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Balaji S, Wiley N, Poorman ME, Kolind SH. Low-field MRI for use in neurological diseases. Curr Opin Neurol 2024; 37:381-391. [PMID: 38813835 DOI: 10.1097/wco.0000000000001282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
PURPOSE OF REVIEW To review recent clinical uses of low-field magnetic resonance imaging (MRI) to guide incorporation into neurological practice. RECENT FINDINGS Use of low-field MRI has been demonstrated in applications including tumours, vascular pathologies, multiple sclerosis, brain injury, and paediatrics. Safety, workflow, and image quality have also been evaluated. SUMMARY Low-field MRI has the potential to increase access to critical brain imaging for patients who otherwise may not obtain imaging in a timely manner. This includes areas such as the intensive care unit and emergency room, where patients could be imaged at the point of care rather than be transported to the MRI scanner. Such systems are often more affordable than conventional systems, allowing them to be more easily deployed in resource constrained settings. A variety of systems are available on the market or in a research setting and are currently being used to determine clinical uses for these devices. The utility of such devices must be fully evaluated in clinical scenarios before adoption into standard practice can be achieved. This review summarizes recent clinical uses of low-field MR as well as safety, workflows, and image quality to aid practitioners in assessing this new technology.
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Affiliation(s)
- Sharada Balaji
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Neale Wiley
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Shannon H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Medicine (Neurology)
- Department of Radiology
- International Collaboration on Repair Discoveries, Blusson Spinal Cord Centre, University of British Columbia, Vancouver, British Columbia, Canada
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2
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Donnay C, Okar SV, Tsagkas C, Gaitán MI, Poorman M, Reich DS, Nair G. Super resolution using sparse sampling at portable ultra-low field MR. Front Neurol 2024; 15:1330203. [PMID: 38854960 PMCID: PMC11157107 DOI: 10.3389/fneur.2024.1330203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 05/03/2024] [Indexed: 06/11/2024] Open
Abstract
Ultra-low field (ULF) magnetic resonance imaging (MRI) holds the potential to make MRI more accessible, given its cost-effectiveness, reduced power requirements, and portability. However, signal-to-noise ratio (SNR) drops with field strength, necessitating imaging with lower resolution and longer scan times. This study introduces a novel Fourier-based Super Resolution (FouSR) approach, designed to enhance the resolution of ULF MRI images with minimal increase in total scan time. FouSR combines spatial frequencies from two orthogonal ULF images of anisotropic resolution to create an isotropic T2-weighted fluid-attenuated inversion recovery (FLAIR) image. We hypothesized that FouSR could effectively recover information from under-sampled slice directions, thereby improving the delineation of multiple sclerosis (MS) lesions and other significant anatomical features. Importantly, the FouSR algorithm can be implemented on the scanner with changes to the k-space trajectory. Paired ULF (Hyperfine SWOOP, 0.064 tesla) and high field (Siemens, Skyra, 3 Tesla) FLAIR scans were collected on the same day from a phantom and a cohort of 10 participants with MS or suspected MS (6 female; mean ± SD age: 44.1 ± 4.1). ULF scans were acquired along both coronal and axial planes, featuring an in-plane resolution of 1.7 mm × 1.7 mm with a slice thickness of 5 mm. FouSR was evaluated against registered ULF coronal and axial scans, their average (ULF average) and a gold standard SR (ANTs SR). FouSR exhibited higher SNR (47.96 ± 12.6) compared to ULF coronal (36.7 ± 12.2) and higher lesion conspicuity (0.12 ± 0.06) compared to ULF axial (0.13 ± 0.07) but did not exhibit any significant differences contrast-to-noise-ratio (CNR) compared to other methods in patient scans. However, FouSR demonstrated superior image sharpness (0.025 ± 0.0040) compared to all other techniques (ULF coronal 0.021 ± 0.0037, q = 5.9, p-adj. = 0.011; ULF axial 0.018 ± 0.0026, q = 11.1, p-adj. = 0.0001; ULF average 0.019 ± 0.0034, q = 24.2, p-adj. < 0.0001) and higher lesion sharpness (-0.97 ± 0.31) when compared to the ULF average (-1.02 ± 0.37, t(543) = -10.174, p = <0.0001). Average blinded qualitative assessment by three experienced MS neurologists showed no significant difference in WML and sulci or gyri visualization between FouSR and other methods. FouSR can, in principle, be implemented on the scanner to produce clinically useful FLAIR images at higher resolution on the fly, providing a valuable tool for visualizing lesions and other anatomical structures in MS.
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Affiliation(s)
- Corinne Donnay
- Translational Neuroradiology Section, National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Serhat V. Okar
- Translational Neuroradiology Section, National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - Charidimos Tsagkas
- Translational Neuroradiology Section, National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - María I. Gaitán
- Translational Neuroradiology Section, National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | | | - Daniel S. Reich
- Translational Neuroradiology Section, National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - Govind Nair
- Quantitative MRI Core, National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
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Cooper R, Hayes RA, Corcoran M, Sheth KN, Arnold TC, Stein JM, Glahn DC, Jalbrzikowski M. Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people. Front Neurol 2024; 15:1339223. [PMID: 38585353 PMCID: PMC10995930 DOI: 10.3389/fneur.2024.1339223] [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: 11/15/2023] [Accepted: 01/19/2024] [Indexed: 04/09/2024] Open
Abstract
Background Portable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in low-resource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people. Methods T1- and T2-weighted structural MR images were obtained from a low-field (64mT) Hyperfine and high-field (3T) Siemens system in N = 70 individuals (mean age = 20.39 years, range 9-26 years). We tested two super-resolution approaches to improve image correspondence between images acquired at high- and low-field: (1) processing via a convolutional neural network ('SynthSR'), and (2) multi-orientation image averaging. We extracted brain region volumes, cortical thickness, and cortical surface area estimates. We used Pearson correlations to test the correspondence between these measures, and Steiger Z tests to compare the difference in correspondence between standard imaging and super-resolution approaches. Results Single pairs of T1- and T2-weighted images acquired at low field showed high correspondence to high-field-strength images for estimates of total intracranial volume, surface area cortical volume, subcortical volume, and total brain volume (r range = 0.60-0.88). Correspondence was lower for cerebral white matter volume (r = 0.32, p = 0.007, q = 0.009) and non-significant for mean cortical thickness (r = -0.05, p = 0.664, q = 0.664). Processing images with SynthSR yielded significant improvements in correspondence for total brain volume, white matter volume, total surface area, subcortical volume, cortical volume, and total intracranial volume (r range = 0.85-0.97), with the exception of global mean cortical thickness (r = 0.14). An alternative multi-orientation image averaging approach improved correspondence for cerebral white matter and total brain volume. Processing with SynthSR also significantly improved correspondence across widespread regions for estimates of cortical volume, surface area and subcortical volume, as well as within isolated prefrontal and temporal regions for estimates of cortical thickness. Conclusion Applying super-resolution approaches to low-field imaging improves regional brain volume and surface area accuracy in young people. Finer-scale brain measurements, such as cortical thickness, remain challenging with the limited resolution of low-field systems.
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Affiliation(s)
- Rebecca Cooper
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Rebecca A. Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, MA, United States
| | - Mary Corcoran
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, MA, United States
| | - Kevin N. Sheth
- Center for Brain and Mind Health, Yale School of Medicine, New Haven, CT, United States
| | - Thomas Campbell Arnold
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, United States
| | - Joel M. Stein
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David C. Glahn
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, United States
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
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Bossert S, Unadkat P, Sheth KN, Sze G, Schulder M. A Novel Portable, Mobile MRI: Comparison with an Established Low-Field Intraoperative MRI System. Asian J Neurosurg 2023; 18:492-498. [PMID: 38152522 PMCID: PMC10749856 DOI: 10.1055/s-0043-1760857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023] Open
Abstract
Background MRI (magnetic resonance imaging) using low-magnet field strength has unique advantages for intraoperative use. We compared a novel, compact, portable MR imaging system to an established intraoperative 0.15 T system to assess potential utility in intracranial neurosurgery. Methods Brain images were acquired with a 0.15 T intraoperative MRI (iMRI) system and a 0.064 T portable MR system. Five healthy volunteers were scanned. Individual sequences were rated on a 5-point (1 to 5) scale for six categories: contrast, resolution, coverage, noise, artifacts, and geometry. Results Overall, the 0.064 T images (M = 3.4, SD = 0.1) had statistically higher ratings than the 0.15 T images (M = 2.4, SD = 0.2) ( p < 0.01). All comparable sequences (T1, T2, T2 FLAIR and SSFP) were rated significantly higher on the 0.064 T and were rated 1.2 points (SD = 0.3) higher than 0.15 T scanner, with the T2 fluid-attenuated inversion recovery (FLAIR) sequences showing the largest increment on the 0.064 T with an average rating difference of 1.5 points (SD = 0.2). Scanning time for the 0.064 T system obtained images more quickly and encompassed a larger field of view than the 0.15 T system. Conclusions A novel, portable 0.064 T self-shielding MRI system under ideal conditions provided images of comparable quality or better and faster acquisition times than those provided by the already well-established 0.15 T iMR system. These results suggest that the 0.064 T MRI has the potential to be adapted for intraoperative use for intracranial neurosurgery.
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Affiliation(s)
- Sharon Bossert
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell Health, New York, United States
| | - Prashin Unadkat
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell Health, New York, United States
- Elmezzi Graduate School of Molecular Medicine, Northwell Health, Manhasset, United States
| | - Kevin N Sheth
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, United States
| | - Gordon Sze
- Department of Radiology, Yale School of Medicine, New Haven, Connecticut, United States
| | - Michael Schulder
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell Health, New York, United States
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Martin MN, Jordanova KV, Kos AB, Russek SE, Keenan KE, Stupic KF. Relaxation measurements of an MRI system phantom at low magnetic field strengths. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01086-y. [PMID: 37209233 PMCID: PMC10386925 DOI: 10.1007/s10334-023-01086-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/23/2023] [Accepted: 03/29/2023] [Indexed: 05/22/2023]
Abstract
OBJECTIVE Temperature controlled T1 and T2 relaxation times are measured on NiCl2 and MnCl2 solutions from the ISMRM/NIST system phantom at low magnetic field strengths of 6.5 mT, 64 mT and 550 mT. MATERIALS AND METHODS The T1 and T2 were measured of five samples with increasing concentrations of NiCl2 and five samples with increasing concentrations of MnCl2. All samples were scanned at 6.5 mT, 64 mT and 550 mT, at sample temperatures ranging from 10 °C to 37 °C. RESULTS The NiCl2 solutions showed little change in T1 and T2 with magnetic field strength, and both relaxation times decreased with increasing temperature. The MnCl2 solutions showed an increase in T1 and a decrease in T2 with increasing magnetic field strength, and both T1 and T2 increased with increasing temperature. DISCUSSION The low field relaxation rates of the NiCl2 and MnCl2 arrays in the ISMRM/NIST system phantom are investigated and compared to results from clinical field strengths of 1.5 T and 3.0 T. The measurements can be used as a benchmark for MRI system functionality and stability, especially when MRI systems are taken out of the radiology suite or laboratory and into less traditional environments.
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Affiliation(s)
- Michele N Martin
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA.
| | - Kalina V Jordanova
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Anthony B Kos
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Stephen E Russek
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Kathryn E Keenan
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Karl F Stupic
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
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Ravi KS, Nandakumar G, Thomas N, Lim M, Qian E, Jimeno MM, Poojar P, Jin Z, Quarterman P, Srinivasan G, Fung M, Vaughan JT, Geethanath S. Accelerated MRI using intelligent protocolling and subject-specific denoising applied to Alzheimer's disease imaging. FRONTIERS IN NEUROIMAGING 2023; 2:1072759. [PMID: 37554641 PMCID: PMC10406274 DOI: 10.3389/fnimg.2023.1072759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 03/15/2023] [Indexed: 08/10/2023]
Abstract
Magnetic Resonance Imaging (MR Imaging) is routinely employed in diagnosing Alzheimer's Disease (AD), which accounts for up to 60-80% of dementia cases. However, it is time-consuming, and protocol optimization to accelerate MR Imaging requires local expertise since each pulse sequence involves multiple configurable parameters that need optimization for contrast, acquisition time, and signal-to-noise ratio (SNR). The lack of this expertise contributes to the highly inefficient utilization of MRI services diminishing their clinical value. In this work, we extend our previous effort and demonstrate accelerated MRI via intelligent protocolling of the modified brain screen protocol, referred to as the Gold Standard (GS) protocol. We leverage deep learning-based contrast-specific image-denoising to improve the image quality of data acquired using the accelerated protocol. Since the SNR of MR acquisitions depends on the volume of the object being imaged, we demonstrate subject-specific (SS) image-denoising. The accelerated protocol resulted in a 1.94 × gain in imaging throughput. This translated to a 72.51% increase in MR Value-defined in this work as the ratio of the sum of median object-masked local SNR values across all contrasts to the protocol's acquisition duration. We also computed PSNR, local SNR, MS-SSIM, and variance of the Laplacian values for image quality evaluation on 25 retrospective datasets. The minimum/maximum PSNR gains (measured in dB) were 1.18/11.68 and 1.04/13.15, from the baseline and SS image-denoising models, respectively. MS-SSIM gains were: 0.003/0.065 and 0.01/0.066; variance of the Laplacian (lower is better): 0.104/-0.135 and 0.13/-0.143. The GS protocol constitutes 44.44% of the comprehensive AD imaging protocol defined by the European Prevention of Alzheimer's Disease project. Therefore, we also demonstrate the potential for AD-imaging via automated volumetry of relevant brain anatomies. We performed statistical analysis on these volumetric measurements of the hippocampus and amygdala from the GS and accelerated protocols, and found that 27 locations were in excellent agreement. In conclusion, accelerated brain imaging with the potential for AD imaging was demonstrated, and image quality was recovered post-acquisition using DL-based image denoising models.
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Affiliation(s)
- Keerthi Sravan Ravi
- Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, United States
- Columbia University Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, United States
| | | | | | | | - Enlin Qian
- Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, United States
- Columbia University Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, United States
| | - Marina Manso Jimeno
- Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, United States
- Columbia University Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, United States
| | - Pavan Poojar
- Department of Diagnostic, Molecular and Interventional Radiology, Accessible MRI Laboratory, Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mt. Sinai, New York, NY, United States
| | - Zhezhen Jin
- Mailman School of Public Health, Columbia University in the City of New York, New York, NY, United States
| | | | | | - Maggie Fung
- MR Clinical Solutions, GE Healthcare, New York, NY, United States
| | - John Thomas Vaughan
- Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, United States
- Columbia University Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, United States
| | - Sairam Geethanath
- Columbia University Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, United States
- Department of Diagnostic, Molecular and Interventional Radiology, Accessible MRI Laboratory, Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mt. Sinai, New York, NY, United States
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7
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Parsa J, Webb A. Specific absorption rate (SAR) simulations for low-field (< 0.1 T) MRI systems. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01073-3. [PMID: 36933091 PMCID: PMC10386976 DOI: 10.1007/s10334-023-01073-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 01/19/2023] [Accepted: 02/23/2023] [Indexed: 03/19/2023]
Abstract
OBJECTIVE To simulate the magnetic and electric fields produced by RF coil geometries commonly used at low field. Based on these simulations, the specific absorption rate (SAR) efficiency can be derived to ensure safe operation even when using short RF pulses and high duty cycles. METHODS Electromagnetic simulations were performed at four different field strengths between 0.05 and 0.1 T, corresponding to the lower and upper limits of current point-of-care (POC) neuroimaging systems. Transmit magnetic and electric fields, as well as transmit efficiency and SAR efficiency were simulated. The effects of a close-fitting shield on the EM fields were also assessed. SAR calculations were performed as a function of RF pulse length in turbo-spin echo (TSE) sequences. RESULTS Simulations of RF coil characteristics and B1+ transmit efficiencies agreed well with corresponding experimentally determined parameters. Overall, the SAR efficiency was, as expected, higher at the lower frequencies studied, and many orders of magnitude greater than at conventional clinical field strengths. The tight-fitting transmit coil results in the highest SAR in the nose and skull, which are not thermally sensitive tissues. The calculated SAR efficiencies showed that only when 180° refocusing pulses of duration ~ 10 ms are used for TSE sequences does SAR need to be carefully considered. CONCLUSION This work presents a comprehensive overview of the transmit and SAR efficiencies for RF coils used for POC MRI neuroimaging. While SAR is not a problem for conventional sequences, the values derived here should be useful for RF intensive sequences such as T1ρ, and also demonstrate that if very short RF pulses are required then SAR calculations should be performed.
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Affiliation(s)
- Javad Parsa
- C.J. Gorter MRI Centre, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Percuros B.V., Leiden, The Netherlands
| | - Andrew Webb
- C.J. Gorter MRI Centre, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
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8
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Deoni SCL, Burton P, Beauchemin J, Cano-Lorente R, De Both MD, Johnson M, Ryan L, Huentelman MJ. Neuroimaging and verbal memory assessment in healthy aging adults using a portable low-field MRI scanner and a web-based platform: results from a proof-of-concept population-based cross-section study. Brain Struct Funct 2023; 228:493-509. [PMID: 36352153 PMCID: PMC9646260 DOI: 10.1007/s00429-022-02595-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 11/01/2022] [Indexed: 11/10/2022]
Abstract
Consumer wearables and health monitors, internet-based health and cognitive assessments, and at-home biosample (e.g., saliva and capillary blood) collection kits are increasingly used by public health researchers for large population-based studies without requiring intensive in-person visits. Alongside reduced participant time burden, remote and virtual data collection allows the participation of individuals who live long distances from hospital or university research centers, or who lack access to transportation. Unfortunately, studies that include magnetic resonance neuroimaging are challenging to perform remotely given the infrastructure requirements of MRI scanners, and, as a result, they often omit socially, economically, and educationally disadvantaged individuals. Lower field strength systems (< 100 mT) offer the potential to perform neuroimaging at a participant's home, enabling more accessible and equitable research. Here we report the first use of a low-field MRI "scan van" with an online assessment of paired-associate learning (PAL) to examine associations between brain morphometry and verbal memory performance. In a sample of 67 individuals, 18-93 years of age, imaged at or near their home, we show expected white and gray matter volume trends with age and find significant (p < 0.05 FWE) associations between PAL performance and hippocampus, amygdala, caudate, and thalamic volumes. High-quality data were acquired in 93% of individuals, and at-home scanning was preferred by all individuals with prior MRI at a hospital or research setting. Results demonstrate the feasibility of remote neuroimaging and cognitive data collection, with important implications for engaging traditionally under-represented communities in neuroimaging research.
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Affiliation(s)
- Sean C L Deoni
- Maternal, Newborn, and Child Health Discovery & Tools, Bill & Melinda Gates Foundation, 500 5th Ave, Seattle, WA, 98109, USA.
| | - Phoebe Burton
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | - Jennifer Beauchemin
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | - Rosa Cano-Lorente
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | | | | | - Lee Ryan
- Department of Psychology, University of Arizona, Tucson, AZ, USA
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9
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Arnold TC, Freeman CW, Litt B, Stein JM. Low-field MRI: Clinical promise and challenges. J Magn Reson Imaging 2023; 57:25-44. [PMID: 36120962 PMCID: PMC9771987 DOI: 10.1002/jmri.28408] [Citation(s) in RCA: 50] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 02/03/2023] Open
Abstract
Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high-field devices remain expensive to install and operate, making them scarce outside of high-income countries and major population centers. Low-field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low-field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low-field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low-field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI-guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low-field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Thomas Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Colbey W. Freeman
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Brian Litt
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neurology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Joel M. Stein
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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10
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Arnold TC, Tu D, Okar SV, Nair G, By S, Kawatra KD, Robert-Fitzgerald TE, Desiderio LM, Schindler MK, Shinohara RT, Reich DS, Stein JM. Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions. Neuroimage Clin 2022; 35:103101. [PMID: 35792417 PMCID: PMC9421456 DOI: 10.1016/j.nicl.2022.103101] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 06/23/2022] [Accepted: 06/24/2022] [Indexed: 12/25/2022]
Abstract
Paired, same-day, 3T and 64mT MRI studies were analyzed in 33 MS patients. 64mT MRI showed 94% sensitivity for detecting any lesions in 3T confirmed cases. The diameter of the smallest detected lesion was larger at 64mT compared to 3T. Total lesion volume estimates were strongly correlated between 3T and 64mT scans. Portable low-field MRI detects white matter lesions, but smaller lesions may be missed.
Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34–0.5 × 0.34–0.5 × 3–5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = –19.0–15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.
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Affiliation(s)
- T Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danni Tu
- Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Serhat V Okar
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | | | - Karan D Kawatra
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Timothy E Robert-Fitzgerald
- Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lisa M Desiderio
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew K Schindler
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russell T Shinohara
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA.
| | - Joel M Stein
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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