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Zsombor Z, Zsély B, Rónaszéki AD, Stollmayer R, Budai BK, Palotás L, Bérczi V, Kalina I, Maurovich Horvat P, Kaposi PN. Comparison of Vendor-Independent Software Tools for Liver Proton Density Fat Fraction Estimation at 1.5 T. Diagnostics (Basel) 2024; 14:1138. [PMID: 38893664 PMCID: PMC11171873 DOI: 10.3390/diagnostics14111138] [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: 05/07/2024] [Revised: 05/27/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
(1) Background: Open-source software tools are available to estimate proton density fat fraction (PDFF). (2) Methods: We compared four algorithms: complex-based with graph cut (GC), magnitude-based (MAG), magnitude-only estimation with Rician noise modeling (MAG-R), and multi-scale quadratic pseudo-Boolean optimization with graph cut (QPBO). The accuracy and reliability of the methods were evaluated in phantoms with known fat/water ratios and a patient cohort with various grades (S0-S3) of steatosis. Image acquisitions were performed at 1.5 Tesla (T). (3) Results: The PDFF estimates showed a nearly perfect correlation (Pearson r = 0.999, p < 0.001) and inter-rater agreement (ICC = from 0.995 to 0.999, p < 0.001) with true fat fractions. The absolute bias was low with all methods (0.001-1%), and an ANCOVA detected no significant difference between the algorithms in vitro. The agreement across the methods was very good in the patient cohort (ICC = 0.891, p < 0.001). However, MAG estimates (-2.30% ± 6.11%, p = 0.005) were lower than MAG-R. The field inhomogeneity artifacts were most frequent in MAG-R (70%) and GC (39%) and absent in QPBO images. (4) Conclusions: The tested algorithms all accurately estimate PDFF in vitro. Meanwhile, QPBO is the least affected by field inhomogeneity artifacts in vivo.
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Affiliation(s)
- Zita Zsombor
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Boglárka Zsély
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Aladár D. Rónaszéki
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Róbert Stollmayer
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Bettina K. Budai
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Lőrinc Palotás
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Viktor Bérczi
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Ildikó Kalina
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Pál Maurovich Horvat
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
| | - Pál Novák Kaposi
- Department of Radiology, Medical Imaging Centre, Semmelweis University, 1083 Budapest, Hungary; (Z.Z.); (B.Z.); (A.D.R.); (R.S.); (B.K.B.); (L.P.); (V.B.); (I.K.); (P.M.H.)
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Wan C, He W, Xu Z. Water-Fat Separation for the Knee on a 50 mT Portable MRI Scanner. IEEE Trans Biomed Eng 2024; 71:1687-1696. [PMID: 38150336 DOI: 10.1109/tbme.2023.3347441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
OBJECTIVE The Dixon method is frequently employed in clinical and scientific research for fat suppression, because it has lower sensitivity to static magnetic field inhomogeneity compared to chemical shift selective saturation or its variants and maintains image signal-to-noise ratio (SNR). Recently, research on very-low-field (VLF < 100 mT) magnetic resonance imaging (MRI) has regained popularity. However, there is limited literature on water-fat separation in VLF MRI. Here, we present a modified two-point Dixon method specifically designed for VLF MRI. METHODS Most experiments were performed on a homemade 50 mT portable MRI scanner. The receiving coil adopted a homemade quadrature receiving coil. The data were acquired using spin-echo and gradient-echo sequences. We considered the T2* effect, and added priori information to existing two-point Dixon method. Then, the method used regional iterative phasor extraction (RIPE) to extract the error phasor. Finally, least squares solutions for water and fat were obtained and fat signal fraction was calculated. RESULTS For phantom evaluation, water-only and fat-only images were obtained and the local fat signal fractions were calculated, with two samples being 0.94 and 0.93, respectively. For knee imaging, cartilage, muscle and fat could be clearly distinguished. The water-only images were able to highlight areas such as cartilage that could not be easily distinguished without separation. CONCLUSION This work has demonstrated the feasibility of using a 50 mT MRI scanner for water-fat separation. SIGNIFICANCE To the best of our knowledge, this is the first reported result of water-fat separation at a 50 mT portable MRI scanner.
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Tian Y, Nayak KS. Real-time water/fat imaging at 0.55T with spiral out-in-out-in sampling. Magn Reson Med 2024; 91:649-659. [PMID: 37815020 PMCID: PMC10841523 DOI: 10.1002/mrm.29885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 08/23/2023] [Accepted: 09/21/2023] [Indexed: 10/11/2023]
Abstract
PURPOSE To develop an efficient and flexible water/fat separated real-time MRI (RT-MRI) method using spiral out-in-out-in (OIOI) sampling and balanced SSFP (bSSFP) at 0.55T. METHODS A bSSFP sequence with golden-angle spiral OIOI readout was developed, capturing three echoes to allow water/fat separation. A low-latency reconstruction that combines all echoes was available for online visualization. An offline reconstruction provided water and fat RT-MRI in two steps: (1) image reconstruction with spatiotemporally constrained reconstruction (STCR) and (2) water/fat separation with hierarchical iterative decomposition of water and fat with echo asymmetry and least-squares estimation (HIDEAL). In healthy volunteers, spiral OIOI was acquired in the wrist during a radial-to-ulnar deviation maneuver, in the heart without breath-hold and cardiac gating, and in the lower abdomen during free-breathing for visualizing small bowel motility. RESULTS We demonstrate successful water/fat separated RT-MRI for all tested applications. In the wrist, resulting images provided clear depiction of ligament gaps and their interactions during the radial-to-ulnar deviation maneuver. In the heart, water/fat RT-MRI depicted epicardial fat, provided improved delineation of epicardial coronary arteries, and provided high blood-myocardial contrast for ventricular function assessment. In the abdomen, water-only RT-MRI captured small bowel mobility clearly with improved water-fat contrast. CONCLUSIONS We have demonstrated a novel and flexible bSSFP spiral OIOI sequence at 0.55T that can provide water/fat separated RT-MRI with a variety of application-specific temporal resolution and spatial resolution requirements.
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Affiliation(s)
- Ye Tian
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Krishna S. Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
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Montrazi ET, Bao Q, Martinho RP, Peters DC, Harris T, Sasson K, Agemy L, Scherz A, Frydman L. Deuterium imaging of the Warburg effect at sub-millimolar concentrations by joint processing of the kinetic and spectral dimensions. NMR IN BIOMEDICINE 2023; 36:e4995. [PMID: 37401393 DOI: 10.1002/nbm.4995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/21/2023] [Accepted: 06/03/2023] [Indexed: 07/05/2023]
Abstract
Deuterium metabolic imaging (DMI) is a promising molecular MRI approach, which follows the administration of deuterated substrates and their metabolization. [6,6'-2 H2 ]-glucose for instance is preferentially converted in tumors to [3,3'-2 H2 ]-lactate as a result of the Warburg effect, providing a distinct resonance whose mapping using time-resolved spectroscopic imaging can diagnose cancer. The MR detection of low-concentration metabolites such as lactate, however, is challenging. It has been recently shown that multi-echo balanced steady-state free precession (ME-bSSFP) increases the signal-to-noise ratio (SNR) of these experiments approximately threefold over regular chemical shift imaging; the present study examines how DMI's sensitivity can be increased further by advanced processing methods. Some of these, such as compressed sensing multiplicative denoising and block-matching/3D filtering, can be applied to any spectroscopic/imaging methods. Sensitivity-enhancing approaches were also specifically tailored to ME-bSSFP DMI, by relying on priors related to the resonances' positions and to features of the metabolic kinetics. Two new methods are thus proposed that use these constraints for enhancing the sensitivity of both the spectral images and the metabolic kinetics. The ability of these methods to improve DMI is evidenced in pancreatic cancer studies carried at 15.2 T, where suitable implementations of the proposals imparted eightfold or more SNR improvement over the original ME-bSSFP data, at no informational cost. Comparisons with other propositions in the literature are briefly discussed.
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Affiliation(s)
- Elton T Montrazi
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Qingjia Bao
- Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Ricardo P Martinho
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
- University of Twente, Enschede, The Netherlands
| | - Dana C Peters
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Talia Harris
- Department of Chemical Research Support, Weizmann Institute of Science, Rehovot, Israel
| | - Keren Sasson
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot, Israel
| | - Lilach Agemy
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot, Israel
| | - Avigdor Scherz
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot, Israel
| | - Lucio Frydman
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
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5
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Wu HX, Lin X, Cheng CL, Jiang HL, Iqbal J, Liu J, Zhou HD. Fat distribution measurements by chemical shift-encoded transition region extraction predict the risk of hyperglycaemia, dyslipidaemia and metabolic syndrome in mice. NMR IN BIOMEDICINE 2023; 36:e4985. [PMID: 37283179 DOI: 10.1002/nbm.4985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/27/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023]
Abstract
Metabolically healthy or unhealthy obesity is closely related to metabolic syndrome (MetS). To validate a more accurate diagnostic method for obesity that reflects the risk of metabolic disorders in a pre-clinical mouse model, C57BL/6J mice were fed high-sucrose-high-fat and chow diets for 12 weeks to induce obesity. MRI was performed and analysed by chemical shift-encoded fat-water separation based on the transition region extraction method. Abdominal fat was divided into upper and lower abdominal regions at the horizontal lower border of the liver. Blood samples were collected, and the glucose level, lipid profile, liver function, HbA1c and insulin were tested. k-means clustering and stepwise logistic regression were applied to validate the diagnosis of hyperglycaemia, dyslipidaemia and MetS, and to ascertain the predictive effect of MRI-derived parameters to the metabolic disorders. Pearson or Spearman correlation was used to assess the relationship between MRI-derived parameters and metabolic traits. The receiver-operating characteristic curve was used to evaluate the diagnostic effect of each logistic regression model. A two-sided p value less than 0.05 was considered to indicate statistical significance for all tests. We made the precise diagnosis of obesity, dyslipidaemia, hyperglycaemia and MetS in mice. In all, 14 mice could be diagnosed as having MetS, and the levels of body weight, HbA1c, triglyceride, total cholesterol and low-density lipoprotein cholesterol were significantly higher than in the normal group. Upper abdominal fat better predicted dyslipidaemia (odds ratio, OR = 2.673; area under the receiver-operating characteristic curve, AUCROC = 0.9153) and hyperglycaemia (OR = 2.456; AUCROC = 0.9454), and the abdominal visceral adipose tissue (VAT) was better for predicting MetS risk (OR = 1.187; AUCROC = 0.9619). We identified the predictive effect of fat volume and distribution in dyslipidaemia, hyperglycaemia and MetS. The upper abdominal fat played a better predictive role for the risk of dyslipidaemia and hyperglycaemia, and the abdominal VAT played a better predictive role for the risk of MetS.
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Affiliation(s)
- Hui-Xuan Wu
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xiao Lin
- Clinical Research Center for Medical Imaging in Hunan Province, Department of Radiology Quality Control Center in Hunan Province, Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chuan-Li Cheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Hong-Li Jiang
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Junaid Iqbal
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jun Liu
- Clinical Research Center for Medical Imaging in Hunan Province, Department of Radiology Quality Control Center in Hunan Province, Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Hou-De Zhou
- National Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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Dimov AV, Li J, Nguyen TD, Roberts AG, Spincemaille P, Straub S, Zun Z, Prince MR, Wang Y. QSM Throughout the Body. J Magn Reson Imaging 2023; 57:1621-1640. [PMID: 36748806 PMCID: PMC10192074 DOI: 10.1002/jmri.28624] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/19/2023] [Accepted: 01/20/2023] [Indexed: 02/08/2023] Open
Abstract
Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.
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Affiliation(s)
- Alexey V. Dimov
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Jiahao Li
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | | | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Sina Straub
- Department of Radiology, Mayo Clinic, Jacksonville, FL, United States
| | - Zungho Zun
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Martin R. Prince
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
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7
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Triay Bagur A, McClymont D, Hutton C, Borghetto A, Gyngell ML, Aljabar P, Robson MD, Brady M, Bulte DP. Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation. Magn Reson Imaging 2023; 97:102-111. [PMID: 36632946 DOI: 10.1016/j.mri.2023.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 01/06/2023] [Indexed: 01/11/2023]
Abstract
Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.
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Affiliation(s)
- Alexandre Triay Bagur
- Department of Engineering Science, University of Oxford, Oxford, UK; Perspectum Ltd, Oxford, UK.
| | | | | | | | | | | | | | | | - Daniel P Bulte
- Department of Engineering Science, University of Oxford, Oxford, UK
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8
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Boehm C, Schlaeger S, Meineke J, Weiss K, Makowski MR, Karampinos DC. On the water-fat in-phase assumption for quantitative susceptibility mapping. Magn Reson Med 2023; 89:1068-1082. [PMID: 36321543 DOI: 10.1002/mrm.29516] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 10/06/2022] [Accepted: 10/15/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE To (a) define multi-peak fat model-based effective in-phase echo times for quantitative susceptibility mapping (QSM) in water-fat regions, (b) analyze the relationship between fat fraction, field map quantification bias and susceptibility bias, and (c) evaluate the susceptibility mapping performance of the proposed effective in-phase echoes in comparison to single-peak in-phase echoes and water-fat separation for regions where both water and fat are present. METHODS Effective multipeak in-phase echo times for a bone marrow and a liver fat spectral model were derived from a single voxel simulation. A Monte Carlo simulation was performed to assess the field map estimation error as a function of fat fraction for the different in-phase echoes. Additionally, a phantom scan and in vivo scans in the liver, spine, and breast were performed and evaluated with respect to quantification accuracy. RESULTS The use of single-peak in-phase echoes can introduce a worst-case susceptibility bias of 0.43 $$ 0.43 $$ ppm. The use of effective multipeak in-phase echoes shows a similar quantitative performance in the numerical simulation, the phantom and in all in vivo anatomies when compared to water-fat separation-based QSM. CONCLUSION QSM based on the proposed effective multipeak in-phase echoes can alleviate the quantification bias present in QSM based on single-peak in-phase echoes. When compared to water-fat separation-based QSM the proposed effective in-phase echo times achieve a similar quantitative performance while drastically reducing the computational expense for field map estimation.
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Affiliation(s)
- Christof Boehm
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Sarah Schlaeger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | | | | | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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9
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Dong Y, Riedel M, Koolstra K, van Osch MJP, Börnert P. Water/fat separation for self-navigated diffusion-weighted multishot echo-planar imaging. NMR IN BIOMEDICINE 2023; 36:e4822. [PMID: 36031585 PMCID: PMC10078174 DOI: 10.1002/nbm.4822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/25/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
The purpose of this study was to develop a self-navigation strategy to improve scan efficiency and image quality of water/fat-separated, diffusion-weighted multishot echo-planar imaging (ms-EPI). This is accomplished by acquiring chemical shift-encoded diffusion-weighted data and using an appropriate water-fat and diffusion-encoded signal model to enable reconstruction directly from k-space data. Multishot EPI provides reduced geometric distortion and improved signal-to-noise ratio in diffusion-weighted imaging compared with single-shot approaches. Multishot acquisitions require corrections for physiological motion-induced shot-to-shot phase errors using either extra navigators or self-navigation principles. In addition, proper fat suppression is important, especially in regions with large B0 inhomogeneity. This makes the use of chemical shift encoding attractive. However, when combined with ms-EPI, shot-to-shot phase navigation can be challenging because of the spatial displacement of fat signals along the phase-encoding direction. In this work, a new model-based, self-navigated water/fat separation reconstruction algorithm is proposed. Experiments in legs and in the head-neck region of 10 subjects were performed to validate the algorithm. The results are compared with an image-based, two-dimensional (2D) navigated water/fat separation approach for ms-EPI and with a conventional fat saturation approach. Compared with the 2D navigated method, the use of self-navigation reduced the shot duration time by 30%-35%. The proposed algorithm provided improved diffusion-weighted water images in both leg and head-neck regions compared with the 2D navigator-based approach. The proposed algorithm also produced better fat suppression compared with the conventional fat saturation technique in the B0 inhomogeneous regions. In conclusion, the proposed self-navigated reconstruction algorithm can produce superior water-only diffusion-weighted EPI images with less artefacts compared with the existing methods.
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Affiliation(s)
- Yiming Dong
- C. J. Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Malte Riedel
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurichSwitzerland
| | - Kirsten Koolstra
- Division of Image Processing, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Matthias J. P. van Osch
- C. J. Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Peter Börnert
- C. J. Gorter Center for High Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
- Philips Research HamburgHamburgGermany
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Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging. Bioengineering (Basel) 2022; 9:bioengineering9100579. [PMID: 36290546 PMCID: PMC9598080 DOI: 10.3390/bioengineering9100579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/12/2022] [Accepted: 10/15/2022] [Indexed: 11/26/2022] Open
Abstract
Conventional water–fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water–fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water–fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.
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11
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Kumar N, Prajesh R. Selectivity enhancement for metal oxide (MOX) based gas sensor using thermally modulated datasets coupled with golden section optimization and chemometric techniques. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:064702. [PMID: 35778012 DOI: 10.1063/5.0083061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
The ever-increasing demand for smart sensors for internet of things applications drove the change in outlook toward smart sensor system design. This paper focuses on using low-cost gas sensors [Metal Oxide (MOX)] for detection of more than one gas, which is otherwise complex due to poor selectivity of MOX sensors. In this work, detection of two gases, namely, ammonia (NH3) and carbon monoxide (CO), using a single metal oxide (pristine tin oxide) sensor is demonstrated. Furthermore, chemometric based algorithms have been used to classify and quantify both gases. The present investigation uses the temperature modulated gas sensor response obtained at different concentrations for the mentioned gases. The golden section based optimization technique has been employed to obtain two different ranges of temperatures for both gases. After applying certain pre-processing techniques, the acquired data from the sensors were fed to various classification techniques, such as partial least squares (PLS) discriminant analysis, k-means, and soft independent modeling by class analogy, and 100% classification results were obtained. Furthermore, PLS regression (PLS-R) was used to perform quantitative analysis on the data using the optimized temperature ranges for both gases, and R2 regression coefficients, 0.999 25 for NH3 and 0.9399 for CO, were obtained. The results obtained from both the qualitative and quantitative analyses make our approach low-cost and smart to mitigate the cross-selectivity of metal oxide semiconductor based smart sensor design.
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Affiliation(s)
- Navjot Kumar
- CSIR-Central Electronics Engineering Research Institute, Pilani 333031, Rajasthan, India
| | - Rahul Prajesh
- CSIR-Central Electronics Engineering Research Institute, Pilani 333031, Rajasthan, India
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12
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Roberts NT, Hernando D, Panagiotopoulos N, Reeder SB. Addressing concomitant gradient phase errors in time-interleaved chemical shift-encoded MRI fat fraction and R 2 * mapping with a pass-specific phase fitting method. Magn Reson Med 2022; 87:2826-2838. [PMID: 35122450 DOI: 10.1002/mrm.29175] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 01/07/2022] [Accepted: 01/10/2022] [Indexed: 11/05/2022]
Abstract
PURPOSE Concomitant gradients induce phase errors that increase quadratically with distance from isocenter. This work proposes a complex-based fitting method that addresses concomitant gradient phase errors in chemical shift encoded (CSE) MRI estimation of proton density fat fraction (PDFF) and R2 * through joint estimation of pass-specific phase terms. This method is applicable to time-interleaved multi-echo gradient-echo acquisitions (i.e., multi-pass acquisitions) and does not require prior knowledge of gradient waveforms typically needed to address concomitant gradient phase errors. THEORY AND METHODS A CSE-MRI spoiled gradient echo signal model, with pass-specific phase terms, is introduced for non-linear least squares estimation of PDFF and R2 * in the presence of concomitant gradient phase errors. Cramér-Rao lower bound analysis was used to determine noise performance tradeoffs of the proposed fitting method, which was then validated in both phantom and in vivo experiments. RESULTS The proposed fitting method removed PDFF and R2 * estimation errors up to 12% and 10 s-1 , respectively, at ±12 cm off isocenter (S/I) in a water phantom. In healthy volunteers, PDFF and R2 * bias was reduced by ~10% (12 cm off-isocenter) and ~30 s-1 (16 cm off-isocenter), respectively. An evaluation in 29 clinical liver datasets demonstrated reduced PDFF bias and variability (8.4% improvement in the coefficient of variation), even with the imaging volume centered at isocenter. CONCLUSION Concomitant gradient induced phase errors in multi-pass CSE-MRI acquisitions can result in PDFF and R2 * estimation biases away from isocenter. The proposed fitting method enables accurate PDFF and R2 * quantification in the presence of concomitant gradient phase errors without knowledge of imaging gradient waveforms.
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Affiliation(s)
- Nathan T Roberts
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Scott B Reeder
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
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13
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Peng H, Cheng C, Wan Q, Jia S, Wang S, Lv J, Liang D, Liu W, Liu X, Zheng H, Zou C. Fast multi-parametric imaging in abdomen by B 1 + corrected dual-flip angle sequence with interleaved echo acquisition. Magn Reson Med 2021; 87:2194-2208. [PMID: 34888911 DOI: 10.1002/mrm.29127] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 11/28/2021] [Accepted: 11/29/2021] [Indexed: 11/07/2022]
Abstract
PURPOSE To achieve simultaneous T1, w /proton density fat fraction (PDFF)/ R 2 ∗ mapping in abdomen within a single breadth-hold, and validate the accuracy using state-of-art measurement. THEORY AND METHODS An optimized multiple echo gradient echo (GRE) sequence with dual flip-angle acquisition was used to realize simultaneous water T1 (T1, w )/PDFF/ R 2 ∗ quantification. A new method, referred to as "solving the fat-water ambiguity based on their T1 difference" (SORT), was proposed to address the fat-water separation problem. This method was based on the finding that compared to the true solution, the wrong (or aliased) solution to fat-water separation problem showed extra dependency on the applied flip angle due to the T1 difference between fat and water. The B 1 + measurement sequence was applied to correct the B 1 + inhomogeneity for T1, w relaxometry. The 2D parallel imaging was incorporated to enable the acquisition within a single breath-hold in abdomen. RESULTS The multi-parametric quantification results of the proposed method were consistent with the results of reference methods in phantom experiments (PDFF quantification: R2 = 0.993, mean error 0.73%; T1, w quantification: R2 = 0.999, mean error 4.3%; R 2 ∗ quantification: R2 = 0.949, mean error 4.07 s-1 ). For volunteer studies, robust fat-water separation was achieved without evident fat-water swaps. Based on the accurate fat-water separation, simultaneous T1, w /PDFF/ R 2 ∗ quantification was realized for whole liver within a single breath-hold. CONCLUSION The proposed method accurately quantified T1, w /PDFF/ R 2 ∗ for the whole liver within a single breath-hold. This technique serves as a quantitative tool for disease management in patients with hepatic steatosis.
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Affiliation(s)
- Hao Peng
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chuanli Cheng
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Qian Wan
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Sen Jia
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Shuai Wang
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jianxun Lv
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Dong Liang
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Wenzhong Liu
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, China
| | - Xin Liu
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Hairong Zheng
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Chao Zou
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
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14
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Dong Y, Koolstra K, Riedel M, van Osch MJP, Börnert P. Regularized joint water-fat separation with B 0 map estimation in image space for 2D-navigated interleaved EPI based diffusion MRI. Magn Reson Med 2021; 86:3034-3051. [PMID: 34255392 PMCID: PMC8596522 DOI: 10.1002/mrm.28919] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 06/09/2021] [Accepted: 06/16/2021] [Indexed: 12/15/2022]
Abstract
Purpose To develop a new water–fat separation and B0 estimation algorithm to effectively suppress the multiple resonances of fat signal in EPI. This is especially relevant for DWI where fat is often a confounding factor. Methods Water–fat separation based on chemical‐shift encoding enables robust fat suppression in routine MRI. However, for EPI the different chemical‐shift displacements of the multiple fat resonances along the phase‐encoding direction can be problematic for conventional separation algorithms. This work proposes a suitable model approximation for EPI under B0 and fat off‐resonance effects, providing a feasible multi‐peak water–fat separation algorithm. Simulations were performed to validate the algorithm. In vivo validation was performed in 6 volunteers, acquiring spin‐echo EPI images in the leg (B0 homogeneous) and head‐neck (B0 inhomogeneous) regions, using a TE‐shifted interleaved EPI sequence with/without diffusion sensitization. The results are numerically and statistically compared with voxel‐independent water–fat separation and fat saturation techniques to demonstrate the performance of the proposed algorithm. Results The reference separation algorithm without the proposed spatial shift correction caused water–fat ambiguities in simulations and in vivo experiments. Some spectrally selective fat saturation approaches also failed to suppress fat in regions with severe B0 inhomogeneities. The proposed algorithm was able to achieve improved fat suppression for DWI data and ADC maps in the head–neck and leg regions. Conclusion The proposed algorithm shows improved suppression of the multi‐peak fat components in multi‐shot interleaved EPI applications compared to the conventional fat saturation approaches and separation algorithms.
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Affiliation(s)
- Yiming Dong
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - Kirsten Koolstra
- Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands
| | - Malte Riedel
- Institute for Signal Processing, University of Lübeck, Lübeck, Germany
| | - Matthias J P van Osch
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter Börnert
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands.,Philips Research Hamburg, Hamburg, Germany
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15
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Boehm C, Diefenbach MN, Makowski MR, Karampinos DC. Improved body quantitative susceptibility mapping by using a variable-layer single-min-cut graph-cut for field-mapping. Magn Reson Med 2020; 85:1697-1712. [PMID: 33151604 DOI: 10.1002/mrm.28515] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 08/20/2020] [Accepted: 08/21/2020] [Indexed: 12/18/2022]
Abstract
PURPOSE To develop a robust algorithm for field-mapping in the presence of water-fat components, large B 0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM). METHODS A framework solving the cost-function of the water-fat separation problem in a single-min-cut graph-cut based on the variable-layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field-mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph-cut algorithm and a formerly proposed single-min-cut graph-cut. RESULTS The proposed method was shown to yield accurate field-map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field-map and susceptibility results compared to iterative graph-cut field-mapping especially in regions with low SNR, strong field-map variations and high R 2 ∗ values. CONCLUSIONS A single-min-cut graph-cut field-mapping method with a variable-layer construction was developed for field-mapping in body water-fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids.
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Affiliation(s)
- Christof Boehm
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Maximilian N Diefenbach
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.,Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
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16
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Kořínek R, Gajdošík M, Trattnig S, Starčuk Z, Krššák M. Low-level fat fraction quantification at 3 T: comparative study of different tools for water-fat reconstruction and MR spectroscopy. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 33:455-468. [PMID: 31980962 DOI: 10.1007/s10334-020-00825-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 12/12/2019] [Accepted: 01/03/2020] [Indexed: 12/22/2022]
Abstract
OBJECTIVES Chemical Shift Encoded Magnetic Resonance Imaging (CSE-MRI)-based quantification of low-level (< 5% of proton density fat fraction-PDFF) fat infiltration requires highly accurate data reconstruction for the assessment of hepatic or pancreatic fat accumulation in diagnostics and biomedical research. MATERIALS AND METHODS We compare three software tools available for water/fat image reconstruction and PDFF quantification with MRS as the reference method. Based on the algorithm exploited in the tested software, the accuracy of fat fraction quantification varies. We evaluate them in phantom and in vivo MRS and MRI measurements. RESULTS The signal model of Intralipid 20% emulsion used for phantoms was established for 3 T and 9.4 T fields. In all cases, we noticed a high coefficient of determination (R-squared) between MRS and MRI-PDFF measurements: in phantoms <0.9924-0.9990>; and in vivo <0.8069-0.9552>. Bland-Altman analysis was applied to phantom and in vivo measurements. DISCUSSION Multi-echo MRI in combination with an advanced algorithm including multi-peak spectrum modeling appears as a valuable and accurate method for low-level PDFF quantification over large FOV in high resolution, and is much faster than MRS methods. The graph-cut algorithm (GC) showed the fewest water/fat swaps in the PDFF maps, and hence stands out as the most robust method of those tested.
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Affiliation(s)
- Radim Kořínek
- Institute of Scientific Instruments of the CAS, Kralovopolska 147, 612 64, Brno, Czech Republic.
| | - Martin Gajdošík
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Centre, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, 1210 Amsterdam Ave, New York, NY, 10027, USA
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Centre, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular Imaging, MOLIMA, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Zenon Starčuk
- Institute of Scientific Instruments of the CAS, Kralovopolska 147, 612 64, Brno, Czech Republic
| | - Martin Krššák
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Centre, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular Imaging, MOLIMA, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Division of Endocrinology and Metabolism, Department of Medicine III, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
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17
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Lin CY, Fessler JA. Efficient Regularized Field Map Estimation in 3D MRI. IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 2020; 6:1451-1458. [PMID: 33693053 PMCID: PMC7943027 DOI: 10.1109/tci.2020.3031082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Magnetic field inhomogeneity estimation is important in some types of magnetic resonance imaging (MRI), including field-corrected reconstruction for fast MRI with long readout times, and chemical shift based water-fat imaging. Regularized field map estimation methods that account for phase wrapping and noise involve nonconvex cost functions that require iterative algorithms. Most existing minimization techniques were computationally or memory intensive for 3D datasets, and are designed for single-coil MRI. This paper considers 3D MRI with optional consideration of coil sensitivity, and addresses the multi-echo field map estimation and water-fat imaging problem. Our efficient algorithm uses a preconditioned nonlinear conjugate gradient method based on an incomplete Cholesky factorization of the Hessian of the cost function, along with a monotonic line search. Numerical experiments show the computational advantage of the proposed algorithm over state-of-the-art methods with similar memory requirements.
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Affiliation(s)
- Claire Yilin Lin
- Department of Mathematics, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Jeffrey A Fessler
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 USA
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18
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Constraints in estimating the proton density fat fraction. Magn Reson Imaging 2019; 66:1-8. [PMID: 31740195 DOI: 10.1016/j.mri.2019.11.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 10/16/2019] [Accepted: 11/09/2019] [Indexed: 11/21/2022]
Abstract
The study evaluates four physically motivated constraints in the estimation of the proton density fat fraction (PDFF). Least squares approaches were developed for constraining the parameters in PDFF quantification based on the physics of magnetic resonance imaging. These were smooth fieldmap, smooth initial phase, nonnegative proton density and moderate R2∗ values. The constraints were evaluated in terms of their influence on the bias and standard deviation of the estimated parameters using numerical simulations and in vivo data acquired at 0.35 T. Results show that unconstrained least squares estimation is noisy and biased and that constraints can be effective at reducing both the standard deviation and bias.
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19
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Guo Y, Liu Z, Wen Y, Spincemaille P, Zhang H, Jafari R, Zhang S, Eskreis-Winkler S, Gillen KM, Yi P, Feng Q, Feng Y, Wang Y. Quantitative susceptibility mapping of the spine using in-phase echoes to initialize inhomogeneous field and R2* for the nonconvex optimization problem of fat-water separation. NMR IN BIOMEDICINE 2019; 32:e4156. [PMID: 31424131 DOI: 10.1002/nbm.4156] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 07/01/2019] [Accepted: 07/02/2019] [Indexed: 06/10/2023]
Abstract
Quantitative susceptibility mapping (QSM) of human spinal vertebrae from a multi-echo gradient-echo (GRE) sequence is challenging, because comparable amounts of fat and water in the vertebrae make it difficult to solve the nonconvex optimization problem of fat-water separation (R2*-IDEAL) for estimating the magnetic field induced by tissue susceptibility. We present an in-phase (IP) echo initialization of R2*-IDEAL for QSM in the spinal vertebrae. Ten healthy human subjects were recruited for spine MRI. A 3D multi-echo GRE sequence was implemented to acquire out-phase and IP echoes. For the IP method, the R2* and field maps estimated by separately fitting the magnitude and phase of IP echoes were used to initialize gradient search R2*-IDEAL to obtain final R2*, field, water, and fat maps, and the final field map was used to generate QSM. The IP method was compared with the existing Zero method (initializing the field to zero), VARPRO-GC (variable projection using graphcuts but still initializing the field to zero), and SPURS (simultaneous phase unwrapping and removal of chemical shift using graphcuts for initialization) on both simulation and in vivo data. The single peak fat model was also compared with the multi-peak fat model. There was no substantial difference on QSM between the single peak and multi-peak fat models, but there were marked differences among different initialization methods. The simulations demonstrated that IP provided the lowest error in the field map. Compared to Zero, VARPRO-GC and SPURS, the proposed IP method provided substantially improved spine QSM in all 10 subjects.
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Affiliation(s)
- Yihao Guo
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
- Department of Biomedical Engineering, Cornell University, Ithaca, New York
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Zhe Liu
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
- Department of Biomedical Engineering, Cornell University, Ithaca, New York
| | - Yan Wen
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
- Department of Biomedical Engineering, Cornell University, Ithaca, New York
| | - Pascal Spincemaille
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
| | - Honglei Zhang
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
| | - Ramin Jafari
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
- Department of Biomedical Engineering, Cornell University, Ithaca, New York
| | - Shun Zhang
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
| | - Sarah Eskreis-Winkler
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
| | - Kelly M Gillen
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
| | - Peiwei Yi
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Qianjin Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Yi Wang
- Department of Radiology, Weill Medical College of Cornell University, New York, New York
- Department of Biomedical Engineering, Cornell University, Ithaca, New York
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20
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Triay Bagur A, Hutton C, Irving B, Gyngell ML, Robson MD, Brady M. Magnitude-intrinsic water-fat ambiguity can be resolved with multipeak fat modeling and a multipoint search method. Magn Reson Med 2019; 82:460-475. [PMID: 30874334 PMCID: PMC6593794 DOI: 10.1002/mrm.27728] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Revised: 01/16/2019] [Accepted: 02/15/2019] [Indexed: 12/21/2022]
Abstract
Purpose To develop a postprocessing algorithm for multiecho chemical‐shift encoded water–fat separation that estimates proton density fat fraction (PDFF) maps over the full dynamic range (0‐100%) using multipeak fat modeling and multipoint search optimization. To assess its accuracy, reproducibility, and agreement with state‐of‐the‐art complex‐based methods, and to evaluate its robustness to artefacts in abdominal PDFF maps. Methods We introduce MAGO (MAGnitude‐Only), a magnitude‐based reconstruction that embodies multipeak liver fat spectral modeling and multipoint optimization, and which is compatible with asymmetric echo acquisitions. MAGO is assessed first for accuracy and reproducibility on publicly available phantom data. Then, MAGO is applied to N = 178 UK Biobank cases, in which its liver PDFF measures are compared using Bland‐Altman analysis with those from a version of the hybrid iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) algorithm, LiverMultiScan IDEAL (LMS IDEAL, Perspectum Diagnostics Ltd, Oxford, UK). Finally, MAGO is tested on a succession of high field challenging cases for which LMS IDEAL generated artefacts in the PDFF maps. Results Phantom data showed accurate, reproducible MAGO PDFF values across manufacturers, field strengths, and acquisition protocols. Moreover, we report excellent agreement between MAGO and LMS IDEAL for 6‐echo, 1.5 tesla human acquisitions (bias = −0.02% PDFF, 95% confidence interval = ±0.13% PDFF). When tested on 12‐echo, 3 tesla cases from different manufacturers, MAGO was shown to be more robust to artefacts compared to LMS IDEAL. Conclusion MAGO resolves the water–fat ambiguity over the entire fat fraction dynamic range without compromising accuracy, therefore enabling robust PDFF estimation where phase data is inaccessible or unreliable and complex‐based and hybrid methods fail.
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Affiliation(s)
| | - Chloe Hutton
- Perspectum Diagnostics Ltd, Oxford, United Kingdom
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21
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Peng H, Zou C, Cheng C, Tie C, Qiao Y, Wan Q, Lv J, He Q, Liang D, Liu X, Liu W, Zheng H. Fat‐water separation based on Transition REgion Extraction (TREE). Magn Reson Med 2019; 82:436-448. [DOI: 10.1002/mrm.27710] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 01/29/2019] [Accepted: 02/05/2019] [Indexed: 12/26/2022]
Affiliation(s)
- Hao Peng
- Huazhong University of Science and Technology Wuhan China
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
| | - Chao Zou
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
| | - Chuanli Cheng
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
| | - Changjun Tie
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
| | - Yangzi Qiao
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
| | - Qian Wan
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
| | - Jianxun Lv
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
| | - Qiang He
- Shanghai United Imaging Healthcare Co., Ltd Shanghai China
| | - Dong Liang
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
| | - Xin Liu
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
| | - Wenzhong Liu
- Huazhong University of Science and Technology Wuhan China
| | - Hairong Zheng
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
- University of Chinese Academy of Sciences Beijing China
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Hu Z, Wang Y, Dong Z, Guo H. Water/fat separation for distortion-free EPI with point spread function encoding. Magn Reson Med 2019; 82:251-262. [PMID: 30847991 DOI: 10.1002/mrm.27717] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 01/30/2019] [Accepted: 02/06/2019] [Indexed: 12/31/2022]
Abstract
PURPOSE Effective removal of chemical-shift artifacts in echo-planar imaging (EPI) is a challenging problem especially with severe field inhomogeneity. This study aims to develop a reliable water/fat separation technique for point spread function (PSF) encoded EPI (PSF-EPI) by using its intrinsic multiple echo-shifted images. THEORY AND METHODS EPI with PSF encoding can achieve distortion-free imaging and can be highly accelerated using the tilted-CAIPI technique. In this study, the chemical-shift encoding existing in the intermediate images with different time shifts of PSF-EPI is used for water/fat separation, which is conducted with latest water/fat separation algorithms. The method was tested in T1-weighted, T2-weighted, and diffusion weighted imaging in healthy volunteers. RESULTS The ability of the proposed method to separate water/fat using intrinsic PSF-EPI signals without extra scans was demonstrated through in vivo T1-weighted, T2-weighted, and diffusion weighted imaging experiments. By exploring different imaging contrasts and regions, the results show that this PSF-EPI based method can separate water/fat and remove fat residues robustly. CONCLUSION By using the intrinsic signals of PSF-EPI for water/fat separation, fat signals can be effectively suppressed in EPI even with severe field inhomogeneity. This water/fat separation method for EPI can be extended to multiple image contrasts. The distortion-free PSF-EPI technique, thus, has the potential to provide anatomical and functional images with high-fidelity and practical acquisition efficiency.
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Affiliation(s)
- Zhangxuan Hu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Yishi Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Zijing Dong
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
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Samsonov A, Liu F, Velikina JV. Resolving estimation uncertainties of chemical shift encoded fat-water imaging using magnetization transfer effect. Magn Reson Med 2019; 82:202-212. [PMID: 30847974 DOI: 10.1002/mrm.27709] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 01/30/2019] [Accepted: 02/04/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE B0 field inhomogeneity may cause significant errors in chemical shift encoding-based fat-water (F/W) separation. We describe a new approach to improve its robustness using novel B0 field map pre-estimation. METHODS Our method exploits insensitivity of fat to magnetization transfer effect, which allows generating fat-insensitive B0 field priors with full or partial spatial support using a low-resolution magnetization transfer-weighted scan. The full prior can be employed by most F/W separation methods for initialization or data demodulation. We also propose a modified region-growing algorithm in which the partial prior is utilized for its initial seeding. RESULTS The magnetization transfer-based B0 priors significantly reduced F/W errors of three representative F/W separation methods in all cases. In cases with moderate B0 inhomogeneity, the full prior allowed error-free separation even with basic, voxel-independent processing. When coupled with methods exploiting B0 field smoothness, it significantly improved separation accuracy even in the presence of strong inhomogeneities. Seeding the region-growing with the partial prior significantly improved performance of F/W separation, including cases with spatially disconnected tissues. CONCLUSION Magnetization transfer-based B0 field pre-estimation provides valuable prior information for F/W separation, which may significantly improve its robustness at the expense of nominal (< 5%-10%) scan time increase.
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Affiliation(s)
- Alexey Samsonov
- Department of Radiology, University of Wisconsin, Madison, Wisconsin
| | - Fang Liu
- Department of Radiology, University of Wisconsin, Madison, Wisconsin
| | - Julia V Velikina
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin
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Goldfarb JW, Craft J, Cao JJ. Water-fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network. J Magn Reson Imaging 2019; 50:655-665. [DOI: 10.1002/jmri.26658] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 01/07/2019] [Accepted: 01/08/2019] [Indexed: 11/08/2022] Open
Affiliation(s)
- James W. Goldfarb
- Department of Research and Education; Saint Francis Hospital; Roslyn New York USA
| | - Jason Craft
- Department of Research and Education; Saint Francis Hospital; Roslyn New York USA
| | - J. Jane Cao
- Department of Research and Education; Saint Francis Hospital; Roslyn New York USA
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Ong F, Cheng J, Lustig M. General phase regularized reconstruction using phase cycling. Magn Reson Med 2018; 80:112-125. [PMID: 29159989 PMCID: PMC5876131 DOI: 10.1002/mrm.27011] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 10/23/2017] [Accepted: 10/24/2017] [Indexed: 12/21/2022]
Abstract
PURPOSE To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. THEORY AND METHODS The problem of enforcing phase constraints in reconstruction was studied under a regularized inverse problem framework. A general phase regularized reconstruction algorithm was proposed to enable various joint reconstruction of partial Fourier imaging, water-fat imaging and flow imaging, along with parallel imaging (PI) and compressed sensing (CS). Since phase regularized reconstruction is inherently non-convex and sensitive to phase wraps in the initial solution, a reconstruction technique, named phase cycling, was proposed to render the overall algorithm invariant to phase wraps. The proposed method was applied to retrospectively under-sampled in vivo datasets and compared with state of the art reconstruction methods. RESULTS Phase cycling reconstructions showed reduction of artifacts compared to reconstructions without phase cycling and achieved similar performances as state of the art results in partial Fourier, water-fat and divergence-free regularized flow reconstruction. Joint reconstruction of partial Fourier + water-fat imaging + PI + CS, and partial Fourier + divergence-free regularized flow imaging + PI + CS were demonstrated. CONCLUSION The proposed phase cycling reconstruction provides an alternative way to perform phase regularized reconstruction, without the need to perform phase unwrapping. It is robust to the choice of initial solutions and encourages the joint reconstruction of phase imaging applications. Magn Reson Med 80:112-125, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Frank Ong
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California
| | - Joseph Cheng
- Department of Radiology, Stanford University, Stanford, California
| | - Michael Lustig
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California
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Rydén H, Berglund J, Norbeck O, Avventi E, Skare S. T1 weighted fat/water separated PROPELLER acquired with dual bandwidths. Magn Reson Med 2018; 80:2501-2513. [DOI: 10.1002/mrm.27228] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 03/28/2018] [Accepted: 03/29/2018] [Indexed: 11/12/2022]
Affiliation(s)
- Henric Rydén
- Department of Neuroradiology; Karolinska University Hospital; Stockholm Sweden
- Department of Clinical Neuroscience; Karolinska Institutet; Stockholm Sweden
| | - Johan Berglund
- Department of Neuroradiology; Karolinska University Hospital; Stockholm Sweden
- Department of Clinical Neuroscience; Karolinska Institutet; Stockholm Sweden
| | - Ola Norbeck
- Department of Neuroradiology; Karolinska University Hospital; Stockholm Sweden
- Department of Clinical Neuroscience; Karolinska Institutet; Stockholm Sweden
| | - Enrico Avventi
- Department of Neuroradiology; Karolinska University Hospital; Stockholm Sweden
- Department of Clinical Neuroscience; Karolinska Institutet; Stockholm Sweden
| | - Stefan Skare
- Department of Neuroradiology; Karolinska University Hospital; Stockholm Sweden
- Department of Clinical Neuroscience; Karolinska Institutet; Stockholm Sweden
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Cui C, Shah A, Wu X, Thedens D, Jacob M. A rapid 3D fat-water decomposition method using globally optimal surface estimation (R-GOOSE). Magn Reson Med 2018; 79:2401-2407. [PMID: 28726301 PMCID: PMC5817637 DOI: 10.1002/mrm.26843] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Revised: 06/26/2017] [Accepted: 06/26/2017] [Indexed: 01/20/2023]
Abstract
PURPOSE To improve the graph model of our previous work GOOSE for fat-water decomposition with higher computational efficiency and quantitative accuracy. METHODS A modification of the GOOSE fat water decomposition algorithm is introduced while the global convergence guarantees of GOOSE are still inherited to minimize fat-water swaps and phase wraps. In this paper, two non-equidistant graph optimization frameworks are proposed as a single-step framework termed as rapid GOOSE (R-GOOSE), and a multi-step framework termed as multi-scale R-GOOSE (mR-GOOSE). Both frameworks contain considerably less graph connectivity than GOOSE, resulting in a great computation reduction thus making it readily applicable to multidimensional fat water applications. The quantitative accuracy and computational time of the novel frameworks are compared with GOOSE on the 2012 ISMRM Challenge datasets to demonstrate the improvement in performance. RESULTS Both frameworks accomplish the same level of high accuracy as GOOSE among all datasets. Compared to 100 layers in GOOSE, only 8 layers were used in the new graph model. Computational time is lowered by an order of magnitude to around 5 s for each dataset in (mR-GOOSE), R-GOOSE achieves an average run-time of 8 s. CONCLUSION The proposed method provides fat-water decomposition results with a lower run-time and higher accuracy compared to the previously proposed GOOSE algorithm. Magn Reson Med 79:2401-2407, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Chen Cui
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa
| | - Abhay Shah
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa
| | - Xiaodong Wu
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa
| | - Dan Thedens
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa
| | - Mathews Jacob
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa
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Andersson J, Ahlström H, Kullberg J. Water-fat separation incorporating spatial smoothing is robust to noise. Magn Reson Imaging 2018; 50:78-83. [PMID: 29601865 DOI: 10.1016/j.mri.2018.03.015] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Revised: 03/19/2018] [Accepted: 03/26/2018] [Indexed: 01/13/2023]
Abstract
PURPOSE To develop and evaluate a noise-robust method for reconstruction of water and fat images for spoiled gradient multi-echo sequences. METHODS The proposed method performs water-fat separation by using a graph cut to minimize an energy function consisting of unary and binary terms. Spatial smoothing is incorporated to increase robustness to noise. The graph cut can fail to find a solution covering the entire image, in which case the relative weighting of the unary term is iteratively increased until a complete solution is found. The proposed method was compared to two previously published methods. Reconstructions were performed on 16 cases taken from the 2012 ISMRM water-fat reconstruction challenge dataset, for which reference reconstructions were provided. Robustness towards noise was evaluated by reconstructing images with different levels of noise added. The percentage of water-fat swaps were calculated to measure performance. RESULTS At low noise levels the proposed method produced similar results to one of the previously published methods, while outperforming the other. The proposed method significantly outperformed both of the previously published methods at moderate and high noise levels. CONCLUSION By incorporating spatial smoothing, an increased robustness towards noise is achieved when performing water-fat reconstruction of spoiled gradient multi-echo sequences.
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Affiliation(s)
- Jonathan Andersson
- Section of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| | - Håkan Ahlström
- Section of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Antaros Medical, Mölndal, Sweden.
| | - Joel Kullberg
- Section of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Antaros Medical, Mölndal, Sweden.
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Diefenbach MN, Ruschke S, Eggers H, Meineke J, Rummeny EJ, Karampinos DC. Improving chemical shift encoding-based water-fat separation based on a detailed consideration of magnetic field contributions. Magn Reson Med 2018; 80:990-1004. [PMID: 29424458 PMCID: PMC6001469 DOI: 10.1002/mrm.27097] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 12/29/2017] [Accepted: 12/31/2017] [Indexed: 12/11/2022]
Abstract
Purpose To improve the robustness of existing chemical shift encoding‐based water–fat separation methods by incorporating a priori information of the magnetic field distortions in complex‐based water–fat separation. Methods Four major field contributions are considered: inhomogeneities of the scanner magnet, the shim field, an object‐based field map estimate, and a residual field. The former two are completely determined by spherical harmonic expansion coefficients directly available from the magnetic resonance (MR) scanner. The object‐based field map is forward simulated from air–tissue interfaces inside the field of view (FOV). The missing residual field originates from the object outside the FOV and is investigated by magnetic field simulations on a numerical whole body phantom. In vivo the spatially linear first‐order component of the residual field is estimated by measuring echo misalignments after demodulation of other field contributions resulting in a linear residual field. Gradient echo datasets of the cervical and the ankle region without and with shimming were acquired, where all four contributions were incorporated in the water–fat separation with two algorithms from the ISMRM water–fat toolbox and compared to water–fat separation with less incorporated field contributions. Results Incorporating all four field contributions as demodulation steps resulted in reduced temporal and spatial phase wraps leading to almost swap‐free water–fat separation results in all datasets. Conclusion Demodulating estimates of major field contributions reduces the phase evolution to be driven by only small differences in local tissue susceptibility, which supports the field smoothness assumption of existing water–fat separation techniques.
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Affiliation(s)
- Maximilian N Diefenbach
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Stefan Ruschke
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | | | | | - Ernst J Rummeny
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
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Kim H, Kim DH, Sohn CH, Park J. Rapid chemical shift encoding with single-acquisition single-slab 3D GRASE. Magn Reson Med 2017; 78:1852-1861. [DOI: 10.1002/mrm.26595] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Revised: 12/08/2016] [Accepted: 12/08/2016] [Indexed: 12/21/2022]
Affiliation(s)
- Hahnsung Kim
- Department of Biomedical Engineering; Sungkyunkwan University; Suwon Republic of Korea
- Department of Electrical and Electronic Engineering; Yonsei University; Seoul Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering; Yonsei University; Seoul Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology; Seoul National University Hospital; Seoul Republic of Korea
| | - Jaeseok Park
- Department of Biomedical Engineering; Sungkyunkwan University; Suwon Republic of Korea
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31
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Berglund J, Skorpil M. Multi-scale graph-cut algorithm for efficient water-fat separation. Magn Reson Med 2016; 78:941-949. [DOI: 10.1002/mrm.26479] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 08/30/2016] [Accepted: 09/01/2016] [Indexed: 12/28/2022]
Affiliation(s)
- Johan Berglund
- Department of Medical Radiation Physics; Karolinska University Hospital; Stockholm Sweden
- Department of Clinical Science; Intervention and Technology, Karolinska Institute; Stockholm Sweden
| | - Mikael Skorpil
- Department of Radiology; Uppsala University Hospital; Uppsala Sweden
- Department of Radiation Sciences; Umeå University; Umeå Sweden
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Zhang X, Li CX. Arterial spin labeling perfusion magnetic resonance imaging of non-human primates. Quant Imaging Med Surg 2016; 6:573-581. [PMID: 27942478 DOI: 10.21037/qims.2016.10.05] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Non-human primates (NHPs) resemble most aspects of humans in brain physiology and anatomy and are excellent animal models for translational research in neuroscience, biomedical research and pharmaceutical development. Cerebral blood flow (CBF) offers essential physiological information of the brain to examine the abnormal functionality in NHP models with cerebral vascular diseases and neurological disorders or dementia. Arterial spin labeling (ASL) perfusion MRI techniques allow for high temporal and spatial CBF measurement and are intensively used in studies of animals and humans. In this article, current high-resolution ASL perfusion MRI techniques for quantitative evaluation of brain physiology and function in NHPs are described and their applications and limitation are discussed as well.
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Affiliation(s)
- Xiaodong Zhang
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA 30329, USA;; Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, USA
| | - Chun-Xia Li
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA 30329, USA
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Cheng C, Zou C, Liang C, Liu X, Zheng H. Fat-water separation using a region-growing algorithm with self-feeding phasor estimation. Magn Reson Med 2016; 77:2390-2401. [DOI: 10.1002/mrm.26297] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2016] [Revised: 05/17/2016] [Accepted: 05/17/2016] [Indexed: 12/16/2022]
Affiliation(s)
- Chuanli Cheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Shenzhen People's Republic of China
- University of Chinese Academy of Sciences; Beijing People's Republic of China
| | - Chao Zou
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Shenzhen People's Republic of China
| | - Changhong Liang
- Department of Radiology, Guangdong General Hospital; Guangdong Academy of Medical Sciences; Guangzhou People's Republic of China
| | - Xin Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Shenzhen People's Republic of China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Shenzhen People's Republic of China
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Zhang T, Chen Y, Bao S, Alley MT, Pauly JM, Hargreaves BA, Vasanawala SS. Resolving phase ambiguity in dual-echo dixon imaging using a projected power method. Magn Reson Med 2016; 77:2066-2076. [PMID: 27221766 DOI: 10.1002/mrm.26287] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2016] [Revised: 05/03/2016] [Accepted: 05/04/2016] [Indexed: 12/11/2022]
Abstract
PURPOSE To develop a fast and robust method to resolve phase ambiguity in dual-echo Dixon imaging. METHODS A major challenge in dual-echo Dixon imaging is to estimate the phase error resulting from field inhomogeneity. In this work, a binary quadratic optimization program was formulated to resolve the phase ambiguity. A projected power method was developed to efficiently solve the optimization problem. Both the 1-peak fat model and 6-peak fat model were applied to three-dimensional (3D) datasets. Additionally, the proposed method was extended to dynamic magnetic resonance imaging (MRI) applications using the 6-peak fat model. With institutional review board (IRB) approval and patient consent/assent, the proposed method was evaluated and compared with region growing on 29 consecutive 3D high-resolution patient datasets. RESULTS Fast and robust water/fat separation was achieved by the proposed method in different representative 3D datasets and dynamic 3D datasets. Superior water/fat separation was achieved using the 6-peak fat model compared with the 1-peak fat model. Compared to region growing, the proposed method reduced water/fat swaps from 76 to 7% of the patient cohort. CONCLUSION The proposed method can achieve fast and robust phase error estimation in dual-echo Dixon imaging. Magn Reson Med 77:2066-2076, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Tao Zhang
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Yuxin Chen
- Department of Electrical Engineering, Princeton University, Princeton, New Jersey, USA
| | - Shanshan Bao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Marcus T Alley
- Department of Radiology, Stanford University, Stanford, California, USA
| | - John M Pauly
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Brian A Hargreaves
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
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Dong J, Liu T, Chen F, Zhou D, Dimov A, Raj A, Cheng Q, Spincemaille P, Wang Y. Simultaneous phase unwrapping and removal of chemical shift (SPURS) using graph cuts: application in quantitative susceptibility mapping. IEEE TRANSACTIONS ON MEDICAL IMAGING 2015; 34:531-540. [PMID: 25312917 DOI: 10.1109/tmi.2014.2361764] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging technique that reveals tissue magnetic susceptibility. It relies on having a high quality field map, typically acquired with a relatively long echo spacing and long final TE. Applications of QSM outside the brain require the removal of fat contributions to the total signal phase. However, current water/fat separation methods applied on typical data acquired for QSM suffer from three issues: inadequacy when using large echo spacing, over-smoothing of the field maps and high computational cost. In this paper, the general phase wrap and chemical shift problem is formulated using a single species fitting and is solved using graph cuts with conditional jump moves. This method is referred as simultaneous phase unwrapping and removal of chemical shift (SPURS). The result from SPURS is then used as the initial guess for a voxel-wise iterative decomposition of water and fat with echo asymmetric and least-squares estimation (IDEAL). The estimated 3-D field maps are used to compute QSM in body regions outside of the brain, such as the liver. Experimental results show substantial improvements in field map estimation, water/fat separation and reconstructed QSM compared to two existing water/fat separation methods on 1.5T and 3T magnetic resonance human data with long echo spacing and rapid field map variation.
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Liu J, Drangova M. Method for B0 off-resonance mapping by non-iterative correction of phase-errors (B0-NICE). Magn Reson Med 2014; 74:1177-88. [PMID: 25351504 DOI: 10.1002/mrm.25497] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2014] [Revised: 09/23/2014] [Accepted: 09/25/2014] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop and evaluate a multiecho phase-unwrapping-based B0 mapping method. METHODS The proposed method estimates a B0 map by Non-Iterative Correction of phase-Errors (B0-NICE). The B0-NICE method generates an initial B0 map from a "pseudo in-phase" data set by introducing a bias frequency shift to the multipeak fat model, followed by correcting the phase errors using both phase and magnitude information. The performance of the B0-NICE method was evaluated with all data cases from the 2012 ISMRM Challenge. RESULTS The B0 field estimates from B0-NICE were compared with those generated by GlObally Optimal Surface Estimation (GOOSE). In the presence of large B0 inhomogeneity, the B0-NICE method was able to generate more realistic B0 maps from multiecho data, compared with GOOSE. Accurate estimation of fat-fraction (FF) map was also achieved using the proposed algorithm. CONCLUSION The primary finding of the present study is that accurate FF and B0 maps are achievable if magnitude data is processed independently and used to correct phase errors existing in B0 maps generated by phase unwrapping. The B0-NICE software is freely available to the scientific community.
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Affiliation(s)
- Junmin Liu
- Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada
| | - Maria Drangova
- Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada.,Department of Medical Biophysics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada
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Chen Y, Cai C, Zhong J, Chen Z. Water-fat separation from a single spatiotemporally encoded echo based on nominal k-space peaking and joint regularized estimation. Magn Reson Med 2014; 73:1441-9. [PMID: 24798405 DOI: 10.1002/mrm.25261] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Revised: 03/26/2014] [Accepted: 04/01/2014] [Indexed: 11/08/2022]
Abstract
PURPOSE To present a new high-resolution single-point water-fat separation algorithm based on the spatiotemporally encoded chemical shift imaging technique. THEORY Identifying water and fat peaks on the ensemble of the nominal k-space profiles of all spatiotemporally encoded lines enables evaluation of the mean off-resonance frequencies of the two components. With utilization of the spatial smoothness and filtering regularizations, the water/fat profiles can be discriminated with twice joint linear least squares estimations line-by-line. METHODS The effectiveness of the proposed algorithm was assessed by experiments on oil-water phantoms and in vivo in rats at 7T using a spatiotemporally encoded variant of the multishot spin-echo sequence. The results were compared with those obtained from previously proposed 1-point Dixon, 2-point Dixon, and 3-point IDEAL methods. RESULTS The results demonstrate that the new technique can achieve high-quality water-fat separations, comparable in signal-to-noise ratio and contrast to the multipoint methods and is more robust in cases when large areas of low signals or motion artifacts jeopardize the results from the 1-point Dixon method. CONCLUSIONS The proposed technique is potentially a new viable alternative for single-point water-fat separation.
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Affiliation(s)
- Ying Chen
- Department of Electronics Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory for Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, China
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Lu L, Donnola SB, Koontz M, Griswold MA, Duerk JL, Flask CA. Lipid elimination with an echo-shifting N/2-ghost acquisition (LEENA) MRI. Magn Reson Med 2014; 73:711-7. [PMID: 24639034 DOI: 10.1002/mrm.25177] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Revised: 01/21/2014] [Accepted: 01/21/2014] [Indexed: 12/22/2022]
Abstract
PURPOSE The Dixon techniques provide uniform water-fat separation but require multiple image sets, which extend the overall acquisition time. Here, an alternative rapid single acquisition method, lipid elimination with an echo-shifting N/2-ghost acquisition (LEENA), was introduced. METHODS The LEENA method utilized a fast imaging with steady-state free precession sequence to obtain a single k-space dataset in which successive k-space lines are acquired to allow the fat magnetization to precess 180°. The LEENA data were then unghosted using either image-domain (LEENA-S) or k-space domain (LEENA-G) parallel imaging techniques to reconstruct water-only and fat-only images. An off-resonance correction technique was incorporated to improve the uniformity of the water-fat separation. RESULTS Uniform water-fat separation was achieved for both the LEENA-S and LEENA-G methods for phantom and human body and leg imaging applications at 1.5T and 3T. The resultant water and fat images were qualitatively similar to conventional 2-point Dixon and fat-suppressed images. CONCLUSION The LEENA-S and LEENA-G methods provide uniform water and fat images from a single MRI acquisition. These straightforward methods can be adapted to 1.5T and 3T clinical MRI scanners and provide comparable fat/water separation with conventional 2-point Dixon and fat-suppression techniques.
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Affiliation(s)
- Lan Lu
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA; Department of Urology, Case Western Reserve University, Cleveland, Ohio, USA
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Cui C, Wu X, Newell JD, Jacob M. Fat water decomposition using globally optimal surface estimation (GOOSE) algorithm. Magn Reson Med 2014; 73:1289-99. [PMID: 24604689 DOI: 10.1002/mrm.25193] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2013] [Revised: 02/04/2014] [Accepted: 02/06/2014] [Indexed: 01/09/2023]
Abstract
PURPOSE This article focuses on developing a novel noniterative fat water decomposition algorithm more robust to fat water swaps and related ambiguities. METHODS Field map estimation is reformulated as a constrained surface estimation problem to exploit the spatial smoothness of the field, thus minimizing the ambiguities in the recovery. Specifically, the differences in the field map-induced frequency shift between adjacent voxels are constrained to be in a finite range. The discretization of the above problem yields a graph optimization scheme, where each node of the graph is only connected with few other nodes. Thanks to the low graph connectivity, the problem is solved efficiently using a noniterative graph cut algorithm. The global minimum of the constrained optimization problem is guaranteed. The performance of the algorithm is compared with that of state-of-the-art schemes. Quantitative comparisons are also made against reference data. RESULTS The proposed algorithm is observed to yield more robust fat water estimates with fewer fat water swaps and better quantitative results than other state-of-the-art algorithms in a range of challenging applications. CONCLUSION The proposed algorithm is capable of considerably reducing the swaps in challenging fat water decomposition problems. The experiments demonstrate the benefit of using explicit smoothness constraints in field map estimation and solving the problem using a globally convergent graph-cut optimization algorithm.
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Affiliation(s)
- Chen Cui
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa, USA
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Sharma SD, Artz NS, Hernando D, Horng DE, Reeder SB. Improving chemical shift encoded water-fat separation using object-based information of the magnetic field inhomogeneity. Magn Reson Med 2014; 73:597-604. [PMID: 24585487 DOI: 10.1002/mrm.25163] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Revised: 12/18/2013] [Accepted: 01/14/2014] [Indexed: 12/11/2022]
Abstract
PURPOSE The purpose of this work was to improve the robustness of existing chemical shift encoded water-fat separation methods by incorporating object-based information of the B0 field inhomogeneity. THEORY The primary challenge in water-fat separation is the estimation of phase shifts that arise from B0 field inhomogeneity, which is composed of the background field and susceptibility-induced field. The susceptibility-induced field can be estimated if the susceptibility distribution is known or can be approximated. In this work, the susceptibility distribution is approximated from the source images using the known susceptibility values of water, fat, and air. The field estimate is then demodulated from the source images before water-fat separation. METHODS Chemical shift encoded source images were acquired in anatomical regions that are prone to water-fat swaps. The images were processed using algorithms from the ISMRM Fat-Water Toolbox, with and without the object-based field map information. The estimates were compared to examine the benefit of using the object-based field map information. RESULTS Multiple cases are shown in which water-fat swaps were avoided by using the object-based information of the B0 field map. CONCLUSION Object-based information of the B0 field may improve the robustness of existing chemical shift encoded water-fat separation methods.
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Affiliation(s)
- Samir D Sharma
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
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Soliman AS, Yuan J, Vigen KK, White JA, Peters TM, McKenzie CA. Max-IDEAL: a max-flow based approach for IDEAL water/fat separation. Magn Reson Med 2013; 72:510-21. [PMID: 24006275 DOI: 10.1002/mrm.24923] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2013] [Revised: 07/08/2013] [Accepted: 07/23/2013] [Indexed: 12/23/2022]
Abstract
PURPOSE To propose a novel approach to water/fat separation using a unique smoothness constraint. THEORY AND METHODS Chemical-shift based water/fat separation is an established noninvasive imaging tool for the visualization of body fat in various anatomies. Nevertheless, B0 magnetic field inhomogeneities can hamper the water/fat separation process. In this work, B0 variations are mapped using a convex-relaxed labeling model which produces a coarse estimate of the field map, while considering T2* decay during the labeling process. Fat and water components are subsequently resolved using T2*-IDEAL. An adaptive spatial filtering (ASF) was introduced to improve the robustness of the estimate. The method was tested on cardiac and abdominal datasets from healthy volunteers and nonalcoholic fatty liver disease (NAFLD) patients. RESULTS Out of 168 cardiac and abdominal images, only 1 case has shown water/fat swaps that can hinder the clinical interpretation of the underlying anatomy. CONCLUSION This work demonstrates a new water/fat separation approach that prevents the occurrence of water/fat swaps, by means of a unique smoothness constraint. Incorporating T2* effect in the labeling procedure and including the ASF processing enhance the robustness of the proposed approach and permit the procedure to handle abrupt B0 variations within the field of view.
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Affiliation(s)
- Abraam S Soliman
- Biomedical Engineering, Western University, London, Canada; Robarts Research Institute, Western University, London, Canada
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Silver HJ, Niswender KD, Kullberg J, Berglund J, Johansson L, Bruvold M, Avison MJ, Welch EB. Comparison of gross body fat-water magnetic resonance imaging at 3 Tesla to dual-energy X-ray absorptiometry in obese women. Obesity (Silver Spring) 2013; 21:765-74. [PMID: 23712980 PMCID: PMC3500572 DOI: 10.1002/oby.20287] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2011] [Accepted: 05/13/2012] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Improved understanding of how depot-specific adipose tissue mass predisposes to obesity-related comorbidities could yield new insights into the pathogenesis and treatment of obesity as well as metabolic benefits of weight loss. We hypothesized that three-dimensional (3D) contiguous "fat-water" MR imaging (FWMRI) covering the majority of a whole-body field of view (FOV) acquired at 3 Tesla (3T) and coupled with automated segmentation and quantification of amount, type, and distribution of adipose and lean soft tissue would show great promise in body composition methodology. DESIGN AND METHODS Precision of adipose and lean soft tissue measurements in body and trunk regions were assessed for 3T FWMRI and compared to dual-energy X-ray absorptiometry (DXA). Anthropometric, FWMRI, and DXA measurements were obtained in 12 women with BMI 30-39.9 kg/m(2) . RESULTS Test-retest results found coefficients of variation (CV) for FWMRI that were all under 3%: gross body adipose tissue (GBAT) 0.80%, total trunk adipose tissue (TTAT) 2.08%, visceral adipose tissue (VAT) 2.62%, subcutaneous adipose tissue (SAT) 2.11%, gross body lean soft tissue (GBLST) 0.60%, and total trunk lean soft tissue (TTLST) 2.43%. Concordance correlation coefficients between FWMRI and DXA were 0.978, 0.802, 0.629, and 0.400 for GBAT, TTAT, GBLST, and TTLST, respectively. CONCLUSIONS While Bland-Altman plots demonstrated agreement between FWMRI and DXA for GBAT and TTAT, a negative bias existed for GBLST and TTLST measurements. Differences may be explained by the FWMRI FOV length and potential for DXA to overestimate lean soft tissue. While more development is necessary, the described 3T FWMRI method combined with fully-automated segmentation is fast (<30-min total scan and post-processing time), noninvasive, repeatable, and cost-effective.
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Affiliation(s)
- Heidi J Silver
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
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Peterson P, Månsson S. Fat quantification using multiecho sequences with bipolar gradients: investigation of accuracy and noise performance. Magn Reson Med 2013; 71:219-29. [PMID: 23412971 DOI: 10.1002/mrm.24657] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2012] [Revised: 12/20/2012] [Accepted: 01/03/2013] [Indexed: 02/01/2023]
Abstract
PURPOSE To investigate the accuracy and noise performance of fat quantification with multiple gradient-echo images acquired using bipolar read-out gradients and compare them with those of the well-established unipolar technique. THEORY The bipolar read-out technique induces phase and amplitude errors caused by gradient delays, eddy currents, and frequency-dependent coil sensitivity. In this study, these errors were corrected for jointly with the fat/water separation by modeling the impact of these effects on the signal. This approach did not require acquisition of reference data or modification of the pulse sequence. METHODS Simulations and a phantom experiment were used to investigate the accuracy and noise performance of the technique and compare them with those of a well-established technique using unipolar read-out gradients. Also, the in vivo feasibility was demonstrated for abdominal applications. RESULTS The phantom experiment demonstrated similar accuracy of the bipolar and unipolar fat quantification techniques. In addition, the noise performance was shown not to be affected by the added estimations of the phase and amplitude errors for most inter-echo times. CONCLUSION The bipolar technique was found to provide accurate fat quantification with noise performance similar to the unipolar technique given an appropriate choice of inter-echo time.
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Affiliation(s)
- Pernilla Peterson
- Department of Medical Radiation Physics, Lund University, Skåne University Hospital, Malmö, Sweden
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Sharma SD, Hu HH, Nayak KS. Chemical shift encoded water-fat separation using parallel imaging and compressed sensing. Magn Reson Med 2013; 69:456-66. [PMID: 22505285 PMCID: PMC3606060 DOI: 10.1002/mrm.24270] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Revised: 03/02/2012] [Accepted: 03/05/2012] [Indexed: 12/21/2022]
Abstract
Chemical shift encoded techniques have received considerable attention recently because they can reliably separate water and fat in the presence of off-resonance. The insensitivity to off-resonance requires that data be acquired at multiple echo times, which increases the scan time as compared to a single echo acquisition. The increased scan time often requires that a compromise be made between the spatial resolution, the volume coverage, and the tolerance to artifacts from subject motion. This work describes a combined parallel imaging and compressed sensing approach for accelerated water-fat separation. In addition, the use of multiscale cubic B-splines for B(0) field map estimation is introduced. The water and fat images and the B(0) field map are estimated via an alternating minimization. Coil sensitivity information is derived from a calculated k-space convolution kernel and l(1)-regularization is imposed on the coil-combined water and fat image estimates. Uniform water-fat separation is demonstrated from retrospectively undersampled data in the liver, brachial plexus, ankle, and knee as well as from a prospectively undersampled acquisition of the knee at 8.6x acceleration.
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Affiliation(s)
- Samir D Sharma
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA.
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Narayan S, Kalhan SC, Wilson DL. Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla. J Magn Reson Imaging 2012; 37:1247-53. [PMID: 23023815 DOI: 10.1002/jmri.23826] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2011] [Accepted: 08/15/2012] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. MATERIALS AND METHODS Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. RESULTS Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. CONCLUSION Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically.
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Affiliation(s)
- Sreenath Narayan
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
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Tsao J, Jiang Y. Hierarchical IDEAL: fast, robust, and multiresolution separation of multiple chemical species from multiple echo times. Magn Reson Med 2012; 70:155-9. [PMID: 22887356 DOI: 10.1002/mrm.24441] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2012] [Revised: 07/05/2012] [Accepted: 07/06/2012] [Indexed: 12/21/2022]
Abstract
We describe a generalized version of hierarchical IDEAL that can flexibly handle arbitrary chemical species at arbitrary echo times. The proposed work is fast and robust, and it has three key features: (1) multiresolution approach, which allows the method to handle images with disjoint regions, makes it less susceptible to local optima, and reduces the ambiguity of the separation; (2) direct phase estimation, which bypasses the phase wrapping issue, and (3) efficient algebraic formulation, which enables fast calculation and insensitivity to spatially varying phase across the image, from sources such as partial echo acquisition, receiver coils, motion, and flow. Representative results at 1.5 T and 3 T are presented from human ankle, wrist, and a water/oil/silicone phantom.
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Affiliation(s)
- Jeffrey Tsao
- Global Imaging Group, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts 02139, USA.
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Hu HH, Börnert P, Hernando D, Kellman P, Ma J, Reeder S, Sirlin C. ISMRM workshop on fat-water separation: insights, applications and progress in MRI. Magn Reson Med 2012; 68:378-88. [PMID: 22693111 PMCID: PMC3575097 DOI: 10.1002/mrm.24369] [Citation(s) in RCA: 130] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2012] [Revised: 05/14/2012] [Accepted: 05/16/2012] [Indexed: 12/12/2022]
Abstract
Approximately 130 attendees convened on February 19-22, 2012 for the first ISMRM-sponsored workshop on water-fat imaging. The motivation to host this meeting was driven by the increasing number of research publications on this topic over the past decade. The scientific program included an historical perspective and a discussion of the clinical relevance of water-fat MRI, a technical description of multiecho pulse sequences, a review of data acquisition and reconstruction algorithms, a summary of the confounding factors that influence quantitative fat measurements and the importance of MRI-based biomarkers, a description of applications in the heart, liver, pancreas, abdomen, spine, pelvis, and muscles, an overview of the implications of fat in diabetes and obesity, a discussion on MR spectroscopy, a review of childhood obesity, the efficacy of lifestyle interventional studies, and the role of brown adipose tissue, and an outlook on federal funding opportunities from the National Institutes of Health.
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Affiliation(s)
- Houchun Harry Hu
- Departments of Radiology and Electrical Engineering, Children's Hospital Los Angeles, University of Southern California, Los Angeles, California 90027, USA.
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Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual-Energy X-Ray Absorptiometry in Obese Women. Obesity (Silver Spring) 2012. [DOI: 10.1038/oby.2012.147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Hernando D, Hines CDG, Yu H, Reeder SB. Addressing phase errors in fat-water imaging using a mixed magnitude/complex fitting method. Magn Reson Med 2012; 67:638-44. [PMID: 21713978 PMCID: PMC3525711 DOI: 10.1002/mrm.23044] [Citation(s) in RCA: 94] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2011] [Revised: 04/20/2011] [Accepted: 05/21/2011] [Indexed: 11/12/2022]
Abstract
Accurate, noninvasive measurements of liver fat content are needed for the early diagnosis and quantitative staging of nonalcoholic fatty liver disease. Chemical shift-based fat quantification methods acquire images at multiple echo times using a multiecho spoiled gradient echo sequence, and provide fat fraction measurements through postprocessing. However, phase errors, such as those caused by eddy currents, can adversely affect fat quantification. These phase errors are typically most significant at the first echo of the echo train, and introduce bias in complex-based fat quantification techniques. These errors can be overcome using a magnitude-based technique (where the phase of all echoes is discarded), but at the cost of significantly degraded signal-to-noise ratio, particularly for certain choices of echo time combinations. In this work, we develop a reconstruction method that overcomes these phase errors without the signal-to-noise ratio penalty incurred by magnitude fitting. This method discards the phase of the first echo (which is often corrupted) while maintaining the phase of the remaining echoes (where phase is unaltered). We test the proposed method on 104 patient liver datasets (from 52 patients, each scanned twice), where the fat fraction measurements are compared to coregistered spectroscopy measurements. We demonstrate that mixed fitting is able to provide accurate fat fraction measurements with high signal-to-noise ratio and low bias over a wide choice of echo combinations.
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Affiliation(s)
- D Hernando
- Department of Radiology, University of Wisconsin, Madison, Wisconsin 53705, USA.
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Soliman AS, Yuan J, White JA, Peters TM, McKenzie CA. A Convex Relaxation Approach to Fat/Water Separation with Minimum Label Description. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2012 2012; 15:519-26. [DOI: 10.1007/978-3-642-33418-4_64] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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