates are significant and may indicate pathological changes of the underlying tissue. We propose a Bayesian approach for the uncertainty quantification of dictionary-based MRF which leads to probability distributions for $T_1$ and $T_2$ in every voxel. The distributions can be used to make probability statements about the relaxation times, and to assign uncertainties to their dictionary-based MRF estimates. All uncertainty calculations are based on the pre-computed dictionary and the observed sequence of undersampled MR images, and they can be calculated in short time. The approach is explored by analyzing MRF measurements of a phantom consisting of several tubes across which MR relaxation times are constant. The proposed uncertainty quantification is quantitatively consistent with the observed within-tube variability of estimated relaxation times. Furthermore, calculated uncertainties are shown to characterize well observed differences between the MRF estimates and the results obtained from high-accurate reference measurements. These findings indicate that a reliable uncertainty quantification is achieved. We also present results for simulated MRF data and an uncertainty quantification for an in vivo MRF measurement. MATLAB$^{\scriptsize \text{\textregistered}}$ source code implementing the proposed approach is made available.
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Affiliation(s)
- Selma Metzner
- Physikalisch-Technische Bundesanstalt, Berlin, GERMANY
| | - Gerd Wuebbeler
- Mathematical Modelling and Data Analysis, Physikalisch - Technische Bundesanstalt, Abbestrasse 2-12, Berlin, D-10587, GERMANY
| | | | - Constance Gatefait
- Physikalisch-Technische Bundesanstalt Abteilung 8 Medizinische Physik und metrologische Informationstechnologie, Berlin, Berlin, GERMANY
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt, Abbestraße 2-12, Berlin, 10587, GERMANY
| | - Clemens Elster
- Data Analysis and Measurement Uncertainty, Physikalisch-Technische Bundesanstalt, Abbestrasse 2-12, D-10587 Berlin, Berlin, GERMANY
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Bustin A, Hua A, Milotta G, Jaubert O, Hajhosseiny R, Ismail TF, Botnar RM, Prieto C. High-Spatial-Resolution 3D Whole-Heart MRI T2 Mapping for Assessment of Myocarditis. Radiology 2021; 298:578-586. [PMID: 33464179 PMCID: PMC7924517 DOI: 10.1148/radiol.2021201630] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 09/25/2020] [Accepted: 10/07/2020] [Indexed: 12/20/2022]
Abstract
Background Clinical guidelines recommend the use of established T2 mapping sequences to detect and quantify myocarditis and edema, but T2 mapping is performed in two dimensions with limited coverage and repetitive breath holds. Purpose To assess the reproducibility of an accelerated free-breathing three-dimensional (3D) whole-heart T2 MRI mapping sequence in phantoms and participants without a history of cardiac disease and to investigate its clinical performance in participants with suspected myocarditis. Materials and Methods Eight participants (three women, mean age, 31 years ± 4 [standard deviation]; cohort 1) without a history of cardiac disease and 25 participants (nine women, mean age, 45 years ± 17; cohort 2) with clinically suspected myocarditis underwent accelerated free-breathing 3D whole-heart T2 mapping with 100% respiratory scanning efficiency at 1.5 T. The participants were enrolled from November 2018 to August 2020. Three repeated scans were performed on 2 separate days in cohort 1. Segmental variations in T2 relaxation times of the left ventricular myocardium were assessed, and intrasession and intersession reproducibility were measured. In cohort 2, segmental myocardial T2 values, detection of focal inflammation, and map quality were compared with those obtained from clinical breath-hold two-dimensional (2D) T2 mapping. Statistical differences were assessed using the nonparametric Mann-Whitney and Kruskal-Wallis tests, whereas the paired Wilcoxon signed-rank test was used to assess subjective scores. Results Whole-heart T2 maps were acquired in a mean time of 6 minutes 53 seconds ± 1 minute 5 seconds at 1.5 mm3 resolution. Breath-hold 2D and free-breathing 3D T2 mapping had similar intrasession (mean T2 change of 3.2% and 2.3% for 2D and 3D, respectively) and intersession (4.8% and 4.9%, respectively) reproducibility. The two T2 mapping sequences showed similar map quality (P = .23, cohort 2). Abnormal myocardial segments were identified with confidence (score 3) in 14 of 25 participants (56%) with 3D T2 mapping and only in 10 of 25 participants (40%) with 2D T2 mapping. Conclusion High-spatial-resolution three-dimensional (3D) whole-heart T2 mapping shows high intrasession and intersession reproducibility and helps provide T2 myocardial characterization in agreement with clinical two-dimensional reference, while enabling 3D assessment of focal disease with higher confidence. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Friedrich in this issue.
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Affiliation(s)
- Aurélien Bustin
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Alina Hua
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Giorgia Milotta
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Olivier Jaubert
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Reza Hajhosseiny
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Tevfik F. Ismail
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - René M. Botnar
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Claudia Prieto
- From the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor, Lambeth Wing, St Thomas’ Hospital, London SE1 7EH, England (A.B., A.H., G.M., O.J., R.H., T.F.I., R.M.B., C.P.); and Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
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Santini F, Deligianni X, Paoletti M, Solazzo F, Weigel M, de Sousa PL, Bieri O, Monforte M, Ricci E, Tasca G, Pichiecchio A, Bergsland N. Fast Open-Source Toolkit for Water T2 Mapping in the Presence of Fat From Multi-Echo Spin-Echo Acquisitions for Muscle MRI. Front Neurol 2021; 12:630387. [PMID: 33716931 PMCID: PMC7952742 DOI: 10.3389/fneur.2021.630387] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 02/05/2021] [Indexed: 11/13/2022] Open
Abstract
Imaging has become a valuable tool in the assessment of neuromuscular diseases, and, specifically, quantitative MR imaging provides robust biomarkers for the monitoring of disease progression. Quantitative evaluation of fat infiltration and quantification of the T2 values of the muscular tissue's water component (wT2) are two of the most essential indicators currently used. As each voxel of the image can contain both water and fat, a two-component model for the estimation of wT2 must be used. In this work, we present a fast method for reconstructing wT2 maps obtained from conventional multi-echo spin-echo (MESE) acquisitions and released as Free Open Source Software. The proposed software is capable of fast reconstruction thanks to extended phase graphs (EPG) simulations and dictionary matching implemented on a general-purpose graphic processing unit. The program can also perform more conventional biexponential least-squares fitting of the data and incorporate information from an external water-fat acquisition to increase the accuracy of the results. The method was applied to the scans of four healthy volunteers and five subjects suffering from facioscapulohumeral muscular dystrophy (FSHD). Conventional multi-slice MESE acquisitions were performed with 17 echoes, and additionally, a 6-echo multi-echo gradient-echo (MEGE) sequence was used for an independent fat fraction calculation. The proposed reconstruction software was applied on the full datasets, and additionally to reduced number of echoes, respectively, to 8, 5, and 3, using EPG and biexponential least-squares fitting, with and without incorporating information from the MEGE acquisition. The incorporation of external fat fraction maps increased the robustness of the fitting with a reduced number of echoes per datasets, whereas with unconstrained fitting, the total of 17 echoes was necessary to retain an independence of wT2 from the level of fat infiltration. In conclusion, the proposed software can successfully be used to calculate wT2 maps from conventional MESE acquisition, allowing the usage of an optimized protocol with similar precision and accuracy as a 17-echo acquisition. As it is freely released to the community, it can be used as a reference for more extensive cohort studies.
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Affiliation(s)
- Francesco Santini
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Xeni Deligianni
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Matteo Paoletti
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Francesca Solazzo
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Matthias Weigel
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Allschwil, Switzerland.,Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Paulo Loureiro de Sousa
- ICube, Université de Strasbourg, Centre National de la Recherche Scientifique (CNRS), Strasbourg, France
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Mauro Monforte
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Enzo Ricci
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.,Dipartimento di Neuroscienze, Istituto di Neurologia, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Giorgio Tasca
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Anna Pichiecchio
- Advanced Imaging and Radiomics Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Niels Bergsland
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States.,Fondazione Don Carlo Gnocchi Onlus (IRCCS), Milan, Italy
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134
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Gao X, Kiselev VG, Lange T, Hennig J, Zaitsev M. Three-dimensional spatially resolved phase graph framework. Magn Reson Med 2021; 86:551-560. [PMID: 33608963 DOI: 10.1002/mrm.28732] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/23/2020] [Accepted: 01/25/2021] [Indexed: 11/12/2022]
Abstract
PURPOSE An open-source spatially resolved phase graph framework is proposed for simulating arbitrary pulse sequences in the presence of piece-wise constant gradients with arbitrary orientations in three dimensions. It generalizes the extended phase graph algorithm for analysis of nonperiodic sequences while preserving its efficiency, and is able to estimate the signal modulation in the 3D spatial domain. METHODS The framework extends the recursive magnetization-evolution algorithm to account for anisotropic diffusion and exploits a novel 3D k-space grid-merging method to balance the computational effort and memory requirements against acceptable simulation errors. A new postsimulation module is proposed to track and visualize the signal evolution both in the k-space and in the image domain, which can be used for simulating image artifacts or finding frequency-response profiles. To illustrate the developed technique, three examples are presented: (1) fast off-resonance calculation for dictionary building in MR fingerprinting, (2) validation of a steady-state sequence with quasi-isotropic diffusion weighting, and (3) investigation of the magnetization evolution in PRESS-based spectroscopic imaging. RESULTS The grid-merging algorithm of the proposed framework demonstrates high calculation efficiency exemplified by frequency-response simulation of pseudo steady-state or diffusion-weighted steady-state sequences. It further helps to visualize the signal evolution in PRESS-based sequences. CONCLUSIONS The proposed simulation framework has been validated based on several different example applications for analyzing signal evolution in the frequency and spatial domain.
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Affiliation(s)
- Xiang Gao
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Valerij G Kiselev
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Maxim Zaitsev
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
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135
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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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136
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Buonincontri G, Kurzawski JW, Kaggie JD, Matys T, Gallagher FA, Cencini M, Donatelli G, Cecchi P, Cosottini M, Martini N, Frijia F, Montanaro D, Gómez PA, Schulte RF, Retico A, Tosetti M. Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T. Neuroimage 2021; 226:117573. [PMID: 33221451 DOI: 10.1016/j.neuroimage.2020.117573] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 11/05/2020] [Accepted: 11/10/2020] [Indexed: 12/19/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is highly promising as a quantitative MRI technique due to its accuracy, robustness, and efficiency. Previous studies have found high repeatability and reproducibility of 2D MRF acquisitions in the brain. Here, we have extended our investigations to 3D MRF acquisitions covering the whole brain using spiral projection k-space trajectories. Our travelling head study acquired test/retest data from the brains of 12 healthy volunteers and 8 MRI systems (3 systems at 3 T and 5 at 1.5 T, all from a single vendor), using a study design not requiring all subjects to be scanned at all sites. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived PD T1 and T2 maps to an anatomical atlas, coefficients of variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated a high repeatability (CVs 0.7-1.3% for T1, 2.0-7.8% for T2, 1.4-2.5% for normalized PD) and reproducibility (CVs of 2.0-5.8% for T1, 7.4-10.2% for T2, 5.2-9.2% for normalized PD) in gray and white matter. Both repeatability and reproducibility improved when compared to similar experiments using 2D acquisitions. Three-dimensional MRF obtains highly repeatable and reproducible estimations of T1 and T2, supporting the translation of MRF-based fast quantitative imaging into clinical applications.
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Affiliation(s)
| | - Jan W Kurzawski
- IRCCS Stella Maris, Pisa, Italy; National Institute for Nuclear Physics (INFN), Pisa, Italy
| | - Joshua D Kaggie
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Tomasz Matys
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Matteo Cencini
- IRCCS Stella Maris, Pisa, Italy; Imago7 Foundation, Pisa, Italy
| | - Graziella Donatelli
- Imago7 Foundation, Pisa, Italy; U.O. Neuroradiologia, Azienda Ospedaliera Universitaria Pisana (AOUP), Pisa, Italy
| | - Paolo Cecchi
- U.O. Neuroradiologia, Azienda Ospedaliera Universitaria Pisana (AOUP), Pisa, Italy
| | - Mirco Cosottini
- Imago7 Foundation, Pisa, Italy; U.O. Neuroradiologia, Azienda Ospedaliera Universitaria Pisana (AOUP), Pisa, Italy; Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Nicola Martini
- U.O.C. Bioingegneria e Ing. Clinica, Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Francesca Frijia
- U.O.C. Bioingegneria e Ing. Clinica, Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Domenico Montanaro
- U.O.C. Risonanza Magnetica Specialistica e Neuroradiologia, Fondazione CNR/Regione Toscana G. Monasterio, Pisa-Massa, Italy
| | - Pedro A Gómez
- Imago7 Foundation, Pisa, Italy; Technical University of Munich, Munich, Germany
| | | | | | - Michela Tosetti
- IRCCS Stella Maris, Pisa, Italy; Imago7 Foundation, Pisa, Italy.
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137
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Sveinsson B, Gold GE, Hargreaves BA, Yoon D. Utilizing shared information between gradient-spoiled and RF-spoiled steady-state MRI signals. Phys Med Biol 2021; 66:01NT03. [PMID: 33246317 DOI: 10.1088/1361-6560/abce8a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
This work presents an analytical relationship between gradient-spoiled and RF-spoiled steady-state signals. The two echoes acquired in double-echo in steady-state scans are shown to lie on a line in the signal plane, where the two axes represent the amplitudes of each echo. The location along the line depends on the amount of spoiling and the diffusivity. The line terminates in a point corresponding to an RF-spoiled signal. In addition to the main contribution of demonstrating this signal relationship, we also include the secondary contribution of preliminary results from an example application of the relationship, in the form of a heuristic denoising method when both types of scans are performed. This is investigated in simulations, phantom scans, and in vivo scans. For the signal model, the main topic of this study, simulations confirmed its accuracy and explored its dependency on signal parameters and image noise. For the secondary topic of its preliminary application to reduce noise, simulations demonstrated the denoising method giving a reduction in noise-induced standard deviation of about 30%. The relative effect of the method on the signals is shown to depend on the slope of the described line, which is demonstrated to be zero at the Ernst angle. The phantom scans show a similar effect as the simulations. In vivo scans showed a slightly lower average improvement of about 28%.
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Affiliation(s)
- Bragi Sveinsson
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Boston, MA, United States of America. Harvard Medical School, Boston, MA, United States of America
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138
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Kiselev VG, Körzdörfer G, Gall P. Toward Quantification: Microstructure and Magnetic Resonance Fingerprinting. Invest Radiol 2021; 56:1-9. [PMID: 33186141 DOI: 10.1097/rli.0000000000000738] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Quantitative magnetic resonance imaging (MRI) is a long-standing challenge. We advocate that the origin of the problem is the simplification applied in commonly used models of the MRI signal relation to the target parameters of biological tissues. Two research fields are briefly reviewed as ways to respond to the challenge of quantitative MRI, both experiencing an exponential growth right now. Microstructure MRI strives to build physiology-based models from cells to signal and, given the signal, back to the cells again. Magnetic resonance fingerprinting aims at efficient simultaneous determination of multiple signal parameters. The synergy of these yet disjoined approaches promises truly quantitative MRI with specific target-oriented diagnostic tools rather than universal imaging methods.
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Affiliation(s)
- Valerij G Kiselev
- From the Medical Physics, Department of Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg
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139
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Keene KR, van Vught L, van de Velde NM, Ciggaar IA, Notting IC, Genders SW, Verschuuren JJ, Tannemaat MR, Kan HE, Beenakker JM. The feasibility of quantitative MRI of extra-ocular muscles in myasthenia gravis and Graves' orbitopathy. NMR IN BIOMEDICINE 2021; 34:e4407. [PMID: 32893386 PMCID: PMC7757175 DOI: 10.1002/nbm.4407] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 08/20/2020] [Accepted: 08/20/2020] [Indexed: 05/02/2023]
Abstract
Although quantitative MRI can be instrumental in the diagnosis and assessment of disease progression in orbital diseases involving the extra-ocular muscles (EOM), acquisition can be challenging as EOM are small and prone to eye-motion artefacts. We explored the feasibility of assessing fat fractions (FF), muscle volumes and water T2 (T2water ) of EOM in healthy controls (HC), myasthenia gravis (MG) and Graves' orbitopathy (GO) patients. FF, EOM volumes and T2water values were determined in 12 HC (aged 22-65 years), 11 MG (aged 28-71 years) and six GO (aged 28-64 years) patients at 7 T using Dixon and multi-echo spin-echo sequences. The EOM were semi-automatically 3D-segmented by two independent observers. MANOVA and t-tests were used to assess differences in FF, T2water and volume of EOM between groups (P < .05). Bland-Altman limits of agreement (LoA) were used to assess the reproducibility of segmentations and Dixon scans. The scans were well tolerated by all subjects. The bias in FF between the repeated Dixon scans was -0.7% (LoA: ±2.1%) for the different observers; the bias in FF was -0.3% (LoA: ±2.8%) and 0.03 cm3 (LoA: ± 0.36 cm3 ) for volume. Mean FF of EOM in MG (14.1% ± 1.6%) was higher than in HC (10.4% ± 2.5%). Mean muscle volume was higher in both GO (1.2 ± 0.4 cm3 ) and MG (0.8 ± 0.2 cm3 ) compared with HC (0.6 ± 0.2 cm3 ). The average T2water for all EOM was 24.6 ± 4.0 ms for HC, 24.0 ± 4.7 ms for MG patients and 27.4 ± 4.2 ms for the GO patient. Quantitative MRI at 7 T is feasible for measuring FF and muscle volumes of EOM in HC, MG and GO patients. The measured T2water was on average comparable with skeletal muscle, although with higher variation between subjects. The increased FF in the EOM in MG patients suggests that EOM involvement in MG is accompanied by fat replacement. The unexpected EOM volume increase in MG may provide novel insights into underlying pathophysiological processes.
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Affiliation(s)
- Kevin R. Keene
- CJ Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
| | - Luc van Vught
- CJ Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Department of OphthalmologyLeiden University Medical CenterLeidenthe Netherlands
| | | | - Isabeau A. Ciggaar
- CJ Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Department of OphthalmologyLeiden University Medical CenterLeidenthe Netherlands
| | - Irene C. Notting
- Department of OphthalmologyLeiden University Medical CenterLeidenthe Netherlands
| | - Stijn W. Genders
- Department of OphthalmologyLeiden University Medical CenterLeidenthe Netherlands
| | - Jan J.G.M. Verschuuren
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
- Duchenne Centerthe Netherlands
| | | | - Hermien E. Kan
- CJ Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Duchenne Centerthe Netherlands
| | - Jan‐Willem M. Beenakker
- CJ Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Department of OphthalmologyLeiden University Medical CenterLeidenthe Netherlands
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140
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Compressive MRI quantification using convex spatiotemporal priors and deep encoder-decoder networks. Med Image Anal 2020; 69:101945. [PMID: 33421921 DOI: 10.1016/j.media.2020.101945] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 11/09/2020] [Accepted: 12/15/2020] [Indexed: 12/12/2022]
Abstract
We propose a dictionary-matching-free pipeline for multi-parametric quantitative MRI image computing. Our approach has two stages based on compressed sensing reconstruction and deep learned quantitative inference. The reconstruction phase is convex and incorporates efficient spatiotemporal regularisations within an accelerated iterative shrinkage algorithm. This minimises the under-sampling (aliasing) artefacts from aggressively short scan times. The learned quantitative inference phase is purely trained on physical simulations (Bloch equations) that are flexible for producing rich training samples. We propose a deep and compact encoder-decoder network with residual blocks in order to embed Bloch manifold projections through multi-scale piecewise affine approximations, and to replace the non-scalable dictionary-matching baseline. Tested on a number of datasets we demonstrate effectiveness of the proposed scheme for recovering accurate and consistent quantitative information from novel and aggressively subsampled 2D/3D quantitative MRI acquisition protocols.
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141
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Drenthen GS, Backes WH, Jansen JFA. Estimating myelin-water content from anatomical and diffusion images using spatially undersampled myelin-water imaging through machine learning. Neuroimage 2020; 226:117626. [PMID: 33301943 DOI: 10.1016/j.neuroimage.2020.117626] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 11/15/2020] [Accepted: 11/28/2020] [Indexed: 12/28/2022] Open
Abstract
Myelin is vital for healthy neuronal development, and can therefore provide valuable information regarding neuronal maturation. Anatomical and diffusion weighted images (DWI) possess information related to the myelin content and the current study investigates whether quantitative myelin markers can be extracted from anatomical and DWI using neural networks. Thirteen volunteers (mean age 29y) are included, and for each subject, a residual neural network was trained using spatially undersampled reference myelin-water markers. The network is trained on a voxel-by-voxel basis, resulting in a large amount of training data for each volunteer. The inputs used are the anatomical contrasts (cT1w, cT2w), the standardized T1w/T2w ratio, estimates of the relaxation times (T1, T2) and their ratio (T1/T2), and common DWI metrics (FA, RD, MD, λ1, λ2, λ3). Furthermore, to estimate the added value of the DWI metrics, neural networks were trained using either the combined set (DWI, T1w and T2w) or only the anatomical (T1w and T2w) images. The reconstructed myelin-water maps are in good agreement with the reference myelin-water content in terms of the coefficient of variation (CoV) and the intraclass correlation coefficient (ICC). A 6-fold undersampling using both anatomical and DWI metrics resulted in ICC = 0.68 and CoV = 5.9%. Moreover, using twice the training data (3-fold undersampling) resulted in an ICC that is comparable to the reproducibility of the myelin-water imaging itself (CoV = 5.5% vs. CoV = 6.7% and ICC = 0.74 vs ICC = 0.80). To achieve this, beside the T1w, T2w images, DWI is required. This preliminary study shows the potential of machine learning approaches to extract specific myelin-content from anatomical and diffusion-weighted scans.
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Affiliation(s)
- Gerhard S Drenthen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands.
| | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | - Jacobus F A Jansen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands
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142
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Felisaz PF, Colelli G, Ballante E, Solazzo F, Paoletti M, Germani G, Santini F, Deligianni X, Bergsland N, Monforte M, Tasca G, Ricci E, Bastianello S, Figini S, Pichiecchio A. Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy. Eur J Radiol 2020; 134:109460. [PMID: 33296803 DOI: 10.1016/j.ejrad.2020.109460] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 09/04/2020] [Accepted: 11/29/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE Quantitative MRI (qMRI) plays a crucial role for assessing disease progression and treatment response in neuromuscular disorders, but the required MRI sequences are not routinely available in every center. The aim of this study was to predict qMRI values of water T2 (wT2) and fat fraction (FF) from conventional MRI, using texture analysis and machine learning. METHOD Fourteen patients affected by Facioscapulohumeral muscular dystrophy were imaged at both thighs using conventional and quantitative MR sequences. Muscle FF and wT2 were calculated for each muscle of the thighs. Forty-seven texture features were extracted for each muscle on the images obtained with conventional MRI. Multiple machine learning regressors were trained to predict qMRI values from the texture analysis dataset. RESULTS Eight machine learning methods (linear, ridge and lasso regression, tree, random forest (RF), generalized additive model (GAM), k-nearest-neighbor (kNN) and support vector machine (SVM) provided mean absolute errors ranging from 0.110 to 0.133 for FF and 0.068 to 0.115 for wT2. The most accurate methods were RF, SVM and kNN to predict FF, and tree, RF and kNN to predict wT2. CONCLUSION This study demonstrates that it is possible to estimate with good accuracy qMRI parameters starting from texture analysis of conventional MRI.
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Affiliation(s)
- Paolo Florent Felisaz
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy; Department of Radiology, Desio Hospital, ASST Monza, Desio, Italy.
| | - Giulia Colelli
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy; Department of Mathematics, University of Pavia, Pavia, Italy
| | - Elena Ballante
- Department of Mathematics, University of Pavia, Pavia, Italy; BioData Science Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Francesca Solazzo
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy
| | - Matteo Paoletti
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy
| | - Giancarlo Germani
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy
| | - Francesco Santini
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Xeni Deligianni
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Mauro Monforte
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Giorgio Tasca
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Enzo Ricci
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Stefano Bastianello
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
| | - Silvia Figini
- Department of Political and Social Sciences, University of Pavia, Pavia, PV, Italy
| | - Anna Pichiecchio
- Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
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143
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López K, Neji R, Bustin A, Rashid I, Hajhosseiny R, Malik SJ, Teixeira RPAG, Razavi R, Prieto C, Roujol S, Botnar RM. Quantitative magnetization transfer imaging for non-contrast enhanced detection of myocardial fibrosis. Magn Reson Med 2020; 85:2069-2083. [PMID: 33201524 DOI: 10.1002/mrm.28577] [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: 02/06/2020] [Revised: 09/10/2020] [Accepted: 10/09/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE To develop a novel gadolinium-free model-based quantitative magnetization transfer (qMT) technique to assess macromolecular changes associated with myocardial fibrosis. METHODS The proposed sequence consists of a two-dimensional breath-held dual shot interleaved acquisition of five MT-weighted (MTw) spoiled gradient echo images, with variable MT flip angles (FAs) and off-resonance frequencies. A two-pool exchange model and dictionary matching were used to quantify the pool size ratio (PSR) and bound pool T2 relaxation ( T 2 B ). The signal model was developed and validated using 25 MTw images on a bovine serum albumin (BSA) phantom and in vivo human thigh muscle. A protocol with five MTw images was optimized for single breath-hold cardiac qMT imaging. The proposed sequence was tested in 10 healthy subjects and 5 patients with myocardial fibrosis and compared to late gadolinium enhancement (LGE). RESULTS PSR values in the BSA phantom were within the confidence interval of previously reported values (concentration 10% BSA = 5.9 ± 0.1%, 15% BSA = 9.4 ± 0.2%). PSR and T 2 B in thigh muscle were also in agreement with literature (PSR = 10.9 ± 0.3%, T 2 B = 6.4 ± 0.4 us). In 10 healthy subjects, global left ventricular PSR was 4.30 ± 0.65%. In patients, PSR was reduced in areas associated with LGE (remote: 4.68 ± 0.70% vs. fibrotic: 3.12 ± 0.78 %, n = 5, P < .002). CONCLUSION In vivo model-based qMT mapping of the heart was performed for the first time, with promising results for non-contrast enhanced assessment of myocardial fibrosis.
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Affiliation(s)
- Karina López
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,MR Research Collaboration, Siemens Healthcare Limited, Frimley, UK
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Imran Rashid
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Shaihan J Malik
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Rui Pedro A G Teixeira
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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144
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Bruijnen T, van der Heide O, Intven MPW, Mook S, Lagendijk JJW, van den Berg CAT, Tijssen RHN. Technical feasibility of magnetic resonance fingerprinting on a 1.5T MRI-linac. Phys Med Biol 2020; 65:22NT01. [PMID: 32977318 DOI: 10.1088/1361-6560/abbb9d] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Hybrid MRI-linac (MRL) systems enable daily multiparametric quantitative MRI to assess tumor response to radiotherapy. Magnetic resonance fingerprinting (MRF) may provide time efficient means of rapid multiparametric quantitative MRI. The accuracy of MRF, however, relies on adequate control over system imperfections, such as eddy currents and [Formula: see text], which are different and not as well established on MRL systems compared to diagnostic systems. In this study we investigate the technical feasibility of gradient spoiled 2D MRF on a 1.5T MRL. We show with phantom experiments that the MRL generates reliable MRF signals that are temporally stable during the day and have good agreement with spin-echo reference measurements. Subsequent in-vivo MRF scans in healthy volunteers and a patient with a colorectal liver metastasis showed good image quality, where the quantitative values of selected organs corresponded with the values reported in literature. Therefore we conclude that gradient spoiled 2D MRF is feasible on a 1.5T MRL with similar performance as on a diagnostic system. The precision and accuracy of the parametric maps are sufficient for further investigation of the clinical utility of MRF for online quantitatively MRI-guided radiotherapy.
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Affiliation(s)
- T Bruijnen
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands. Computational Imaging Group for MRI Diagnostics and Therapy, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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145
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Fatemi Y, Danyali H, Helfroush MS, Amiri H. Fast T 2 mapping using multi-echo spin-echo MRI: A linear order approach. Magn Reson Med 2020; 84:2815-2830. [PMID: 32430979 PMCID: PMC7402028 DOI: 10.1002/mrm.28309] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 04/13/2020] [Accepted: 04/15/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE Multi-echo spin-echo sequence is commonly used for T2 mapping. The estimated values using conventional exponential fit, however, are hampered by stimulated and indirect echoes leading to overestimation of T2 . Here, we present fast analysis of multi-echo spin-echo (FAMESE) as a novel approach to decrease the complexity of the search space, which leads to accelerated measurement of T2 . METHODS We developed FAMESE based on mathematical analysis of the Bloch equations in which the search space dimension decreased to only one. Then, we tested it in both phantom and human brain. Bland-Altman plot was used to assess the agreement between the estimated T2 values from FAMESE and the ones estimated from single-echo spin-echo sequence. The reliability of FAMESE was assessed by intraclass correlation coefficients. In addition, we investigated the noise stability of the method in synthetic and experimental data. RESULTS In both phantom and healthy participants, FAMESE provided accelerated and SNR-resistant T2 maps. The FAMESE had a very good agreement with the single-echo spin echo for the whole range of T2 values. The intraclass correlation coefficient values for FAMESE were excellent (ie, 0.9998 and 0.9860 < intraclass correlation coefficient < 0.9942 for the phantom and humans, respectively). CONCLUSION Our developed method FAMESE could be considered as a candidate for rapid T2 mapping with a clinically feasible scan time.
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Affiliation(s)
- Yaghoub Fatemi
- Department of Electrical and Electronics EngineeringShiraz University of TechnologyShirazIran
| | - Habibollah Danyali
- Department of Electrical and Electronics EngineeringShiraz University of TechnologyShirazIran
| | | | - Houshang Amiri
- Neuroscience Research CenterInstitute of NeuropharmacologyKerman University of Medical SciencesKermanIran
- Department of Radiology and Nuclear MedicineVU University Medical CenterAmsterdamthe Netherlands
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146
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Time‐resolved magnetic resonance fingerprinting for radiotherapy motion management. Med Phys 2020; 47:6286-6293. [DOI: 10.1002/mp.14513] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 08/20/2020] [Accepted: 09/21/2020] [Indexed: 01/13/2023] Open
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147
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Sharafi A, Zibetti MVW, Chang G, Cloos M, Regatte RR. MR fingerprinting for rapid simultaneous T 1 , T 2 , and T 1ρ relaxation mapping of the human articular cartilage at 3T. Magn Reson Med 2020; 84:2636-2644. [PMID: 32385949 PMCID: PMC7396294 DOI: 10.1002/mrm.28308] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 04/12/2020] [Accepted: 04/13/2020] [Indexed: 12/25/2022]
Abstract
PURPOSE To implement a novel technique for simultaneous, quantitative multiparametric mapping of the knee articular cartilage. METHODS A novel MR fingerprinting pulse sequence is proposed and implemented for simultaneous measurements of proton density, T1 , T2, and T1ρ relaxation times at 3T. The repeatability and reproducibility of the proposed technique were assessed in model phantoms. Institutional review board-approved MR fingerprinting imaging sequence was performed on healthy volunteers and patients with mild knee osteoarthritis. The Wilcoxon test was used to compare healthy controls and patients. The intra- and intersubject repeatability were assessed with coefficient of variation and the RMS coefficient of variation, respectively RESULTS: The Bland-Altman plots demonstrated an average difference of 4.67 ms, -0.09 ms, and 0.05 ms between 2 scans in the same scanner; and 9.68 ms, 0.29 ms, and -0.72 ms between the scans acquired on 2 different scanners for T1 , T2 , and T1ρ , respectively. The in vivo knee study showed excellent repeatability with RMS coefficient of variation less than 3%, 6%, and 5% for T1 , T2 , and T1ρ , respectively. The Wilcoxon test showed a significant difference between control and mild osteoarthritis patients for T1 (P = .04), T2 (P = .01), and T1ρ (P = .02) relaxation time in medial tibial cartilage, as well as for T2 relaxation time (P = .02) in medial femoral cartilage. CONCLUSION The proposed MRF sequence is fast and can simultaneously measure the T1 , T2 , T1ρ , and B 1 + maps in a single scan. It is able to discriminate between mild osteoarthritis patients and healthy volunteers.
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Affiliation(s)
- Azadeh Sharafi
- Bernard and Irene Schwartz Center for Biomedical ImagingDepartment of RadiologyNew York University School of MedicineNew YorkNYUSA
| | - Marcelo V. W. Zibetti
- Bernard and Irene Schwartz Center for Biomedical ImagingDepartment of RadiologyNew York University School of MedicineNew YorkNYUSA
| | - Gregory Chang
- Bernard and Irene Schwartz Center for Biomedical ImagingDepartment of RadiologyNew York University School of MedicineNew YorkNYUSA
| | - Martijn Cloos
- Bernard and Irene Schwartz Center for Biomedical ImagingDepartment of RadiologyNew York University School of MedicineNew YorkNYUSA
| | - Ravinder R. Regatte
- Bernard and Irene Schwartz Center for Biomedical ImagingDepartment of RadiologyNew York University School of MedicineNew YorkNYUSA
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148
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Chaudhari AS, Kogan F, Pedoia V, Majumdar S, Gold GE, Hargreaves BA. Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis. J Magn Reson Imaging 2020; 52:1321-1339. [PMID: 31755191 PMCID: PMC7925938 DOI: 10.1002/jmri.26991] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 10/22/2019] [Accepted: 10/22/2019] [Indexed: 12/16/2022] Open
Abstract
Osteoarthritis (OA) of the knee is a major source of disability that has no known treatment or cure. Morphological and compositional MRI is commonly used for assessing the bone and soft tissues in the knee to enhance the understanding of OA pathophysiology. However, it is challenging to extend these imaging methods and their subsequent analysis techniques to study large population cohorts due to slow and inefficient imaging acquisition and postprocessing tools. This can create a bottleneck in assessing early OA changes and evaluating the responses of novel therapeutics. The purpose of this review article is to highlight recent developments in tools for enhancing the efficiency of knee MRI methods useful to study OA. Advances in efficient MRI data acquisition and reconstruction tools for morphological and compositional imaging, efficient automated image analysis tools, and hardware improvements to further drive efficient imaging are discussed in this review. For each topic, we discuss the current challenges as well as potential future opportunities to alleviate these challenges. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
| | - Feliks Kogan
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Valentina Pedoia
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Center of Digital Health Innovation (CDHI), University of California San Francisco, San Francisco, California, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Center of Digital Health Innovation (CDHI), University of California San Francisco, San Francisco, California, USA
| | - Garry E. Gold
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Orthopaedic Surgery, Stanford University, Stanford, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Brian A. Hargreaves
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
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Nolte T, Scholten H, Gross-Weege N, Amthor T, Koken P, Doneva M, Schulz V. Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects. Magn Reson Med 2020; 85:1865-1880. [PMID: 33118649 DOI: 10.1002/mrm.28545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 09/03/2020] [Accepted: 09/14/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T1 and T2 estimation in the female breast at 1.5T. METHODS Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE. RESULTS Theoretic analysis predicts T1 under-/T2 overestimation if the nominal flip angles are underestimated and inversely, T1 under-/T2 overestimation if omitting slice profile correction, and T1 under-/T2 underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T2 left-right inhomogeneity between both breasts. Their correction decreased the T2 difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T2 most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions. CONCLUSION Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.
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Affiliation(s)
- Teresa Nolte
- Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Hannah Scholten
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
| | - Nicolas Gross-Weege
- Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Thomas Amthor
- Tomographic Imaging Systems, Philips Research Europe, Hamburg, Germany
| | - Peter Koken
- Tomographic Imaging Systems, Philips Research Europe, Hamburg, Germany
| | - Mariya Doneva
- Tomographic Imaging Systems, Philips Research Europe, Hamburg, Germany
| | - Volkmar Schulz
- Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.,Hyperion Hybrid Imaging Systems GmbH, Aachen, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.,Physics Institute III B, RWTH Aachen University, Aachen, Germany
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150
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Jaubert O, Cruz G, Bustin A, Hajhosseiny R, Nazir S, Schneider T, Koken P, Doneva M, Rueckert D, Masci PG, Botnar RM, Prieto C. T1, T2, and Fat Fraction Cardiac MR Fingerprinting: Preliminary Clinical Evaluation. J Magn Reson Imaging 2020; 53:1253-1265. [PMID: 33124081 DOI: 10.1002/jmri.27415] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 10/13/2020] [Accepted: 10/13/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Dixon cardiac magnetic resonance fingerprinting (MRF) has been recently introduced to simultaneously provide water T1 , water T2 , and fat fraction (FF) maps. PURPOSE To assess Dixon cardiac MRF repeatability in healthy subjects and its clinical feasibility in a cohort of patients with cardiovascular disease. POPULATION T1MES phantom, water-fat phantom, 11 healthy subjects and 19 patients with suspected cardiovascular disease. STUDY TYPE Prospective. FIELD STRENGTH/SEQUENCE 1.5T, inversion recovery spin echo (IRSE), multiecho spin echo (MESE), modified Look-Locker inversion recovery (MOLLI), T2 gradient spin echo (T2 -GRASE), 6-echo gradient rewound echo (GRE), and Dixon cardiac MRF. ASSESSMENT Dixon cardiac MRF precision was assessed through repeated scans against conventional MOLLI, T2 -GRASE, and PDFF in phantom and 11 healthy subjects. Dixon cardiac MRF native T1 , T2 , FF, postcontrast T1 and synthetic extracellular volume (ECV) maps were assessed in 19 patients in comparison to conventional sequences. Measurements in patients were performed in the septum and in late gadolinium enhanced (LGE) areas and assessed using mean value distributions, correlation, and Bland-Altman plots. Image quality and diagnostic confidence were assessed by three experts using 5-point scoring scales. STATISTICAL TESTS Paired Wilcoxon rank signed test and paired t-tests were applied. Statistical significance was indicated by *(P < 0.05). RESULTS Dixon cardiac MRF showed good overall precision in phantom and in vivo. Septal average repeatability was ~23 msec for T1 , ~2.2 msec for T2 , and ~1% for FF. Biases in healthy subjects/patients were measured at +37 msec*/+60 msec* and -8.8 msec*/-8 msec* when compared to MOLLI and T2 -GRASE, respectively. No statistically significant differences in postcontrast T1 (P = 0.17) and synthetic ECV (P = 0.19) measurements were observed in patients. DATA CONCLUSION Dixon cardiac MRF attained good overall precision in phantom and healthy subjects, while providing coregistered T1 , T2 , and fat fraction maps in a single breath-hold scan with similar or better image quality than conventional methods in patients. LEVEL OF EVIDENCE 2. TECHNICAL EFFICACY STAGE 2.
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Affiliation(s)
- Olivier Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | | | | | | | - Daniel Rueckert
- Department of Computing, Imperial College London, London, UK
| | - Pier-Giorgio Masci
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Rene M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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