51
|
Zhang X, Cao YZ, Mu XH, Sun Y, Schmidt M, Forman C, Speier P, Lu SS, Hong XN. Highly accelerated compressed sensing time-of-flight magnetic resonance angiography may be reliable for diagnosing head and neck arterial steno-occlusive disease: a comparative study with digital subtraction angiography. Eur Radiol 2020; 30:3059-3065. [PMID: 32064562 DOI: 10.1007/s00330-020-06682-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 12/10/2019] [Accepted: 01/28/2020] [Indexed: 11/29/2022]
Abstract
INTRODUCTION We aimed to investigate the utility of compressed sensing time-of-flight magnetic resonance angiography (CS TOF-MRA) for diagnosing intracranial and cervical arterial stenosis by using digital subtraction angiography (DSA) as the reference standard. METHODS Thirty-seven patients with head and neck arterial stenoses who underwent CS TOF-MRA and DSA were retrospectively enrolled. The reconstructed resolution of CS TOF-MRA was 0.4 × 0.4 × 0.4 mm3. The scan time was 5 min and 2 s. The image quality of CS TOF-MRA was independently ranked by two neuroradiologists in 1031 arterial segments. The luminal stenosis grades on CS TOF-MRA and DSA were analyzed in 61 arterial segments and were compared using the Wilcoxon signed-rank test. The ability of CS TOF-MRA to predict moderate to severe stenosis or occlusion was analyzed. RESULTS The image quality of most arterial segments (95.2%) on CS TOF-MRA was excellent. Arterial segments with low image quality were mainly the V3-4 segments of the vertebral artery. The majority of arterial stenoses (62.3%) were located in the cervical internal carotid artery. The luminal stenosis grades of CS TOF-MRA were concordant with that of DSA in 50 of 61 segments (p = 0.366). CS TOF-MRA had a sensitivity of 84.4% and a specificity of 88.5% for predicting moderate to severe stenosis. For detecting occlusion lesions, it had a sensitivity of 100% and a specificity of 94.1%. CONCLUSION CS TOF-MRA provides adequate image quality within a reasonable acquisition time and is a reliable tool for diagnosing head and neck arterial steno-occlusive disease. KEY POINTS • CS TOF-MRA provides a relatively large coverage (16 cm), high resolution (0.4 × 0.4 × 0.4 mm3) and good image quality of head and neck arteries within 5 min and 2 s. • The diagnostic accuracy of CS TOF-MRA in the assessment of moderate to severe stenosis and occlusion was comparable with that of DSA. • Arterial segments with low image quality were mainly the V3 and V4 segments of the vertebral artery.
Collapse
Affiliation(s)
- Xuan Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou district, Nanjing, Jiangsu Province, China
| | - Yue Zhou Cao
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou district, Nanjing, Jiangsu Province, China
| | - Xi Hu Mu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou district, Nanjing, Jiangsu Province, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | | | | | | | - Shan Shan Lu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou district, Nanjing, Jiangsu Province, China.
| | - Xun Ning Hong
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou district, Nanjing, Jiangsu Province, China.
| |
Collapse
|
52
|
Schoormans J, Strijkers GJ, Hansen AC, Nederveen AJ, Coolen BF. Compressed sensing MRI with variable density averaging (CS-VDA) outperforms full sampling at low SNR. ACTA ACUST UNITED AC 2020; 65:045004. [DOI: 10.1088/1361-6560/ab63b7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
|
53
|
Lei KM, Ha D, Song YQ, Westervelt RM, Martins R, Mak PI, Ham D. Portable NMR with Parallelism. Anal Chem 2020; 92:2112-2120. [PMID: 31894967 DOI: 10.1021/acs.analchem.9b04633] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Portable NMR combining a permanent magnet and a complementary metal-oxide-semiconductor (CMOS) integrated circuit has recently emerged to offer the long desired online, on-demand, or in situ NMR analysis of small molecules for chemistry and biology. Here we take this cutting-edge technology to the next level by introducing parallelism to a state-of-the-art portable NMR platform to accelerate its experimental throughput, where NMR is notorious for inherently low throughput. With multiple (N) samples inside a single magnet, we perform simultaneous NMR analyses using a single silicon electronic chip, going beyond the traditional single-sample-per-magnet paradigm. We execute the parallel analyses via either time-interleaving or magnetic resonance imaging (MRI). In the time-interleaving method, the N samples occupy N separate NMR coils: we connect these N NMR coils to the single silicon chip one after another and repeat these sequential NMR scans. This time-interleaving is an effective parallelization, given a long recovery time of a single NMR scan. To demonstrate this time-interleaved parallelism, we use N = 2 for high-resolution multidimensional spectroscopy such as J-coupling resolved free induction decay spectroscopy and correlation spectroscopy (COSY) with the field homogeneity carefully optimized (<0.16 ppm) and N = 4 for multidimensional relaxometry such as diffusion-edited T2 mapping and T1-T2 correlation mapping, expediting the throughput by 2-4 times. In the MRI technique, the N samples (N = 18 in our demonstration) share 1 NMR coil connected to the single silicon chip and are imaged all at once multiple times, which reveals the relaxation time of all N samples simultaneously. This imaging-based approach accelerates the relaxation time measurement by 4.5 times, and it could be by 18 times if the signal-to-noise were not limited. Overall, this work demonstrates the first portable high-resolution multidimensional NMR with throughput-accelerating parallelism.
Collapse
Affiliation(s)
- Ka-Meng Lei
- State Key Laboratory of Analog and Mixed-Signal VLSI , University of Macau , Macau , P. R. China.,John A. Paulson School of Engineering and Applied Sciences , Harvard University , Cambridge , Massachusetts 02138 , United States
| | - Dongwan Ha
- John A. Paulson School of Engineering and Applied Sciences , Harvard University , Cambridge , Massachusetts 02138 , United States
| | - Yi-Qiao Song
- Schlumberger-Doll Research Center , Cambridge , Massachusetts 02139 , United States
| | - Robert M Westervelt
- John A. Paulson School of Engineering and Applied Sciences , Harvard University , Cambridge , Massachusetts 02138 , United States.,Department of Physics , Harvard University , Cambridge , Massachusetts 02138 , United States
| | - Rui Martins
- State Key Laboratory of Analog and Mixed-Signal VLSI , University of Macau , Macau , P. R. China.,Instituto Superior Técnico , Universidade de Lisboa , Lisbon 1049-001 , Portugal
| | - Pui-In Mak
- State Key Laboratory of Analog and Mixed-Signal VLSI , University of Macau , Macau , P. R. China
| | - Donhee Ham
- John A. Paulson School of Engineering and Applied Sciences , Harvard University , Cambridge , Massachusetts 02138 , United States
| |
Collapse
|
54
|
Zevenhoven KCJ, Mäkinen AJ, Ilmoniemi RJ. Superconducting receiver arrays for magnetic resonance imaging. Biomed Phys Eng Express 2020; 6:015016. [PMID: 33438604 DOI: 10.1088/2057-1976/ab5c61] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Superconducting QUantum-Interference Devices (SQUIDs) make magnetic resonance imaging (MRI) possible in ultra-low microtesla-range magnetic fields. In this work, we investigate the design parameters affecting the signal and noise performance of SQUID-based sensors and multichannel magnetometers for MRI of the brain. Besides sensor intrinsics, various noise sources along with the size, geometry and number of superconducting detector coils are important factors affecting the image quality. We derive figures of merit based on optimal combination of multichannel data, analyze different sensor array designs, and provide tools for understanding the signal detection and the different noise mechanisms. The work forms a guide to making design decisions for both imaging- and sensor-oriented readers.
Collapse
Affiliation(s)
- Koos C J Zevenhoven
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, FI-00076 AALTO, Finland
| | | | | |
Collapse
|
55
|
Zheng Q, Xu L, Xiong L, Cui X, Nan J, He T. Coil combination using linear deconvolution in k-space for phase imaging. Quant Imaging Med Surg 2019; 9:1792-1803. [PMID: 31867233 DOI: 10.21037/qims.2019.10.08] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background The combination of multi-channel data is a critical step for the imaging of phase and susceptibility contrast in magnetic resonance imaging (MRI). Magnitude-weighted phase combination methods often produce noise and aliasing artifacts in the magnitude images at accelerated imaging sceneries. To address this issue, an optimal coil combination method through deconvolution in k-space is proposed in this paper. Methods The proposed method firstly employs the sum-of-squares and phase aligning method to yield a complex reference coil image which is then used to calculate the coil sensitivity and its Fourier transform. Then, the coil k-space combining weights is computed, taking into account the truncated frequency data of coil sensitivity and the acquired k-space data. Finally, combining the coil k-space data with the acquired weights generates the k-space data of proton distribution, with which both phase and magnitude information can be obtained straightforwardly. Both phantom and in vivo imaging experiments were conducted to evaluate the performance of the proposed method. Results Compared with magnitude-weighted method and MCPC-C, the proposed method can alleviate the phase cancellation in coil combination, resulting in a less wrapped phase. Conclusions The proposed method provides an effective and efficient approach to combine multiple coil image in parallel MRI reconstruction, and has potential to benefit routine clinical practice in the future.
Collapse
Affiliation(s)
- Qian Zheng
- Zhengzhou University of Light Industry, Zhengzhou 450002, China
| | - Lin Xu
- Chengdu University of Information Technology, Chengdu 610225, China
| | - Liang Xiong
- Chengdu University of Information Technology, Chengdu 610225, China
| | - Xiao Cui
- Zhengzhou University of Light Industry, Zhengzhou 450002, China
| | - Jiaofen Nan
- Zhengzhou University of Light Industry, Zhengzhou 450002, China
| | - Taigang He
- Imperial College London, London SW7 2AZ, UK.,St George's, University of London, London SW17 0RE, UK
| |
Collapse
|
56
|
Huang J, Wang L, Chu C, Liu W, Zhu Y. Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint. MAGMA (NEW YORK, N.Y.) 2019; 32:407-422. [PMID: 30903326 DOI: 10.1007/s10334-019-00747-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Revised: 03/08/2019] [Accepted: 03/11/2019] [Indexed: 06/09/2023]
Abstract
OBJECTIVE Diffusion tensor magnetic resonance imaging (DT-MRI, or DTI) is a promising technique for invasively probing biological tissue structures. However, DTI is known to suffer from much longer acquisition time with respect to conventional MRI and the problem is worsened when dealing with in vivo acquisitions. Therefore, faster DTI for both ex vivo and in vivo scans is highly desired. MATERIALS AND METHODS This paper proposes a new compressed sensing (CS) reconstruction method that employs local low-rank (LLR) model and three-dimensional (3D) total variation (TV) constraint to reconstruct cardiac diffusion-weighted (DW) images from highly undersampled k-space data. The LLR model takes the set of DW images corresponding to different diffusion gradient directions as a 3D image volume and decomposes the latter into overlapping 3D blocks. Then, the 3D blocks are stacked as two-dimensional (2D) matrix. Finally, low-rank property is applied to each block matrix and the 3D TV constraint to the 3D image volume. The underlying constrained optimization problem is finally solved using the first-order fast method. The proposed method is evaluated on real ex vivo cardiac DTI data as a prerequisite to in vivo cardiac DTI applications. RESULTS The results on real human ex vivo cardiac DTI images demonstrate that the proposed method exhibits lower reconstruction errors for DTI indices, including fractional anisotropy (FA), mean diffusivities (MD), transverse angle (TA), and helix angle (HA), compared to existing CS-based DTI image reconstruction techniques. CONCLUSION The proposed method provides better reconstruction quality and more accurate DTI indices in comparison with the state-of-the-art CS-based DW image reconstruction methods.
Collapse
Affiliation(s)
- Jianping Huang
- College of Mechanical and Electrical Engineering, Northeast Forestry University, Heilongjiang, 150040, Harbin, China.
- Metislab, LIA CNRS, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China.
- CREATIS, CNRS UMR5220, Inserm U1206, INSA Lyon, University of Lyon, Lyon, France.
| | - Lihui Wang
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Chunyu Chu
- College of Engineering, Bohai University, Jinzhou, 121013, China
| | - Wanyu Liu
- Metislab, LIA CNRS, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China
| | - Yuemin Zhu
- Metislab, LIA CNRS, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China
- CREATIS, CNRS UMR5220, Inserm U1206, INSA Lyon, University of Lyon, Lyon, France
| |
Collapse
|
57
|
Hansen RB, Sánchez‐Heredia JD, Bøgh N, Hansen ESS, Laustsen C, Hanson LG, Ardenkjær‐Larsen JH. Coil profile estimation strategies for parallel imaging with hyperpolarized
13
C MRI. Magn Reson Med 2019; 82:2104-2117. [DOI: 10.1002/mrm.27892] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 06/12/2019] [Accepted: 06/13/2019] [Indexed: 01/16/2023]
Affiliation(s)
- Rie B. Hansen
- Department of Health Technology Technical University of Denmark Kongens Lyngby Denmark
| | | | - Nikolaj Bøgh
- MR Research Centre Aarhus University Aarhus Denmark
| | | | | | - Lars G. Hanson
- Department of Health Technology Technical University of Denmark Kongens Lyngby Denmark
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital Hvidovre Copenhagen Denmark
| | - Jan H. Ardenkjær‐Larsen
- Department of Health Technology Technical University of Denmark Kongens Lyngby Denmark
- GE Healthcare Brøndby Denmark
| |
Collapse
|
58
|
Arif O, Afzal H, Abbas H, Amjad MF, Wan J, Nawaz R. Accelerated Dynamic MRI Using Kernel-Based Low Rank Constraint. J Med Syst 2019; 43:271. [DOI: 10.1007/s10916-019-1399-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 06/25/2019] [Indexed: 11/24/2022]
|
59
|
Wang N, Zhang J, Cofer G, Qi Y, Anderson RJ, White LE, Allan Johnson G. Neurite orientation dispersion and density imaging of mouse brain microstructure. Brain Struct Funct 2019; 224:1797-1813. [PMID: 31006072 DOI: 10.1007/s00429-019-01877-x] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 04/11/2019] [Indexed: 12/14/2022]
Abstract
Advanced biophysical models like neurite orientation dispersion and density imaging (NODDI) have been developed to estimate the microstructural complexity of voxels enriched in dendrites and axons for both in vivo and ex vivo studies. NODDI metrics derived from high spatial and angular resolution diffusion MRI using the fixed mouse brain as a reference template have not yet been reported due in part to the extremely long scan time required. In this study, we modified the three-dimensional diffusion-weighted spin-echo pulse sequence for multi-shell and undersampling acquisition to reduce the scan time. This allowed us to acquire several exhaustive datasets that would otherwise not be attainable. NODDI metrics were derived from a complex 8-shell diffusion (1000-8000 s/mm2) dataset with 384 diffusion gradient-encoding directions at 50 µm isotropic resolution. These provided a foundation for exploration of tradeoffs among acquisition parameters. A three-shell acquisition strategy covering low, medium, and high b values with at least angular resolution of 64 is essential for ex vivo NODDI experiments. The good agreement between neurite density index (NDI) and the orientation dispersion index (ODI) with the subsequent histochemical analysis of myelin and neuronal density highlights that NODDI could provide new insight into the microstructure of the brain. Furthermore, we found that NDI is sensitive to microstructural variations in the corpus callosum using a well-established demyelination cuprizone model. The study lays the ground work for developing protocols for routine use of high-resolution NODDI method in characterizing brain microstructure in mouse models.
Collapse
Affiliation(s)
- Nian Wang
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA.
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA.
| | - Jieying Zhang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Gary Cofer
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA
| | - Yi Qi
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA
| | - Robert J Anderson
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA
| | - Leonard E White
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - G Allan Johnson
- Center for In Vivo Microscopy, Department of Radiology, Duke Medical Center, Duke University, 3302, Durham, NC, 27710, USA.
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
| |
Collapse
|
60
|
Zhang J, Chu Y, Ding W, Kang L, Xia L, Jaiswal S, Wang Z, Chen Z. HF-SENSE: an improved partially parallel imaging using a high-pass filter. BMC Med Imaging 2019; 19:27. [PMID: 30943909 PMCID: PMC6448231 DOI: 10.1186/s12880-019-0327-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 03/25/2019] [Indexed: 11/17/2022] Open
Abstract
Background One of the major limitations of MRI is its slow acquisition speed. To accelerate data acquisition, partially parallel imaging (PPI) methods have been widely used in clinical applications such as sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA). SENSE is a popular image-domain partially parallel imaging method, which suffers from residual aliasing artifacts when the reduction factor goes higher. Undersampling the k-space data and then reconstruct images with artificial sparsity is an efficient way to accelerate data acquisition. By exploiting artificial sparsity with a high-pass filter, an improved SENSE method is proposed in this work, termed high-pass filtered SENSE (HF-SENSE). Methods First, a high-pass filter was applied to the raw k-space data, the result of which was used as the inputs of sensitivity estimation and undersampling process. Second, the adaptive array coil combination method was adopted to calculate sensitivity maps on a block-by-block basis. Third, Tikhonov regularized SENSE was then used to reconstruct magnetic resonance images. Fourth, the reconstructed images were transformed into k-space data, which was filtered with the corresponding inverse filter. Results Both simulation and in vivo experiments demonstrate that HF-SENSE method significantly reduces noise level of the reconstructed images compared with SENSE. Furthermore, it is found that HF-SENSE can achieve lower normalized root-mean-square error value than SENSE. Conclusions The proposed method explores artificial sparsity with a high-pass filter. Experiments demonstrate that the proposed HF-SENSE method can improve the image quality of SENSE reconstruction. The high-pass filter parameters can be predefined. With this image reconstruction method, high acceleration factors can be achieved, which will improve the clinical applicability of SENSE. This retrospective study (HF-SENSE: an improved partially parallel imaging using a high-pass filter) was approved by Institute Review Board of 2nd Affiliated Hospital of Zhejiang University (ethical approval number 2018–314). Participant for all images have informed consent that he knew the risks and agreed to participate in the research.
Collapse
Affiliation(s)
- Jucheng Zhang
- Department of Clinical Engineering, 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Yonghua Chu
- Department of Clinical Engineering, 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenhong Ding
- Department of Radiology, 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Liyi Kang
- Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Ling Xia
- Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.,State Key Lab of CAD & CG, Zhejiang University, Hangzhou, Zhejiang, China
| | - Sanjay Jaiswal
- School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhikang Wang
- Department of Clinical Engineering, 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhifeng Chen
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.
| |
Collapse
|
61
|
Bödenler M, de Rochefort L, Ross PJ, Chanet N, Guillot G, Davies GR, Gösweiner C, Scharfetter H, Lurie DJ, Broche LM. Comparison of fast field-cycling magnetic resonance imaging methods and future perspectives. Mol Phys 2018. [DOI: 10.1080/00268976.2018.1557349] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Markus Bödenler
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Ludovic de Rochefort
- CNRS, Center for Magnetic Resonance in Biology and Medicine (CRMBM) UMR 7339, Aix Marseille Univ, Marseille, France
| | - P. James Ross
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - Nicolas Chanet
- Imagerie par Résonance Magnétique Médicale et Multi-Modalités, IR4M UMR 8081, Université Paris Saclay, Orsay, France
| | - Geneviève Guillot
- Imagerie par Résonance Magnétique Médicale et Multi-Modalités, IR4M UMR 8081, Université Paris Saclay, Orsay, France
| | - Gareth R. Davies
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - Christian Gösweiner
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Hermann Scharfetter
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - David J. Lurie
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - Lionel M. Broche
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| |
Collapse
|
62
|
Jones DK, Alexander DC, Bowtell R, Cercignani M, Dell'Acqua F, McHugh DJ, Miller KL, Palombo M, Parker GJM, Rudrapatna US, Tax CMW. Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI. Neuroimage 2018; 182:8-38. [PMID: 29793061 DOI: 10.1016/j.neuroimage.2018.05.047] [Citation(s) in RCA: 105] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Revised: 05/17/2018] [Accepted: 05/18/2018] [Indexed: 12/13/2022] Open
Abstract
The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.
Collapse
Affiliation(s)
- D K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; School of Psychology, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, 3065, Australia.
| | - D C Alexander
- Centre for Medical Image Computing (CMIC), Department of Computer Science, UCL (University College London), Gower Street, London, UK; Clinical Imaging Research Centre, National University of Singapore, Singapore
| | - R Bowtell
- Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - M Cercignani
- Department of Psychiatry, Brighton and Sussex Medical School, Brighton, UK
| | - F Dell'Acqua
- Natbrainlab, Department of Neuroimaging, King's College London, London, UK
| | - D J McHugh
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK; CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge and Manchester, UK
| | - K L Miller
- Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK
| | - M Palombo
- Centre for Medical Image Computing (CMIC), Department of Computer Science, UCL (University College London), Gower Street, London, UK
| | - G J M Parker
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK; CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge and Manchester, UK; Bioxydyn Ltd., Manchester, UK
| | - U S Rudrapatna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - C M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| |
Collapse
|
63
|
Microstructural imaging of human neocortex in vivo. Neuroimage 2018; 182:184-206. [DOI: 10.1016/j.neuroimage.2018.02.055] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 02/13/2018] [Accepted: 02/26/2018] [Indexed: 12/12/2022] Open
|
64
|
Liu Y, Lyu M, Barth M, Yi Z, Leong ATL, Chen F, Feng Y, Wu EX. PEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction. Magn Reson Med 2018; 81:1924-1934. [PMID: 30368895 DOI: 10.1002/mrm.27546] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 08/17/2018] [Accepted: 09/01/2018] [Indexed: 12/15/2022]
Abstract
PURPOSE To provide simultaneous multislice (SMS) EPI reconstruction with k-space implementation and robust Nyquist ghost correction. METHODS 2D phase error correction SENSE (PEC-SENSE) was recently developed for Nyquist ghost correction in SMS EPI reconstruction for which virtual coil simultaneous autocalibration and k-space estimation (VC-SAKE) was used to remove slice-dependent Nyquist ghosts and intershot 2D phase variations in multi-shot EPI reference scan. However, masking coil sensitivity maps to exclude background region in PEC-SENSE and manually selecting slice-wise target ranks in VC-SAKE are cumbersome procedures in practice. To avoid masking, the concept of PEC-SENSE is extended to k-space implementation and termed as PEC-GRAPPA. Furthermore, a singular value shrinkage scheme is incorporated in VC-SAKE to circumvent the empirical slice-wise target rank selection. PEC-GRAPPA was evaluated and compared to PEC-SENSE with/without masking and 1D linear phase correction GRAPPA. RESULTS PEC-GRAPPA robustly reconstructed SMS EPI images from 7T phantom and human brain data, effectively removing the phase error-induced artifacts. The resulting residual artifact level and temporal SNR were comparable to those by PEC-SENSE with careful tuning. PEC-GRAPPA outperformed PEC-SENSE without masking and 1D linear phase correction GRAPPA. CONCLUSION Our proposed PEC-GRAPPA approach effectively removes the artifacts caused by Nyquist ghosts in SMS EPI without cumbersome tuning. This approach provides a robust and practical implementation of SMS EPI reconstruction in k-space with slice-dependent 2D Nyquist ghost correction.
Collapse
Affiliation(s)
- Yilong Liu
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Mengye Lyu
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Markus Barth
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Zheyuan Yi
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, People's Republic of China
| | - Alex T L Leong
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, People's Republic of China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, People's Republic of China
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| |
Collapse
|
65
|
Hoge WS, Setsompop K, Polimeni JR. Dual-polarity slice-GRAPPA for concurrent ghost correction and slice separation in simultaneous multi-slice EPI. Magn Reson Med 2018; 80:1364-1375. [PMID: 29424460 PMCID: PMC6085171 DOI: 10.1002/mrm.27113] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 01/04/2018] [Accepted: 01/08/2018] [Indexed: 12/15/2022]
Abstract
PURPOSE A ghost correction strategy for Simultaneous Multi-Slice (SMS) EPI methods that provides improved ghosting artifact reduction compared to conventional methods is presented. Conventional Nyquist ghost correction methods for SMS-EPI rely on navigator data that contain phase errors from all slices in the simultaneously acquired slice-group. These navigator data may contain spatially nonlinear phase differences near regions of B0 inhomogeneity, which violates the linear model employed by most EPI ghost correction algorithms, resulting in poor reconstructions. METHODS Dual-Polarity GRAPPA (DPG) was previously shown to accurately model and correct both spatially nonlinear and 2D phase errors in conventional single-slice EPI data. Here, an extension we call Dual-Polarity slice-GRAPPA (DPsG) is adapted to the slice-GRAPPA method and applied to SMS-EPI data for slice separation and ghost correction concurrently-eliminating the need for a separate ghost correction step while also providing improved slice-specific EPI phase error correction. RESULTS Images from in vivo SMS-EPI data reconstructed using DPsG in place of conventional Nyquist ghost correction and slice-GRAPPA are presented. DPsG is shown to reduce ghosting artifacts and provide improved temporal SNR compared to the conventional reconstruction. CONCLUSION The proposed use of DPsG for SMS-EPI reconstruction can provide images with lower artifact levels, higher image fidelity, and improved time-series stability compared to conventional reconstruction methods.
Collapse
Affiliation(s)
- W. Scott Hoge
- Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| |
Collapse
|
66
|
Impulse response timing differences in BOLD and CBV weighted fMRI. Neuroimage 2018; 181:292-300. [PMID: 29981905 DOI: 10.1016/j.neuroimage.2018.07.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 07/03/2018] [Accepted: 07/04/2018] [Indexed: 11/23/2022] Open
Abstract
Recent advances in BOLD fMRI scan techniques have substantially improved spatial and temporal resolution, currently reaching to sub-millimeter and sub-second levels respectively. Unfortunately, there remain physiological barriers that prevent achieving this resolution in practice. BOLD contrast relies on the hemodynamic response to neuronal activity, whose associated cerebral blood oxygenation (CBO) changes may spread over several millimeters and last several seconds. Recent reports have suggested that significant improvements may be possible with cerebral blood volume (CBV)-weighted fMRI, which highlights the CBV changes rather than the BOLD changes associated with the hemodynamic response. Nevertheless, quantitative comparisons between CBV and BOLD are sparse, in particular regarding their temporal characteristics in human brain. To address this, we studied a cohort of subjects that received injection of ferumoxytol, an intravascular iron-oxide based contrast agent that introduces strong CBV contrast. An event-related visual stimulus paradigm was used to compare the impulse response (IR) for CBV and BOLD contrast, obtained with and without ferumoxytol, respectively. Experiments performed at 7 T (n = 5) at 1.2-1.5 mm spatial and 1 s temporal resolution showed that the onset time and time-to-peak of the CBV IR averaged 0.8 and 3.5 s respectively, both 0.6 s shorter than the BOLD IR. While significant, these improvements are relatively small and not expected to lead to practical advantages for the extraction of temporal information about neural activity. Nonlinearities in the observed IR were also compared and found to be similar between the CBV and BOLD, indicating that these are likely not caused by a 'ceiling' effect in the CBO response, but rather support a previously proposed model of vascular compliance, in which changes in vascular tone elicited by a preceding stimulus affect the IR.
Collapse
|
67
|
Hyun CM, Kim HP, Lee SM, Lee S, Seo JK. Deep learning for undersampled MRI reconstruction. Phys Med Biol 2018; 63:135007. [PMID: 29787383 DOI: 10.1088/1361-6560/aac71a] [Citation(s) in RCA: 193] [Impact Index Per Article: 32.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This paper presents a deep learning method for faster magnetic resonance imaging (MRI) by reducing k-space data with sub-Nyquist sampling strategies and provides a rationale for why the proposed approach works well. Uniform subsampling is used in the time-consuming phase-encoding direction to capture high-resolution image information, while permitting the image-folding problem dictated by the Poisson summation formula. To deal with the localization uncertainty due to image folding, a small number of low-frequency k-space data are added. Training the deep learning net involves input and output images that are pairs of the Fourier transforms of the subsampled and fully sampled k-space data. Our experiments show the remarkable performance of the proposed method; only 29[Formula: see text] of the k-space data can generate images of high quality as effectively as standard MRI reconstruction with the fully sampled data.
Collapse
Affiliation(s)
- Chang Min Hyun
- Department of Computational Science and Engineering, Yonsei University, Seoul, Republic of Korea
| | | | | | | | | |
Collapse
|
68
|
Yaghoobi N, Hasanzadeh RPR. De-noising of 3D multiple-coil MR images using modified LMMSE estimator. Magn Reson Imaging 2018; 52:102-117. [PMID: 29935256 DOI: 10.1016/j.mri.2018.06.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 05/13/2018] [Accepted: 06/18/2018] [Indexed: 10/28/2022]
Abstract
De-noising is a crucial topic in Magnetic Resonance Imaging (MRI) which focuses on less loss of Magnetic Resonance (MR) image information and details preservation during the noise suppression. Nowadays multiple-coil MRI system is preferred to single one due to its acceleration in the imaging process. Due to the fact that the model of noise in single-coil and multiple-coil MRI systems are different, the de-noising methods that mostly are adapted to single-coil MRI systems, do not work appropriately with multiple-coil one. The model of noise in single-coil MRI systems is Rician while in multiple-coil one (if no subsampling occurs in k-space or GRAPPA reconstruction process is being done in the coils), it obeys noncentral Chi (nc-χ). In this paper, a new filtering method based on the Linear Minimum Mean Square Error (LMMSE) estimator is proposed for multiple-coil MR Images ruined by nc-χ noise. In the presented method, to have an optimum similarity selection of voxels, the Bayesian Mean Square Error (BMSE) criterion is used and proved for nc-χ noise model and also a nonlocal voxel selection methodology is proposed for nc-χ distribution. The results illustrate robust and accurate performance compared to the related state-of-the-art methods, either on ideal nc-χ images or GRAPPA reconstructed ones.
Collapse
Affiliation(s)
- Nima Yaghoobi
- Department of Electrical Engineering, University of Guilan, Rasht, Iran
| | | |
Collapse
|
69
|
Advances in MR angiography with 7T MRI: From microvascular imaging to functional angiography. Neuroimage 2018; 168:269-278. [DOI: 10.1016/j.neuroimage.2017.01.019] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Revised: 01/03/2017] [Accepted: 01/09/2017] [Indexed: 01/15/2023] Open
|
70
|
Song Y, Seo JK, Chauhan M, Indahlastari A, Ashok Kumar N, Sadleir R. Accelerating acquisition strategies for low-frequency conductivity imaging using MREIT. Phys Med Biol 2018; 63:045011. [PMID: 29345626 DOI: 10.1088/1361-6560/aaa8d2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
We sought to improve efficiency of magnetic resonance electrical impedance tomography data acquisition so that fast conductivity changes or electric field variations could be monitored. Undersampling of k-space was used to decrease acquisition times in spin-echo-based sequences by a factor of two. Full MREIT data were reconstructed using continuity assumptions and preliminary scans gathered without current. We found that phase data were reconstructed faithfully from undersampled data. Conductivity reconstructions of phantom data were also possible. Therefore, undersampled k-space methods can potentially be used to accelerate MREIT acquisition. This method could be an advantage in imaging real-time conductivity changes with MREIT.
Collapse
Affiliation(s)
- Yizhuang Song
- School of Mathematics and Statistics, Institute of Data Science and Technology, Shandong Normal University, Jinan, Shandong, 250014, People's Republic of China
| | | | | | | | | | | |
Collapse
|
71
|
Mehranian A, Belzunce MA, Prieto C, Hammers A, Reader AJ. Synergistic PET and SENSE MR Image Reconstruction Using Joint Sparsity Regularization. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:20-34. [PMID: 28436851 DOI: 10.1109/tmi.2017.2691044] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
In this paper, we propose a generalized joint sparsity regularization prior and reconstruction framework for the synergistic reconstruction of positron emission tomography (PET) and under sampled sensitivity encoded magnetic resonance imaging data with the aim of improving image quality beyond that obtained through conventional independent reconstructions. The proposed prior improves upon the joint total variation (TV) using a non-convex potential function that assigns a relatively lower penalty for the PET and MR gradients, whose magnitudes are jointly large, thus permitting the preservation and formation of common boundaries irrespective of their relative orientation. The alternating direction method of multipliers (ADMM) optimization framework was exploited for the joint PET-MR image reconstruction. In this framework, the joint maximum a posteriori objective function was effectively optimized by alternating between well-established regularized PET and MR image reconstructions. Moreover, the dependency of the joint prior on the PET and MR signal intensities was addressed by a novel alternating scaling of the distribution of the gradient vectors. The proposed prior was compared with the separate TV and joint TV regularization methods using extensive simulation and real clinical data. In addition, the proposed joint prior was compared with the recently proposed linear parallel level sets (PLSs) method using a benchmark simulation data set. Our simulation and clinical data results demonstrated the improved quality of the synergistically reconstructed PET-MR images compared with the unregularized and conventional separately regularized methods. It was also found that the proposed prior can outperform both the joint TV and linear PLS regularization methods in assisting edge preservation and recovery of details, which are otherwise impaired by noise and aliasing artifacts. In conclusion, the proposed joint sparsity regularization within the presented a ADMM reconstruction framework is a promising technique, nonetheless our clinical results showed that the clinical applicability of joint reconstruction might be limited in current PET-MR scanners, mainly due to the lower resolution of PET images.
Collapse
|
72
|
Elahi S, Kaleem M, Omer H. Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 286:91-98. [PMID: 29223565 DOI: 10.1016/j.jmr.2017.11.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 10/19/2017] [Accepted: 11/17/2017] [Indexed: 06/07/2023]
Abstract
Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k-space. This paper introduces an improved iterative algorithm based on p-thresholding technique for CS-MRI image reconstruction. The use of p-thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p-thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p-thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.
Collapse
Affiliation(s)
- Sana Elahi
- Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan
| | - Muhammad Kaleem
- Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan.
| | - Hammad Omer
- Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan
| |
Collapse
|
73
|
Yao J, Xu Z, Huang X, Huang J. An efficient algorithm for dynamic MRI using low-rank and total variation regularizations. Med Image Anal 2017; 44:14-27. [PMID: 29175383 DOI: 10.1016/j.media.2017.11.003] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 10/25/2017] [Accepted: 11/06/2017] [Indexed: 11/27/2022]
Abstract
In this paper, we propose an efficient algorithm for dynamic magnetic resonance (MR) image reconstruction. With the total variation (TV) and the nuclear norm (NN) regularization, the TVNNR model can utilize both spatial and temporal redundancy in dynamic MR images. Such prior knowledge can help model dynamic MRI data significantly better than a low-rank or a sparse model alone. However, it is very challenging to efficiently minimize the energy function due to the non-smoothness and non-separability of both TV and NN terms. To address this issue, we propose an efficient algorithm by solving a primal-dual form of the original problem. We theoretically prove that the proposed algorithm achieves a convergence rate of O(1/N) for N iterations. In comparison with state-of-the-art methods, extensive experiments on single-coil and multi-coil dynamic MR data demonstrate the superior performance of the proposed method in terms of both reconstruction accuracy and time complexity.
Collapse
Affiliation(s)
- Jiawen Yao
- Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA; Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, 18015, USA; Tencent AI Lab, Shenzhen, 518057, China
| | - Zheng Xu
- Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA; Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, 18015, USA; Tencent AI Lab, Shenzhen, 518057, China
| | - Xiaolei Huang
- Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA; Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, 18015, USA; Tencent AI Lab, Shenzhen, 518057, China
| | - Junzhou Huang
- Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA; Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, 18015, USA; Tencent AI Lab, Shenzhen, 518057, China.
| |
Collapse
|
74
|
Advanced Imaging Techniques in the Knee: Benefits and Limitations of New Rapid Acquisition Strategies for Routine Knee MRI. AJR Am J Roentgenol 2017. [DOI: 10.2214/ajr.17.18228] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
|
75
|
Siddiqui MF, Reza AW, Shafique A, Omer H, Kanesan J. FPGA implementation of real-time SENSE reconstruction using pre-scan and Emaps sensitivities. Magn Reson Imaging 2017; 44:82-91. [PMID: 28855113 DOI: 10.1016/j.mri.2017.08.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2016] [Revised: 07/22/2017] [Accepted: 08/23/2017] [Indexed: 10/19/2022]
Abstract
Sensitivity Encoding (SENSE) is a widely used technique in Parallel Magnetic Resonance Imaging (MRI) to reduce scan time. Reconfigurable hardware based architecture for SENSE can potentially provide image reconstruction with much less computation time. Application specific hardware platform for SENSE may dramatically increase the power efficiency of the system and can decrease the execution time to obtain MR images. A new implementation of SENSE on Field Programmable Gate Array (FPGA) is presented in this study, which provides real-time SENSE reconstruction right on the receiver coil data acquisition system with no need to transfer the raw data to the MRI server, thereby minimizing the transmission noise and memory usage. The proposed SENSE architecture can reconstruct MR images using receiver coil sensitivity maps obtained using pre-scan and eigenvector (E-maps) methods. The results show that the proposed system consumes remarkably less computation time for SENSE reconstruction, i.e., 0.164ms @ 200MHz, while maintaining the quality of the reconstructed images with good mean SNR (29+ dB), less RMSE (<5×10-2) and comparable artefact power (<9×10-4) to conventional SENSE reconstruction. A comparison of the center line profiles of the reconstructed and reference images also indicates a good quality of the reconstructed images. Furthermore, the results indicate that the proposed architectural design can prove to be a significant tool for SENSE reconstruction in modern MRI scanners and its low power consumption feature can be remarkable for portable MRI scanners.
Collapse
Affiliation(s)
- Muhammad Faisal Siddiqui
- Faculty of Engineering, Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia; Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan.
| | - Ahmed Wasif Reza
- Department of Computer Science & Engineering, Faculty of Science & Engineering, East West University, Dhaka 1212, Bangladesh.
| | - Abubakr Shafique
- Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan.
| | - Hammad Omer
- Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan.
| | - Jeevan Kanesan
- Faculty of Engineering, Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia.
| |
Collapse
|
76
|
Chen J, Liu S, Huang M. Low-Rank and Sparse Decomposition Model for Accelerating Dynamic MRI Reconstruction. JOURNAL OF HEALTHCARE ENGINEERING 2017; 2017:9856058. [PMID: 29093806 PMCID: PMC5591906 DOI: 10.1155/2017/9856058] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 05/17/2017] [Indexed: 12/15/2022]
Abstract
The reconstruction of dynamic magnetic resonance imaging (dMRI) from partially sampled k-space data has to deal with a trade-off between the spatial resolution and temporal resolution. In this paper, a low-rank and sparse decomposition model is introduced to resolve this issue, which is formulated as an inverse problem regularized by robust principal component analysis (RPCA). The inverse problem can be solved by convex optimization method. We propose a scalable and fast algorithm based on the inexact augmented Lagrange multipliers (IALM) to carry out the convex optimization. The experimental results demonstrate that our proposed algorithm can achieve superior reconstruction quality and faster reconstruction speed in cardiac cine image compared to existing state-of-art reconstruction methods.
Collapse
Affiliation(s)
- Junbo Chen
- College of Physical Science and Technology, Central China Normal University, Wuhan 430079, Hubei, China
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, South-Central University for Nationalities, Wuhan 430074, Hubei, China
| | - Shouyin Liu
- College of Physical Science and Technology, Central China Normal University, Wuhan 430079, Hubei, China
| | - Min Huang
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, South-Central University for Nationalities, Wuhan 430074, Hubei, China
- Hubei Key Laboatory of Medical Information Analysis & Tumor Diagnosis and Treatment, Wuhan 430074, Hubei, China
| |
Collapse
|
77
|
Havsteen I, Ohlhues A, Madsen KH, Nybing JD, Christensen H, Christensen A. Are Movement Artifacts in Magnetic Resonance Imaging a Real Problem?-A Narrative Review. Front Neurol 2017; 8:232. [PMID: 28611728 PMCID: PMC5447676 DOI: 10.3389/fneur.2017.00232] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2016] [Accepted: 05/12/2017] [Indexed: 12/29/2022] Open
Abstract
Movement artifacts compromise image quality and may interfere with interpretation, especially in magnetic resonance imaging (MRI) applications with low signal-to-noise ratio such as functional MRI or diffusion tensor imaging, and when imaging small lesions. High image resolution has high sensitivity to motion artifacts and often prolongs scan time that again aggravates movement artifacts. During the scan fast imaging techniques and sequences, optimal receiver coils, careful patient positioning, and instruction may minimize movement artifacts. Physiological noise sources are motion from respiration, flow and pulse coupled to cardiac cycles, from the swallowing reflex and small spontaneous head movements. Par example, in resting-state functional MRI spontaneous neuronal activity adds 1–2% of signal change, even under optimal conditions signal contributions from physiological noise remain a considerable fraction hereof. Movement tracking during imaging may allow for prospective correction or postprocessing steps separating signal and noise.
Collapse
Affiliation(s)
- Inger Havsteen
- Department of Radiology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Anders Ohlhues
- Department of Clinical Engineering Diagnostic Imaging Section, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Kristoffer H Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Janus Damm Nybing
- Department of Radiology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Hanne Christensen
- Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Anders Christensen
- Department of Radiology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| |
Collapse
|
78
|
DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic. Top Magn Reson Imaging 2017; 25:245-254. [PMID: 27748710 PMCID: PMC5081190 DOI: 10.1097/rmr.0000000000000103] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice.
Collapse
|
79
|
Mezer A, Rokem A, Berman S, Hastie T, Wandell BA. Evaluating quantitative proton-density-mapping methods. Hum Brain Mapp 2016; 37:3623-35. [PMID: 27273015 DOI: 10.1002/hbm.23264] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Revised: 04/30/2016] [Accepted: 05/10/2016] [Indexed: 11/11/2022] Open
Abstract
Quantitative magnetic resonance imaging (qMRI) aims to quantify tissue parameters by eliminating instrumental bias. We describe qMRI theory, simulations, and software designed to estimate proton density (PD), the apparent local concentration of water protons in the living human brain. First, we show that, in the absence of noise, multichannel coil data contain enough information to separate PD and coil sensitivity, a limiting instrumental bias. Second, we show that, in the presence of noise, regularization by a constraint on the relationship between T1 and PD produces accurate coil sensitivity and PD maps. The ability to measure PD quantitatively has applications in the analysis of in-vivo human brain tissue and enables multisite comparisons between individuals and across instruments. Hum Brain Mapp 37:3623-3635, 2016. © 2016 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Aviv Mezer
- The Hebrew University of Jerusalem, Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
| | - Ariel Rokem
- The University of Washington, eScience Institute, Seattle, WA, USA
| | - Shai Berman
- The Hebrew University of Jerusalem, Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
| | - Trevor Hastie
- Stanford University, Department of Psychology, Stanford, CA, USA
| | - Brian A Wandell
- Stanford University, Department of Psychology, Stanford, CA, USA.,Stanford University, Center for Cognitive and Neurobiological Imaging, Stanford, CA, USA
| |
Collapse
|
80
|
Agostini A, Kircher MF, Do R, Borgheresi A, Monti S, Giovagnoni A, Mannelli L. Magnetic Resonance Imaging of the Liver (Including Biliary Contrast Agents) Part 1: Technical Considerations and Contrast Materials. Semin Roentgenol 2016; 51:308-316. [PMID: 27743567 DOI: 10.1053/j.ro.2016.05.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- A Agostini
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY; Department of Radiology, School of Radiology, Universita' Politecnica delle Marche Ancona, Italy
| | - M F Kircher
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - R Do
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - A Borgheresi
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY; Department of Radiology, School of Radiology, Universita' degli Studi di Firenze Firenze, Italy
| | | | - A Giovagnoni
- Department of Radiology, School of Radiology, Universita' Politecnica delle Marche Ancona, Italy
| | - L Mannelli
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY.
| |
Collapse
|
81
|
Herrmann KH, Krämer M, Reichenbach JR. Time Efficient 3D Radial UTE Sampling with Fully Automatic Delay Compensation on a Clinical 3T MR Scanner. PLoS One 2016; 11:e0150371. [PMID: 26975051 PMCID: PMC4790903 DOI: 10.1371/journal.pone.0150371] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2015] [Accepted: 02/12/2016] [Indexed: 11/28/2022] Open
Abstract
This work’s aim was to minimize the acquisition time of a radial 3D ultra-short echo-time (UTE) sequence and to provide fully automated, gradient delay compensated, and therefore artifact free, reconstruction. The radial 3D UTE sequence (echo time 60 μs) was implemented as single echo acquisition with center-out readouts and improved time efficient spoiling on a clinical 3T scanner without hardware modifications. To assess the sequence parameter dependent gradient delays each acquisition contained a quick calibration scan and utilized the phase of the readouts to detect the actual k-space center. This calibration scan does not require any user interaction. To evaluate the robustness of this automatic delay estimation phantom experiments were performed and 19 in vivo imaging data of the head, tibial cortical bone, feet and lung were acquired from 6 volunteers. As clinical application of this fast 3D UTE acquisition single breath-hold lung imaging is demonstrated. The proposed sequence allowed very short repetition times (TR~1ms), thus reducing total acquisition time. The proposed, fully automated k-phase based gradient delay calibration resulted in accurate delay estimations (difference to manually determined optimal delay −0.13 ± 0.45 μs) and allowed unsupervised reconstruction of high quality images for both phantom and in vivo data. The employed fast spoiling scheme efficiently suppressed artifacts caused by incorrectly refocused echoes. The sequence proved to be quite insensitive to motion, flow and susceptibility artifacts and provides oversampling protection against aliasing foldovers in all directions. Due to the short TR, acquisition times are attractive for a wide range of clinical applications. For short T2* mapping this sequence provides free choice of the second TE, usually within less scan time as a comparable dual echo UTE sequence.
Collapse
Affiliation(s)
- Karl-Heinz Herrmann
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Martin Krämer
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| |
Collapse
|
82
|
Agarwal S, Grajo JR, Fuentes-Orrego JM, Abtahi SM, Harisinghani MG, Saini S, Hahn PF. Distinguishing hemangiomas from metastases on liver MRI performed with gadoxetate disodium: Value of the extended washout sign. Eur J Radiol 2016; 85:635-40. [DOI: 10.1016/j.ejrad.2015.12.028] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Revised: 12/07/2015] [Accepted: 12/29/2015] [Indexed: 12/11/2022]
|
83
|
Zong F, d’Eurydice MN, Galvosas P. Fast reconstruction of highly undersampled MR images using one and two dimensional principal component analysis. Magn Reson Imaging 2016; 34:227-38. [DOI: 10.1016/j.mri.2015.10.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2015] [Revised: 09/19/2015] [Accepted: 10/18/2015] [Indexed: 10/22/2022]
|
84
|
Rodgers CT, Robson MD. Coil combination for receive array spectroscopy: Are data-driven methods superior to methods using computed field maps? Magn Reson Med 2016; 75:473-87. [PMID: 25820303 PMCID: PMC4744755 DOI: 10.1002/mrm.25618] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Revised: 12/01/2014] [Accepted: 12/22/2014] [Indexed: 11/12/2022]
Abstract
PURPOSE Combining spectra from receive arrays, particularly X-nuclear spectra with low signal-to-noise ratios (SNRs), is challenging. We test whether data-driven combination methods are better than using computed coil sensitivities. THEORY Several combination algorithms are recast into the notation of Roemer's classic formula, showing that they differ primarily in their estimation of coil receive sensitivities. This viewpoint reveals two extensions of the whitened singular-value decomposition (WSVD) algorithm, using temporal or temporal + spatial apodization to improve the coil sensitivities, and thus the combined spectral SNR. METHODS Radiofrequency fields from an array were simulated and used to make synthetic spectra. These were combined with 10 algorithms. The combined spectra were then assessed in terms of their SNR. Validation used phantoms and cardiac (31) P spectra from five subjects at 3T. RESULTS Combined spectral SNRs from simulations, phantoms, and humans showed the same trends. In phantoms, the combined SNR using computed coil sensitivities was lower than with WSVD combination whenever the WSVD SNR was >14 (or >11 with temporal apodization, or >9 with temporal + spatial apodization). These new apodized WSVD methods gave higher SNRs than other data-driven methods. CONCLUSION In the human torso, at frequencies ≥49 MHz, data-driven combination is preferable to using computed coil sensitivities. Magn Reson, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Magn Reson Med 75:473-487, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Collapse
Affiliation(s)
- Christopher T. Rodgers
- Oxford Centre for Clinical Magnetic Resonance ResearchUniversity of Oxford, John Radcliffe HospitalOxfordUnited Kingdom
| | - Matthew D. Robson
- Oxford Centre for Clinical Magnetic Resonance ResearchUniversity of Oxford, John Radcliffe HospitalOxfordUnited Kingdom
| |
Collapse
|
85
|
Kayvanrad M, Lin A, Joshi R, Chiu J, Peters T. Diagnostic quality assessment of compressed sensing accelerated magnetic resonance neuroimaging. J Magn Reson Imaging 2016; 44:433-44. [PMID: 26777856 DOI: 10.1002/jmri.25149] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2015] [Accepted: 12/26/2015] [Indexed: 11/05/2022] Open
Abstract
PURPOSE To determine the efficacy of compressed sensing (CS) reconstructions for specific clinical magnetic resonance neuroimaging applications beyond more conventional acceleration techniques such as parallel imaging (PI) and low-resolution acquisitions. MATERIALS AND METHODS Raw k-space data were acquired from five healthy volunteers on a 3T scanner using a 32-channel head coil using T2 -FLAIR, FIESTA-C, time of flight (TOF), and spoiled gradient echo (SPGR) sequences. In a series of blinded studies, three radiologists independently evaluated CS, PI (GRAPPA), and low-resolution images at up to 5× accelerations. Synthetic T2 -FLAIR images with artificial lesions were used to assess diagnostic accuracy for CS reconstructions. RESULTS CS reconstructions were of diagnostically acceptable quality at up to 4× acceleration for T2 -FLAIR and FIESTA-C (average qualitative scores 3.7 and 4.3, respectively, on a 5-point scale at 4× acceleration), and at up to 3× acceleration for TOF and SPGR (average scores 4.0 and 3.7, respectively, at 3× acceleration). The qualitative scores for CS reconstructions were significantly better than low-resolution images for T2 -FLAIR, FIESTA-C, and TOF and significantly better than GRAPPA for TOF and SPGR (Wilcoxon signed rank test, P < 0.05) with no significant difference found otherwise. Diagnostic accuracy was acceptable for both CS and low-resolution images at up to 3× acceleration (area under the ROC curve 0.97 and 0.96, respectively.) CONCLUSION Mild to moderate accelerations are possible for those sequences by a combined CS and PI reconstruction. Nevertheless, for certain sequences/applications one might mildly reduce the acquisition time by appropriately reducing the imaging resolution rather than the more complicated CS reconstruction. J. Magn. Reson. Imaging 2016;44:433-444.
Collapse
Affiliation(s)
- Mohammad Kayvanrad
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, ON, Canada.,Biomedical Engineering Program, Western University, London, ON, Canada
| | - Amy Lin
- Department of Medical Imaging, Western University, London, ON, Canada
| | - Rohit Joshi
- Department of Medical Imaging, Western University, London, ON, Canada.,Juravinski Hospital and Cancer Centre, McMaster University, Hamilton Health Sciences, Hamilton, ON, Canada
| | - Jack Chiu
- Department of Medical Imaging, Western University, London, ON, Canada
| | - Terry Peters
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, ON, Canada.,Biomedical Engineering Program, Western University, London, ON, Canada.,Department of Medical Imaging, Western University, London, ON, Canada
| |
Collapse
|
86
|
Andersson JLR, Sotiropoulos SN. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 2016; 125:1063-1078. [PMID: 26481672 PMCID: PMC4692656 DOI: 10.1016/j.neuroimage.2015.10.019] [Citation(s) in RCA: 2113] [Impact Index Per Article: 264.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Revised: 09/23/2015] [Accepted: 10/09/2015] [Indexed: 01/02/2023] Open
Abstract
In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. The method is based on registering the individual volumes to a model free prediction of what each volume should look like, thereby enabling its use on high b-value data where the contrast is vastly different in different volumes. In addition we show that the linear EC-model commonly used is insufficient for the data used in the present paper (high spatial and angular resolution data acquired with Stejskal-Tanner gradients on a 3T Siemens Verio, a 3T Siemens Connectome Skyra or a 7T Siemens Magnetome scanner) and that a higher order model performs significantly better. The method is already in extensive practical use and is used by four major projects (the WU-UMinn HCP, the MGH HCP, the UK Biobank and the Whitehall studies) to correct for distortions and subject movement.
Collapse
|
87
|
Bashar SK, Lee SY, Hasan MK. Empirical mode decomposition based GRAPPA reconstruction algorithm for parallel MRI. Biomed Phys Eng Express 2015. [DOI: 10.1088/2057-1976/1/4/045006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
88
|
Fang Z, Van Le N, Choy M, Lee JH. High spatial resolution compressed sensing (HSPARSE) functional MRI. Magn Reson Med 2015; 76:440-55. [PMID: 26511101 DOI: 10.1002/mrm.25854] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 06/05/2015] [Accepted: 07/02/2015] [Indexed: 12/27/2022]
Abstract
PURPOSE To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. METHODS A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. RESULTS The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. CONCLUSION The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Collapse
Affiliation(s)
- Zhongnan Fang
- Department of Electrical Engineering, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, California, USA
| | - Nguyen Van Le
- Department of Electrical Engineering, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, California, USA
| | - ManKin Choy
- Department of Neurology & Neurological Sciences, Stanford University, Stanford, California, USA
| | - Jin Hyung Lee
- Department of Electrical Engineering, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, California, USA.,Department of Neurology & Neurological Sciences, Stanford University, Stanford, California, USA.,Department of Bioengineering, Stanford University, Stanford, California, USA.,Department of Neurosurgery, Stanford University, Stanford, California, USA.,Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, California, USA.,Neuroscience, and Biomedical Engineering Interdepartmental Program, University of California, Los Angeles, California, USA
| |
Collapse
|
89
|
Nunes RG, Malik SJ, Hajnal JV. Single shot fast spin echo diffusion imaging with correction for non-linear phase errors using tailored RF pulses. Magn Reson Med 2015; 71:691-701. [PMID: 23463486 DOI: 10.1002/mrm.24711] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
PURPOSE The use of tailored RF excitation pulses for prospective correction of non-linear motion-induced phase patterns is shown to enable diffusion-weighted (DW) fast spin echo (FSE) imaging in vivo. Echo-planar imaging (EPI) remains the most used sequence for DW imaging. Despite being highly sensitive to field inhomogeneities, EPI is robust to motion-induced phase shifts. FSE sequences are much less sensitive to field inhomogeneities, but require precise control of the transverse magnetization phase, which is hard to achieve with DW. Real time measurements and correction of phase ramps due to rigid-body motion had been proposed, but performance remained unsatisfactory because of non-linear phase patterns related to pulsatile motion. METHODS Reproducible non-linear phase components are calibrated using 2D-EPI navigators and tailored RF excitation pulses designed. Real time correction of rigid-body motion was not yet implemented. RESULTS Phase correction was confirmed with full signal DW-FSE images obtained on co-operative subjects. Full diffusion tensor acquisitions were obtained and color-coded maps displaying principal fiber directionality calculated. Results were consistent with corresponding EPI acquisitions except for absence of spatial distortions. CONCLUSION Combining the proposed method with real time compensation of rigid-body motion has the potential to allow high quality, distortion free diffusion imaging throughout the brain.
Collapse
Affiliation(s)
- Rita G Nunes
- Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, Lisbon, Portugal; Robert Steiner MRI Unit, Department of Imaging Sciences, Hammersmith Hospital Campus, Imperial College London, UK; Division of Imaging Sciences and Biomedical Engineering, Center for the Developing Brain, King's College London, UK
| | | | | |
Collapse
|
90
|
Shin PJ, Larson PE, Uecker M, Reed GD, Kerr AB, Tropp J, Ohliger MA, Nelson SJ, Pauly JM, Lustig M, Vigneron DB. Chemical shift separation with controlled aliasing for hyperpolarized (13) C metabolic imaging. Magn Reson Med 2015; 74:978-89. [PMID: 25298086 PMCID: PMC4390401 DOI: 10.1002/mrm.25473] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 08/15/2014] [Accepted: 09/05/2014] [Indexed: 12/21/2022]
Abstract
PURPOSE A chemical shift separation technique for hyperpolarized (13) C metabolic imaging with high spatial and temporal resolution was developed. Specifically, a fast three-dimensional pulse sequence and a reconstruction method were implemented to acquire signals from multiple (13) C species simultaneously with subsequent separation into individual images. THEORY AND METHODS A stack of flyback echo-planar imaging readouts and a set of multiband excitation radiofrequency pulses were designed to spatially modulate aliasing patterns of the acquired metabolite images, which translated the chemical shift separation problem into parallel imaging reconstruction problem. An eight-channel coil array was used for data acquisition and a parallel imaging method based on nonlinear inversion was developed to separate the aliased images. RESULTS Simultaneous acquisitions of pyruvate and lactate in a phantom study and in vivo rat experiments were performed. The results demonstrated successful separation of the metabolite distributions into individual images having high spatial resolution. CONCLUSION This method demonstrated the ability to provide accelerated metabolite imaging in hyperpolarized (13) C MR using multichannel coils, tailored readout, and specialized RF pulses.
Collapse
Affiliation(s)
- Peter J. Shin
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
- The UC Berkeley - UCSF Graduate Program in Bioengineering, California, USA
| | - Peder E.Z. Larson
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
- The UC Berkeley - UCSF Graduate Program in Bioengineering, California, USA
| | - Martin Uecker
- Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, California, USA
| | - Galen D. Reed
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
- The UC Berkeley - UCSF Graduate Program in Bioengineering, California, USA
| | - Adam B. Kerr
- Magnetic Resonance Systems Research Laboratory, Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - James Tropp
- General Electric Healthcare, Fremont, California, USA
| | - Michael A. Ohliger
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
| | - Sarah J. Nelson
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
- The UC Berkeley - UCSF Graduate Program in Bioengineering, California, USA
| | - John M. Pauly
- Magnetic Resonance Systems Research Laboratory, Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Michael Lustig
- The UC Berkeley - UCSF Graduate Program in Bioengineering, California, USA
- Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, California, USA
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
- The UC Berkeley - UCSF Graduate Program in Bioengineering, California, USA
| |
Collapse
|
91
|
Kimura T, Shigeta T. Magnitude-based Asymmetric Fourier Imaging (MagAFI). Magn Reson Med Sci 2015; 15:94-104. [PMID: 26346401 DOI: 10.2463/mrms.2014-0147] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
PURPOSE We propose and assess 2 novel asymmetric Fourier imaging (AFI) techniques, magnitude-based AFI (MagAFI) and MagAFI combined with projection on to convex sets (POCS) (MagAFI+POCS). MagAFI does not require phase information because it uses only the magnitude image with zero-filling. MagAFI+POCS requires phase information but further reduces image errors. MATERIALS AND METHODS We initially compared phase maps obtained using asymmetrically sampled data for the whole of the k-space and symmetrically sampled data for the low frequency part of the k-space. We used one-dimensional simulation data and 3-dimensional gradient echo data for 2 different echo times (TEs) of the brains of volunteers and assessed the differences between the image reconstructed from the full k-space data and AFI images reconstructed from truncated k-space data. We generated AFI images in this study using the zero-filling, Margosian (homodyne), Margosian+POCS (standard POCS), MagAFI, and MagAFI+POCS techniques. RESULTS We confirmed the assumption of smaller phase errors for the full k-space data than for the symmetric low frequency k-space data. Our proposed MagAFI technique provides images with smaller phase-induced errors than those obtained using conventional methods, including standard POCS methods, which have been regarded as the best methods. MagAFI+POCS improves image quality as well as robustness. CONCLUSION Our proposed MagAFI technique achieves a practical balance of image quality and simplicity to perform better than conventional methods using only the 0-filled magnitude image. Combined with POCS, this technique can produce images of even better quality.
Collapse
Affiliation(s)
- Tokunori Kimura
- Clinical Application Research and Development Department, Center for Medical Research and Development, Toshiba Medical Systems Corporation
| | | |
Collapse
|
92
|
Campbell-Washburn AE, Faranesh AZ, Lederman RJ, Hansen MS. Magnetic Resonance Sequences and Rapid Acquisition for MR-Guided Interventions. Magn Reson Imaging Clin N Am 2015; 23:669-79. [PMID: 26499283 DOI: 10.1016/j.mric.2015.05.006] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Interventional MR uses rapid imaging to guide diagnostic and therapeutic procedures. One of the attractions of MR-guidance is the abundance of inherent contrast mechanisms available. Dynamic procedural guidance with real-time imaging has pushed the limits of MR technology, demanding rapid acquisition and reconstruction paired with interactive control and device visualization. This article reviews the technical aspects of real-time MR sequences that enable MR-guided interventions.
Collapse
Affiliation(s)
- Adrienne E Campbell-Washburn
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room B1D416, Bethesda, MD 20892, USA.
| | - Anthony Z Faranesh
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 2C713, Bethesda, MD 20892, USA
| | - Robert J Lederman
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 2C713, Bethesda, MD 20892, USA
| | - Michael S Hansen
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room B1D416, Bethesda, MD 20892, USA
| |
Collapse
|
93
|
Fair MJ, Gatehouse PD, DiBella EVR, Firmin DN. A review of 3D first-pass, whole-heart, myocardial perfusion cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2015; 17:68. [PMID: 26231784 PMCID: PMC4522116 DOI: 10.1186/s12968-015-0162-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 06/23/2015] [Indexed: 01/19/2023] Open
Abstract
A comprehensive review is undertaken of the methods available for 3D whole-heart first-pass perfusion (FPP) and their application to date, with particular focus on possible acceleration techniques. Following a summary of the parameters typically desired of 3D FPP methods, the review explains the mechanisms of key acceleration techniques and their potential use in FPP for attaining 3D acquisitions. The mechanisms include rapid sequences, non-Cartesian k-space trajectories, reduced k-space acquisitions, parallel imaging reconstructions and compressed sensing. An attempt is made to explain, rather than simply state, the varying methods with the hope that it will give an appreciation of the different components making up a 3D FPP protocol. Basic estimates demonstrating the required total acceleration factors in typical 3D FPP cases are included, providing context for the extent that each acceleration method can contribute to the required imaging speed, as well as potential limitations in present 3D FPP literature. Although many 3D FPP methods are too early in development for the type of clinical trials required to show any clear benefit over current 2D FPP methods, the review includes the small but growing quantity of clinical research work already using 3D FPP, alongside the more technical work. Broader challenges concerning FPP such as quantitative analysis are not covered, but challenges with particular impact on 3D FPP methods, particularly with regards to motion effects, are discussed along with anticipated future work in the field.
Collapse
Affiliation(s)
- Merlin J Fair
- National Heart & Lung Institute, Imperial College London, London, UK.
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP, UK.
| | - Peter D Gatehouse
- National Heart & Lung Institute, Imperial College London, London, UK.
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP, UK.
| | - Edward V R DiBella
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT, USA.
| | - David N Firmin
- National Heart & Lung Institute, Imperial College London, London, UK.
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP, UK.
| |
Collapse
|
94
|
Yokoo T, Yuan Q, Sénégas J, Wiethoff AJ, Pedrosa I. Quantitative R2* MRI of the liver with rician noise models for evaluation of hepatic iron overload: Simulation, phantom, and early clinical experience. J Magn Reson Imaging 2015; 42:1544-59. [PMID: 25996989 DOI: 10.1002/jmri.24948] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2014] [Accepted: 04/28/2015] [Indexed: 12/11/2022] Open
Abstract
PURPOSE To compare Rician and non-Rician noise models for quantitative R2 * magnetic resonance imaging (MRI), in a simulation, phantom, and human study. MATERIALS AND METHODS Synthetic 12-echo spoiled GRE (SGRE) datasets were generated with various R2 * rates (0-2000 sec(-1) ) at a signal-to-noise ratio (SNR) of 50, 20, 10, and 5. Phantoms of different MnCl2 concentrations (0-25 mM) were constructed and imaged using a 12-echo 3D SGRE sequence at 1.5T. Increasing levels of synthetic noise was added to the original data to simulate sequentially lower SNR conditions. Sixteen patients with suspected or known iron overload were imaged using 12-echo 3D SGRE at 1.5T. Various R2 * quantification methods, based on Rician and non-Rician noise models, were compared in the simulation, phantom, and human datasets. RESULTS Non-Rician R2 * estimates were variably inaccurate in the high R2 * range (>500 sec(-1) ), with SNR-dependent linear goodness-of-fit statistic (R(2) ) of 0.373-0.999. Rician R2 * estimates were accurate even in the high R2 * range, with high R(2) of 0.940-0.999 regardless of SNR. Non-Rician R2 * estimates were variably nonlinear at high MnCl2 concentrations, with SNR-dependent R(2) of 0.345-0.994. Rician R2 * estimates were linear even at high MnCl2 concentrations, with high R(2) of 0.923-0.994 regardless of SNR. Between-method agreement of the R2 * estimates was excellent in patients with low ferritin but poor in patients with high ferritin. Rician R2 * estimates had excellent correlation with ferritin (r = 0.966 P < 0.001). CONCLUSION Rician R2 * estimates were most consistent in the high R2 * conditions and under varying SNR, and may be more reliable when high iron load is suspected.
Collapse
Affiliation(s)
- Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Qing Yuan
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | - Andrea J Wiethoff
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Briarcliff Manor, New York, USA
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| |
Collapse
|
95
|
Zaitsev M, Maclaren J, Herbst M. Motion artifacts in MRI: A complex problem with many partial solutions. J Magn Reson Imaging 2015; 42:887-901. [PMID: 25630632 DOI: 10.1002/jmri.24850] [Citation(s) in RCA: 356] [Impact Index Per Article: 39.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Accepted: 12/22/2014] [Indexed: 01/29/2023] Open
Abstract
Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations.
Collapse
Affiliation(s)
- Maxim Zaitsev
- Department of Radiology, University Medical Centre Freiburg, Freiburg, Germany
| | - Julian Maclaren
- Department of Radiology, University Medical Centre Freiburg, Freiburg, Germany.,Department of Radiology, Stanford University, Stanford, California, USA
| | - Michael Herbst
- Department of Radiology, University Medical Centre Freiburg, Freiburg, Germany.,University of Hawaii, Department of Medicine, John A. Burns School of Medicine, Honolulu, Hawaii, USA
| |
Collapse
|
96
|
Kayvanrad MH, McLeod AJ, Baxter JS, McKenzie CA, Peters TM. Stationary wavelet transform for under-sampled MRI reconstruction. Magn Reson Imaging 2014; 32:1353-64. [PMID: 25131624 DOI: 10.1016/j.mri.2014.08.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2014] [Revised: 06/10/2014] [Accepted: 08/08/2014] [Indexed: 10/24/2022]
|
97
|
Aja-Fernández S, Pieciak T, Vegas-Sánchez-Ferrero G. Spatially variant noise estimation in MRI: a homomorphic approach. Med Image Anal 2014; 20:184-97. [PMID: 25499191 DOI: 10.1016/j.media.2014.11.005] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 11/11/2014] [Accepted: 11/15/2014] [Indexed: 11/25/2022]
Abstract
The reliable estimation of noise characteristics in MRI is a task of great importance due to the influence of noise features in extensively used post-processing algorithms. Many methods have been proposed in the literature to retrieve noise features from the magnitude signal. However, most of them assume a stationary noise model, i.e., the features of noise do not vary with the position inside the image. This assumption does not hold when modern scanning techniques are considered, e.g., in the case of parallel reconstruction and intensity correction. Therefore, new noise estimators must be found to cope with non-stationary noise. Some methods have been recently proposed in the literature. However, they require multiple acquisitions or extra information which is usually not available (biophysical models, sensitivity of coils). In this work we overcome this drawback by proposing a new method that can accurately estimate the non-stationary parameters of noise from just a single magnitude image. In the derivation, we considered the noise to follow a non-stationary Rician distribution, since it is the most common model in real acquisitions (e.g., SENSE reconstruction), though it can be easily generalized to other models. The proposed approach makes use of a homomorphic separation of the spatially variant noise in two terms: a stationary noise term and one low frequency signal that correspond to the x-dependent variance of noise. The non-stationary variance of noise is then estimated by a low pass filtering with a Rician bias correction. Results in real and synthetic experiments evidence the better performance and the lowest error variance of the proposed methodology when compared to the state-of-the-art methods.
Collapse
Affiliation(s)
| | - Tomasz Pieciak
- AGH University of Science and Technology, Krakow, Poland.
| | | |
Collapse
|
98
|
Herédia V, Dale B, Op de Campos R, Ramalho M, Burke L, Sams C, de Toni M, Semelka R. Comparación de una secuencia en 3D con eco de gradiente potenciada en T1 con 3 factores de reducción de imagen en paralelo diferentes, en apnea y respiración libre, utilizando una bobina de 32 canales a 1,5T. Estudio preliminar. RADIOLOGIA 2014; 56:533-40. [DOI: 10.1016/j.rx.2012.06.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2011] [Revised: 04/11/2012] [Accepted: 06/20/2012] [Indexed: 10/27/2022]
|
99
|
Herédia V, Dale B, Op de Campos R, Ramalho M, Burke L, Sams C, de Toni M, Semelka R. A comparison of a T1 weighted 3D gradient-echo sequence with three different parallel imaging reduction factors, breath hold and free breathing, using a 32 channel coil at 1.5T. A preliminary study. RADIOLOGIA 2014. [DOI: 10.1016/j.rxeng.2012.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
|
100
|
Cengic I, Tureli D, Aydin H, Bugdayci O, Imeryuz N, Tuney D. Magnetic resonance enterography in refractory iron deficiency anemia: A pictorial overview. World J Gastroenterol 2014; 20:14004-14009. [PMID: 25320540 PMCID: PMC4194586 DOI: 10.3748/wjg.v20.i38.14004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2014] [Revised: 05/12/2014] [Accepted: 06/17/2014] [Indexed: 02/06/2023] Open
Abstract
AIM: To highlight magnetic resonance enterography (MRE) for diagnosis of patients with refractory iron deficiency anemia and normal endoscopy results.
METHODS: Fifty-three patients diagnosed with iron deficiency anemia refractory to treatment and normal gastroscopy and colonoscopy results were admitted to this prospective study between June 2013 and December 2013. All patients underwent a standardized MRE examination with a 1.5 Tesla magnetic resonance imaging system using two six-channel phased-array abdominal coils. Adequate bowel distention and fast imaging sequences were utilized to achieve diagnostic accuracy. All segments of the small bowel, duodenum, jejunum, and ileum were examined in detail. All cases were examined independently by two radiologists with > 5 years of experience in abdominal magnetic resonance imaging. A consensus reading was performed for each patient following image examination. Both radiologists were blinded to patient history, laboratory findings, and endoscopy results.
RESULTS: Twenty (37.7%) male and 33 (62.3%) female patients were included in the study. The mean age of the patients was 52.2 ± 13.6 years (range: 19-81 years, median 51.0). The age difference between the male and female patient groups was not statistically significant (54.8 ± 16.3 years vs 50.7 ± 11.7 years). MRE results were normal for 49 patients (92.5%). Four patients had abnormal MRE results. One patient with antral thickening was diagnosed with antral gastritis in the second-look gastroscopy. One patient had focal wall thickening in the 3rd and 4th portions of the duodenum. The affected areas were biopsied in a subsequent duodenoscopy, and adenocarcinoma was diagnosed. One patient had a fistula and focal contrast enhancement in the distal ileal segments, consistent with Crohn’s disease. One patient had focal wall thickening with luminal narrowing in the mid-jejunum that was later biopsied during a double-balloon enteroscopy, and lymphoma was diagnosed.
CONCLUSION: MRE is a non-invasive and effective alternative for evaluating possible malignancies of the small intestines and can serve as a guide for a second-look endoscopy.
Collapse
|