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Kits A, Al-Saadi J, De Luca F, Janzon F, Mazya MV, Lundberg J, Sprenger T, Skare S, Delgado AF. 2.5-Minute Fast Brain MRI with Multiple Contrasts in Acute Ischemic Stroke. Neuroradiology 2024; 66:737-747. [PMID: 38462584 PMCID: PMC11031482 DOI: 10.1007/s00234-024-03331-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 03/04/2024] [Indexed: 03/12/2024]
Abstract
PURPOSE To assess the performance of a 2.5-minute multi-contrast brain MRI sequence (NeuroMix) in diagnosing acute cerebral infarctions. METHODS Adult patients with a clinical suspicion of acute ischemic stroke were retrospectively included. Brain MRI at 3 T included NeuroMix and routine clinical MRI (cMRI) sequences, with DWI/ADC, T2-FLAIR, T2-weighted, T2*, SWI-EPI, and T1-weighted contrasts. Three radiologists (R1-3) independently assessed NeuroMix and cMRI for the presence of acute infarcts (DWI ↑, ADC = or ↓) and infarct-associated abnormalities on other image contrasts. Sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) were calculated and compared using DeLong's test. Inter- and intra-rater agreements were studied with kappa statistics. Relative DWI (rDWI) and T2-FLAIR (rT2-FLAIR) signal intensity for infarctions were semi-automatically rendered, and the correlation between methods was evaluated. RESULTS According to the reference standard, acute infarction was present in 34 out of 44 (77%) patients (63 ± 17 years, 31 men). Other infarct-associated signal abnormalities were reported in similar frequencies on NeuroMix and cMRI (p > .08). Sensitivity for infarction detection was 94%, 100%, and 94% evaluated by R1, R2, R3, for NeuroMix and 94%, 100%, and 100% for cMRI. Specificity was 100%, 90%, and 100% for NeuroMix and 100%, 100%, and 100% for cMRI. AUC for NeuroMix was .97, .95, and .97 and .97, 1, and 1 for cMRI (DeLong p = 1, .32, .15), respectively. Inter- and intra-rater agreement was κ = .88-1. The correlation between NeuroMix and cMRI was R = .73 for rDWI and R = .83 for rT2-FLAIR. CONCLUSION Fast multi-contrast MRI NeuroMix has high diagnostic performance for detecting acute cerebral infarctions.
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Affiliation(s)
- Annika Kits
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden.
| | - Jonathan Al-Saadi
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden
| | - Francesca De Luca
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden
- Department of Radiology, Karolinska University Hospital, Stockholm, Sweden
| | - Fredrik Janzon
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden
- Department of Radiology, Danderyd Hospital, Stockholm, Sweden
| | - Michael V Mazya
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Lundberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden
| | - Tim Sprenger
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- MR Applied Science Laboratory Europe, GE Healthcare, Stockholm, Sweden
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden
| | - Anna Falk Delgado
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Solna, 17176, Stockholm, Sweden
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Lang M, Clifford B, Lo WC, Applewhite BP, Tabari A, Filho ALMG, Hosseini Z, Longo MGF, Cauley SF, Setsompop K, Bilgic B, Feiweier T, Lev MH, Schaefer PW, Rapalino O, Huang SY, Conklin J. Clinical Evaluation of a 2-Minute Ultrafast Brain MR Protocol for Evaluation of Acute Pathology in the Emergency and Inpatient Settings. AJNR Am J Neuroradiol 2024; 45:379-385. [PMID: 38453413 DOI: 10.3174/ajnr.a8143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/07/2023] [Indexed: 03/09/2024]
Abstract
BACKGROUND AND PURPOSE The use of MR imaging in emergency settings has been limited by availability, long scan times, and sensitivity to motion. This study assessed the diagnostic performance of an ultrafast brain MR imaging protocol for evaluation of acute intracranial pathology in the emergency department and inpatient settings. MATERIALS AND METHODS Sixty-six adult patients who underwent brain MR imaging in the emergency department and inpatient settings were included in the study. All patients underwent both the reference and the ultrafast brain MR protocols. Both brain MR imaging protocols consisted of T1-weighted, T2/T2*-weighted, FLAIR, and DWI sequences. The ultrafast MR images were reconstructed by using a machine-learning assisted framework. All images were reviewed by 2 blinded neuroradiologists. RESULTS The average acquisition time was 2.1 minutes for the ultrafast brain MR protocol and 10 minutes for the reference brain MR protocol. There was 98.5% agreement on the main clinical diagnosis between the 2 protocols. In head-to-head comparison, the reference protocol was preferred in terms of image noise and geometric distortion (P < .05 for both). The ultrafast ms-EPI protocol was preferred over the reference protocol in terms of reduced motion artifacts (P < .01). Overall diagnostic quality was not significantly different between the 2 protocols (P > .05). CONCLUSIONS The ultrafast brain MR imaging protocol provides high accuracy for evaluating acute pathology while only requiring a fraction of the scan time. Although there was greater image noise and geometric distortion on the ultrafast brain MR protocol images, there was significant reduction in motion artifacts with similar overall diagnostic quality between the 2 protocols.
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Affiliation(s)
- Min Lang
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Bryan Clifford
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
| | - Wei-Ching Lo
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
| | - Brooks P Applewhite
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Azadeh Tabari
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | | | - Zahra Hosseini
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
| | - Maria Gabriela Figueiro Longo
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Stephen F Cauley
- Siemens Medical Solutions (B.C., W.-C.L., Z.H., S.F.C.), Boston, Massachusetts
- Harvard-MIT Health Sciences and Technology (S.F.C., B.B., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Kawin Setsompop
- Departments of Radiology and Electrical Engineering (K.S.), Stanford University, Stanford, California
| | - Berkin Bilgic
- Harvard-MIT Health Sciences and Technology (S.F.C., B.B., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | | | - Michael H Lev
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Pamela W Schaefer
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Otto Rapalino
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
| | - Susie Y Huang
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
- Harvard-MIT Health Sciences and Technology (S.F.C., B.B., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - John Conklin
- From the Department of Radiology (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School (M.L., B.P.A., A.T., M.G.F.L., M.H.L., P.W.S., O.R., S.Y.H., J.C.), Boston, Massachusetts
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Ganesh VKSV, Kamepalli HK, Sharma DP, Thomas B, Kesavadas C. Multi-contrast echo-planar imaging sequence (Echo-planar imaging mix) in clinical situations demanding faster MRI-brain scans. J Neurosci Rural Pract 2024; 15:341-348. [PMID: 38746507 PMCID: PMC11090545 DOI: 10.25259/jnrp_508_2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 03/10/2024] [Indexed: 05/16/2024] Open
Abstract
Objectives The excellent resolution offered by magnetic resonance imaging (MRI) has a trade-off in the form of scan duration. The purpose of the present study was to assess the clinical utility of echo-planar imaging mix (EPIMix), an echo-planar imaging-based MRI sequence for the brain with a short acquisition time. Materials and Methods This was a retrospective observational study of 50 patients, who could benefit from faster MRI brain scans. The T1, T2, fluid attenuated inversion recovery, diffusion-weighted imaging (DWI), and T2*/susceptibility-weighted imaging sequences were acquired, conventionally and with EPIMix. Conventional and EPIMix images were assessed by two radiologists for overall quality, motion, and susceptibility artifacts and scored on a Likert scale. The scores given for conventional and EPIMix images were compared. The diagnostic performance of EPIMix was also assessed by the ability to detect clinically relevant findings. Results The acquisition time for conventional MRI was 11 min and 45 s and for EPIMix 1 min and 15 s. All EPIMix images were sufficient for diagnostic use. On assessment of the diagnostic performance, it was excellent for ischemic and hemorrhagic strokes. Smaller lesions, lesions adjacent to bone, and post-operative tumors were difficult to identify. Moderate to perfect agreement (Kappa values 0.41-1) was seen between radiologists for all categories except skull base, calvarial, and orbital lesions. Image quality, artifact assessment showed excellent interobserver agreement (>90%) for the scores. All EPIMix images showed reduced motion artifacts. The EPIMix-DWI was comparable to conventional-DWI in terms of quality and artifacts. The remaining sequences showed reduced quality and increased susceptibility. Conclusion The EPIMix has a significantly reduced acquisition time than conventional MRI and could be used instead of conventional MRI in situations demanding faster scans such as suspected acute ischemic or hemorrhagic stroke. In other clinical scenarios, it could help tailor the MRI examination for each patient.
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Affiliation(s)
- Viswanadh Kalaparti Sri Venkata Ganesh
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Hari Kishore Kamepalli
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | | | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Chandrasekharan Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
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Kumar S, Saber H, Charron O, Freeman L, Tamir JI. Correcting synthetic MRI contrast-weighted images using deep learning. Magn Reson Imaging 2024; 106:43-54. [PMID: 38092082 DOI: 10.1016/j.mri.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 11/30/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023]
Abstract
Synthetic magnetic resonance imaging (MRI) offers a scanning paradigm where a fast multi-contrast sequence can be used to estimate underlying quantitative tissue parameter maps, which are then used to synthesize any desirable clinical contrast by retrospectively changing scan parameters in silico. Two benefits of this approach are the reduced exam time and the ability to generate arbitrary contrasts offline. However, synthetically generated contrasts are known to deviate from the contrast of experimental scans. The reason for contrast mismatch is the necessary exclusion of some unmodeled physical effects such as partial voluming, diffusion, flow, susceptibility, magnetization transfer, and more. The inclusion of these effects in signal encoding would improve the synthetic images, but would make the quantitative imaging protocol impractical due to long scan times. Therefore, in this work, we propose a novel deep learning approach that generates a multiplicative correction term to capture unmodeled effects and correct the synthetic contrast images to better match experimental contrasts for arbitrary scan parameters. The physics inspired deep learning model implicitly accounts for some unmodeled physical effects occurring during the scan. As a proof of principle, we validate our approach on synthesizing arbitrary inversion recovery fast spin-echo scans using a commercially available 2D multi-contrast sequence. We observe that the proposed correction visually and numerically reduces the mismatch with experimentally collected contrasts compared to conventional synthetic MRI. Finally, we show results of a preliminary reader study and find that the proposed method statistically significantly improves in contrast and SNR as compared to synthetic MR images.
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Affiliation(s)
- Sidharth Kumar
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin 78712, TX, USA.
| | - Hamidreza Saber
- Dell Medical School Department of Neurology, The University of Texas at Austin, Austin 78712, TX, USA; Dell Medical School Department of Neurosurgery, The University of Texas at Austin, Austin 78712, TX, USA
| | - Odelin Charron
- Dell Medical School Department of Neurology, The University of Texas at Austin, Austin 78712, TX, USA
| | - Leorah Freeman
- Dell Medical School Department of Neurology, The University of Texas at Austin, Austin 78712, TX, USA; Dell Medical School Department of Diagnostic Medicine, The University of Texas at Austin, Austin 78712, TX, USA
| | - Jonathan I Tamir
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin 78712, TX, USA; Dell Medical School Department of Diagnostic Medicine, The University of Texas at Austin, Austin 78712, TX, USA; Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin 78712, TX, USA
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De Luca F, Kits A, Martin Muñoz D, Aspelin Å, Kvist O, Österman Y, Diaz Ruiz S, Skare S, Falk Delgado A. Elective one-minute full brain multi-contrast MRI versus brain CT in pediatric patients: a prospective feasibility study. BMC Med Imaging 2024; 24:23. [PMID: 38267889 PMCID: PMC10809606 DOI: 10.1186/s12880-024-01196-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 01/08/2024] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND Brain CT can be used to evaluate pediatric patients with suspicion of cerebral pathology when anesthetic and MRI resources are scarce. This study aimed to assess if pediatric patients referred for an elective brain CT could endure a diagnostic fast brain MRI without general anesthesia using a one-minute multi-contrast EPI-based sequence (EPIMix) with comparable diagnostic performance. METHODS Pediatric patients referred for an elective brain CT between March 2019 and March 2020 were prospectively included and underwent EPIMix without general anesthesia in addition to CT. Three readers (R1-3) independently evaluated EPIMix and CT images on two separate occasions. The two main study outcomes were the tolerance to undergo an EPIMix scan without general anesthesia and its performance to classify a scan as normal or abnormal. Secondary outcomes were assessment of disease category, incidental findings, diagnostic image quality, diagnostic confidence, and image artifacts. Further, a side-by-side evaluation of EPIMix and CT was performed. The signal-to-noise ratio (SNR) was calculated for EPIMix on T1-weighted, T2-weighted, and ADC images. Descriptive statistics, Fisher's exact test, and Chi-squared test were used to compare the two imaging modalities. RESULTS EPIMix was well tolerated by all included patients (n = 15) aged 5-16 (mean 11, SD 3) years old. Thirteen cases on EPIMix and twelve cases on CT were classified as normal by all readers (R1-3), while two cases on EPIMix and three cases on CT were classified as abnormal by one reader (R1), (R1-3, p = 1.00). There was no evidence of a difference in diagnostic confidence, image quality, or the presence of motion artifacts between EPIMix and CT (R1-3, p ≥ 0.10). Side-by-side evaluation (R2 + R4 + R5) reviewed all scans as lacking significant pathological findings on EPIMix and CT images. CONCLUSIONS Full brain MRI-based EPIMix sequence was well tolerated without general anesthesia with a diagnostic performance comparable to CT in elective pediatric patients. TRIAL REGISTRATION This study was approved by the Swedish Ethical Review Authority (ethical approval number/ID Ethical approval 2017/2424-31/1). This study was a clinical trial study, with study protocol published at ClinicalTrials.gov with Trial registration number NCT03847051, date of registration 18/02/2019.
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Affiliation(s)
- Francesca De Luca
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
- Department of Radiology, Karolinska University Hospital, Stockholm, Sweden.
| | - Annika Kits
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Martin Muñoz
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Åsa Aspelin
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Ola Kvist
- Department of Pediatric Radiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden
| | - Yords Österman
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Sandra Diaz Ruiz
- Department of Pediatric Radiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden
- Department of Radiology, Lund University, Lund, Sweden
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Falk Delgado
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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Altmann S, Abello Mercado MA, Brockstedt L, Kronfeld A, Clifford B, Feiweier T, Uphaus T, Groppa S, Brockmann MA, Othman AE. Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and Multi-shot EPI. Acad Radiol 2023; 30:2988-2998. [PMID: 37211480 DOI: 10.1016/j.acra.2023.04.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 05/23/2023]
Abstract
RATIONALE AND OBJECTIVES To evaluate clinical feasibility and image quality of a comprehensive ultrafast brain MRI protocol with multi-shot echo planar imaging and deep learning-enhanced reconstruction at 1.5T. MATERIALS AND METHODS Thirty consecutive patients who underwent clinically indicated MRI at a 1.5 T scanner were prospectively included. A conventional MRI (c-MRI) protocol, including T1-, T2-, T2*-, T2-FLAIR, and diffusion-weighted images (DWI)-weighted sequences were acquired. In addition, ultrafast brain imaging with deep learning-enhanced reconstruction and multi-shot EPI (DLe-MRI) was performed. Subjective image quality was evaluated by three readers using a 4-point Likert scale. To assess interrater agreement, Fleiss' kappa (ϰ) was determined. For objective image analysis, relative signal intensity levels for grey matter, white matter, and cerebrospinal fluid were calculated. RESULTS Time of acquisition (TA) of c-MRI protocols added up to 13:55 minutes, whereas the TA of DLe-MRI-based protocol added up to 3:04 minutes, resulting in a time reduction of 78%. All DLe-MRI acquisitions yielded diagnostic image quality with good absolute values for subjective image quality. C-MRI demonstrated slight advantages for DWI in overall subjective image quality (c-MRI: 3.93 [+/- 0.25] vs DLe-MRI: 3.87 [+/- 0.37], P = .04) and diagnostic confidence (c-MRI: 3.93 [+/- 0.25] vs DLe-MRI: 3.83 [+/- 3.83], P = .01). For most evaluated quality scores, moderate interobserver agreement was found. Objective image evaluation revealed comparable results for both techniques. CONCLUSION DLe-MRI is feasible and allows for highly accelerated comprehensive brain MRI within 3minutes at 1.5 T with good image quality. This technique may potentially strengthen the role of MRI in neurological emergencies.
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Affiliation(s)
- Sebastian Altmann
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Langenbeckst. 1, 55131 Mainz, Germany (S.A., M.A.M., L.B., A.K., M.A.B., A.E.O.).
| | - Mario Alberto Abello Mercado
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Langenbeckst. 1, 55131 Mainz, Germany (S.A., M.A.M., L.B., A.K., M.A.B., A.E.O.)
| | - Lavinia Brockstedt
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Langenbeckst. 1, 55131 Mainz, Germany (S.A., M.A.M., L.B., A.K., M.A.B., A.E.O.)
| | - Andrea Kronfeld
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Langenbeckst. 1, 55131 Mainz, Germany (S.A., M.A.M., L.B., A.K., M.A.B., A.E.O.)
| | - Bryan Clifford
- Siemens Medical Solutions USA, Boston, Massachusetts (B.C.)
| | | | - Timo Uphaus
- Department of Neurology, University Medical Center Mainz, Johannes Gutenberg University, Mainz, Germany (T.U., S.G.)
| | - Sergiu Groppa
- Department of Neurology, University Medical Center Mainz, Johannes Gutenberg University, Mainz, Germany (T.U., S.G.)
| | - Marc A Brockmann
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Langenbeckst. 1, 55131 Mainz, Germany (S.A., M.A.M., L.B., A.K., M.A.B., A.E.O.)
| | - Ahmed E Othman
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Langenbeckst. 1, 55131 Mainz, Germany (S.A., M.A.M., L.B., A.K., M.A.B., A.E.O.)
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7
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Li Z, Ooi MB, Murchison JA, Karis JP. Rapid T 2 ∗ -weighted MRI using multishot EPI with retrospective motion and phase correction in the emergency department. Magn Reson Med 2023; 90:2500-2509. [PMID: 37668095 DOI: 10.1002/mrm.29809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 07/07/2023] [Accepted: 07/08/2023] [Indexed: 09/06/2023]
Abstract
PURPOSE Brain MRI is increasingly used in the emergency department (ED), whereT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI is an essential tool for detecting hemorrhage and stroke. The goal of this study was to develop a rapidT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI technique capable of correcting motion-induced artifacts, thereby simultaneously improving scan time and motion robustness for ED applications. METHODS A 2D gradient-echo (GRE)-based multishot EPI (msEPI) technique was implemented using a navigator echo for estimating motion-induced errors. Bulk rigid head motion and phase errors were retrospectively corrected using an iterative conjugate gradient approach in the reconstruction pipeline. Three volunteers and select patients were imaged at 3 T and/or 1.5 T with an approximately 1-min full-brain protocol using the proposed msEPI technique and compared to an approximately 3-min standard-of-care GRE protocol to examine its performance. RESULTS Data from volunteers demonstrated that in-plane motion artifacts could be effectively corrected with the proposed msEPI technique, and through-plane motion artifacts could be mitigated. Patient images were qualitatively reviewed by one radiologist without a formal statistical analysis. These results suggested the proposed technique could correct motion-induced artifacts in the clinical setting. In addition, the conspicuity of susceptibility-related lesions using the proposed msEPI technique was comparable, or improved, compared to GRE. CONCLUSION A 1-min full-brainT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI technique was developed using msEPI with a navigator echo to correct motion-induced errors. Preliminary clinical results suggest faster scans and improved motion robustness and lesion conspicuity make msEPI a competitive alternative to traditionalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI techniques for brain studies in the ED.
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Affiliation(s)
- Zhiqiang Li
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, Arizona, USA
| | | | - James A Murchison
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - John P Karis
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, Arizona, USA
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Poojar P, Qian E, Fernandes TT, Nunes RG, Fung M, Quarterman P, Jambawalikar SR, Lignelli A, Geethanath S. Tailored magnetic resonance fingerprinting. Magn Reson Imaging 2023; 99:81-90. [PMID: 36764630 DOI: 10.1016/j.mri.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/27/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023]
Abstract
Neuroimaging of certain pathologies requires both multi-parametric qualitative and quantitative imaging. The role of the quantitative MRI (qMRI) is well accepted but suffers from long acquisition times leading to patient discomfort, especially in geriatric and pediatric patients. Previous studies show that synthetic MRI can be used in order to reduce the scan time and provide qMRI as well as multi-contrast data. However, this approach suffers from artifacts such as partial volume and flow. In order to increase the scan efficiency (the number of contrasts and quantitative maps acquired per unit time), we designed, simulated, and demonstrated rapid, simultaneous, multi-contrast qualitative (T1 weighted, T1 fluid attenuated inversion recovery (FLAIR), T2 weighted, water, and fat), and quantitative imaging (T1 and T2 maps) through the approach of tailored MR fingerprinting (TMRF) to cover whole-brain in approximately four minutes. We performed TMRF on in vivo four healthy human brains and in vitro ISMRM/NIST phantom and compared with vendor supplied gold standard (GS) and MRF sequences. All scans were performed on a 3 T GE Premier system and images were reconstructed offline using MATLAB. The reconstructed qualitative images were then subjected to custom DL denoising and gradient anisotropic diffusion denoising. The quantitative tissue parametric maps were reconstructed using a dense neural network to gain computational speed compared to dictionary matching. The grey matter and white matter tissues in qualitative and quantitative data for the in vivo datasets were segmented semi-automatically. The SNR and mean contrasts were plotted and compared across all three methods. The GS images show better SNR in all four subjects compared to MRF and TMRF (GS > TMRF>MRF). The T1 and T2 values of MRF are relatively overestimated as compared to GS and TMRF. The scan efficiency for TMRF is 1.72 min-1 which is higher compared to GS (0.32 min-1) and MRF (0.90 min-1).
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Affiliation(s)
- Pavan Poojar
- Icahn School of Medicine at Mt. Sinai, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the city of New York, NY, USA
| | - Enlin Qian
- Columbia Magnetic Resonance Research Center, Columbia University in the city of New York, NY, USA
| | - Tiago T Fernandes
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Rita G Nunes
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Maggie Fung
- GE Healthcare Applied Sciences Laboratory East, New York, NY, USA
| | | | - Sachin R Jambawalikar
- Department of Radiology, Columbia University Irving Medical Center, Columbia University in the city of New York, NY, USA
| | - Angela Lignelli
- Department of Radiology, Columbia University Irving Medical Center, Columbia University in the city of New York, NY, USA
| | - Sairam Geethanath
- Icahn School of Medicine at Mt. Sinai, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the city of New York, NY, USA.
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9
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Verclytte S, Gnanih R, Verdun S, Feiweier T, Clifford B, Ambarki K, Pasquini M, Ding J. Ultrafast MRI using deep learning echoplanar imaging for a comprehensive assessment of acute ischemic stroke. Eur Radiol 2023; 33:3715-3725. [PMID: 36928567 DOI: 10.1007/s00330-023-09508-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 12/09/2022] [Accepted: 01/30/2023] [Indexed: 03/18/2023]
Abstract
OBJECTIVES Acute ischemic stroke (AIS) is an emergency requiring both fast and informative MR sequences. We aimed to assess the performance of an artificial intelligence-enhanced ultrafast (UF) protocol, compared to the reference protocol, in the AIS management. METHODS We included patients admitted in the emergency department for suspected AIS. Each patient underwent a 3-T MR protocol, including reference acquisitions of T2-FLAIR, DWI, and SWI (duration: 7 min 54 s) and their accelerated multishot EPI counterparts for T2-FLAIR and T2*, complemented by a single-shot EPI DWI (duration: 1 min 54 s). Two blinded neuroradiologists reviewed each dataset, assessing DWI (detection, location, number of acute lesions), FLAIR (vascular hyperintensities, visibility of acute lesions), and SWI/T2* (hemorrhagic transformation, thrombus). We compared the agreement between the diagnoses obtained with both protocols using kappa coefficients. RESULTS A total of 173 patients were included consecutively, of whom 80 with an AIS in DWI. We found an almost perfect agreement between the UF and reference protocols regarding the detection, distribution, number of AIS in DWI (κ = 0.98, 0.98, and 0.87 respectively), the presence of vascular hyperintensities, and the presence of a parenchymal hyperintensity in the AIS region in FLAIR (κ = 0.93 and 0.89 respectively). Agreement was substantial in T2*/SWI for thrombus detection, and fair for hemorrhagic transformation detection (κ = 0.64 and 0.38 respectively). Differential diagnoses were similarly detected by both protocols (κ = 1). CONCLUSIONS Our AI-enhanced ultrafast MRI protocol allowed an effective detection and characterization of both AIS and differential diagnoses in less than 2 min. KEY POINTS • The AI-enhanced ultrafast MRI protocol allowed an effective detection of acute stroke. • Characterization of stroke features with the UF protocol was equivalent to the reference sequences. • Differential diagnoses were detected similarly by the UF and reference protocols.
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Affiliation(s)
- Sebastien Verclytte
- Imaging Department, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France.
| | - Robin Gnanih
- Imaging Department, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France
| | - Stephane Verdun
- Biostatistics Department - Delegation for Clinical Research and Innovation, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France
| | | | | | | | - Marta Pasquini
- Department of Neurology, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France
| | - Juliette Ding
- Imaging Department, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France
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10
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Lang M, Tabari A, Polak D, Ford J, Clifford B, Lo WC, Manzoor K, Splitthoff DN, Wald LL, Rapalino O, Schaefer P, Conklin J, Cauley S, Huang SY. Clinical Evaluation of Scout Accelerated Motion Estimation and Reduction Technique for 3D MR Imaging in the Inpatient and Emergency Department Settings. AJNR Am J Neuroradiol 2023; 44:125-133. [PMID: 36702502 PMCID: PMC9891324 DOI: 10.3174/ajnr.a7777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 12/11/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE A scout accelerated motion estimation and reduction (SAMER) framework has been developed for efficient retrospective motion correction. The goal of this study was to perform an initial evaluation of SAMER in a series of clinical brain MR imaging examinations. MATERIALS AND METHODS Ninety-seven patients who underwent MR imaging in the inpatient and emergency department settings were included in the study. SAMER motion correction was retrospectively applied to an accelerated T1-weighted MPRAGE sequence that was included in brain MR imaging examinations performed with and without contrast. Two blinded neuroradiologists graded images with and without SAMER motion correction on a 5-tier motion severity scale (none = 1, minimal = 2, mild = 3, moderate = 4, severe = 5). RESULTS The median SAMER reconstruction time was 1 minute 47 seconds. SAMER motion correction significantly improved overall motion grades across all examinations (P < .005). Motion artifacts were reduced in 28% of cases, unchanged in 64% of cases, and increased in 8% of cases. SAMER improved motion grades in 100% of moderate motion cases and 75% of severe motion cases. Sixty-nine percent of nondiagnostic motion cases (grades 4 and 5) were considered diagnostic after SAMER motion correction. For cases with minimal or no motion, SAMER had negligible impact on the overall motion grade. For cases with mild, moderate, and severe motion, SAMER improved the motion grade by an average of 0.3 (SD, 0.5), 1.1 (SD, 0.3), and 1.1 (SD, 0.8) grades, respectively. CONCLUSIONS SAMER improved the diagnostic image quality of clinical brain MR imaging examinations with motion artifacts. The improvement was most pronounced for cases with moderate or severe motion.
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Affiliation(s)
- M Lang
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - A Tabari
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - D Polak
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Siemens Healthcare GmbH (D.P., D.N.S.), Erlangen, Germany
| | - J Ford
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - B Clifford
- Siemens Medical Solutions (B.C., W.-C.L.), Boston, Massachusetts
| | - W-C Lo
- Siemens Medical Solutions (B.C., W.-C.L.), Boston, Massachusetts
| | - K Manzoor
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - D N Splitthoff
- Siemens Healthcare GmbH (D.P., D.N.S.), Erlangen, Germany
| | - L L Wald
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
- Harvard-MIT Health Sciences and Technology (L.L.W.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - O Rapalino
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - P Schaefer
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - J Conklin
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - S Cauley
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
| | - S Y Huang
- From the Department of Radiology (M.L., A.T., D.P., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (M.L., A.T., J.F., K.M., L.L.W., O.R., P.S., J.C., S.C., S.Y.H.), Boston, Massachusetts
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11
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Gudino N, Littin S. Advancements in Gradient System Performance for Clinical and Research MRI. J Magn Reson Imaging 2023; 57:57-70. [PMID: 36073722 DOI: 10.1002/jmri.28421] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/18/2022] [Accepted: 08/18/2022] [Indexed: 02/03/2023] Open
Abstract
In magnetic resonance imaging (MRI), spatial field gradients are applied along each axis to encode the location of the nuclear spin in the frequency domain. During recent years, the development of new gradient technologies has been focused on the generation of stronger and faster gradient fields for imaging with higher spatial and temporal resolution. This benefits imaging methods, such as brain diffusion and functional MRI, and enables human imaging at ultra-high field MRI. In addition to improving gradient performance, new technologies have been presented to minimize peripheral nerve stimulation and gradient-related acoustic noise, both generated by the rapid switching of strong gradient fields. This review will provide a general background on the gradient system and update on the state-of-the-art gradient technology. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Natalia Gudino
- MRI Engineering Core, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Sebastian Littin
- Medical Physics, Department of Radiology, Faculty of Medicine, University Freiburg, Freiburg, Germany
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12
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Gallo-Bernal S, Bedoya MA, Gee MS, Jaimes C. Pediatric magnetic resonance imaging: faster is better. Pediatr Radiol 2022:10.1007/s00247-022-05529-x. [PMID: 36261512 DOI: 10.1007/s00247-022-05529-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/29/2022] [Accepted: 10/03/2022] [Indexed: 10/24/2022]
Abstract
Magnetic resonance imaging (MRI) has emerged as the preferred imaging modality for evaluating a wide range of pediatric medical conditions. Nevertheless, the long acquisition times associated with this technique can limit its widespread use in young children, resulting in motion-degraded or non-diagnostic studies. As a result, sedation or general anesthesia is often necessary to obtain diagnostic images, which has implications for the safety profile of MRI, the cost of the exam and the radiology department's clinical workflow. Over the last decade, several techniques have been developed to increase the speed of MRI, including parallel imaging, single-shot acquisition, controlled aliasing techniques, compressed sensing and artificial-intelligence-based reconstructions. These are advantageous because shorter examinations decrease the need for sedation and the severity of motion artifacts, increase scanner throughput, and improve system efficiency. In this review we discuss a framework for image acceleration in children that includes the synergistic use of state-of-the-art MRI hardware and optimized pulse sequences. The discussion is framed within the context of pediatric radiology and incorporates the authors' experience in deploying these techniques in routine clinical practice.
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Affiliation(s)
- Sebastian Gallo-Bernal
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - M Alejandra Bedoya
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., 2nd floor, Main Building, Boston, MA, 02115, USA
| | - Michael S Gee
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Camilo Jaimes
- Department of Radiology, Harvard Medical School, Boston, MA, USA. .,Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., 2nd floor, Main Building, Boston, MA, 02115, USA.
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13
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Lang M, Rapalino O, Huang S, Lev MH, Conklin J, Wald LL. Emerging Techniques and Future Directions: Fast and Portable Magnetic Resonance Imaging. Magn Reson Imaging Clin N Am 2022; 30:565-582. [PMID: 35995480 DOI: 10.1016/j.mric.2022.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Fast MRI and portable MRI are emerging as promising technologies to improve the speed, efficiency, and availability of MR imaging. Fast MRI methods are increasingly being adopted to create screening protocols for the diagnosis and management of acute pathology in the emergency department. Faster imaging can facilitate timely diagnosis, reduce motion artifacts, and improve departmental MR operations. Point-of-care and portable MRI are emerging technologies that require radiologists to reenvision the role of MRI as a tool with greater accessibility, fewer siting constraints, and the ability to provide valuable diagnostic information at the bedside. Recently introduced commercially available pulse sequences and new MRI scanners are bringing these technologies closer to the patient's clinical setting, and we expect their use to only increase over the coming decade. This article provides an overview of these emerging technologies for emergency radiologists.
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Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Susie Huang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
| | - Lawrence L Wald
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
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14
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Hobday H, Cole JH, Stanyard RA, Daws RE, Giampietro V, O'Daly O, Leech R, Váša F. Tissue volume estimation and age prediction using rapid structural brain scans. Sci Rep 2022; 12:12005. [PMID: 35835813 PMCID: PMC9283414 DOI: 10.1038/s41598-022-14904-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 06/14/2022] [Indexed: 11/30/2022] Open
Abstract
The multicontrast EPImix sequence generates six contrasts, including a T1-weighted scan, in ~1 min. EPImix shows comparable diagnostic performance to conventional scans under qualitative clinical evaluation, and similarities in simple quantitative measures including contrast intensity. However, EPImix scans have not yet been compared to standard MRI scans using established quantitative measures. In this study, we compared conventional and EPImix-derived T1-weighted scans of 64 healthy participants using tissue volume estimates and predicted brain-age. All scans were pre-processed using the SPM12 DARTEL pipeline, generating measures of grey matter, white matter and cerebrospinal fluid volume. Brain-age was predicted using brainageR, a Gaussian Processes Regression model previously trained on a large sample of standard T1-weighted scans. Estimates of both global and voxel-wise tissue volume showed significantly similar results between standard and EPImix-derived T1-weighted scans. Brain-age estimates from both sequences were significantly correlated, although EPImix T1-weighted scans showed a systematic offset in predictions of chronological age. Supplementary analyses suggest that this is likely caused by the reduced field of view of EPImix scans, and the use of a brain-age model trained using conventional T1-weighted scans. However, this systematic error can be corrected using additional regression of T1-predicted brain-age onto EPImix-predicted brain-age. Finally, retest EPImix scans acquired for 10 participants demonstrated high test-retest reliability in all evaluated quantitative measurements. Quantitative analysis of EPImix scans has potential to reduce scanning time, increasing participant comfort and reducing cost, as well as to support automation of scanning, utilising active learning for faster and individually-tailored (neuro)imaging.
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Affiliation(s)
- Harriet Hobday
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - James H Cole
- Department of Computer Science, Centre for Medical Image Computing, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Ryan A Stanyard
- Department of Forensic and Developmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Richard E Daws
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Vincent Giampietro
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robert Leech
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - František Váša
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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15
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Hwang KP, Fujita S. Synthetic MR: Physical principles, clinical implementation, and new developments. Med Phys 2022; 49:4861-4874. [PMID: 35535442 DOI: 10.1002/mp.15686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 04/05/2022] [Accepted: 04/08/2022] [Indexed: 11/07/2022] Open
Abstract
Current clinical MR imaging practices rely on the qualitative assessment of images for diagnosis and treatment planning. While contrast in MR images is dependent on the spin parameters of the imaged tissue, pixel values on MR images are relative and are not scaled to represent any tissue properties. Synthetic MR is a fully featured imaging workflow consisting of efficient multiparameter mapping acquisition, synthetic image generation, and volume quantitation of brain tissues. As the application becomes more widely available on multiple vendors and scanner platforms, it has also gained widespread adoption as clinicians begin to recognize the benefits of rapid quantitation. This review will provide details about the sequence with a focus on the physical principles behind its relaxometry mechanisms. It will present an overview of the products in their current form and some potential issues when implementing it in the clinic. It will conclude by highlighting some recent advances of the technique, including a 3D mapping method and its associated applications. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, 77030
| | - Shohei Fujita
- Department of Radiology, Graduate School of Medicine, The University of Tokyo.,Department of Radiology, Juntendo University, Tokyo, Japan
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16
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Af Burén S, Kits A, Lönn L, De Luca F, Sprenger T, Skare S, Falk Delgado A. A 78 Seconds Complete Brain MRI Examination in Ischemic Stroke: A Prospective Cohort Study. J Magn Reson Imaging 2022; 56:884-892. [PMID: 35170134 PMCID: PMC9544312 DOI: 10.1002/jmri.28107] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/01/2022] [Accepted: 02/02/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Fast 78-second multicontrast echo-planar MRI (EPIMix) has shown good diagnostic performance for detecting infarctions at a comprehensive stroke center, but its diagnostic performance has not been evaluated in a prospective study at a primary stroke center. PURPOSE To prospectively determine whether EPIMix was noninferior in detecting ischemic lesions compared to routine clinical MRI. STUDY TYPE Prospective cohort study. POPULATION A total of 118 patients with acute MRI and symptoms of ischemic stroke. FIELD STRENGTH AND SEQUENCE A 3 T. EPIMix (echo-planar based: T1-FLAIR, T2-weighted, T2-FLAIR, T2*, DWI) and routine clinical MRI sequences (T1-weighted fast spin echo, T2-weighted PROPELLER, T2-weighted-FLAIR fast spin echo, T2* gradient echo echo-planar, and DWI spin echo echo-planar). ASSESSMENT Three radiologists, blinded for clinical information, assessed signs of ischemic lesions (DWI↑, ADC↓, and T2/T2-FLAIR↑) on EPIMix and routine clinical MRI, with disagreements solved in consensus with a fourth reader to establish the reference standard. STATISTICAL TESTS Diagnostic performance including sensitivity and specificity against the reference standard was evaluated. EPIMix sensitivity was tested for noninferiority compared to the reference standard using Nam's restricted maximum likelihood estimation (RMLE) Score. A P-value < 0.05 was considered statistically significant. RESULTS Of 118 patients (mean age 62 ± 16 years, 58% males), 25% (n = 30) had MRI signs of acute infarcts. EPIMix was noninferior with 97% (95% CI 83-100) sensitivity for reader 1, 100% (95% CI 88-100) sensitivity for reader 2, and 90% (95% CI 88-98) sensitivity for reader 3 vs. 93% (95% CI 78-99) sensitivity for readers 1 and 2 and 90% (95% CI 74-98) for reader 3 on routine clinical MRI. Specificity was 99% (95% CI 94-100) for reader 1, 100% (95% CI 96-100) for reader 2, and 98% (95% CI 92-100) for reader 3 on EPIMix vs. 100% (95% CI 96-100) for all readers on routine clinical MRI. CONCLUSION EPIMix was noninferior to routine clinical MRI for the diagnosis of acute ischemic stroke. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Siri Af Burén
- Department of Radiology, Capio Saint Göran Hospital, Stockholm, Sweden.,Department of Clinical Science, Intervention and Technology, Karolinska Institute, Stockholm, Sweden
| | - Annika Kits
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Lucas Lönn
- Department of Radiology, Capio Saint Göran Hospital, Stockholm, Sweden
| | - Francesca De Luca
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Tim Sprenger
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden.,MR Applied Science Laboratory Europe, GE Healthcare, Stockholm, Sweden
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Falk Delgado
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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17
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Qian E, Poojar P, Vaughan JT, Jin Z, Geethanath S. Tailored Magnetic Resonance Fingerprinting for simultaneous non-synthetic and quantitative imaging: A repeatability study. Med Phys 2022; 49:1673-1685. [PMID: 35084744 DOI: 10.1002/mp.15465] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/25/2021] [Accepted: 12/26/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE The goals of this study include: (a) generating tailored magnetic resonance fingerprinting (TMRF) based non-synthetic imaging; (b) assessing the repeatability of TMRF and deep learning-based mapping of in vitro ISMRM/NIST phantom and in vivo brain data of healthy human subjects. METHODS We have acquired qualitative images obtained from the vendor-supplied gold standard, MRF (synthetic), and TMRF (non-synthetic) on one representative healthy human brain. We also acquired thirty datasets on the ISMRM/NIST phantom for the in vitro repeatability study on a GE Discovery 3T MR750w scanner using the TMRF sequence. We compared T1 and T2 maps generated from thirty ISMRM/NIST phantom datasets to the spin-echo (SE) based gold standard (GS) method as part of the in vitro repeatability study. R-squared coefficient of determination in a simple linear regression and Bland-Altman analysis were computed for thirty datasets of ISMRM/NIST phantom to assess the accuracy of in vitro quantitative TMRF data. The repeatability of T1 and T2 estimates by TMRF was evaluated by calculating the standard deviation (SD) divided by the average of thirty datasets for each sphere, respectively. We acquired ten volunteers for the in vivo repeatability study on the same scanner using the same TMRF sequence. These volunteers were imaged five times with two runs per repetition, resulting in one hundred in vivo datasets. Five contrasts, T1 and T2 maps of ten human volunteers acquired over five repetitions, were evaluated in the in vivo repeatability study. We computed the intraclass correlation coefficient (ICC) of the signal-to-noise ratio (SNR), signal intensities, T1 and T2 relaxation times in white matter (WM) and gray matter (GM). RESULTS The synthetic images generated from MRF show partial volume and flow artifacts compared to non-synthetic images obtained from TMRF images and the gold standard. in vitro studies show that TMRF estimates have less than 5% variations except sphere 14 in the T2 array (6.36%). TMRF and spin-echo relaxometry measurements were strongly correlated; R2 values were 0.9958 and 0.9789 for T1 and T2 estimates, respectively. Based on the ICC values, SNR, mean intensity values, and relaxation times of WM and GM for the in vivo studies were consistent. T1 and T2 values of WM and GM were similar to previously published values. The mean ± SD of T1 and T2 for WM for ten subjects and five repeats are 992 ± 41 ms and 99 ± 6 ms, while the corresponding values for T1 and T2 for GM are 1598 ± 73 ms and 152 ± 14 ms. CONCLUSION TMRF and deep learning-based reconstruction produce repeatable, non-synthetic multi-contrast images and parametric maps simultaneously. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Enlin Qian
- Columbia Magnetic Resonance Research Center, Columbia University, New York, NY, 10027, USA
| | - Pavan Poojar
- Columbia Magnetic Resonance Research Center, Columbia University, New York, NY, 10027, USA
| | - John Thomas Vaughan
- Columbia Magnetic Resonance Research Center, Columbia University, New York, NY, 10027, USA
| | - Zhezhen Jin
- Department of Biostatistics, Columbia University, New York, NY, 10032, USA
| | - Sairam Geethanath
- Columbia Magnetic Resonance Research Center, Columbia University, New York, NY, 10027, USA
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18
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Benzakoun J, Deslys MA, Legrand L, Hmeydia G, Turc G, Hassen WB, Charron S, Debacker C, Naggara O, Baron JC, Thirion B, Oppenheim C. Synthetic FLAIR as a Substitute for FLAIR Sequence in Acute Ischemic Stroke. Radiology 2022; 303:153-159. [PMID: 35014901 DOI: 10.1148/radiol.211394] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Background In acute ischemic stroke (AIS), fluid-attenuated inversion recovery (FLAIR) is used for treatment decisions when onset time is unknown. Synthetic FLAIR could be generated with deep learning from information embedded in diffusion-weighted imaging (DWI) and could replace acquired FLAIR sequence (real FLAIR) and shorten MRI duration. Purpose To compare performance of synthetic and real FLAIR for DWI-FLAIR mismatch estimation and identification of patients presenting within 4.5 hours from symptom onset. Materials and Methods In this retrospective study, all pretreatment and early follow-up (<48 hours after symptom onset) MRI data sets including DWI (b = 0-1000 sec/mm2) and FLAIR sequences obtained in consecutive patients with AIS referred for reperfusion therapies between January 2002 and May 2019 were included. On the training set (80%), a generative adversarial network was trained to produce synthetic FLAIR with DWI as input. On the test set (20%), synthetic FLAIR was computed without real FLAIR knowledge. The DWI-FLAIR mismatch was evaluated on both FLAIR data sets by four independent readers. Interobserver reproducibility and DWI-FLAIR mismatch concordance between synthetic and real FLAIR were evaluated with κ statistics. Sensitivity and specificity for identification of AIS within 4.5 hours were compared in patients with known onset time by using McNemar test. Results The study included 1416 MRI scans (861 patients; median age, 71 years [interquartile range, 57-81 years]; 375 men), yielding 1134 and 282 scans for training and test sets, respectively. Regarding DWI-FLAIR mismatch, interobserver reproducibility was substantial for real and synthetic FLAIR (κ = 0.80 [95% CI: 0.74, 0.87] and 0.80 [95% CI: 0.74, 0.87], respectively). After consensus, concordance between real and synthetic FLAIR was almost perfect (κ = 0.88; 95% CI: 0.82, 0.93). Diagnostic value for identifying AIS within 4.5 hours did not differ between real and synthetic FLAIR (sensitivity: 107 of 131 [82%] vs 111 of 131 [85%], P = .2; specificity: 96 of 104 [92%] vs 96 of 104 [92%], respectively, P > .99). Conclusion Synthetic fluid-attenuated inversion recovery (FLAIR) had diagnostic performances similar to real FLAIR in depicting diffusion-weighted imaging-FLAIR mismatch and in helping to identify early acute ischemic stroke, and it may accelerate MRI protocols. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Carroll and Hurley in this issue.
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Affiliation(s)
- Joseph Benzakoun
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Marc-Antoine Deslys
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Laurence Legrand
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Ghazi Hmeydia
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Guillaume Turc
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Wagih Ben Hassen
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Sylvain Charron
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Clément Debacker
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Olivier Naggara
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Jean-Claude Baron
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Bertrand Thirion
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
| | - Catherine Oppenheim
- From the Departments of Neuroradiology (J.B., L.L., G.H., W.B.H., O.N., C.O.) and Neurology (G.T., J.C.B.), GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, 1 rue Cabanis, 75014 Paris, France; INSERM U1266, Paris, France (J.B., M.A.D., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); Université de Paris, FHU Neurovasc, Paris, France (J.B., L.L., G.T., W.B.H., S.C., C.D., O.N., J.C.B., C.O.); and PARIETAL Team, INRIA, Saclay, France (B.T.)
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19
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Demir S, Clifford B, Lo WC, Tabari A, Goncalves Filho ALM, Lang M, Cauley SF, Setsompop K, Bilgic B, Lev MH, Schaefer PW, Rapalino O, Huang SY, Hilbert T, Feiweier T, Conklin J. Optimization of magnetization transfer contrast for EPI FLAIR brain imaging. Magn Reson Med 2022; 87:2380-2387. [PMID: 34985151 PMCID: PMC8847235 DOI: 10.1002/mrm.29141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/10/2021] [Accepted: 12/11/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE To evaluate the impact of magnetization transfer (MT) on brain tissue contrast in turbo-spin-echo (TSE) and EPI fluid-attenuated inversion recovery (FLAIR) images, and to optimize an MT-prepared EPI FLAIR pulse sequence to match the tissue contrast of a clinical reference TSE FLAIR protocol. METHODS Five healthy volunteers underwent 3T brain MRI, including single slice TSE FLAIR, multi-slice TSE FLAIR, EPI FLAIR without MT-preparation, and MT-prepared EPI FLAIR with variations of the MT-preparation parameters, including number of preparation pulses, pulse amplitude, and resonance offset. Automated co-registration and gray matter (GM) versus white matter (WM) segmentation was performed using a T1-MPRAGE acquisition, and the GM versus WM signal intensity ratio (contrast ratio) was calculated for each FLAIR acquisition. RESULTS Without MT preparation, EPI FLAIR showed poor tissue contrast (contrast ratio = 0.98), as did single slice TSE FLAIR. Multi-slice TSE FLAIR provided high tissue contrast (contrast ratio = 1.14). MT-prepared EPI FLAIR closely approximated the contrast of the multi-slice TSE FLAIR images for two combinations of the MT-preparation parameters (contrast ratio = 1.14). Optimized MT-prepared EPI FLAIR provided a 50% reduction in scan time compared to the reference TSE FLAIR acquisition. CONCLUSION Optimized MT-prepared EPI FLAIR provides comparable brain tissue contrast to the multi-slice TSE FLAIR images used in clinical practice.
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Affiliation(s)
- Serdest Demir
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Bryan Clifford
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Wei-Ching Lo
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Min Lang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Stephen F Cauley
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Berkin Bilgic
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
| | | | | | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
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20
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Henry D, Fulton R, Maclaren J, Aksoy M, Bammer R, Kyme A. Optimizing a Feature-Based Motion Tracking System for Prospective Head Motion Estimation in MRI and PET/MRI. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022. [DOI: 10.1109/trpms.2021.3063260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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21
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Polak D, Splitthoff DN, Clifford B, Lo WC, Huang SY, Conklin J, Wald LL, Setsompop K, Cauley S. Scout accelerated motion estimation and reduction (SAMER). Magn Reson Med 2022; 87:163-178. [PMID: 34390505 PMCID: PMC8616778 DOI: 10.1002/mrm.28971] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 06/29/2021] [Accepted: 07/26/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE To demonstrate a navigator/tracking-free retrospective motion estimation technique that facilitates clinically acceptable reconstruction time. METHODS Scout accelerated motion estimation and reduction (SAMER) uses a single 3-5 s, low-resolution scout scan and a novel sequence reordering to independently determine motion states by minimizing the data-consistency error in a SENSE plus motion forward model. This eliminates time-consuming alternating optimization as no updates to the imaging volume are required during the motion estimation. The SAMER approach was assessed quantitatively through extensive simulation and was evaluated in vivo across multiple motion scenarios and clinical imaging contrasts. Finally, SAMER was synergistically combined with advanced encoding (Wave-CAIPI) to facilitate rapid motion-free imaging. RESULTS The highly accelerated scout provided sufficient information to achieve accurate motion trajectory estimation (accuracy ~0.2 mm or degrees). The novel sequence reordering improved the stability of the motion parameter estimation and image reconstruction while preserving the clinical imaging contrast. Clinically acceptable computation times for the motion estimation (~4 s/shot) are demonstrated through a fully separable (non-alternating) motion search across the shots. Substantial artifact reduction was demonstrated in vivo as well as corresponding improvement in the quantitative error metric. Finally, the extension of SAMER to Wave-encoding enabled rapid high-quality imaging at up to R = 9-fold acceleration. CONCLUSION SAMER significantly improved the computational scalability for retrospective motion estimation and correction.
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Affiliation(s)
- Daniel Polak
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Siemens Healthcare GmbH, Erlangen, Germany
| | | | | | | | - Susie Y. Huang
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, 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
| | - John Conklin
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Lawrence L. Wald
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, 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
- Department of Radiology, Stanford School of Medicine, Stanford, California, USA
| | - Stephen Cauley
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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22
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Clifford B, Conklin J, Huang SY, Feiweier T, Hosseini Z, Goncalves Filho ALM, Tabari A, Demir S, Lo WC, Longo MGF, Lev M, Schaefer P, Rapalino O, Setsompop K, Bilgic B, Cauley S. An artificial intelligence-accelerated 2-minute multi-shot echo planar imaging protocol for comprehensive high-quality clinical brain imaging. Magn Reson Med 2021; 87:2453-2463. [PMID: 34971463 DOI: 10.1002/mrm.29117] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 10/29/2021] [Accepted: 11/22/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE We introduce and validate an artificial intelligence (AI)-accelerated multi-shot echo-planar imaging (msEPI)-based method that provides T1w, T2w, T 2 ∗ , T2-FLAIR, and DWI images with high SNR, high tissue contrast, low specific absorption rates (SAR), and minimal distortion in 2 minutes. METHODS The rapid imaging technique combines a novel machine learning (ML) scheme to limit g-factor noise amplification and improve SNR, a magnetization transfer preparation module to provide clinically desirable contrast, and high per-shot EPI undersampling factors to reduce distortion. The ML training and image reconstruction incorporates a tunable parameter for controlling the level of denoising/smoothness. The performance of the reconstruction method is evaluated across various acceleration factors, contrasts, and SNR conditions. The 2-minute protocol is directly compared to a 10-minute clinical reference protocol through deployment in a clinical setting, where five representative cases with pathology are examined. RESULTS Optimization of custom msEPI sequences and protocols was performed to balance acquisition efficiency and image quality compared to the five-fold longer clinical reference. Training data from 16 healthy subjects across multiple contrasts and orientations were used to produce ML networks at various acceleration levels. The flexibility of the ML reconstruction was demonstrated across SNR levels, and an optimized regularization was determined through radiological review. Network generalization toward novel pathology, unobserved during training, was illustrated in five clinical case studies with clinical reference images provided for comparison. CONCLUSION The rapid 2-minute msEPI-based protocol with tunable ML reconstruction allows for advantageous trade-offs between acquisition speed, SNR, and tissue contrast when compared to the five-fold slower standard clinical reference exam.
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Affiliation(s)
- Bryan Clifford
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | | | | | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Serdest Demir
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Wei-Ching Lo
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | | | - Michael Lev
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Pam Schaefer
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology and Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Berkin Bilgic
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephen Cauley
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Váša F, Hobday H, Stanyard RA, Daws RE, Giampietro V, O'Daly O, Lythgoe DJ, Seidlitz J, Skare S, Williams SCR, Marquand AF, Leech R, Cole JH. Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging. Hum Brain Mapp 2021; 43:1749-1765. [PMID: 34953014 PMCID: PMC8886661 DOI: 10.1002/hbm.25755] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 11/02/2021] [Accepted: 11/21/2021] [Indexed: 12/17/2022] Open
Abstract
Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1 -weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1 -FLAIR, T2 , T2 *, T2 -FLAIR, DWI and ADC contrasts, acquired in ~1 min), as well as to slower, more standard single-contrast T1 -weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix T1 -FLAIR and single-contrast T1 -weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test-retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients.
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Affiliation(s)
- František Váša
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Harriet Hobday
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ryan A Stanyard
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Forensic & Developmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Richard E Daws
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK
| | - Vincent Giampietro
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Stefan Skare
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Steven C R Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andre F Marquand
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands.,Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Robert Leech
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - James H Cole
- Department of Computer Science, Centre for Medical Image Computing, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
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24
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Sprenger T, Kits A, Norbeck O, van Niekerk A, Berglund J, Rydén H, Avventi E, Skare S. NeuroMix-A single-scan brain exam. Magn Reson Med 2021; 87:2178-2193. [PMID: 34904751 DOI: 10.1002/mrm.29120] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 01/15/2023]
Abstract
PURPOSE Implement a fast, motion-robust pulse sequence that acquires T1 -weighted, T2 -weighted, T2 * -weighted, T2 fluid-attenuated inversion recovery, and DWI data in one run with only one prescription and one prescan. METHODS A software framework was developed that configures and runs several sequences in one main sequence. Based on that framework, the NeuroMix sequence was implemented, containing motion robust single-shot sequences using EPI and fast spin echo (FSE) readouts (without EPI distortions). Optional multi-shot sequences that provide better contrast, higher resolution, or isotropic resolution could also be run within the NeuroMix sequence. An optimized acquisition order was implemented that minimizes times where no data is acquired. RESULTS NeuroMix is customizable and takes between 1:20 and 4 min for a full brain scan. A comparison with the predecessor EPIMix revealed significant improvements for T2 -weighted and T2 fluid-attenuated inversion recovery, while taking only 8 s longer for a similar configuration. The optional contrasts were less motion robust but offered a significant increase in quality, detail, and contrast. Initial clinical scans on 1 pediatric and 1 adult patient showed encouraging image quality. CONCLUSION The single-shot FSE readouts for T2 -weighted and T2 fluid-attenuated inversion recovery and the optional multishot FSE and 3D-EPI contrasts significantly increased diagnostic value compared with EPIMix, allowing NeuroMix to be considered as a standalone brain MRI application.
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Affiliation(s)
- Tim Sprenger
- MR Applied Science Laboratory Europe, GE Healthcare, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Annika Kits
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Ola Norbeck
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Adam van Niekerk
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Berglund
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Henric Rydén
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Enrico Avventi
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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25
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Ji S, Jeong J, Oh SH, Nam Y, Choi SH, Shin HG, Shin D, Jung W, Lee J. Quad-Contrast Imaging: Simultaneous Acquisition of Four Contrast-Weighted Images (PD-Weighted, T₂-Weighted, PD-FLAIR and T₂-FLAIR Images) With Synthetic T₁-Weighted Image, T₁- and T₂-Maps. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3617-3626. [PMID: 34191724 DOI: 10.1109/tmi.2021.3093617] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Magnetic resonance imaging (MRI) can provide multiple contrast-weighted images using different pulse sequences and protocols. However, a long acquisition time of the images is a major challenge. To address this limitation, a new pulse sequence referred to as quad-contrast imaging is presented. The quad-contrast sequence enables the simultaneous acquisition of four contrast-weighted images (proton density (PD)-weighted, T2-weighted, PD-fluid attenuated inversion recovery (FLAIR), and T2-FLAIR), and the synthesis of T1-weighted images and T1- and T2-maps in a single scan. The scan time is less than 6 min and is further reduced to 2 min 50 s using a deep learning-based parallel imaging reconstruction. The natively acquired quad contrasts demonstrate high quality images, comparable to those from the conventional scans. The deep learning-based reconstruction successfully reconstructed highly accelerated data (acceleration factor 6), reporting smaller normalized root mean squared errors (NRMSEs) and higher structural similarities (SSIMs) than those from conventional generalized autocalibrating partially parallel acquisitions (GRAPPA)-reconstruction (mean NRMSE of 4.36% vs. 10.54% and mean SSIM of 0.990 vs. 0.953). In particular, the FLAIR contrast is natively acquired and does not suffer from lesion-like artifacts at the boundary of tissue and cerebrospinal fluid, differentiating the proposed method from synthetic imaging methods. The quad-contrast imaging method may have the potentials to be used in a clinical routine as a rapid diagnostic tool.
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26
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Manhard MK, Stockmann J, Liao C, Park D, Han S, Fair M, van den Boomen M, Polimeni J, Bilgic B, Setsompop K. A multi-inversion multi-echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts. Magn Reson Med 2021; 86:866-880. [PMID: 33764563 PMCID: PMC8793364 DOI: 10.1002/mrm.28761] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 02/02/2021] [Accepted: 02/12/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE Brain imaging exams typically take 10-20 min and involve multiple sequential acquisitions. A low-distortion whole-brain echo planar imaging (EPI)-based approach was developed to efficiently encode multiple contrasts in one acquisition, allowing for calculation of quantitative parameter maps and synthetic contrast-weighted images. METHODS Inversion prepared spin- and gradient-echo EPI was developed with slice-order shuffling across measurements for efficient acquisition with T1 , T2 , and T 2 ∗ weighting. A dictionary-matching approach was used to fit the images to quantitative parameter maps, which in turn were used to create synthetic weighted images with typical clinical contrasts. Dynamic slice-optimized multi-coil shimming with a B0 shim array was used to reduce B0 inhomogeneity and, therefore, image distortion by >50%. Multi-shot EPI was also implemented to minimize distortion and blurring while enabling high in-plane resolution. A low-rank reconstruction approach was used to mitigate errors from shot-to-shot phase variation. RESULTS The slice-optimized shimming approach was combined with in-plane parallel-imaging acceleration of 4× to enable single-shot EPI with more than eight-fold distortion reduction. The proposed sequence efficiently obtained 40 contrasts across the whole-brain in just over 1 min at 1.2 × 1.2 × 3 mm resolution. The multi-shot variant of the sequence achieved higher in-plane resolution of 1 × 1 × 4 mm with good image quality in 4 min. Derived quantitative maps showed comparable values to conventional mapping methods. CONCLUSION The approach allows fast whole-brain imaging with quantitative parameter maps and synthetic weighted contrasts. The slice-optimized multi-coil shimming and multi-shot reconstruction approaches result in minimal EPI distortion, giving the sequence the potential to be used in rapid screening applications.
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Affiliation(s)
- Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jason Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Daniel Park
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Sohyun Han
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of
| | - Merlin Fair
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maaike van den Boomen
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Jon Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
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27
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Kits A, De Luca F, Kolloch J, Müller S, Mazya MV, Skare S, Falk Delgado A. One-Minute Multi-contrast Echo Planar Brain MRI in Ischemic Stroke: A Retrospective Observational Study of Diagnostic Performance. J Magn Reson Imaging 2021; 54:1088-1095. [PMID: 33942426 DOI: 10.1002/jmri.27641] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/27/2021] [Accepted: 03/31/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Fast multi-contrast echo planar MRI (EPIMix) has comparable diagnostic performance to standard MRI for detecting brain pathology but its performance in detecting acute cerebral infarctions has not been determined. PURPOSE To assess the diagnostic performance of EPIMix for the detection of acute cerebral infarctions. STUDY TYPE Retrospective observational cohort. POPULATION One hundred and seventy-two consecutive patients with a clinical suspicion of non-hyperacute ischemic stroke (January 2018 to December 2019). FIELD STRENGTH AND SEQUENCE 1.5 T or 3 T. EPIMix ((echo-planar based: diffusion weighted (DWI), T2*-weighted, T2-weighted, T2- and T1-fluid attenuated inversion recovery (FLAIR) images) vs. standard MRI: echo-planar DWI, echo-planar T2*-weighted or susceptibility weighted, turbo spin-echo T2-weighted, T2- and T1-FLAIR turbo spin-echo sequences. ASSESSMENT Three neuroradiologists rated EPIMix and standard MRI on two separate occasions. Incongruent assessments were resolved in consensus with the fourth reader. The ratings included the diagnostic category (acute infarct, normal, and other pathology). Congruent diagnoses together with consensus diagnoses served as the reference standard. STATISTICAL TESTS The diagnostic performance of EPIMix and standard MRI against the reference standard was calculated by the area under the receiver operating characteristic curve (AUC) and compared by DeLong's test. Sensitivity and specificity were determined. Inter-rater agreements were evaluated by Fleiss's kappa. RESULTS Of 172 patients (61 ± 16 years, 103 men), acute infarcts were present in 80/172 (47%), normal findings in 60/172 (35%), and other pathology in 32/172 (19%). Across readers, the AUCs were .94-.95 for EPIMix and .95-.99 for standard MRI, with overlapping 95% CI (P = .02-.18). Inter-rater agreement for EPIMix was 0.90 and for standard MRI was 0.93. The sensitivity for EPIMix and standard MRI was 88-91% and 91-98%, respectively, while the specificity was 98-100% and 98-99%, both with overlapping 95% CI. CONCLUSION Multi-contrast echo planar MRI showed a high but marginally lower diagnostic performance compared to standard MRI for the detection and characterization of acute brain infarct. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Annika Kits
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Francesca De Luca
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Jens Kolloch
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Susanne Müller
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Michael V Mazya
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Falk Delgado
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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28
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Kubota Y, Yokota H, Sakai T, Yoneyama M, Ohira K, Uno T. Clinical feasibility of single-shot fluid-attenuated inversion recovery with wide inversion recovery pulse designed to reduce cerebrospinal fluid and motion artifacts for evaluation of uncooperative patients in acute stroke protocol. J Magn Reson Imaging 2020; 53:1833-1838. [PMID: 33368729 DOI: 10.1002/jmri.27483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 12/08/2020] [Accepted: 12/10/2020] [Indexed: 11/06/2022] Open
Abstract
Fluid-attenuated inversion recovery (FLAIR) imaging is a key sequence for stroke assessment. Motion artifact reduction with short acquisition time is still challenging, but necessary in the magnetic resonance (MR) stroke protocol, especially for uncooperative patients suspected of stroke. The aim of this study is to investigate the feasibility of modified single-shot FLAIR with wide inversion recovery pulses for use in stroke patients. This is a prospective study, which included 30 patients clinically suspected of stroke who were examined by MR stroke protocol from January 2018 to September 2018. A 1.5 T, multi-shot-turbo spin-echo (TSE) conventional FLAIR, and single-shot-TSE-FLAIR with wide inversion recovery pulse were used. Modified single-shot FLAIR was obtained for 30 patients with suspected stroke who moved during conventional FLAIR scan. Motion artifacts were randomly and independently scored using a 5-grade scale by three radiologists in blinded fashion. Whether the FLAIR vessel hyperintensity sign was present was visually evaluated. Statistical tests included Wilcoxon-signed rank test and weighted Cohen's kappa statistics. The motion artifact score was significantly lower in single-shot FLAIR than in conventional FLAIR (0.37 ± 0.56 vs. 1.83 ± 1.18; p < 0.05. The vessel hyperintensity sign was visualized in 6 and 5 patients on single-shot and conventional FLAIR images, respectively. This study demonstrates the value of single-shot FLAIR for stroke assessment. Single-shot FLAIR reduced motion artifact and visualized vessel hyperintensity sign more than conventional FLAIR. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Yoshihiro Kubota
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Hajime Yokota
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Takayuki Sakai
- Department of Radiology, Eastern Chiba Medical Center, Chiba, Japan
| | | | - Kenji Ohira
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Takashi Uno
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
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29
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Berglund J, van Niekerk A, Rydén H, Sprenger T, Avventi E, Norbeck O, Glimberg SL, Olesen OV, Skare S. Prospective motion correction for diffusion weighted EPI of the brain using an optical markerless tracker. Magn Reson Med 2020; 85:1427-1440. [PMID: 32989859 PMCID: PMC7756594 DOI: 10.1002/mrm.28524] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 07/31/2020] [Accepted: 08/28/2020] [Indexed: 01/25/2023]
Abstract
PURPOSE To enable motion-robust diffusion weighted imaging of the brain using well-established imaging techniques. METHODS An optical markerless tracking system was used to estimate and correct for rigid body motion of the head in real time during scanning. The imaging coordinate system was updated before each excitation pulse in a single-shot EPI sequence accelerated by GRAPPA with motion-robust calibration. Full Fourier imaging was used to reduce effects of motion during diffusion encoding. Subjects were imaged while performing prescribed motion patterns, each repeated with prospective motion correction on and off. RESULTS Prospective motion correction with dynamic ghost correction enabled high quality DWI in the presence of fast and continuous motion within a 10° range. Images acquired without motion were not degraded by the prospective correction. Calculated diffusion tensors tolerated the motion well, but ADC values were slightly increased. CONCLUSIONS Prospective correction by markerless optical tracking minimizes patient interaction and appears to be well suited for EPI-based DWI of patient groups unable to remain still including those who are not compliant with markers.
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Affiliation(s)
- Johan Berglund
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Adam van Niekerk
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Henric Rydén
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Tim Sprenger
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,MR Applied Science Laboratory, GE Healthcare, Stockholm, Sweden
| | - Enrico Avventi
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Ola Norbeck
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | | | | | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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30
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Lanzman BA, Huang Y, Lee EH, Iv M, Moseley ME, Holdsworth SJ, Yeom KW. Simultaneous time of flight-MRA and T2* imaging for cerebrovascular MRI. Neuroradiology 2020; 63:243-251. [PMID: 32945913 DOI: 10.1007/s00234-020-02499-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Accepted: 07/13/2020] [Indexed: 11/25/2022]
Abstract
PURPOSE 3D multi-echo gradient-recalled echo (ME-GRE) can simultaneously generate time-of-flight magnetic resonance angiography (pTOF) in addition to T2*-based susceptibility-weighted images (SWI). We assessed the clinical performance of pTOF generated from a 3D ME-GRE acquisition compared with conventional TOF-MRA (cTOF). METHODS Eighty consecutive children were retrospectively identified who obtained 3D ME-GRE alongside cTOF. Two blinded readers independently assessed pTOF derived from 3D ME-GRE and compared them with cTOF. A 5-point Likert scale was used to rank lesion conspicuity and to assess for diagnostic confidence. RESULTS Across 80 pediatric neurovascular pathologies, a similar number of lesions were reported on pTOF and cTOF (43-40%, respectively, p > 0.05). Rating of lesion conspicuity was higher with cTOF (4.5 ± 1.0) as compared with pTOF (4.0 ± 0.7), but this was not significantly different (p = 0.06). Diagnostic confidence was rated higher with cTOF (4.8 ± 0.5) than that of pTOF (3.7 ± 0.6; p < 0.001). Overall, the inter-rater agreement between two readers for lesion count on pTOF was classified as almost perfect (κ = 0.98, 96% CI 0.8-1.0). CONCLUSIONS In this study, TOF-MRA simultaneously generated in addition to SWI from 3D MR-GRE can serve as a diagnostic adjunct, particularly for proximal vessel disease and when conventional TOF-MRA images are absent.
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Affiliation(s)
- Bryan A Lanzman
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Yuhao Huang
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Edward H Lee
- Department of Radiology, Stanford University, Stanford, CA, USA.,Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Michael Iv
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Samantha J Holdsworth
- Mātai Medical Research Institute, Gisborne-Tairāwhiti, Gisborne, New Zealand.,Department of Anatomy and Medical Imaging & Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Kristen W Yeom
- Department of Radiology, Stanford University, Stanford, CA, USA. .,Lucile Packard Children's Hospital, Palo Alto, CA, USA.
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31
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Stirnberg R, Stöcker T. Segmented K-space blipped-controlled aliasing in parallel imaging for high spatiotemporal resolution EPI. Magn Reson Med 2020; 85:1540-1551. [PMID: 32936488 DOI: 10.1002/mrm.28486] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/29/2020] [Accepted: 07/30/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE A segmented k-space blipped-controlled aliasing in parallel imaging (skipped-CAIPI) sampling strategy for EPI is proposed, which allows for a flexible choice of EPI factor and phase encode bandwidth independent of the controlled aliasing in parallel imaging (CAIPI) sampling pattern. THEORY AND METHODS With previously proposed approaches, exactly two EPI trajectories were possible given a specific CAIPI pattern, either with slice gradient blips (blipped-CAIPI) or following a shot-selective CAIPI approach (higher resolution). Recently, interleaved multi-shot segmentation along shot-selective CAIPI trajectories has been applied for high-resolution anatomical imaging. For more flexibility and a broader range of applications, we propose segmentation along any blipped-CAIPI trajectory. Thus, all EPI factors and phase encode bandwidths available with traditional segmented EPI can be combined with controlled aliasing. RESULTS Temporal SNR maps of moderate-to-high-resolution time series acquisitions at varying undersampling factors demonstrate beneficial sampling alternatives to blipped-CAIPI or shot-selective CAIPI. Rapid high-resolution scans furthermore demonstrate SNR-efficient and motion-robust structural imaging with almost arbitrary EPI factor and minimal noise penalty. CONCLUSION Skipped-CAIPI sampling increases protocol flexibility for high spatiotemporal resolution EPI. In terms of SNR and efficiency, high-resolution functional or structural scans benefit vastly from a free choice of the CAIPI pattern. Even at moderate resolutions, the independence of sampling pattern, TE, and image matrix size is valuable for optimized functional protocol design. Although demonstrated with 3D-EPI, skipped-CAIPI is also applicable with simultaneous multislice EPI.
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Affiliation(s)
| | - Tony Stöcker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
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32
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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] [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.
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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
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33
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One-Minute Ultrafast Brain MRI With Full Basic Sequences: Can It Be a Promising Way Forward for Pediatric Neuroimaging? AJR Am J Roentgenol 2020; 215:198-205. [PMID: 32255685 DOI: 10.2214/ajr.19.22378] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVE. The long scan time of brain MRI is a major drawback that limits its clinical use for evaluating pediatric patients who are inherently prone to motion and frequently require sedatives. This study investigated the clinical feasibility of a 1-minute ultrafast brain MRI protocol in pediatric patients by assessing its image quality in comparison with that of routine brain MRI. MATERIALS AND METHODS. Twenty-three patients were enrolled who underwent 1-minute ultrafast MRI and routine brain MRI protocols including five essential sequences (T1-weighted imaging, T2-weighted imaging, DWI, FLAIR, and T2*-weighted imaging). Total scan time for the same image contrast levels was 1 minute 11 seconds for ultrafast MRI versus 9 minutes 51 seconds for routine brain MRI. Two readers independently reviewed all images from the two MRI protocols and graded the image quality on a 4-point Likert scale. The Wilcoxon signed rank test was used to compare the readers' ratings; interobserver agreement between the readers was also assessed. RESULTS. Although the mean scores of overall image quality and anatomic delineation in ultrafast brain MR images were significantly lower than those in routine brain MR images, ultrafast brain MRI showed sufficient overall image quality and anatomic delineation with more than 2 points on the 4-point scale. CONCLUSION. The 1-minute ultrafast brain MRI protocol showed at least sufficient image quality compared with routine brain MRI. Therefore, 1-minute ultrafast brain MRI can be a viable first-line neuroimaging study for pediatric patients because of its shorter scan time, absence of radiation hazard, and reduced sedation requirements.
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Norbeck O, Sprenger T, Avventi E, Rydén H, Kits A, Berglund J, Skare S. Optimizing 3D EPI for rapid T
1
‐weighted imaging. Magn Reson Med 2020; 84:1441-1455. [DOI: 10.1002/mrm.28222] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 01/14/2020] [Accepted: 01/29/2020] [Indexed: 01/17/2023]
Affiliation(s)
- Ola Norbeck
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Tim Sprenger
- MR Applied Science Laboratory Europe, GE Healthcare Stockholm Sweden
| | - Enrico Avventi
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Henric Rydén
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Annika Kits
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Johan Berglund
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Stefan Skare
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
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Ryu KH, Baek HJ, Skare S, Moon JI, Choi BH, Park SE, Ha JY, Kim TB, Hwang MJ, Sprenger T. Clinical Experience of 1-Minute Brain MRI Using a Multicontrast EPI Sequence in a Different Scan Environment. AJNR Am J Neuroradiol 2020; 41:424-429. [PMID: 32029473 DOI: 10.3174/ajnr.a6427] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 01/02/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND PURPOSE The long scan time of MR imaging is a major drawback limiting its clinical use in neuroimaging; therefore, we aimed to investigate the clinical feasibility of a 1-minute full-brain MR imaging using a multicontrast EPI sequence on a different MR imaging scanner than the ones previously reported. MATERIALS AND METHODS We retrospectively reviewed the records of 146 patients who underwent a multicontrast EPI sequence, including T1-FLAIR, T2-FLAIR, T2WI, DWI, and T2*WI sequences. Two attending neuroradiologists assessed the image quality of each sequence to compare the multicontrast EPI sequence with routine MR imaging protocols. We used the Wilcoxon signed rank test and McNemar test to compare the 2 MR imaging protocols. RESULTS The multicontrast EPI sequence generally showed sufficient image quality of >2 points using a 4-point assessment scale. Regarding image quality and susceptibility artifacts, there was no significant difference between the multicontrast EPI sequence DWI and routine DWI (P > .05), attesting to noninferiority of the multicontrast EPI, whereas there were significant differences in the other 4 sequences between the 2 MR imaging protocols. CONCLUSIONS The multicontrast EPI sequence showed sufficient image quality for clinical use with a shorter scan time; however, it was limited by inferior image quality and frequent susceptibility artifacts compared with routine brain MR imaging. Therefore, the multicontrast EPI sequence cannot completely replace the routine MR imaging protocol at present; however, it may be a feasible option in specific clinical situations such as screening, time-critical diseases or for use with patients prone to motion.
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Affiliation(s)
- K H Ryu
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - H J Baek
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea .,Department of Radiology (H.J.B.), Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju, Republic of Korea
| | - S Skare
- Department of Clinical Neuroscience (S.S., T.S.), Karolinska Institute, Stockholm, Sweden.,Department of Neuroradiology (S.S.), Karolinska University Hospital, Stockholm, Sweden
| | - J I Moon
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - B H Choi
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - S E Park
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - J Y Ha
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - T B Kim
- From the Department of Radiology (K.H.R., H.J.B., J.I.M., B.H.C., S.E.P., J.Y.H., T.B.K.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - M J Hwang
- MR Applications and Workflow, GE Healthcare (M.J.H.), Seoul, Republic of Korea
| | - T Sprenger
- Department of Clinical Neuroscience (S.S., T.S.), Karolinska Institute, Stockholm, Sweden.,MR Applied Science Laboratory Europe (T.S.), GE Healthcare Stockholm, Sweden
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Bilgic B, Chatnuntawech I, Manhard MK, Tian Q, Liao C, Iyer SS, Cauley SF, Huang SY, Polimeni JR, Wald LL, Setsompop K. Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction. Magn Reson Med 2019; 82:1343-1358. [PMID: 31106902 PMCID: PMC6626584 DOI: 10.1002/mrm.27813] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 04/22/2019] [Accepted: 04/22/2019] [Indexed: 12/13/2022]
Abstract
PURPOSE To introduce a combined machine learning (ML)- and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI) and demonstrate its application in high-resolution structural and diffusion imaging. METHODS Single-shot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging because of severe distortion artifacts and blurring. Although msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image. We utilize deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase variations attributed to shot-to-shot changes. These variations are then included in a joint virtual coil sensitivity encoding (JVC-SENSE) reconstruction to utilize data from all shots and improve upon the ML solution. RESULTS Our combined ML + physics approach enabled Rinplane × multiband (MB) = 8- × 2-fold acceleration using 2 EPI shots for multiecho imaging, so that whole-brain T2 and T2 * parameter maps could be derived from an 8.3-second acquisition at 1 × 1 × 3-mm3 resolution. This has also allowed high-resolution diffusion imaging with high geometrical fidelity using 5 shots at Rinplane × MB = 9- × 2-fold acceleration. To make these possible, we extended the state-of-the-art MUSSELS reconstruction technique to simultaneous multislice encoding and used it as an input to our ML network. CONCLUSION Combination of ML and JVC-SENSE enabled navigator-free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end-to-end ML approaches.
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Affiliation(s)
- Berkin Bilgic
- 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
| | - Itthi Chatnuntawech
- National Nanotechnology Center, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Siddharth S. Iyer
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stephen F. Cauley
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Susie Y. Huang
- 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
| | - Jonathan R. Polimeni
- 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
| | - 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
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Cole JH, Lorenz R, Geranmayeh F, Wood T, Hellyer P, Williams S, Turkheimer F, Leech R. Active Acquisition for multimodal neuroimaging. Wellcome Open Res 2019; 3:145. [PMID: 31667357 PMCID: PMC6807153 DOI: 10.12688/wellcomeopenres.14918.2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2019] [Indexed: 02/02/2023] Open
Abstract
In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field -of -view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.
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Affiliation(s)
- James H. Cole
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Romy Lorenz
- MRC Centre for Cognition and Brain Sciences, University of Cambridge, Cambridge, UK
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Fatemeh Geranmayeh
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Tobias Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Peter Hellyer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Steven Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Rob Leech
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
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Polak D, Cauley S, Huang SY, Longo MG, Conklin J, Bilgic B, Ohringer N, Raithel E, Bachert P, Wald LL, Setsompop K. Highly-accelerated volumetric brain examination using optimized wave-CAIPI encoding. J Magn Reson Imaging 2019; 50:961-974. [PMID: 30734388 PMCID: PMC6687581 DOI: 10.1002/jmri.26678] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 01/17/2019] [Accepted: 01/17/2019] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Rapid volumetric imaging protocols could better utilize limited scanner resources. PURPOSE To develop and validate an optimized 6-minute high-resolution volumetric brain MRI examination using Wave-CAIPI encoding. STUDY TYPE Prospective. POPULATION/SUBJECTS Ten healthy subjects and 20 patients with a variety of intracranial pathologies. FIELD STRENGTH/SEQUENCE At 3 T, MPRAGE, T2 -weighted SPACE, SPACE FLAIR, and SWI were acquired at 9-fold acceleration using Wave-CAIPI and for comparison at 2-4-fold acceleration using conventional GRAPPA. ASSESSMENT Extensive simulations were performed to optimize the Wave-CAIPI protocol and minimize both g-factor noise amplification and potential T1 /T2 blurring artifacts. Moreover, refinements in the autocalibrated reconstruction of Wave-CAIPI were developed to ensure high-quality reconstructions in the presence of gradient imperfections. In a randomized and blinded fashion, three neuroradiologists assessed the diagnostic quality of the optimized 6-minute Wave-CAIPI exam and compared it to the roughly 3× slower GRAPPA accelerated protocol using both an individual and head-to-head analysis. STATISTICAL TEST A noninferiority test was used to test whether the diagnostic quality of Wave-CAIPI was noninferior to the GRAPPA acquisition, with a 15% noninferiority margin. RESULTS Among all sequences, Wave-CAIPI achieved negligible g-factor noise amplification (gavg ≤ 1.04) and burring artifacts from T1 /T2 relaxation. Improvements of our autocalibration approach for gradient imperfections enabled increased robustness to gradient mixing imperfections in tilted-field of view (FOV) prescriptions as well as variations in gradient and analog-to-digital converter (ADC) sampling rates. In the clinical evaluation, Wave-CAIPI achieved similar mean scores when compared with GRAPPA (MPRAGE: ØW = 4.03, ØG = 3.97; T2 w SPACE: ØW = 4.00, ØG = 4.00; SPACE FLAIR: ØW = 3.97, ØG = 3.97; SWI: ØW = 3.93, ØG = 3.83) and was statistically noninferior (N = 30, P < 0.05 for all sequences). DATA CONCLUSION The proposed volumetric brain exam retained comparable image quality when compared with the much longer conventional protocol. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:961-974.
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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, Massachusetts, USA
- Siemens Healthcare, Erlangen, Germany
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Stephen Cauley
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Maria Gabriela Longo
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - John Conklin
- Harvard Medical School, Boston, Massachusetts, USA
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Berkin Bilgic
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Ned Ohringer
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | | | - Peter Bachert
- Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lawrence L Wald
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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van Zijl P, Knutsson L. In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2019; 306:55-65. [PMID: 31377150 PMCID: PMC6703925 DOI: 10.1016/j.jmr.2019.07.034] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 06/19/2019] [Accepted: 07/08/2019] [Indexed: 05/07/2023]
Abstract
Over the past decades, the field of in vivo magnetic resonance (MR) has built up an impressive repertoire of data acquisition and analysis technologies for anatomical, functional, physiological, and molecular imaging, the description of which requires many book volumes. As such it is impossible for a few authors to have an authoritative overview of the field and for a brief article to be inclusive. We will therefore focus mainly on data acquisition and attempt to give some insight into the principles underlying current advanced methods in the field and the potential for further innovation. In our view, the foreseeable future is expected to show continued rapid progress, for instance in imaging of microscopic tissue properties in vivo, assessment of functional and anatomical connectivity, higher resolution physiologic and metabolic imaging, and even imaging of receptor binding. In addition, acquisition speed and information content will continue to increase due to the continuous development of approaches for parallel imaging (including simultaneous multi-slice imaging), compressed sensing, and MRI fingerprinting. Finally, artificial intelligence approaches are becoming more realistic and will have a tremendous effect on both acquisition and analysis strategies. Together, these developments will continue to provide opportunity for scientific discovery and, in combination with large data sets from other fields such as genomics, allow the ultimate realization of precision medicine in the clinic.
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Affiliation(s)
- Peter van Zijl
- Department of Radiology, Johns Hopkins University, F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
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Falk Delgado A, Zommorodi S, Falk Delgado A. Sentinel Lymph Node Biopsy and Complete Lymph Node Dissection for Melanoma. Curr Oncol Rep 2019; 21:54. [PMID: 31028497 PMCID: PMC6486528 DOI: 10.1007/s11912-019-0798-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Purpose of Review The main surgical treatment for invasive malignant melanoma consists of wide surgical and examination of the sentinel node and in selected cases complete lymph node dissection. The aim of this review is to present data for the optimal surgical management of patients with malignant melanoma. Recent Findings A surgical excision margin of 1–2 cm is recommended for invasive melanoma depending on the thickness of the melanoma. Sentinel node biopsy may be considered for patients with at least T1b melanomas thickness 0.8 to 1.0 mm or less than 0.8 mm Breslow thickness with ulceration, classified as T1b lesion, per recent AJCC guidelines. Two randomized controlled trials have been published—DeCOG (German Dermatologic Cooperative Oncology Group Selective Lymphadenectomy) and MSLT-2 (Multicenter Selective Lymphadenectomy Trial) comparing the complete lymph node dissection (CLND) with observation after positive sentinel node biopsy. In the MSLT-2 study, the disease control rate was improved in the immediate CLND group compared with observation but there was no difference in 3-year melanoma specific survival (86% ± 1.3% and 86% ± 1.2%, respectively; p = 0.42). Isolated limb perfusion (ILP) or isolated limb infusion (ILI) with melphalan and actinomycin D is recommended for large and multiple in-transit metastases and satellite metastases in the extremities when local excision is considered ineffective or too extensive. Summary In light of new adjuvant treatment options and new indications for checkpoint inhibitors, and the lack of survival benefit after CLND, we can expect open surgery to decrease in melanoma disease.
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Affiliation(s)
- Alberto Falk Delgado
- Department of Plastic Surgery, Uppsala University, Ing 85, Akademiska Sjukhuset, 75185, Uppsala, Sweden.
| | - Sayid Zommorodi
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Department of Plastic Surgery, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Falk Delgado
- Clinical neurosciences, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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41
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Delgado AF, Kits A, Bystam J, Kaijser M, Skorpil M, Sprenger T, Skare S. Diagnostic performance of a new multicontrast one‐minute full brain exam (EPIMix) in neuroradiology: A prospective study. J Magn Reson Imaging 2019; 50:1824-1833. [DOI: 10.1002/jmri.26742] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 03/21/2019] [Accepted: 03/21/2019] [Indexed: 12/25/2022] Open
Affiliation(s)
- Anna F. Delgado
- Department of Clinical NeuroscienceKarolinska Institutet Stockholm Sweden
- Department of NeuroradiologyKarolinska University Hospital Stockholm Sweden
| | - Annika Kits
- Department of NeuroradiologyKarolinska University Hospital Stockholm Sweden
| | - Jessica Bystam
- Department of NeuroradiologyKarolinska University Hospital Stockholm Sweden
| | - Magnus Kaijser
- Department of NeuroradiologyKarolinska University Hospital Stockholm Sweden
- Department of Medicine, SolnaKarolinska Institutet Stockholm Sweden
| | - Mikael Skorpil
- Department of NeuroradiologyKarolinska University Hospital Stockholm Sweden
- Department of Molecular Medicine and SurgeryKarolinska Institutet Stockholm Sweden
| | - Tim Sprenger
- Department of Clinical NeuroscienceKarolinska Institutet Stockholm Sweden
- MR Applied Science Laboratory EuropeGE Healthcare Stockholm Sweden
| | - Stefan Skare
- Department of Clinical NeuroscienceKarolinska Institutet Stockholm Sweden
- Department of NeuroradiologyKarolinska University Hospital Stockholm Sweden
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Ryu KH, Choi DS, Baek HJ, Cho SB, Ha JY, Kim TB, Hwang MJ. Clinical feasibility of 1-min ultrafast brain MRI compared with routine brain MRI using synthetic MRI: a single center pilot study. J Neurol 2018; 266:431-439. [DOI: 10.1007/s00415-018-9149-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 12/03/2018] [Accepted: 12/04/2018] [Indexed: 12/24/2022]
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43
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Cole JH, Lorenz R, Geranmayeh F, Wood T, Hellyer P, Williams S, Turkheimer F, Leech R. Active Acquisition for multimodal neuroimaging. Wellcome Open Res 2018; 3:145. [PMID: 31667357 PMCID: PMC6807153 DOI: 10.12688/wellcomeopenres.14918.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2018] [Indexed: 02/02/2023] Open
Abstract
In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field -of -view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.
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Affiliation(s)
- James H. Cole
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Romy Lorenz
- MRC Centre for Cognition and Brain Sciences, University of Cambridge, Cambridge, UK
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Fatemeh Geranmayeh
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Tobias Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Peter Hellyer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Steven Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Rob Leech
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
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