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Misaka T, Hashimoto Y, Ashikaga R, Ishida T. Chemical shift-encoded MRI with compressed sensing combined with parallel imaging for proton density fat fraction measurement of the lumbar vertebral bone marrow. Medicine (Baltimore) 2024; 103:e37748. [PMID: 38608106 PMCID: PMC11018235 DOI: 10.1097/md.0000000000037748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 03/07/2024] [Indexed: 04/14/2024] Open
Abstract
We aimed to investigate the accuracy of proton density fat fraction (PDFF) measurement of the lumbar vertebral bone marrow using chemical shift-encoded magnetic resonance imaging (CSE-MRI) with compressed sensing combined with parallel imaging (CSPI). This study recruited a commercially available phantom, and 43 patients. Fully sampled data without CSPI and under-sampled data with CSPI acceleration factors of 2.4, 3.6, and 4.8 were acquired using a 1.5T imaging system. The relationships between PDFF measurements obtained with the no-CSPI acquisition and those obtained with each CSPI acquisition were assessed using Pearson correlation coefficient (r), linear regression analyses, and Bland-Altman analysis. The intra- and inter-observer variabilities of the PDFF measurements were evaluated using the intraclass correlation coefficient. PDFF measurements obtained with all acquisitions showed a significant correlation and strong agreement with the reference PDFF measurement of the phantom. PDFF measurements obtained using CSE-MRI with and without CSPI were positively correlated (all acquisitions: r = 0.99; P < .001). The mean bias was -0.31% to -0.17% with 95% limits of agreement within ±2.02%. The intra- and inter-observer agreements were excellent (intraclass correlation coefficient: 0.988 and 0.981, respectively). A strong agreement and positive correlation were observed between the PDFF measurements obtained using CSE-MRI with and without CSPI. PDFF measurement of the lumbar vertebral bone marrow using CSE-MRI with CSPI can be acquired with a maximum reduction of approximately 75% in the acquisition time compared with a fully sampled acquisition.
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Affiliation(s)
- Tomofumi Misaka
- Department of Radiology, Kindai University Nara Hospital, Ikoma, Japan
- Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan
| | | | | | - Takayuki Ishida
- Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan
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Lakhani DA, Zhou X, Tao S, Westerhold EM, Eidelman BH, Singh Sandhu SJ, Middlebrooks EH. Clinical application of ultra-high resolution compressed sensing time-of-flight MR angiography at 7T to detect small vessel pathology. Neuroradiol J 2023; 36:335-340. [PMID: 36173305 PMCID: PMC10268099 DOI: 10.1177/19714009221129576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
3D time-of-flight (TOF) MR angiography (MRA) benefits from ultra-high-field MRI (≥7 T) due to improved contrast and increased signal-to-noise ratio. However, high-resolution TOF MRA at 7T usually requires longer acquisition times. In addition, relatively higher specific absorption rate (SAR) at 7T limits the choice of optimal pulse sequence parameters, especially if venous saturation is employed. Here, we illustrate the clinical application of ultra-high resolution cerebral 7T TOF MRA using compressed sensing in cases of artery of Percheron and lacunar infarcts, which showed superior resolution and exquisite details pertinent to the clinical diagnosis. The technical challenges associated with high-resolution 7T imaging were alleviated by optimization of sequence parameters and utilization of compressed sensing acceleration.
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Affiliation(s)
- Dhairya A Lakhani
- Department of Radiology, West Virginia University, Morgantown, WV, USA
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Xiangzhi Zhou
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Shengzhen Tao
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
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Comi GP, Niks EH, Vandenborne K, Cinnante CM, Kan HE, Willcocks RJ, Velardo D, Magri F, Ripolone M, van Benthem JJ, van de Velde NM, Nava S, Ambrosoli L, Cazzaniga S, Bettica PU. Givinostat for Becker muscular dystrophy: A randomized, placebo-controlled, double-blind study. Front Neurol 2023; 14:1095121. [PMID: 36793492 PMCID: PMC9923355 DOI: 10.3389/fneur.2023.1095121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/09/2023] [Indexed: 02/03/2023] Open
Abstract
Objective No treatments are approved for Becker muscular dystrophy (BMD). This study investigated the efficacy and safety of givinostat, a histone deacetylase pan-inhibitor, in adults with BMD. Methods Males aged 18-65 years with a diagnosis of BMD confirmed by genetic testing were randomized 2:1 to 12 months treatment with givinostat or placebo. The primary objective was to demonstrate statistical superiority of givinostat over placebo for mean change from baseline in total fibrosis after 12 months. Secondary efficacy endpoints included other histological parameters, magnetic resonance imaging and spectroscopy (MRI and MRS) measures, and functional evaluations. Results Of 51 patients enrolled, 44 completed treatment. At baseline, there was greater disease involvement in the placebo group than givinostat, based on total fibrosis (mean 30.8 vs. 22.8%) and functional endpoints. Mean total fibrosis did not change from baseline in either group, and the two groups did not differ at Month 12 (least squares mean [LSM] difference 1.04%; p = 0.8282). Secondary histology parameters, MRS, and functional evaluations were consistent with the primary. MRI fat fraction in whole thigh and quadriceps did not change from baseline in the givinostat group, but values increased with placebo, with LSM givinostat-placebo differences at Month 12 of -1.35% (p = 0.0149) and -1.96% (p = 0.0022), respectively. Adverse events, most mild or moderate, were reported by 88.2% and 52.9% patients receiving givinostat and placebo. Conclusion The study failed to achieve the primary endpoint. However, there was a potential signal from the MRI assessments suggesting givinostat could prevent (or slow down) BMD disease progression.
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Affiliation(s)
- Giacomo P. Comi
- Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy,Department of Pathophysiology and Transplantation, Dino Ferrari Center, University of Milan, Milan, Italy,*Correspondence: Giacomo P. Comi ✉
| | - Erik H. Niks
- Department of Neurology, Leiden University Medical Center, Leiden, Netherlands,Duchenne Center Netherlands, Netherlands
| | | | | | - Hermien E. Kan
- Duchenne Center Netherlands, Netherlands,Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, Netherlands
| | | | - Daniele Velardo
- Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Francesca Magri
- Neurology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Michela Ripolone
- Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Jules J. van Benthem
- Department of Orthopedics, Rehabilitation and Physiotherapy, Leiden University Medical Center, Leiden, Netherlands
| | - Nienke M. van de Velde
- Department of Neurology, Leiden University Medical Center, Leiden, Netherlands,Duchenne Center Netherlands, Netherlands
| | - Simone Nava
- Radiology Department, Istituto Auxologico Italiano, IRCCS, Milan, Italy
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Trotier AJ, Dilharreguy B, Anandra S, Corbin N, Lefrançois W, Ozenne V, Miraux S, Ribot EJ. The Compressed Sensing MP2RAGE as a Surrogate to the MPRAGE for Neuroimaging at 3 T. Invest Radiol 2022; 57:366-378. [PMID: 35030106 PMCID: PMC9390231 DOI: 10.1097/rli.0000000000000849] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/08/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVES The magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequence provides quantitative T1 maps in addition to high-contrast morphological images. Advanced acceleration techniques such as compressed sensing (CS) allow its acquisition time to be compatible with clinical applications. To consider its routine use in future neuroimaging protocols, the repeatability of the segmented brain structures was evaluated and compared with the standard morphological sequence (magnetization-prepared rapid gradient echo [MPRAGE]). The repeatability of the T1 measurements was also assessed. MATERIALS AND METHODS Thirteen healthy volunteers were scanned either 3 or 4 times at several days of interval, on a 3 T clinical scanner, with the 2 sequences (CS-MP2RAGE and MPRAGE), set with the same spatial resolution (0.8-mm isotropic) and scan duration (6 minutes 21 seconds). The reconstruction time of the CS-MP2RAGE outputs (including the 2 echo images, the MP2RAGE image, and the T1 map) was 3 minutes 33 seconds, using an open-source in-house algorithm implemented in the Gadgetron framework.Both precision and variability of volume measurements obtained from CAT12 and VolBrain were assessed. The T1 accuracy and repeatability were measured on phantoms and on humans and were compared with literature.Volumes obtained from the CS-MP2RAGE and the MPRAGE images were compared using Student t tests (P < 0.05 was considered significant). RESULTS The CS-MP2RAGE acquisition provided morphological images of the same quality and higher contrasts than the standard MPRAGE images. Similar intravolunteer variabilities were obtained with the CS-MP2RAGE and the MPRAGE segmentations. In addition, high-resolution T1 maps were obtained from the CS-MP2RAGE. T1 times of white and gray matters and several deep gray nuclei are consistent with the literature and show very low variability (<1%). CONCLUSIONS The CS-MP2RAGE can be used in future protocols to rapidly obtain morphological images and quantitative T1 maps in 3-dimensions while maintaining high repeatability in volumetry and relaxation times.
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Affiliation(s)
- Aurélien J. Trotier
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Bixente Dilharreguy
- Biomedical Imaging Facility (pIBIO), UMS3767, CNRS/Université de Bordeaux, Bordeaux, France
| | - Serge Anandra
- Biomedical Imaging Facility (pIBIO), UMS3767, CNRS/Université de Bordeaux, Bordeaux, France
| | - Nadège Corbin
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
- UCL Queen Square Institute of Neurology, Wellcome Centre for Human Neuroimaging, University College of London, London, United Kingdom
| | - William Lefrançois
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Valery Ozenne
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Sylvain Miraux
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Emeline J. Ribot
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
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Comi GP, Niks EH, Cinnante CM, Kan HE, Vandenborne K, Willcocks RJ, Velardo D, Ripolone M, van Benthem JJ, van de Velde NM, Nava S, Ambrosoli L, Cazzaniga S, Bettica PU. Characterization of patients with Becker muscular dystrophy by histology, magnetic resonance imaging, function, and strength assessments. Muscle Nerve 2021; 65:326-333. [PMID: 34918368 PMCID: PMC9302983 DOI: 10.1002/mus.27475] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 12/07/2021] [Accepted: 12/11/2021] [Indexed: 12/21/2022]
Abstract
Introduction/Aims Becker muscular dystrophy (BMD) is characterized by variable disease severity and progression, prompting the identification of biomarkers for clinical trials. We used data from an ongoing phase II study to provide a comprehensive characterization of a cohort of patients with BMD, and to assess correlations between histological and magnetic resonance imaging (MRI) markers with muscle function and strength. Methods Eligible patients were ambulatory males with BMD, aged 18 to 65 years (200 to 450 meters on 6‐minute walk test). The following data were obtained: function test results, strength, fat‐fraction quantification using chemical shift‐encoded MRI (whole thigh and quadriceps), and fibrosis and muscle fiber area (MFA) of the brachial biceps. Results Of 70 patients screened, 51 entered the study. There was substantial heterogeneity between patients in muscle morphology (histology and MRI), with high fat replacement. Total fibrosis correlated significantly and mostly moderately with all functional endpoints, including both upper arm strength assessments (left and right elbow flexion rho −.574 and −.588, respectively [both P < .0001]), as did MRI fat fraction (whole thigh and quadriceps), for example, with four‐stair‐climb velocity −.554 and −.550, respectively (both P < .0001). Total fibrosis correlated significantly and moderately with both MRI fat fraction assessments (.500 [P = .0003] and .423 [.0024], respectively). Discussion In this BMD cohort, micro‐ and macroscopic morphological muscle parameters correlated moderately with each other and with functional parameters, potentially supporting the use of MRI fat fraction and histology as surrogate outcome measures in patients with BMD, although additional research is required to validate this.
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Affiliation(s)
- Giacomo P Comi
- Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.,Dino Ferrari Center, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Erik H Niks
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Duchenne Center Netherlands, The Netherlands
| | - Claudia M Cinnante
- Neuroradiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Hermien E Kan
- Duchenne Center Netherlands, The Netherlands.,C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Krista Vandenborne
- ImagingDMD and Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Rebecca J Willcocks
- ImagingDMD and Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Daniele Velardo
- Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.,Dino Ferrari Center, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Michela Ripolone
- Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Jules J van Benthem
- Department of Orthopedics, Rehabilitation and Physiotherapy, Leiden University Medical Center, Leiden, The Netherlands
| | - Nienke M van de Velde
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Duchenne Center Netherlands, The Netherlands
| | - Simone Nava
- Neuroradiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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Veeger TTJ, van Zwet EW, al Mohamad D, Naarding KJ, van de Velde NM, Hooijmans MT, Webb AG, Niks EH, de Groot JH, Kan HE. Muscle architecture is associated with muscle fat replacement in Duchenne and Becker muscular dystrophies. Muscle Nerve 2021; 64:576-584. [PMID: 34383334 PMCID: PMC9290788 DOI: 10.1002/mus.27399] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 08/02/2021] [Accepted: 08/07/2021] [Indexed: 12/21/2022]
Abstract
INTRODUCTION/AIMS Duchenne and Becker muscular dystrophies (DMD and BMD, respectively) are characterized by fat replacement of different skeletal muscles in a specific temporal order. Given the structural role of dystrophin in skeletal muscle mechanics, muscle architecture could be important in the progressive pathophysiology of muscle degeneration. Therefore, the aim of this study was to assess the role of muscle architecture in the progression of fat replacement in DMD and BMD. METHODS We assessed the association between literature-based leg muscle architectural characteristics and muscle fat fraction from 22 DMD and 24 BMD patients. Dixon-based magnetic resonance imaging estimates of fat fractions at baseline and 12 (only DMD) and 24 months were related to fiber length and physiological cross-sectional area (PCSA) using age-controlled linear mixed modeling. RESULTS DMD and BMD muscles with long fibers and BMD muscles with large PCSAs were associated with increased fat fraction. The effect of fiber length was stronger in muscles with larger PCSA. DISCUSSION Muscle architecture may explain the pathophysiology of muscle degeneration in dystrophinopathies, in which proximal muscles with a larger mass (fiber length × PCSA) are more susceptible, confirming the clinical observation of a temporal proximal-to-distal progression. These results give more insight into the mechanical role in the pathophysiology of muscular dystrophies. Ultimately, this new information can be used to help support the selection of current and the development of future therapies.
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Affiliation(s)
- Thom T. J. Veeger
- C.J. Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Erik W. van Zwet
- Department of BiostatisticsLeiden University Medical CenterLeidenThe Netherlands
| | - Diaa al Mohamad
- Department of BiostatisticsLeiden University Medical CenterLeidenThe Netherlands
| | - Karin J. Naarding
- Department of NeurologyLeiden University Medical CenterLeidenThe Netherlands
| | | | - Melissa T. Hooijmans
- Department of Radiology & Nuclear MedicineAmsterdam University Medical Centers, Location AMCAmsterdamThe Netherlands
| | - Andrew G. Webb
- C.J. Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Erik H. Niks
- Department of NeurologyLeiden University Medical CenterLeidenThe Netherlands
| | - Jurriaan H. de Groot
- Department of Rehabilitation MedicineLeiden University Medical CenterLeidenThe Netherlands
| | - Hermien E. Kan
- C.J. Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
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Li G, Wu D, Xu Z, Zuo X, Li X, Chang S, Dai Y. Evaluation of an accelerated 3D modulated flip-angle technique in refocused imaging with an extended echo-train sequence with compressed sensing for imaging of the knee: comparison with routine 2D MRI sequences. Clin Radiol 2020; 76:158.e13-158.e18. [PMID: 33250173 DOI: 10.1016/j.crad.2020.10.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 10/28/2020] [Indexed: 11/24/2022]
Abstract
AIM To accelerate the acquisition of high-resolution magnetic resonance imaging (MRI) by using the three-dimensional (3D) matrix sequence with compressed sensing and to compare it with conventional two-dimensional (2D) proton-density (PD) and fast spin-echo (FSE) sequences. MATERIALS AND METHODS 3D matrix, 2D FSE, and PD sequences were acquired from 68 participants using 3 T magnetic resonance imaging (MRI). Two radiologists scored image quality independently on a four-point scale. The structural similarity index (SSIM), and signal- (SNRs) and contrast-to-noise ratios (CNRs) of different anatomical structures of the knee were assessed and compared between sequences using Wilcoxon signed-rank tests and Cohen's kappa. RESULTS The median acquisition time reduction was 44.5%. There was a substantial to perfect agreement for the rating between the 3D matrix FSE and 2D FSE or PD sequences when evaluating cartilage, subchondral bone, and ligaments (κ=0.783-872, p>0.05). The mean SSIM values between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences was 0.994 and 0.971, respectively, which are acceptable. No significant differences were found in SNR between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences, even though the SNR appeared to be higher on routine 2D sequences. The CNR of subchondral bone-meniscus, subchondral bone-joint fluid, and meniscus-joint fluid did not differentiate significantly between the 3D matrix sequence and routine 2D sequences. CONCLUSIONS 3D matrix reduced the acquisition time in routine clinical knee MRI without the loss in image quality, SNR, and CNR.
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Affiliation(s)
- G Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - D Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, Shanghai, China
| | - Z Xu
- Xinzhuang Community Health Center, Shanghai, China
| | - X Zuo
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - X Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - S Chang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| | - Y Dai
- Central Research Institute, United Imaging Healthcare, Shanghai, China
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Iuga AI, Abdullayev N, Weiss K, Haneder S, Brüggemann-Bratke L, Maintz D, Rau R, Bratke G. Accelerated MRI of the knee. Quality and efficiency of compressed sensing. Eur J Radiol 2020; 132:109273. [DOI: 10.1016/j.ejrad.2020.109273] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/26/2020] [Accepted: 09/06/2020] [Indexed: 10/23/2022]
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Benjamin AJV, Bano W, Mair G, Thompson G, Casado A, Di Perri C, Davies M, Marshall I. Diagnostic quality assessment of IR-prepared 3D magnetic resonance neuroimaging accelerated using compressed sensing and k-space sampling order optimization. Magn Reson Imaging 2020; 74:31-45. [PMID: 32890675 DOI: 10.1016/j.mri.2020.08.025] [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: 01/30/2020] [Revised: 07/28/2020] [Accepted: 08/30/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE To evaluate the clinical diagnostic efficacy of accelerated 3D magnetic resonance (MR) neuroimaging by radiological assessment for image quality and artefacts. STUDY TYPE Prospective healthy volunteer study. SUBJECTS Eight healthy subjects. FIELD STRENGTH/SEQUENCE Inversion Recovery (IR) prepared 3D Gradient Echo (GRE) sequence on a 1.5 T GE Signa HDx scanner. ASSESSMENT Independent radiological diagnostic quality assessments of accelerated 3D MR brain datasets were carried out by four experienced neuro-radiologists who were blinded to the acceleration factor and to the subject. The radiological grading was based on a previously reported radiological scoring key that was used for image quality assessment of human brains. STATISTICAL TESTS Bland-Altman analysis. RESULTS Optimization of the k-space sampling order was important for preserving contrast in accelerated scans. Despite having lower scores than fully sampled datasets, the majority of the compressed sensing (CS) accelerated brain datasets with k-space sampling order optimization (19/24 datasets by Radiologist 1, 24/24 datasets by Radiologist 2 and 16/24 datasets by Radiologist 3) were graded to be fully diagnostic indicating that there was adequate confidence for performing gross structural assessment of the brain. CONCLUSION Optimization of k-space acquisition order improves the clinical utility of CS accelerated 3D neuroimaging. This method may be appropriate for routine radiological assessment of the brain.
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Affiliation(s)
- Arnold Julian Vinoj Benjamin
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, United Kingdom; Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom.
| | - Wajiha Bano
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, United Kingdom; Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom
| | - Grant Mair
- Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom
| | - Gerard Thompson
- Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom
| | - Ana Casado
- Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom
| | - Carol Di Perri
- Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom
| | - Michael Davies
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, United Kingdom
| | - Ian Marshall
- Centre for Clinical Brain Sciences, The University of Edinburgh, United Kingdom
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Wu Y, Ma Y, Capaldi DP, Liu J, Zhao W, Du J, Xing L. Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI. Magn Reson Imaging 2020; 66:93-103. [PMID: 30880112 PMCID: PMC6745016 DOI: 10.1016/j.mri.2019.03.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Revised: 03/01/2019] [Accepted: 03/13/2019] [Indexed: 11/28/2022]
Abstract
For sparse sampling that accelerates magnetic resonance (MR) image acquisition, non-linear reconstruction algorithms have been developed, which incorporated patient specific a prior information. More generic a prior information could be acquired via deep learning and utilized for image reconstruction. In this study, we developed a volumetric hierarchical deep residual convolutional neural network, referred to as T-Net, to provide a data-driven end-to-end mapping from sparsely sampled MR images to fully sampled MR images, where cartilage MR images were acquired using an Ultra-short TE sequence and retrospectively undersampled using pseudo-random Cartesian and radial acquisition schemes. The network had a hierarchical architecture that promoted the sparsity of feature maps and increased the receptive field, which were valuable for signal synthesis and artifact suppression. Relatively dense local connections and global shortcuts were established to facilitate residual learning and compensate for details lost in hierarchical processing. Additionally, volumetric processing was adopted to fully exploit spatial continuity in three-dimensional space. Data consistency was further enforced. The network was trained with 336 three-dimensional images (each consisting of 32 slices) and tested by 24 images. The incorporation of a priori information acquired via deep learning facilitated high acceleration factors (as high as 8) while maintaining high image fidelity (quantitatively evaluated using the structural similarity index measurement). The proposed T-Net had an improved performance as compared to several state-of-the-art networks.
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Affiliation(s)
- Yan Wu
- Radiation Oncology Department, Stanford University, Stanford 94305, CA, USA.
| | - Yajun Ma
- Radiology Department, University of California San Diego, La Jolla 92093, CA, USA.
| | | | - Jing Liu
- Radiology Department, University of California San Francisco, San Francisco 94107, CA, USA.
| | - Wei Zhao
- Radiation Oncology Department, Stanford University, Stanford 94305, CA, USA.
| | - Jiang Du
- Radiology Department, University of California San Diego, La Jolla 92093, CA, USA.
| | - Lei Xing
- Radiation Oncology Department, Stanford University, Stanford 94305, CA, USA.
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Strijkers GJ, Araujo EC, Azzabou N, Bendahan D, Blamire A, Burakiewicz J, Carlier PG, Damon B, Deligianni X, Froeling M, Heerschap A, Hollingsworth KG, Hooijmans MT, Karampinos DC, Loudos G, Madelin G, Marty B, Nagel AM, Nederveen AJ, Nelissen JL, Santini F, Scheidegger O, Schick F, Sinclair C, Sinkus R, de Sousa PL, Straub V, Walter G, Kan HE. Exploration of New Contrasts, Targets, and MR Imaging and Spectroscopy Techniques for Neuromuscular Disease - A Workshop Report of Working Group 3 of the Biomedicine and Molecular Biosciences COST Action BM1304 MYO-MRI. J Neuromuscul Dis 2020; 6:1-30. [PMID: 30714967 PMCID: PMC6398566 DOI: 10.3233/jnd-180333] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Neuromuscular diseases are characterized by progressive muscle degeneration and muscle weakness resulting in functional disabilities. While each of these diseases is individually rare, they are common as a group, and a large majority lacks effective treatment with fully market approved drugs. Magnetic resonance imaging and spectroscopy techniques (MRI and MRS) are showing increasing promise as an outcome measure in clinical trials for these diseases. In 2013, the European Union funded the COST (co-operation in science and technology) action BM1304 called MYO-MRI (www.myo-mri.eu), with the overall aim to advance novel MRI and MRS techniques for both diagnosis and quantitative monitoring of neuromuscular diseases through sharing of expertise and data, joint development of protocols, opportunities for young researchers and creation of an online atlas of muscle MRI and MRS. In this report, the topics that were discussed in the framework of working group 3, which had the objective to: Explore new contrasts, new targets and new imaging techniques for NMD are described. The report is written by the scientists who attended the meetings and presented their data. An overview is given on the different contrasts that MRI can generate and their application, clinical needs and desired readouts, and emerging methods.
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Affiliation(s)
| | - Ericky C.A. Araujo
- NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology & NMR Laboratory, CEA/DRF/IBFJ/MIRCen, Paris, France
| | - Noura Azzabou
- NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology & NMR Laboratory, CEA/DRF/IBFJ/MIRCen, Paris, France
| | | | - Andrew Blamire
- Institute of Cellular Medicine, Newcastle University, Newcastle-upon-Tyne, UK
| | - Jedrek Burakiewicz
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Pierre G. Carlier
- NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology & NMR Laboratory, CEA/DRF/IBFJ/MIRCen, Paris, France
| | - Bruce Damon
- Vanderbilt University Medical Center, Nashville, USA
| | - Xeni Deligianni
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland & Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | | | - Arend Heerschap
- Radboud University Medical Center, Nijmegen, the Netherlands
| | | | | | | | | | | | - Benjamin Marty
- NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology & NMR Laboratory, CEA/DRF/IBFJ/MIRCen, Paris, France
| | - Armin M. Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany & Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - Francesco Santini
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland & Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Olivier Scheidegger
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Fritz Schick
- University of Tübingen, Section on Experimental Radiology, Tübingen, Germany
| | | | | | | | - Volker Straub
- Institute of Cellular Medicine, Newcastle University, Newcastle-upon-Tyne, UK
| | | | - Hermien E. Kan
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
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12
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Hu HH, Branca RT, Hernando D, Karampinos DC, Machann J, McKenzie CA, Wu HH, Yokoo T, Velan SS. Magnetic resonance imaging of obesity and metabolic disorders: Summary from the 2019 ISMRM Workshop. Magn Reson Med 2019; 83:1565-1576. [PMID: 31782551 DOI: 10.1002/mrm.28103] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/04/2019] [Accepted: 11/11/2019] [Indexed: 02/06/2023]
Abstract
More than 100 attendees from Australia, Austria, Belgium, Canada, China, Germany, Hong Kong, Indonesia, Japan, Malaysia, the Netherlands, the Philippines, Republic of Korea, Singapore, Sweden, Switzerland, the United Kingdom, and the United States convened in Singapore for the 2019 ISMRM-sponsored workshop on MRI of Obesity and Metabolic Disorders. The scientific program brought together a multidisciplinary group of researchers, trainees, and clinicians and included sessions in diabetes and insulin resistance; an update on recent advances in water-fat MRI acquisition and reconstruction methods; with applications in skeletal muscle, bone marrow, and adipose tissue quantification; a summary of recent findings in brown adipose tissue; new developments in imaging fat in the fetus, placenta, and neonates; the utility of liver elastography in obesity studies; and the emerging role of radiomics in population-based "big data" studies. The workshop featured keynote presentations on nutrition, epidemiology, genetics, and exercise physiology. Forty-four proffered scientific abstracts were also presented, covering the topics of brown adipose tissue, quantitative liver analysis from multiparametric data, disease prevalence and population health, technical and methodological developments in data acquisition and reconstruction, newfound applications of machine learning and neural networks, standardization of proton density fat fraction measurements, and X-nuclei applications. The purpose of this article is to summarize the scientific highlights from the workshop and identify future directions of work.
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Affiliation(s)
- Houchun H Hu
- Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio
| | - Rosa Tamara Branca
- Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jürgen Machann
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany.,German Center for Diabetes Research, Tübingen, Germany.,Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Charles A McKenzie
- Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada
| | - Holden H Wu
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California
| | - Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - S Sendhil Velan
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore.,Singapore BioImaging Consortium, Agency for Science Technology and Research, Singapore
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13
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Lohöfer FK, Kaissis GA, Müller-Leisse C, Franz D, Katemann C, Hock A, Peeters JM, Rummeny EJ, Karampinos D, Braren RF. Acceleration of chemical shift encoding-based water fat MRI for liver proton density fat fraction and T2* mapping using compressed sensing. PLoS One 2019; 14:e0224988. [PMID: 31730658 PMCID: PMC6857925 DOI: 10.1371/journal.pone.0224988] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/25/2019] [Indexed: 01/22/2023] Open
Abstract
Objectives To evaluate proton density fat fraction (PDFF) and T2* measurements of the liver with combined parallel imaging (sensitivity encoding, SENSE) and compressed sensing (CS) accelerated chemical shift encoding-based water-fat separation. Methods Six-echo Dixon imaging was performed in the liver of 89 subjects. The first acquisition variant used acceleration based on SENSE with a total acceleration factor equal to 2.64 (acquisition labeled as SENSE). The second acquisition variant used acceleration based on a combination of CS with SENSE with a total acceleration factor equal to 4 (acquisition labeled as CS+SENSE). Acquisition times were compared between acquisitions and proton density fat fraction (PDFF) and T2*-values were measured and compared separately for each liver segment. Results Total scan duration was 14.5 sec for the SENSE accelerated image acquisition and 9.3 sec for the CS+SENSE accelerated image acquisition. PDFF and T2* values did not differ significantly between the two acquisitions (paired Mann-Whitney and paired t-test P>0.05 in all cases). CS+SENSE accelerated acquisition showed reduced motion artifacts (1.1%) compared to SENSE acquisition (12.3%). Conclusion CS+SENSE accelerates liver PDFF and T2*mapping while retaining the same quantitative values as an acquisition using only SENSE and reduces motion artifacts.
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Affiliation(s)
- Fabian K. Lohöfer
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
| | - Georgios A. Kaissis
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
| | - Christina Müller-Leisse
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
| | - Daniela Franz
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
| | | | | | | | - Ernst J. Rummeny
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
| | - Dimitrios Karampinos
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
| | - Rickmer F. Braren
- Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
- * E-mail:
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14
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Barnard AM, Lott DJ, Batra A, Triplett WT, Forbes SC, Riehl SL, Willcocks RJ, Smith BK, Vandenborne K, Walter GA. Imaging respiratory muscle quality and function in Duchenne muscular dystrophy. J Neurol 2019; 266:2752-2763. [PMID: 31350642 DOI: 10.1007/s00415-019-09481-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 07/17/2019] [Accepted: 07/18/2019] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Duchenne muscular dystrophy (DMD) is characterized by damage to muscles including the muscles involved in respiration. Dystrophic muscles become weak and infiltrated with fatty tissue, resulting in progressive respiratory impairment. The objective of this study was to assess respiratory muscle quality and function in DMD using magnetic resonance imaging and to determine the relationship to clinical respiratory function. METHODS Individuals with DMD (n = 36) and unaffected controls (n = 12) participated in this cross sectional magnetic resonance imaging study. Participants underwent dynamic imaging of the thorax to assess diaphragm and chest wall mobility and chemical shift-encoded imaging of the chest and abdomen to determine fatty infiltration of the accessory respiratory muscles. Additionally, clinical pulmonary function measures were obtained. RESULTS Thoracic cavity area was decreased in individuals with DMD compared to controls during tidal and maximal breathing. Individuals with DMD had reduced chest wall movement in the anterior-posterior direction during maximal inspirations and expirations, but diaphragm descent during maximal inspirations (normalized to height) was only decreased in a subset of individuals with maximal inspiratory pressures less than 60% predicted. Muscle fat fraction was elevated in all three expiratory muscles assessed (p < 0.001), and the degree of fatty infiltration correlated with percent predicted maximal expiratory pressures (r = - 0.70, p < 0.001). The intercostal muscles demonstrated minimal visible fatty infiltration; however, this analysis was qualitative and resolution limited. INTERPRETATION This magnetic resonance imaging investigation of diaphragm movement, chest wall movement, and accessory respiratory muscle fatty infiltration provides new insights into the relationship between disease progression and clinical respiratory function.
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Affiliation(s)
- Alison M Barnard
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA.,Department of Physiology and Functional Genomics, University of Florida, Gainesville, FL, USA
| | - Donovan J Lott
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | - Abhinandan Batra
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | - William T Triplett
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | - Sean C Forbes
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | - Samuel L Riehl
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | | | - Barbara K Smith
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | - Krista Vandenborne
- Department of Physical Therapy, University of Florida, Gainesville, FL, USA
| | - Glenn A Walter
- Department of Physiology and Functional Genomics, University of Florida, Gainesville, FL, USA.
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15
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Krishnamurthy R, Wang DJJ, Cervantes B, McAllister A, Nelson E, Karampinos DC, Hu HH. Recent Advances in Pediatric Brain, Spine, and Neuromuscular Magnetic Resonance Imaging Techniques. Pediatr Neurol 2019; 96:7-23. [PMID: 31023603 DOI: 10.1016/j.pediatrneurol.2019.03.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 02/25/2019] [Accepted: 03/03/2019] [Indexed: 12/21/2022]
Abstract
Magnetic resonance imaging (MRI) is a powerful radiologic tool with the ability to generate a variety of proton-based signal contrast from tissues. Owing to this immense flexibility in signal generation, new MRI techniques are constantly being developed, tested, and optimized for clinical utility. In addition, the safe and nonionizing nature of MRI makes it a suitable modality for imaging in children. In this review article, we summarize a few of the most popular advances in MRI techniques in recent years. In particular, we highlight how these new developments have affected brain, spine, and neuromuscular imaging and focus on their applications in pediatric patients. In the first part of the review, we discuss new approaches such as multiphase and multidelay arterial spin labeling for quantitative perfusion and angiography of the brain, amide proton transfer MRI of the brain, MRI of brachial plexus and lumbar plexus nerves (i.e., neurography), and T2 mapping and fat characterization in neuromuscular diseases. In the second part of the review, we focus on describing new data acquisition strategies in accelerated MRI aimed collectively at reducing the scan time, including simultaneous multislice imaging, compressed sensing, synthetic MRI, and magnetic resonance fingerprinting. In discussing the aforementioned, the review also summarizes the advantages and disadvantages of each method and their current state of commercial availability from MRI vendors.
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Affiliation(s)
| | - Danny J J Wang
- Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Barbara Cervantes
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | | | - Eric Nelson
- Center for Biobehavioral Health, Nationwide Children's Hospital, Columbus, Ohio
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
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16
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Neal MA, Pippard BJ, Hollingsworth KG, Maunder A, Dutta P, Simpson AJ, Blamire AM, Wild JM, Thelwall PE. Optimized and accelerated 19 F-MRI of inhaled perfluoropropane to assess regional pulmonary ventilation. Magn Reson Med 2019; 82:1301-1311. [PMID: 31099437 PMCID: PMC6767591 DOI: 10.1002/mrm.27805] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 03/12/2019] [Accepted: 04/15/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE To accelerate 19 F-MR imaging of inhaled perfluoropropane using compressed sensing methods, and to optimize critical scan acquisition parameters for assessment of lung ventilation properties. METHODS Simulations were performed to determine optimal acquisition parameters for maximal perfluoropropane signal-to-noise ratio (SNR) in human lungs for a spoiled gradient echo sequence. Optimized parameters were subsequently employed for 19 F-MRI of inhaled perfluoropropane in a cohort of 11 healthy participants using a 3.0 T scanner. The impact of 1.8×, 2.4×, and 3.0× undersampling ratios on 19 F-MRI acquisitions was evaluated, using both retrospective and prospective compressed sensing methods. RESULTS 3D spoiled gradient echo 19 F-MR ventilation images were acquired at 1-cm isotropic resolution within a single breath hold. Mean SNR was 11.7 ± 4.1 for scans acquired within a single breath hold (duration = 18 s). Acquisition of 19 F-MRI scans at shorter scan durations (4.5 s) was also demonstrated as feasible. Application of both retrospective (n = 8) and prospective (n = 3) compressed sensing methods demonstrated that 1.8× acceleration had negligible impact on qualitative image appearance, with no statistically significant change in measured lung ventilated volume. Acceleration factors of 2.4× and 3.0× resulted in increasing differences between fully sampled and undersampled datasets. CONCLUSION This study demonstrates methods for determining optimal acquisition parameters for 19 F-MRI of inhaled perfluoropropane and shows significant reduction in scan acquisition times (and thus participant breath hold duration) by use of compressed sensing.
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Affiliation(s)
- Mary A Neal
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Benjamin J Pippard
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Kieren G Hollingsworth
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Adam Maunder
- POLARIS, Academic Unit of Radiology, University of Sheffield, Royal Hallamshire Hospital, Sheffield, United Kingdom
| | - Prosenjit Dutta
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - A John Simpson
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.,Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Andrew M Blamire
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - James M Wild
- POLARIS, Academic Unit of Radiology, University of Sheffield, Royal Hallamshire Hospital, Sheffield, United Kingdom
| | - Peter E Thelwall
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom
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17
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Yi J, Lee YH, Hahn S, Albakheet SS, Song HT, Suh JS. Fast isotropic volumetric magnetic resonance imaging of the ankle: Acceleration of the three-dimensional fast spin echo sequence using compressed sensing combined with parallel imaging. Eur J Radiol 2019; 112:52-58. [DOI: 10.1016/j.ejrad.2019.01.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 01/05/2019] [Accepted: 01/08/2019] [Indexed: 11/26/2022]
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18
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Evaluation of compressed sensing MRI for accelerated bowel motility imaging. Eur Radiol Exp 2019; 3:7. [PMID: 30725241 PMCID: PMC6365583 DOI: 10.1186/s41747-018-0079-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 11/20/2018] [Indexed: 11/13/2022] Open
Abstract
Background To investigate the feasibility of compressed sensing and parallel imaging (CS-PI)-accelerated bowel motility magnetic resonance imaging (MRI) and to compare its image quality and diagnostic quality to conventional sensitivity encoding (SENSE) accelerated scans. Methods Bowel MRI was performed in six volunteers using a three-dimensional balanced fast field-echo sequence. Static scans were performed after the administration of a spasmolytic agent to prevent bowel motion artefacts. Fully sampled reference scans and multiple prospectively 3× to 7× undersampled CS-PI and SENSE scans were acquired. Additionally, fully sampled CS-PI and SENSE scans were retrospectively undersampled and reconstructed. Dynamic scans were performed using 5× to 7× accelerated scans in the presence of bowel motion. Retrospectively, undersampled scans were compared to fully sampled scans using structural similarity indices. All reconstructions were visually assessed for image quality and diagnostic quality by two radiologists. Results For static imaging, the performance of CS-PI was lower than that of fully sampled and SENSE scans: the diagnostic quality was assessed as adequate or good for 100% of fully sampled scans, 95% of SENSE, but only for 55% of CS-PI scans. For dynamic imaging, CS-PI image quality was scored similar to SENSE at high acceleration. Diagnostic quality of all scans was scored as adequate or good; 55% of CS-PI and 83% of SENSE scans were scored as good. Conclusion Compared to SENSE, current implementation of CS-PI performed less or equally good in terms of image quality and diagnostic quality. CS-PI did not show advantages over SENSE for three-dimensional bowel motility imaging.
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19
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Lazarus C, Weiss P, Vignaud A, Ciuciu P. An empirical study of the maximum degree of undersampling in compressed sensing for T 2*-weighted MRI. Magn Reson Imaging 2018; 53:112-122. [PMID: 30036651 DOI: 10.1016/j.mri.2018.07.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 07/03/2018] [Accepted: 07/14/2018] [Indexed: 12/30/2022]
Abstract
Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging modalities used in clinical routine today. Yet, one major limitation to this technique resides in its long acquisition times. Over the last decade, Compressed Sensing (CS) has been increasingly used to address this issue and offers to shorten MR scans by reconstructing images from undersampled Fourier data. Nevertheless, a quantitative guide on the degree of acceleration applicable to a given acquisition scenario is still lacking today, leading in practice to a trial-and-error approach in the selection of the appropriate undersampling factor. In this study, we shortly point out the existing theoretical sampling results in CS and their limitations which motivate the focus of this work: an empirical and quantitative analysis of the maximum degree of undersampling allowed by CS in the specific context of T2*-weighted MRI. We make use of a generic method based on retrospective undersampling to quantitatively deduce the maximum acceleration factor Rmax which preserves a desired image quality as a function of the image resolution and the available signal-to-noise ratio (SNR). Our results quantify how larger acceleration factors can be applied to higher resolution images as long as a minimum SNR is guaranteed. In practice however, the maximum acceleration factor for a given resolution appears to be constrained by the available SNR inherent to the considered acquisition. Our analysis enables to take this a priori knowledge into account, allowing to derive a sequence-specific maximum acceleration factor adapted to the intrinsic SNR of any MR pipeline. These results obtained on an analytical T2*-weighted phantom image were corroborated by prospective experiments performed on MR data collected with radial trajectories on a 7 T scanner with the same contrast. The proposed framework allows to study other sequence weightings and therefore better optimize sequences when accelerated using CS.
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Affiliation(s)
- Carole Lazarus
- NeuroSpin, CEA Saclay, Gif-sur-Yvette cedex 91191, France; Université Paris-Saclay, France; Parietal, INRIA, Palaiseau 91120, France
| | - Pierre Weiss
- ITAV USR3505 CNRS, Toulouse 31000, France; IMT UMR 5219 CNRS, Toulouse 31400, France
| | - Alexandre Vignaud
- NeuroSpin, CEA Saclay, Gif-sur-Yvette cedex 91191, France; Université Paris-Saclay, France.
| | - Philippe Ciuciu
- NeuroSpin, CEA Saclay, Gif-sur-Yvette cedex 91191, France; Université Paris-Saclay, France; Parietal, INRIA, Palaiseau 91120, France.
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20
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Carlier PG, Marty B, Scheidegger O, Loureiro de Sousa P, Baudin PY, Snezhko E, Vlodavets D. Skeletal Muscle Quantitative Nuclear Magnetic Resonance Imaging and Spectroscopy as an Outcome Measure for Clinical Trials. J Neuromuscul Dis 2018; 3:1-28. [PMID: 27854210 PMCID: PMC5271435 DOI: 10.3233/jnd-160145] [Citation(s) in RCA: 127] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Recent years have seen tremendous progress towards therapy of many previously incurable neuromuscular diseases. This new context has acted as a driving force for the development of novel non-invasive outcome measures. These can be organized in three main categories: functional tools, fluid biomarkers and imagery. In the latest category, nuclear magnetic resonance imaging (NMRI) offers a considerable range of possibilities for the characterization of skeletal muscle composition, function and metabolism. Nowadays, three NMR outcome measures are frequently integrated in clinical research protocols. They are: 1/ the muscle cross sectional area or volume, 2/ the percentage of intramuscular fat and 3/ the muscle water T2, which quantity muscle trophicity, chronic fatty degenerative changes and oedema (or more broadly, “disease activity”), respectively. A fourth biomarker, the contractile tissue volume is easily derived from the first two ones. The fat fraction maps most often acquired with Dixon sequences have proven their capability to detect small changes in muscle composition and have repeatedly shown superior sensitivity over standard functional evaluation. This outcome measure will more than likely be the first of the series to be validated as an endpoint by regulatory agencies. The versatility of contrast generated by NMR has opened many additional possibilities for characterization of the skeletal muscle and will result in the proposal of more NMR biomarkers. Ultra-short TE (UTE) sequences, late gadolinium enhancement and NMR elastography are being investigated as candidates to evaluate skeletal muscle interstitial fibrosis. Many options exist to measure muscle perfusion and oxygenation by NMR. Diffusion NMR as well as texture analysis algorithms could generate complementary information on muscle organization at microscopic and mesoscopic scales, respectively. 31P NMR spectroscopy is the reference technique to assess muscle energetics non-invasively during and after exercise. In dystrophic muscle, 31P NMR spectrum at rest is profoundly perturbed, and several resonances inform on cell membrane integrity. Considerable efforts are being directed towards acceleration of image acquisitions using a variety of approaches, from the extraction of fat content and water T2 maps from one single acquisition to partial matrices acquisition schemes. Spectacular decreases in examination time are expected in the near future. They will reinforce the attractiveness of NMR outcome measures and will further facilitate their integration in clinical research trials.
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Affiliation(s)
- Pierre G Carlier
- Institute of Myology, Pitie-Salpetriere University Hospital, Paris, France.,CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France.,National Academy of Sciences, United Institute for Informatics Problems, Minsk, Belarus
| | - Benjamin Marty
- Institute of Myology, Pitie-Salpetriere University Hospital, Paris, France.,CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France
| | - Olivier Scheidegger
- Institute of Myology, Pitie-Salpetriere University Hospital, Paris, France.,Support Center for Advanced Neuroimaging (SCAN), Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, and University of Bern, Switzerland
| | | | | | - Eduard Snezhko
- National Academy of Sciences, United Institute for Informatics Problems, Minsk, Belarus
| | - Dmitry Vlodavets
- N.I. Prirogov Russian National Medical Research University, Clinical Research Institute of Pediatrics, Moscow, Russian Federation
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21
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Burakiewicz J, Sinclair CDJ, Fischer D, Walter GA, Kan HE, Hollingsworth KG. Quantifying fat replacement of muscle by quantitative MRI in muscular dystrophy. J Neurol 2017; 264:2053-2067. [PMID: 28669118 PMCID: PMC5617883 DOI: 10.1007/s00415-017-8547-3] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 06/12/2017] [Accepted: 06/13/2017] [Indexed: 12/15/2022]
Abstract
The muscular dystrophies are rare orphan diseases, characterized by progressive muscle weakness: the most common and well known is Duchenne muscular dystrophy which affects young boys and progresses quickly during childhood. However, over 70 distinct variants have been identified to date, with different rates of progression, implications for morbidity, mortality, and quality of life. There are presently no curative therapies for these diseases, but a range of potential therapies are presently reaching the stage of multi-centre, multi-national first-in-man clinical trials. There is a need for sensitive, objective end-points to assess the efficacy of the proposed therapies. Present clinical measurements are often too dependent on patient effort or motivation, and lack sensitivity to small changes, or are invasive. Quantitative MRI to measure the fat replacement of skeletal muscle by either chemical shift imaging methods (Dixon or IDEAL) or spectroscopy has been demonstrated to provide such a sensitive, objective end-point in a number of studies. This review considers the importance of the outcome measures, discusses the considerations required to make robust measurements and appropriate quality assurance measures, and draws together the existing literature for cross-sectional and longitudinal cohort studies using these methods in muscular dystrophy.
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Affiliation(s)
- Jedrzej Burakiewicz
- Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
| | - Christopher D J Sinclair
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, UK.,Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK
| | - Dirk Fischer
- Division of Neuropaediatrics, University of Basel Children's Hospital, Spitalstrasse 33, Postfach, Basel, 4031, Switzerland.,Department of Neurology, University of Basel Hospital, Petersgraben 4, Basel, 4031, Switzerland
| | - Glenn A Walter
- Department of Physiology and Functional Genomics, University of Florida, Gainesville, FL, 32610, USA
| | - Hermien E Kan
- Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
| | - Kieren G Hollingsworth
- Newcastle Magnetic Resonance Centre, Institute of Cellular Medicine, Newcastle University, Newcastle-upon-Tyne, UK.
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Liu D, Steingoetter A, Parker HL, Curcic J, Kozerke S. Accelerating MRI fat quantification using a signal model-based dictionary to assess gastric fat volume and distribution of fat fraction. Magn Reson Imaging 2017; 37:81-89. [DOI: 10.1016/j.mri.2016.11.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 11/15/2016] [Accepted: 11/15/2016] [Indexed: 12/14/2022]
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Shi C, Xie G, Zhang Y, Zhang X, Chen M, Su S, Dong Y, Liu X, Ji J. Accelerated susceptibility-based positive contrast imaging of MR compatible metallic devices based on modified fast spin echo sequences. Phys Med Biol 2017; 62:2505-2520. [DOI: 10.1088/1361-6560/aa5fa3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Lugauer F, Nickel D, Wetzl J, Kiefer B, Hornegger J, Maier A. Accelerating multi-echo water-fat MRI with a joint locally low-rank and spatial sparsity-promoting reconstruction. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2016; 30:189-202. [PMID: 27822655 DOI: 10.1007/s10334-016-0595-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Revised: 10/09/2016] [Accepted: 10/11/2016] [Indexed: 12/22/2022]
Abstract
OBJECTIVES Our aim was to demonstrate the benefits of using locally low-rank (LLR) regularization for the compressed sensing reconstruction of highly-accelerated quantitative water-fat MRI, and to validate fat fraction (FF) and [Formula: see text] relaxation against reference parallel imaging in the abdomen. MATERIALS AND METHODS Reconstructions using spatial sparsity regularization (SSR) were compared to reconstructions with LLR and the combination of both (LLR+SSR) for up to seven fold accelerated 3-D bipolar multi-echo GRE imaging. For ten volunteers, the agreement with the reference was assessed in FF and [Formula: see text] maps. RESULTS LLR regularization showed superior noise and artifact suppression compared to reconstructions using SSR. Remaining residual artifacts were further reduced in combination with SSR. Correlation with the reference was excellent for FF with [Formula: see text] = 0.99 (all methods) and good for [Formula: see text] with [Formula: see text] = [0.93, 0.96, 0.95] for SSR, LLR and LLR+SSR. The linear regression gave slope and bias (%) of (0.99, 0.50), (1.01, 0.19) and (1.01, 0.10), and the hepatic FF/[Formula: see text] standard deviation was 3.5%/12.1 s[Formula: see text], 1.9%/6.4 s[Formula: see text] and 1.8%/6.3 s[Formula: see text] for SSR, LLR and LLR+SSR, indicating the least bias and highest SNR for LLR+SSR. CONCLUSION A novel reconstruction using both spatial and spectral regularization allows obtaining accurate FF and [Formula: see text] maps for prospectively highly accelerated acquisitions.
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Affiliation(s)
- Felix Lugauer
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany.
| | - Dominik Nickel
- Siemens Healthcare GmbH, Diagnostic Imaging, Erlangen, Germany
| | - Jens Wetzl
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany
| | - Berthold Kiefer
- Siemens Healthcare GmbH, Diagnostic Imaging, Erlangen, Germany
| | - Joachim Hornegger
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany
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Ricotti V, Evans MRB, Sinclair CDJ, Butler JW, Ridout DA, Hogrel JY, Emira A, Morrow JM, Reilly MM, Hanna MG, Janiczek RL, Matthews PM, Yousry TA, Muntoni F, Thornton JS. Upper Limb Evaluation in Duchenne Muscular Dystrophy: Fat-Water Quantification by MRI, Muscle Force and Function Define Endpoints for Clinical Trials. PLoS One 2016; 11:e0162542. [PMID: 27649492 PMCID: PMC5029878 DOI: 10.1371/journal.pone.0162542] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Accepted: 08/24/2016] [Indexed: 01/16/2023] Open
Abstract
Objective A number of promising experimental therapies for Duchenne muscular dystrophy (DMD) are emerging. Clinical trials currently rely on invasive biopsies or motivation-dependent functional tests to assess outcome. Quantitative muscle magnetic resonance imaging (MRI) could offer a valuable alternative and permit inclusion of non-ambulant DMD subjects. The aims of our study were to explore the responsiveness of upper-limb MRI muscle-fat measurement as a non-invasive objective endpoint for clinical trials in non-ambulant DMD, and to investigate the relationship of these MRI measures to those of muscle force and function. Methods 15 non-ambulant DMD boys (mean age 13.3 y) and 10 age-gender matched healthy controls (mean age 14.6 y) were recruited. 3-Tesla MRI fat-water quantification was used to measure forearm muscle fat transformation in non-ambulant DMD boys compared with healthy controls. DMD boys were assessed at 4 time-points over 12 months, using 3-point Dixon MRI to measure muscle fat-fraction (f.f.). Images from ten forearm muscles were segmented and mean f.f. and cross-sectional area recorded. DMD subjects also underwent comprehensive upper limb function and force evaluation. Results Overall mean baseline forearm f.f. was higher in DMD than in healthy controls (p<0.001). A progressive f.f. increase was observed in DMD over 12 months, reaching significance from 6 months (p<0.001, n = 7), accompanied by a significant loss in pinch strength at 6 months (p<0.001, n = 9) and a loss of upper limb function and grip force observed over 12 months (p<0.001, n = 8). Conclusions These results support the use of MRI muscle f.f. as a biomarker to monitor disease progression in the upper limb in non-ambulant DMD, with sensitivity adequate to detect group-level change over time intervals practical for use in clinical trials. Clinical validity is supported by the association of the progressive fat transformation of muscle with loss of muscle force and function.
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Affiliation(s)
- Valeria Ricotti
- Dubowitz Neuromuscular Centre, UCL Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom
- * E-mail:
| | - Matthew R. B. Evans
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
- Neuroradiological Academic Unit, UCL Institute of Neurology, London, United Kingdom
| | - Christopher D. J. Sinclair
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
- Neuroradiological Academic Unit, UCL Institute of Neurology, London, United Kingdom
| | - Jordan W. Butler
- Dubowitz Neuromuscular Centre, UCL Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom
| | - Deborah A. Ridout
- Population, Policy and Practice Programme, UCL Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom
| | | | - Ahmed Emira
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
- Neuroradiological Academic Unit, UCL Institute of Neurology, London, United Kingdom
| | - Jasper M. Morrow
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
| | - Mary M. Reilly
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
| | - Michael G. Hanna
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
| | | | - Paul M. Matthews
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
- Division of Brain Sciences and Centre for Neurotechnology, Imperial College London, United Kingdom
| | - Tarek A. Yousry
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
- Neuroradiological Academic Unit, UCL Institute of Neurology, London, United Kingdom
| | - Francesco Muntoni
- Dubowitz Neuromuscular Centre, UCL Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
| | - John S. Thornton
- MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology, London, United Kingdom
- Neuroradiological Academic Unit, UCL Institute of Neurology, London, United Kingdom
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Yang ACY, Kretzler M, Sudarski S, Gulani V, Seiberlich N. Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption. Invest Radiol 2016; 51:349-64. [PMID: 27003227 PMCID: PMC4948115 DOI: 10.1097/rli.0000000000000274] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.
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Affiliation(s)
- Alice Chieh-Yu Yang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
| | - Madison Kretzler
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, USA
| | - Sonja Sudarski
- Institute for Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim - Heidelberg University, Heidelberg, Germany
| | - Vikas Gulani
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
- Department of Radiology, University Hospitals of Cleveland, Cleveland, USA
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
- Department of Radiology, University Hospitals of Cleveland, Cleveland, USA
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Hollingsworth KG, Al-Mrabeh A, Steven S, Taylor R. Pancreatic triacylglycerol distribution in type 2 diabetes. Diabetologia 2015; 58:2676-8. [PMID: 26232098 DOI: 10.1007/s00125-015-3718-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Accepted: 07/15/2015] [Indexed: 02/07/2023]
Affiliation(s)
- Kieren G Hollingsworth
- Magnetic Resonance Centre, Institute of Cellular Medicine, Campus for Ageing & Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Ahmad Al-Mrabeh
- Magnetic Resonance Centre, Institute of Cellular Medicine, Campus for Ageing & Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sarah Steven
- Magnetic Resonance Centre, Institute of Cellular Medicine, Campus for Ageing & Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Roy Taylor
- Magnetic Resonance Centre, Institute of Cellular Medicine, Campus for Ageing & Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK.
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Hollingsworth KG. Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction. Phys Med Biol 2015; 60:R297-322. [PMID: 26448064 DOI: 10.1088/0031-9155/60/21/r297] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
MRI is often the most sensitive or appropriate technique for important measurements in clinical diagnosis and research, but lengthy acquisition times limit its use due to cost and considerations of patient comfort and compliance. Once an image field of view and resolution is chosen, the minimum scan acquisition time is normally fixed by the amount of raw data that must be acquired to meet the Nyquist criteria. Recently, there has been research interest in using the theory of compressed sensing (CS) in MR imaging to reduce scan acquisition times. The theory argues that if our target MR image is sparse, having signal information in only a small proportion of pixels (like an angiogram), or if the image can be mathematically transformed to be sparse then it is possible to use that sparsity to recover a high definition image from substantially less acquired data. This review starts by considering methods of k-space undersampling which have already been incorporated into routine clinical imaging (partial Fourier imaging and parallel imaging), and then explains the basis of using compressed sensing in MRI. The practical considerations of applying CS to MRI acquisitions are discussed, such as designing k-space undersampling schemes, optimizing adjustable parameters in reconstructions and exploiting the power of combined compressed sensing and parallel imaging (CS-PI). A selection of clinical applications that have used CS and CS-PI prospectively are considered. The review concludes by signposting other imaging acceleration techniques under present development before concluding with a consideration of the potential impact and obstacles to bringing compressed sensing into routine use in clinical MRI.
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Jaspan ON, Fleysher R, Lipton ML. Compressed sensing MRI: a review of the clinical literature. Br J Radiol 2015; 88:20150487. [PMID: 26402216 DOI: 10.1259/bjr.20150487] [Citation(s) in RCA: 194] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
MRI is one of the most dynamic and safe imaging techniques available in the clinic today. However, MRI acquisitions tend to be slow, limiting patient throughput and limiting potential indications for use while driving up costs. Compressed sensing (CS) is a method for accelerating MRI acquisition by acquiring less data through undersampling of k-space. This has the potential to mitigate the time-intensiveness of MRI. The limited body of research evaluating the effects of CS on MR images has been mostly positive with regards to its potential as a clinical tool. Studies have successfully accelerated MRI with this technology, with varying degrees of success. However, more must be performed before its diagnostic efficacy and benefits are clear. Studies involving a greater number radiologists and images must be completed, rating CS based on its diagnostic efficacy. Also, standardized methods for determining optimal imaging parameters must be developed.
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Affiliation(s)
- Oren N Jaspan
- 1 Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Roman Fleysher
- 2 The Gruss Magnetic Resonance Research Center, Department of Radiology, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Michael L Lipton
- 3 The Gruss Magnetic Resonance Research Center, Departments of Radiology, Psychiatry and Behavioral Sciences and The Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, The Bronx, NY, USA
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Mann LW, Higgins DM, Peters CN, Cassidy S, Hodson KK, Coombs A, Taylor R, Hollingsworth KG. Accelerating MR Imaging Liver Steatosis Measurement Using Combined Compressed Sensing and Parallel Imaging: A Quantitative Evaluation. Radiology 2015. [PMID: 26218662 DOI: 10.1148/radiol.2015150320] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
PURPOSE To determine the limits of agreement of hepatic fat fraction and R2* relaxation rate quantified with accelerated magnetic resonance (MR) imaging reconstructed with combined compressed sensing and parallel imaging compared with conventional fully sampled acquisitions. MATERIALS AND METHODS Eleven subjects with type 2 diabetes and a healthy control subject were recruited with the approval of the Newcastle and North Tyneside 2 ethics committee and written consent. Undersampled data at ratios of 2.6×, 2.9×, 3.8×, and 4.8× were prospectively acquired in addition to fully sampled data by using five gradient echoes per repetition time at 3.0 T. Fat fraction maps were calculated by using combined compressed sensing and parallel imaging (CS-PI) reconstruction and Bland-Altman analysis performed to assess bias and 95% limits of agreement. Inter- and intrarater analysis was performed for quantitative fat fraction and R2* relaxation rate, and image quality was assessed with a four-point scale by two independent observers. RESULTS The fat fractions from the accelerated acquisitions had 95% limits of agreement of 1.2%, 1.2%, 1.1%, and 1.5%, respectively, with no bias. When compared with the intra- and interrater 95% limits of agreement (0.7% and 0.8%), acceleration of up to 3.8× did not greatly degrade the fat fraction measurements. No or minimal artifact was detected at 2.6× and 2.9× accelerations, moderate artifact was detected at 3.8× acceleration, and substantial artifact was detected at 4.8× acceleration. CONCLUSION Prospective undersampling and CS-PI reconstruction of liver fat fractions can be used to accelerate liver fat fraction measurements. The fat fractions and image quality produced were acceptable up to a factor of 3.8×, thereby shortening the required breath-hold duration from 17.7 seconds to 4.7 seconds.
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Affiliation(s)
- Louis W Mann
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - David M Higgins
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - Carl N Peters
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - Sophie Cassidy
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - Kenneth K Hodson
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - Anna Coombs
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - Roy Taylor
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
| | - Kieren G Hollingsworth
- From the Newcastle Magnetic Resonance Centre (L.W.M., C.N.P., K.K.H., A.C., R.T., K.G.H.) and MoveLab (S.C.), Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE4 5PL, England; and Philips Healthcare, Guildford, England (D.M.H.)
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Berman BP, Pandey A, Li Z, Jeffries L, Trouard TP, Oliva I, Cortopassi F, Martin DR, Altbach MI, Bilgin A. Volumetric MRI of the lungs during forced expiration. Magn Reson Med 2015; 75:2295-302. [DOI: 10.1002/mrm.25798] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Revised: 05/06/2015] [Accepted: 05/11/2015] [Indexed: 01/11/2023]
Affiliation(s)
- Benjamin P. Berman
- Program in Applied Mathematics; University of Arizona; Tucson Arizona USA
| | - Abhishek Pandey
- Department of Electrical and Computer Engineering; University of Arizona; Tucson Arizona USA
| | - Zhitao Li
- Department of Electrical and Computer Engineering; University of Arizona; Tucson Arizona USA
| | - Lindsie Jeffries
- Department of Biomedical Engineering; University of Arizona; Tucson Arizona USA
| | - Theodore P. Trouard
- Department of Biomedical Engineering; University of Arizona; Tucson Arizona USA
- Department of Medical Imaging; University of Arizona; Tucson Arizona USA
| | - Isabel Oliva
- Department of Medical Imaging; University of Arizona; Tucson Arizona USA
| | - Felipe Cortopassi
- Department of Medical Imaging; University of Arizona; Tucson Arizona USA
| | - Diego R. Martin
- Department of Medical Imaging; University of Arizona; Tucson Arizona USA
| | - Maria I. Altbach
- Department of Medical Imaging; University of Arizona; Tucson Arizona USA
| | - Ali Bilgin
- Department of Electrical and Computer Engineering; University of Arizona; Tucson Arizona USA
- Department of Biomedical Engineering; University of Arizona; Tucson Arizona USA
- Department of Medical Imaging; University of Arizona; Tucson Arizona USA
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Loughran T, Higgins DM, McCallum M, Coombs A, Straub V, Hollingsworth KG. Improving highly accelerated fat fraction measurements for clinical trials in muscular dystrophy: origin and quantitative effect of R2* changes. Radiology 2015; 275:570-8. [PMID: 25575118 DOI: 10.1148/radiol.14141191] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Purpose To investigate the effect of R2* modeling in conventional and accelerated measurements of skeletal muscle fat fraction in control subjects and patients with muscular dystrophy. Materials and Methods Eight patients with Becker muscular dystrophy and eight matched control subjects were recruited with approval from the Newcastle and North Tyneside 2 Research Ethics Committee and with written consent. Chemical-shift images with six widely spaced echo times (in 3.5-msec increments) were acquired to correlate R2* and muscle fat fraction. The effect of incorporating or neglecting R2* modeling on fat fraction magnitude and variance was evaluated in a typical three-echo protocol (with 0.78-msec increments). Accelerated acquisitions with this protocol with 3.65×, 4.94×, and 6.42× undersampling were reconstructed by using combined compressed sensing and parallel imaging and fat fraction maps produced with R2* modeling. Results Muscle R2* at 3.0 T (33-125 sec(-1)) depended on the morphology of fat replacement, the highest values occurring with the greatest interdigitation of fat. The inclusion of R2* modeling removed bias, which was greatest at low fat fraction, but did not increase variance. The 95% limits of agreement of the accelerated acquisitions were tight and not degraded by R2* modeling (1.65%, 1.95%, and 2.22% for 3.65×, 4.94×, and 6.42× acceleration, respectively). Conclusion Incorporating R2* modeling prevents systematic errors in muscle fat fraction by up to 3.5% without loss of precision and should be incorporated into all muscular dystrophy studies. Fat fraction measurements can be accelerated fivefold by using combined compressed sensing and parallel imaging, modeling for R2* without loss of fidelity.
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Affiliation(s)
- Thomas Loughran
- From the Newcastle Magnetic Resonance Centre, Institute of Cellular Medicine, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE4 5PL, England (T.L., A.C., K.G.H.); Philips Healthcare, Guildford, Surrey, England (D.M.H.); and The John Walton Muscular Dystrophy Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, England (M.M., V.S.)
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