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Cortes-Albornoz MC, Clifford B, Lo WC, Yee S, Applewhite BP, Tabari A, White-Dzuro C, Cauley SF, Schaefer PW, Rapalino O, Lev MH, Bilgic B, Feiweier T, Huang SY, Conklin JM, Lang M. A 3-Minute Ultrafast MRI and MRA Protocol for Screening of Acute Ischemic Stroke. J Am Coll Radiol 2025; 22:366-375. [PMID: 40044316 DOI: 10.1016/j.jacr.2025.01.002] [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: 09/27/2024] [Revised: 12/26/2024] [Accepted: 01/06/2025] [Indexed: 05/13/2025]
Abstract
OBJECTIVE To evaluate the diagnostic performance of a 3-min ultrafast brain MRI and MRA protocol for screening of acute ischemic stroke. METHODS This study involved 67 adult patients who underwent ultrafast and reference MRI and MRA scans from September 2023 to June 2024 for stroke evaluation. Two readers independently assessed the ultrafast and reference MRI and MRA images in a masked and randomized manner for acute and chronic infarct and hemorrhage as well as large-vessel occlusion and severe stenosis. A 3-point Likert scale was used to evaluate diagnostic quality of the ultrafast sequences and Cohen's κ was used to assess interrater agreement. RESULTS The ultrafast MRI and MRA protocol showed high diagnostic quality, with 98% of sequences rated as diagnostic. Raters showed perfect agreement in identifying acute infarcts, aneurysms, and vascular occlusions using both ultrafast and reference protocols and near-perfect agreement (>95%) for detecting acute hemorrhage and severe stenosis. For chronic conditions such as chronic infarction and chronic hemorrhage, there was substantial agreement with κ values ranging from 0.73 to 0.76. DISCUSSION The screening ultrafast MRI and MRA protocol can effectively identify acute ischemic stroke and intracranial large-vessel occlusion with high diagnostic accuracy while significantly reducing acquisition time, making it suitable for initial stroke triage. Evaluation for chronic pathologies on the ultrafast protocol is inferior compared with standard MRI and MRA imaging.
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Affiliation(s)
- Maria Camila Cortes-Albornoz
- Pediatric Imaging Research Center, Massachusetts General Hospital, Boston, Massachusetts; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | | | - Wei-Ching Lo
- Siemens Medical Solutions USA, Boston, Massachusetts
| | - Seonghwan Yee
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Brooks P Applewhite
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | | | - Stephen F Cauley
- Siemens Medical Solutions USA, Boston, Massachusetts; Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Theresa McLoud Endowed Chair in Radiology Education, Harvard Medical School, Boston, Massachusetts; Vice Chair, Faculty Affairs, Massachusetts General Hospital, Boston, Massachusetts
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Director, Emergency Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Berkin Bilgic
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | | | - Susie Y Huang
- Harvard Medical School, Boston, Massachusetts; Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts; Associate Chair, Faculty Affairs, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Co-Director, Mass General Neuroscience; Director of Translational Neuro MR Imaging, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts
| | - John M Conklin
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Siemens Medical Solutions USA, Boston, Massachusetts; Director of Emergency MRI, Division of Emergency Imaging, Massachusetts General Hospital, Boston, Massachusetts
| | - Min Lang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Director of Innovation and Research, Mass General Brigham Medical Extended Reality Lab, Mass General Brigham, Boston, Massachusetts.
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2
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Lang M, Lo WC, Sharp A, Hartmann SP, Pianykh OS, Melski LM, Herrington JA, Sellers R, Deshpande V, Clifford B, Brink JA, Husseini JS, Harisinghani MG, Huang SY. Improving Workflow Efficiency at an Outpatient MRI Imaging Facility: A Case Study. J Am Coll Radiol 2024; 21:1875-1879. [PMID: 38908740 DOI: 10.1016/j.jacr.2024.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/11/2024] [Accepted: 06/11/2024] [Indexed: 06/24/2024]
Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Wei-Ching Lo
- Siemens Medical Solutions USA, Boston, Massachusetts
| | - Andrew Sharp
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Sean P Hartmann
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Oleg S Pianykh
- Director of Medical Analytics, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Lauren M Melski
- MRI Operations Manager, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Jeremy A Herrington
- Clinical Director, MRI & 3D Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | | | - Vibhas Deshpande
- Vice President, Sustainability Innovation and Strategic Research, Siemens Medical Solutions USA, Inc, Austin, Texas
| | | | - James A Brink
- Radiologist-in-Chief, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Jad S Husseini
- MRI Service Chief, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Mukesh G Harisinghani
- Director of Abdominal MRI, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Susie Y Huang
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts; Associate Chair of Faculty Affairs, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; Director of Translational Neuro MR Imaging, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts.
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3
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Mazurek MH, Abruzzo AR, King AH, Koranteng E, Rigney G, Lie W, Razak S, Gupta R, Mehan WA, Lev MH, Hirsch JA, Buch K, Succi MD. Implementation of a Survey Spine MR Imaging Protocol for Cord Compression in the Emergency Department: Experience at a Level 1 Trauma Center. AJNR Am J Neuroradiol 2024; 45:1378-1384. [PMID: 38702066 PMCID: PMC11392377 DOI: 10.3174/ajnr.a8326] [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: 01/28/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND AND PURPOSE Imaging stewardship in the emergency department (ED) is vital in ensuring patients receive optimized care. While suspected cord compression (CC) is a frequent indication for total spine MR imaging in the ED, the incidence of CC is low. Recently, our level 1 trauma center introduced a survey spine MR imaging protocol to evaluate for suspected CC while reducing examination time to avoid imaging overutilization. This study aims to evaluate the time savings, frequency of ordering patterns of the survey, and the symptoms and outcomes of patients undergoing the survey. MATERIALS AND METHODS This retrospective study examined patients who received a survey spine MR imaging in the ED at our institution between 2018 and 2022. All examinations were performed on a 1.5T GE Healthcare scanner by using our institutional CC survey protocol, which includes sagittal T2WI and STIR sequences through the cervical, thoracic, and lumbar spine. Examinations were read by a blinded, board-certified neuroradiologist. RESULTS A total of 2002 patients received a survey spine MR imaging protocol during the study period. Of these patients, 845 (42.2%, mean age 57 ± 19 years, 45% women) received survey spine MR imaging examinations for the suspicion of CC, and 120 patients (14.2% positivity rate) had radiographic CC. The survey spine MR imaging averaged 5 minutes and 50 seconds (79% faster than routine MR imaging). On multivariate analysis, trauma, back pain, lower extremity weakness, urinary or bowel incontinence, numbness, ataxia, and hyperreflexia were each independently associated with CC. Of the 120 patients with CC, 71 underwent emergent surgery, 20 underwent nonemergent surgery, and 29 were managed medically. CONCLUSIONS The survey spine protocol was positive for CC in 14% of patients in our cohort and acquired at a 79% faster rate compared with routine total spine. Understanding the positivity rate of CC, the clinical symptoms that are most associated with CC, and the subsequent care management for patients presenting with suspected cord compression who received the survey spine MR imaging may better inform the broad adoption and subsequent utilization of survey imaging protocols in emergency settings to increase throughput, improve allocation of resources, and provide efficient care for patients with suspected CC.
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Affiliation(s)
- Mercy H Mazurek
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Annie R Abruzzo
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Alexander H King
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Erica Koranteng
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Grant Rigney
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Winston Lie
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Shahaan Razak
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Rajiv Gupta
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - William A Mehan
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Michael H Lev
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Joshua A Hirsch
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Karen Buch
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Marc D Succi
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
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4
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Awan KM, Goncalves Filho ALM, Tabari A, Applewhite BP, Lang M, Lo WC, Sellers R, Kollasch P, Clifford B, Nickel D, Husseni J, Rapalino O, Schaefer P, Cauley S, Huang SY, Conklin J. Diagnostic evaluation of deep learning accelerated lumbar spine MRI. Neuroradiol J 2024; 37:323-331. [PMID: 38195418 PMCID: PMC11138337 DOI: 10.1177/19714009231224428] [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] [Indexed: 01/11/2024] Open
Abstract
BACKGROUND AND PURPOSE Deep learning (DL) accelerated MR techniques have emerged as a promising approach to accelerate routine MR exams. While prior studies explored DL acceleration for specific lumbar MRI sequences, a gap remains in comprehending the impact of a fully DL-based MRI protocol on scan time and diagnostic quality for routine lumbar spine MRI. To address this, we assessed the image quality and diagnostic performance of a DL-accelerated lumbar spine MRI protocol in comparison to a conventional protocol. METHODS We prospectively evaluated 36 consecutive outpatients undergoing non-contrast enhanced lumbar spine MRIs. Both protocols included sagittal T1, T2, STIR, and axial T2-weighted images. Two blinded neuroradiologists independently reviewed images for foraminal stenosis, spinal canal stenosis, nerve root compression, and facet arthropathy. Grading comparison employed the Wilcoxon signed rank test. For the head-to-head comparison, a 5-point Likert scale to assess image quality, considering artifacts, signal-to-noise ratio (SNR), anatomical structure visualization, and overall diagnostic quality. We applied a 15% noninferiority margin to determine whether the DL-accelerated protocol was noninferior. RESULTS No significant differences existed between protocols when evaluating foraminal and spinal canal stenosis, nerve compression, or facet arthropathy (all p > .05). The DL-spine protocol was noninferior for overall diagnostic quality and visualization of the cord, CSF, intervertebral disc, and nerve roots. However, it exhibited reduced SNR and increased artifact perception. Interobserver reproducibility ranged from moderate to substantial (κ = 0.50-0.76). CONCLUSION Our study indicates that DL reconstruction in spine imaging effectively reduces acquisition times while maintaining comparable diagnostic quality to conventional MRI.
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Affiliation(s)
- Komal M Awan
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | | | - Azadeh Tabari
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | - Brooks P Applewhite
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | - Min Lang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | | | | | | | | | | | - Jad Husseni
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | - Otto Rapalino
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | - Pamela Schaefer
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
| | | | - Susie Y Huang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, USA
| | - John Conklin
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard Medical School, USA
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5
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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: 11] [Impact Index Per Article: 5.5] [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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6
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Tabari A, Lang M, Awan K, Liu W, Clifford B, Lo WC, Splitthoff DN, Cauley S, Rapalino O, Schaefer P, Huang SY, Conklin J. Optimized flow compensation for contrast-enhanced T1-weighted Wave-CAIPI 3D MPRAGE imaging of the brain. Eur Radiol Exp 2023; 7:34. [PMID: 37394534 DOI: 10.1186/s41747-023-00351-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/25/2023] [Indexed: 07/04/2023] Open
Abstract
Flow-related artifacts have been observed in highly accelerated T1-weighted contrast-enhanced wave-controlled aliasing in parallel imaging (CAIPI) magnetization-prepared rapid gradient-echo (MPRAGE) imaging and can lead to diagnostic uncertainty. We developed an optimized flow-mitigated Wave-CAIPI MPRAGE acquisition protocol to reduce these artifacts through testing in a custom-built flow phantom. In the phantom experiment, maximal flow artifact reduction was achieved with the combination of flow compensation gradients and radial reordered k-space acquisition and was included in the optimized sequence. Clinical evaluation of the optimized MPRAGE sequence was performed in 64 adult patients, who all underwent contrast-enhanced Wave-CAIPI MPRAGE imaging without flow-compensation and with optimized flow-compensation parameters. All images were evaluated for the presence of flow-related artifacts, signal-to-noise ratio (SNR), gray-white matter contrast, enhancing lesion contrast, and image sharpness on a 3-point Likert scale. In the 64 cases, the optimized flow mitigation protocol reduced flow-related artifacts in 89% and 94% of the cases for raters 1 and 2, respectively. SNR, gray-white matter contrast, enhancing lesion contrast, and image sharpness were rated as equivalent for standard and flow-mitigated Wave-CAIPI MPRAGE in all subjects. The optimized flow mitigation protocol successfully reduced the presence of flow-related artifacts in the majority of cases.Relevance statementAs accelerated MRI using novel encoding schemes become increasingly adopted in clinical practice, our work highlights the need to recognize and develop strategies to minimize the presence of unexpected artifacts and reduction in image quality as potential compromises to achieving short scan times.Key points• Flow-mitigation technique led to an 89-94% decrease in flow-related artifacts.• Image quality, signal-to-noise ratio, enhancing lesion conspicuity, and image sharpness were preserved with the flow mitigation technique.• Flow mitigation reduced diagnostic uncertainty in cases where flow-related artifacts mimicked enhancing lesions.
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Affiliation(s)
- Azadeh Tabari
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA.
- Harvard Medical School, Boston, MA, USA.
| | - Min Lang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
| | - Komal Awan
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | | | | | | | - Stephen Cauley
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
| | - Otto Rapalino
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
| | - Pamela Schaefer
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
| | - Susie Y Huang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - John Conklin
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 55 Fruit Street, Charlestown, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, USA
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7
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Goncalves Filho ALM, Awan KM, Conklin J, Ngamsombat C, Cauley SF, Setsompop K, Liu W, Splitthoff DN, Lo WC, Kirsch JE, Schaefer PW, Rapalino O, Huang SY. Validation of a highly accelerated post-contrast wave-controlled aliasing in parallel imaging (CAIPI) 3D-T1 MPRAGE compared to standard 3D-T1 MPRAGE for detection of intracranial enhancing lesions on 3-T MRI. Eur Radiol 2023; 33:2905-2915. [PMID: 36460923 PMCID: PMC9718459 DOI: 10.1007/s00330-022-09265-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 09/26/2022] [Accepted: 09/30/2022] [Indexed: 12/04/2022]
Abstract
OBJECTIVES High-resolution post-contrast T1-weighted imaging is a workhorse sequence in the evaluation of neurological disorders. The T1-MPRAGE sequence has been widely adopted for the visualization of enhancing pathology in the brain. However, this three-dimensional (3D) acquisition is lengthy and prone to motion artifact, which often compromises diagnostic quality. The goal of this study was to compare a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) post-contrast 3D T1-MPRAGE sequence (Wave-T1-MPRAGE) with the standard 3D T1-MPRAGE sequence for visualizing enhancing lesions in brain imaging at 3 T. METHODS This study included 80 patients undergoing contrast-enhanced brain MRI. The participants were scanned with a standard post-contrast T1-MPRAGE sequence (acceleration factor [R] = 2 using GRAPPA parallel imaging technique, acquisition time [TA] = 5 min 18 s) and a prototype post-contrast Wave-T1-MPRAGE sequence (R = 4, TA = 2 min 32 s). Two neuroradiologists performed a head-to-head evaluation of both sequences and rated the visualization of enhancement, sharpness, noise, motion artifacts, and overall diagnostic quality. A 15% noninferiority margin was used to test whether post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE. Inter-rater and intra-rater agreement were calculated. Quantitative assessment of CNR/SNR was performed. RESULTS Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE for delineating enhancing lesions with unanimous agreement in all cases between raters. Wave-T1-MPRAGE was noninferior in the perception of noise (p < 0.001), motion artifact (p < 0.001), and overall diagnostic quality (p < 0.001). CONCLUSION High-accelerated post-contrast Wave-T1-MPRAGE enabled a two-fold reduction in acquisition time compared to the standard sequence with comparable performance for visualization of enhancing pathology and equivalent perception of noise, motion artifacts and overall diagnostic quality without loss of clinically important information. KEY POINTS • Post-contrast wave-controlled aliasing in parallel imaging (CAIPI) T1-MPRAGE accelerated the acquisition of three-dimensional (3D) high-resolution post-contrast images by more than two-fold. • Post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE with unanimous agreement between reviewers (100% in 80 cases) for the visualization of intracranial enhancing lesions. • Wave-T1-MPRAGE was equivalent to the standard sequence in the perception of noise in 94% (75 of 80) of cases and was preferred in 16% (13 of 80) of cases for decreased motion artifact.
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Affiliation(s)
- Augusto Lio M Goncalves Filho
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Komal Manzoor Awan
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Chanon Ngamsombat
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Nakhon Pathom, Thailand
| | - Stephen F Cauley
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | | | | | - John E Kirsch
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, 55 Fruit St, GRB-273A, Boston, MA, 02114, USA.
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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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