1
|
Lang M, Cartmell S, Tabari A, Briggs D, Pianykh O, Kirsch J, Cauley S, Lo WC, Risacher S, Filho AG, Succi MD, Rapalino O, Schaefer P, Conklin J, Huang SY. Evaluation of the Aggregated Time Savings in Adopting Fast Brain MRI Techniques for Outpatient Brain MRI. Acad Radiol 2023; 30:341-348. [PMID: 34635436 PMCID: PMC8989721 DOI: 10.1016/j.acra.2021.07.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 06/29/2021] [Accepted: 07/02/2021] [Indexed: 01/11/2023]
Abstract
INTRODUCTION Clinical validation studies have demonstrated the ability of accelerated MRI sequences to decrease acquisition time and motion artifact while preserving image quality. The operational benefits, however, have been less explored. Here, we report our initial clinical experience in implementing fast MRI techniques for outpatient brain imaging during the COVID-19 pandemic. METHODS Aggregate acquisition times were extracted from the medical record on consecutive imaging examinations performed during matched pre-implementation (7/1/2019-12/31/2019) and post-implementation periods (7/1/2020-12/31/2020). Expected acquisition time reduction for each MRI protocol was calculated through manual collection of acquisition times for the conventional and accelerated sequences performed during the pre- and post-implementation periods. Aggregate and expected acquisition times were compared for the five most frequently performed brain MRI protocols: brain without contrast (BR-), brain with and without contrast (BR+), multiple sclerosis (MS), memory loss (MML), and epilepsy (EPL). RESULTS The expected time reductions for BR-, BR+, MS, MML, and EPL protocols were 6.6 min, 11.9 min, 14 min, 10.8 min, and 14.1 min, respectively. The overall median aggregate acquisition time was 31 [25, 36] min for the pre-implementation period and 18 [15, 22] min for the post-implementation period, with a difference of 13 min (42%). The median acquisition time was reduced by 4 min (25%) for BR-, 14.0 min (44%) for BR+, 14 min (38%) for MS, 11 min (52%) for MML, and 16 min (35%) for EPL. CONCLUSION The implementation of fast brain MRI sequences significantly reduced the acquisition times for the most commonly performed outpatient brain MRI protocols.
Collapse
Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Samuel Cartmell
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Daniel Briggs
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Oleg Pianykh
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - John Kirsch
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Stephen Cauley
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Wei-Ching Lo
- Siemens Medical Solutions, Boston, Massachusetts
| | - Seretha Risacher
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Augusto Goncalves Filho
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Marc D Succi
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Pamela Schaefer
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts.
| |
Collapse
|
2
|
Li Z, Tian Q, Ngamsombat C, Cartmell S, Conklin J, Filho ALMG, Lo WC, Wang G, Ying K, Setsompop K, Fan Q, Bilgic B, Cauley S, Huang SY. High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN). Med Phys 2021; 49:1000-1014. [PMID: 34961944 DOI: 10.1002/mp.15427] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 11/22/2021] [Accepted: 12/12/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The goal of this study is to leverage an advanced fast imaging technique, wave-controlled aliasing in parallel imaging (Wave-CAIPI), and a generative adversarial network (GAN) for denoising to achieve accelerated high-quality high-signal-to-noise-ratio (SNR) volumetric MRI. METHODS Three-dimensional (3D) T2 -weighted fluid-attenuated inversion recovery (FLAIR) image data were acquired on 33 multiple sclerosis (MS) patients using a prototype Wave-CAIPI sequence (acceleration factor R = 3×2, 2.75 minutes) and a standard T2 -SPACE FLAIR sequence (R = 2, 7.25 minutes). A hybrid denoising GAN entitled "HDnGAN" consisting of a 3D generator and a 2D discriminator was proposed to denoise highly accelerated Wave-CAIPI images. HDnGAN benefits from the improved image synthesis performance provided by the 3D generator and increased training samples from a limited number of patients for training the 2D discriminator. HDnGAN was trained and validated on data from 25 MS patients with the standard FLAIR images as the target and evaluated on data from 8 MS patients not seen during training. HDnGAN was compared to other denoising methods including AONLM, BM4D, MU-Net, and 3D GAN in qualitative and quantitative analysis of output images using the mean squared error (MSE) and VGG perceptual loss compared to standard FLAIR images, and a reader assessment by two neuroradiologists regarding sharpness, SNR, lesion conspicuity, and overall quality. Finally, the performance of these denoising methods was compared at higher noise levels using simulated data with added Rician noise. RESULTS HDnGAN effectively denoised low-SNR Wave-CAIPI images with sharpness and rich textural details, which could be adjusted by controlling the contribution of the adversarial loss to the total loss when training the generator. Quantitatively, HDnGAN (λ = 10-3 ) achieved low MSE and the lowest VGG perceptual loss. The reader study showed that HDnGAN (λ = 10-3 ) significantly improved the SNR of Wave-CAIPI images (P<0.001), outperformed AONLM (P = 0.015), BM4D (P<0.001), MU-Net (P<0.001) and 3D GAN (λ = 10-3 ) (P<0.001) regarding image sharpness, and outperformed MU-Net (P<0.001) and 3D GAN (λ = 10-3 ) (P = 0.001) regarding lesion conspicuity. The overall quality score of HDnGAN (λ = 10-3 ) (4.25±0.43) was significantly higher than those from Wave-CAIPI (3.69±0.46, P = 0.003), BM4D (3.50±0.71, P = 0.001), MU-Net (3.25±0.75, P<0.001), and 3D GAN (λ = 10-3 ) (3.50±0.50, P<0.001), with no significant difference compared to standard FLAIR images (4.38±0.48, P = 0.333). The advantages of HDnGAN over other methods were more obvious at higher noise levels. CONCLUSION HDnGAN provides robust and feasible denoising while preserving rich textural detail in empirical volumetric MRI data. Our study using empirical patient data and systematic evaluation supports the use of HDnGAN in combination with modern fast imaging techniques such as Wave-CAIPI to achieve high-fidelity fast volumetric MRI and represents an important step to the clinical translation of GANs. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Ziyu Li
- Department of Biomedical Engineering, Tsinghua University, Beijing, P.R. China
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Chanon Ngamsombat
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Department of Radiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol, Thailand
| | - Samuel Cartmell
- Department of Radiology, Massachusetts General Hospital, Boston, USA
| | - John Conklin
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA.,Department of Radiology, Massachusetts General Hospital, Boston, USA
| | - Augusto Lio M Gonçalves Filho
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Department of Radiology, Massachusetts General Hospital, Boston, USA
| | | | - Guangzhi Wang
- Department of Biomedical Engineering, Tsinghua University, Beijing, P.R. China
| | - Kui Ying
- Department of Engineering Physics, Tsinghua University, Beijing, P. R. China
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stephen Cauley
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| |
Collapse
|
3
|
Goncalves Filho ALM, Longo MGF, Conklin J, Cauley SF, Polak D, Liu W, Splitthoff DN, Lo WC, Kirsch JE, Setsompop K, Schaefer PW, Huang SY, Rapalino O. MRI Highly Accelerated Wave-CAIPI T1-SPACE versus Standard T1-SPACE to detect brain gadolinium-enhancing lesions at 3T. J Neuroimaging 2021; 31:893-901. [PMID: 34081374 DOI: 10.1111/jon.12893] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 05/10/2021] [Accepted: 05/21/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE High-resolution three-dimensional (3D) post-contrast imaging of the brain is essential for comprehensive evaluation of inflammatory, neoplastic, and neurovascular diseases of the brain. 3D T1-weighted spin-echo-based sequences offer increased sensitivity for the detection of enhancing lesions but are relatively prolonged examinations. We evaluated whether a highly accelerated Wave-controlled aliasing in parallel imaging (Wave-CAIPI) post-contrast 3D T1-sampling perfection with application-optimized contrasts using different flip angle evolutions (T1-SPACE) sequence (Wave-T1-SPACE) was noninferior to the standard high-resolution 3D T1-SPACE sequence for visualizing enhancing lesions with comparable diagnostic quality. METHODS One hundred and three consecutive patients were prospectively evaluated with a standard post-contrast 3D T1-SPACE sequence (acquisition time [TA] = 4 min 19 s) and an optimized Wave-CAIPI 3D T1-SPACE sequence (TA = 1 min 40 s) that was nearly three times faster than the standard sequence. Two blinded neuroradiologists performed a head-to-head comparison to evaluate the visualization of enhancing pathology, perception of artifacts, and overall diagnostic quality. A 15% margin was used to test whether post-contrast Wave-T1-SPACE was noninferior to standard T1-SPACE. RESULTS Wave-T1-SPACE was noninferior to standard T1-SPACE for delineating parenchymal and meningeal enhancing pathology (p < 0.01). Wave-T1-SPACE showed marginally higher background noise compared to the standard sequence and was noninferior in the overall diagnostic quality (p = 0.03). CONCLUSIONS Our findings show that Wave-T1-SPACE was noninferior to standard T1-SPACE for visualization of enhancing pathology and overall diagnostic quality with a three-fold reduction in acquisition time compared to the standard sequence. Wave-T1-SPACE may be used to accelerate 3D post-contrast T1-weighted spin-echo imaging without loss of clinically important information.
Collapse
Affiliation(s)
- Augusto Lio M Goncalves Filho
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
| | - M Gabriela Figueiro Longo
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephen F Cauley
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
| | | | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | | | - Wei-Ching Lo
- Siemens Medical Solutions, Boston, Massachusetts, USA
| | - John E Kirsch
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
4
|
Goncalves Filho ALM, Conklin J, Longo MGF, Cauley SF, Polak D, Liu W, Splitthoff DN, Lo WC, Kirsch JE, Setsompop K, Schaefer PW, Huang SY, Rapalino O. Accelerated Post-contrast Wave-CAIPI T1 SPACE Achieves Equivalent Diagnostic Performance Compared With Standard T1 SPACE for the Detection of Brain Metastases in Clinical 3T MRI. Front Neurol 2020; 11:587327. [PMID: 33193054 PMCID: PMC7653188 DOI: 10.3389/fneur.2020.587327] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 09/30/2020] [Indexed: 12/12/2022] Open
Abstract
Background and Purpose: Brain magnetic resonance imaging (MRI) examinations using high-resolution 3D post-contrast sequences offer increased sensitivity for the detection of metastases in the central nervous system but are usually long exams. We evaluated whether the diagnostic performance of a highly accelerated Wave-controlled aliasing in parallel imaging (Wave-CAIPI) post-contrast 3D T1 SPACE sequence was non-inferior to the standard high-resolution 3D T1 SPACE sequence for the evaluation of brain metastases. Materials and Methods: Thirty-three patients undergoing evaluation for brain metastases were prospectively evaluated with a standard post-contrast 3D T1 SPACE sequence and an optimized Wave-CAIPI 3D T1 SPACE sequence, which was three times faster than the standard sequence. Two blinded neuroradiologists performed a head-to-head comparison to evaluate the visualization of pathology, perception of artifacts, and the overall diagnostic quality. Wave-CAIPI post-contrast T1 SPACE was tested for non-inferiority relative to standard T1 SPACE using a 15% non-inferiority margin. Results: Wave-CAIPI post-contrast T1 SPACE was non-inferior to the standard T1 SPACE for visualization of enhancing lesions (P < 0.01) and offered equivalent diagnostic quality performance and only marginally higher background noise compared to the standard sequence. Conclusions: Our findings suggest that Wave-CAIPI post-contrast T1 SPACE provides equivalent visualization of pathology and overall diagnostic quality with three times reduced scan time compared to the standard 3D T1 SPACE.
Collapse
Affiliation(s)
- Augusto Lio M Goncalves Filho
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - Maria Gabriela F Longo
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - Stephen F Cauley
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - Daniel Polak
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Siemens Healthcare GmbH, Erlangen, Germany
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | | | - Wei-Ching Lo
- Siemens Medical Solutions, Boston, MA, United States
| | - John E Kirsch
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - Kawin Setsompop
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States.,Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.,Harvard Medical School, Boston, MA, United States.,Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.,Harvard Medical School, Boston, MA, United States
| |
Collapse
|
5
|
Polak D, Cauley S, Bilgic B, Gong E, Bachert P, Adalsteinsson E, Setsompop K. Joint multi-contrast variational network reconstruction (jVN) with application to rapid 2D and 3D imaging. Magn Reson Med 2020; 84:1456-1469. [PMID: 32129529 PMCID: PMC7539238 DOI: 10.1002/mrm.28219] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 01/20/2020] [Accepted: 01/29/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To improve the image quality of highly accelerated multi-channel MRI data by learning a joint variational network that reconstructs multiple clinical contrasts jointly. METHODS Data from our multi-contrast acquisition were embedded into the variational network architecture where shared anatomical information is exchanged by mixing the input contrasts. Complementary k-space sampling across imaging contrasts and Bunch-Phase/Wave-Encoding were used for data acquisition to improve the reconstruction at high accelerations. At 3T, our joint variational network approach across T1w, T2w and T2-FLAIR-weighted brain scans was tested for retrospective under-sampling at R = 6 (2D) and R = 4 × 4 (3D) acceleration. Prospective acceleration was also performed for 3D data where the combined acquisition time for whole brain coverage at 1 mm isotropic resolution across three contrasts was less than 3 min. RESULTS Across all test datasets, our joint multi-contrast network better preserved fine anatomical details with reduced image-blurring when compared to the corresponding single-contrast reconstructions. Improvement in image quality was also obtained through complementary k-space sampling and Bunch-Phase/Wave-Encoding where the synergistic combination yielded the overall best performance as evidenced by exemplary slices and quantitative error metrics. CONCLUSION By leveraging shared anatomical structures across the jointly reconstructed scans, our joint multi-contrast approach learnt more efficient regularizers, which helped to retain natural image appearance and avoid over-smoothing. When synergistically combined with advanced encoding techniques, the performance was further improved, enabling up to R = 16-fold acceleration with good image quality. This should help pave the way to very rapid high-resolution brain exams.
Collapse
Affiliation(s)
- Daniel Polak
- Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Siemens Healthcare GmbH, Erlangen, Germany
| | - Stephen Cauley
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Berkin Bilgic
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Peter Bachert
- Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kawin Setsompop
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| |
Collapse
|
6
|
Poser BA, Setsompop K. Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field. Neuroimage 2018; 168:101-118. [PMID: 28392492 PMCID: PMC5630499 DOI: 10.1016/j.neuroimage.2017.04.006] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 04/01/2017] [Accepted: 04/03/2017] [Indexed: 12/18/2022] Open
Abstract
The SNR and CNR benefits of ultra-high field (UHF) have helped push the envelope of achievable spatial resolution in MRI. For applications based on susceptibility contrast where there is a large CNR gain, high quality sub-millimeter resolution imaging is now being routinely performed, particularly in fMRI and phase imaging/QSM. This has enabled the study of structure and function of very fine-scale structures in the brain. UHF has also helped push the spatial resolution of many other MRI applications as will be outlined in this review. However, this push in resolution comes at a cost of a large encoding burden leading to very lengthy scans. Developments in parallel imaging with controlled aliasing and the move away from 2D slice-by-slice imaging to much more SNR-efficient simultaneous multi-slice (SMS) and 3D acquisitions have helped address this issue. In particular, these developments have revolutionized the efficiency of UHF MRI to enable high spatiotemporal resolution imaging at an order of magnitude faster acquisition. In addition to describing the main approaches to these techniques, this review will also outline important key practical considerations in using these methods in practice. Furthermore, new RF pulse design to tackle the B1+ and SAR issues of UHF and the increased SAR and power requirement of SMS RF pulses will also be touched upon. Finally, an outlook into new developments of smart encoding in more dimensions, particularly through using better temporal/across-contrast encoding and reconstruction will be described. Just as controlled aliasing fully exploits spatial encoding in parallel imaging to provide large multiplicative gains in accelerations, the complimentary use of these new approaches in temporal and across-contrast encoding are expected to provide exciting opportunities for further large gains in efficiency to further push the spatiotemporal resolution of MRI.
Collapse
Affiliation(s)
- Benedikt A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Kawin Setsompop
- Department of Radiology, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| |
Collapse
|
7
|
Bilgic B, Ye H, Wald LL, Setsompop K. Simultaneous Time Interleaved MultiSlice (STIMS) for Rapid Susceptibility Weighted acquisition. Neuroimage 2017; 155:577-586. [PMID: 28435102 DOI: 10.1016/j.neuroimage.2017.04.036] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 04/14/2017] [Accepted: 04/15/2017] [Indexed: 01/30/2023] Open
Abstract
T2* weighted 3D Gradient Echo (GRE) acquisition is the main sequence used for Susceptibility Weighted Imaging (SWI) and Quantitative Susceptibility Mapping (QSM). These applications require a long echo time (TE) to build up phase contrast, requiring a long repetition time (TR), and leading to excessively lengthy scans. The long TE acquisition creates a significant amount of unused time within each TR, which can be utilized for either multi-echo sampling or additional image encoding with the echo-shift technique. The latter leads to significant saving in acquisition time while retaining the desired phase and T2* contrast. In this work, we introduce the Simultaneous Time Interleaved MultiSlice (STIMS) echo-shift technique, which mitigates slab boundary artifacts by interleaving comb-shaped slice groups with Simultaneous MultiSlice (SMS) excitation. This enjoys the same SNR benefit of 3D signal averaging as previously introduced multi-slab version, where each slab group is sub-resolved with kz phase encoding. Further, we combine SMS echo-shift with Compressed Sensing (CS) Wave acceleration, which enhances Wave-CAIPI acquisition/reconstruction with random undersampling and sparsity prior. STIMS and CS-Wave combination thus yields up to 45-fold acceleration over conventional full encoding, allowing a 15sec full-brain acquisition with 1.5 mm isotropic resolution at long TE of 39 ms at 3T. In addition to utilizing empty sequence time due to long TE, STIMS is a general concept that could exploit gaps due to e.g. inversion modules in magnetization-prepared rapid gradient-echo (MPRAGE) and fluid attenuated inversion recovery (FLAIR) sequences.
Collapse
Affiliation(s)
- Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Huihui Ye
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China; Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| |
Collapse
|
8
|
Chatnuntawech I, McDaniel P, Cauley SF, Gagoski BA, Langkammer C, Martin A, Grant PE, Wald LL, Setsompop K, Adalsteinsson E, Bilgic B. Single-step quantitative susceptibility mapping with variational penalties. NMR Biomed 2017; 30:10.1002/nbm.3570. [PMID: 27332141 PMCID: PMC5179325 DOI: 10.1002/nbm.3570] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Revised: 04/21/2016] [Accepted: 05/09/2016] [Indexed: 05/21/2023]
Abstract
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from the gradient echo (GRE) phase signal through background phase removal and dipole inversion steps. Each of these steps typically requires the solution of an ill-posed inverse problem and thus necessitates additional regularization. Recently developed single-step QSM algorithms directly relate the unprocessed GRE phase to the unknown susceptibility distribution, thereby requiring the solution of a single inverse problem. In this work, we show that such a holistic approach provides susceptibility estimation with artifact mitigation and develop efficient algorithms that involve simple analytical solutions for all of the optimization steps. Our methods employ total variation (TV) and total generalized variation (TGV) to jointly perform the background removal and dipole inversion in a single step. Using multiple spherical mean value (SMV) kernels of varying radii permits high-fidelity background removal whilst retaining the phase information in the cortex. Using numerical simulations, we demonstrate that the proposed single-step methods reduce the reconstruction error by up to 66% relative to the multi-step methods that involve SMV background filtering with the same number of SMV kernels, followed by TV- or TGV-regularized dipole inversion. In vivo single-step experiments demonstrate a dramatic reduction in dipole streaking artifacts and improved homogeneity of image contrast. These acquisitions employ the rapid three-dimensional echo planar imaging (3D EPI) and Wave-CAIPI (controlled aliasing in parallel imaging) trajectories for signal-to-noise ratio-efficient whole-brain imaging. Herein, we also demonstrate the multi-echo capability of the Wave-CAIPI sequence for the first time, and introduce an automated, phase-sensitive coil sensitivity estimation scheme based on a 4-s calibration acquisition. Copyright © 2016 John Wiley & Sons, Ltd.
Collapse
Affiliation(s)
- Itthi Chatnuntawech
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Correspondence to: Itthi Chatnuntawech, Massachusetts Institute of Technology, Room 36-776A, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, , Phone: 617-324-1738
| | - Patrick McDaniel
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Stephen F. Cauley
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan A. Gagoski
- Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Adrian Martin
- Applied Mathematics, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain
| | - P. Ellen Grant
- Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Lawrence L. Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kawin Setsompop
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Berkin Bilgic
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| |
Collapse
|
9
|
Bilgic B, Xie L, Dibb R, Langkammer C, Mutluay A, Ye H, Polimeni JR, Augustinack J, Liu C, Wald LL, Setsompop K. Rapid multi-orientation quantitative susceptibility mapping. Neuroimage 2015; 125:1131-1141. [PMID: 26277773 DOI: 10.1016/j.neuroimage.2015.08.015] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2015] [Revised: 08/02/2015] [Accepted: 08/04/2015] [Indexed: 01/10/2023] Open
Abstract
Three-dimensional gradient echo (GRE) is the main workhorse sequence used for susceptibility weighted imaging (SWI), quantitative susceptibility mapping (QSM), and susceptibility tensor imaging (STI). Achieving optimal phase signal-to-noise ratio requires late echo times, thus necessitating a long repetition time (TR). Combined with the large encoding burden of whole-brain coverage with high resolution, this leads to increased scan time. Further, the dipole kernel relating the tissue phase to the underlying susceptibility distribution undersamples the frequency content of the susceptibility map. Scans at multiple head orientations along with calculation of susceptibility through multi-orientation sampling (COSMOS) are one way to effectively mitigate this issue. Additionally, STI requires a minimum of 6 head orientations to solve for the independent tensor elements in each voxel. The requirements of high-resolution imaging with long TR at multiple orientations substantially lengthen the acquisition of COSMOS and STI. The goal of this work is to dramatically speed up susceptibility mapping at multiple head orientations. We demonstrate highly efficient acquisition using 3D-GRE with Wave-CAIPI and dramatically reduce the acquisition time of these protocols. Using R=15-fold acceleration with Wave-CAIPI permits acquisition per head orientation in 90s at 1.1mm isotropic resolution, and 5:35min at 0.5mm isotropic resolution. Since Wave-CAIPI fully harnesses the 3D spatial encoding capability of receive arrays, the maximum g-factor noise amplification remains below 1.30 at 3T and 1.12 at 7T. This allows a 30-min exam for STI with 12 orientations, thus paving the way to its clinical application.
Collapse
Affiliation(s)
- Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Luke Xie
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, USA
| | - Russell Dibb
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, USA; Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Christian Langkammer
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Neurology, Medical University of Graz, Graz, Austria; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | | | - Huihui Ye
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Chunlei Liu
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, USA; Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
10
|
Gagoski BA, Bilgic B, Eichner C, Bhat H, Grant PE, Wald LL, Setsompop K. RARE/turbo spin echo imaging with Simultaneous Multislice Wave-CAIPI. Magn Reson Med 2015; 73:929-938. [PMID: 25640187 DOI: 10.1002/mrm.25615] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Revised: 12/21/2014] [Accepted: 12/22/2014] [Indexed: 02/04/2023]
Abstract
PURPOSE To enable highly accelerated RARE/Turbo Spin Echo (TSE) imaging using Simultaneous MultiSlice (SMS) Wave-CAIPI acquisition with reduced g-factor penalty. METHODS SMS Wave-CAIPI incurs slice shifts across simultaneously excited slices while playing sinusoidal gradient waveforms during the readout of each encoding line. This results in an efficient k-space coverage that spreads aliasing in all three dimensions to fully harness the encoding power of coil sensitivities. The novel MultiPINS radiofrequency (RF) pulses dramatically reduce the power deposition of multiband (MB) refocusing pulse, thus allowing high MB factors within the Specific Absorption Rate (SAR) limit. RESULTS Wave-CAIPI acquisition with MultiPINS permits whole brain coverage with 1 mm isotropic resolution in 70 s at effective MB factor 13, with maximum and average g-factor penalties of gmax = 1.34 and gavg = 1.12, and without √R penalty. With blipped-CAIPI, the g-factor performance was degraded to gmax = 3.24 and gavg = 1.42; a 2.4-fold increase in gmax relative to Wave-CAIPI. At this MB factor, the SAR of the MultiBand and PINS pulses are 4.2 and 1.9 times that of the MultiPINS pulse, while the peak RF power are 19.4 and 3.9 times higher. CONCLUSION Combination of the two technologies, Wave-CAIPI and MultiPINS pulse, enables highly accelerated RARE/TSE imaging with low SNR penalty at reduced SAR.
Collapse
Affiliation(s)
- Borjan A Gagoski
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgic
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Cornelius Eichner
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Himanshu Bhat
- Siemens Medical Solutions USA Inc., Charlestown, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Lawrence L Wald
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard-MIT Health Sciences and Technology, Cambridge, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| |
Collapse
|