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      A portable scanner for brain MRI

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          Abstract

          Access to scanners for magnetic resonance imaging (MRI) is typically limited by cost and by infrastructure requirements. Here, we report the design and testing of a portable prototype scanner for brain MRI that uses a compact and lightweight permanent rare-earth magnet with a built-in readout field gradient. The 122-kg low-field (80 mT) magnet uses has a Halbach-cylinder design that results in minimal stray field and requires neither cryogenics nor external power. The built-in magnetic-field gradient reduces the reliance on high-power gradient drivers, lowering the overall requirements for power and cooling, and reducing acoustic noise. Imperfections in the encoding fields are mitigated with a generalized iterative image-reconstruction technique that leverages prior characterization of the field patterns. In healthy adult volunteers, the scanner can generate T 1-weighted, T 2-weighted and proton-density-weighted brain images with a spatial resolution of 2.2 × 1.3 × 6.8 mm 3. Future versions of the scanner could improve the accessibility of brain MRI at the point of care, particularly for critically ill patients.

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          Most cited references31

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          Is Open Access

          Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

          Summary Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding Bill & Melinda Gates Foundation.
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            Effects of Diffusion on Free Precession in Nuclear Magnetic Resonance Experiments

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              RARE imaging: a fast imaging method for clinical MR.

              Based on the principles of echo imaging, we present a method to acquire sufficient data for a 256 X 256 image in from 2 to 40 s. The image contrast is dominated by the transverse relaxation time T2. Sampling all projections for 2D FT image reconstruction in one (or a few) echo trains leads to image artifacts due to the different T2 weighting of the echo. These artifacts cannot be described by a simple smearing out of the image in the phase direction. Proper distribution of the phase-encoding steps on the echoes can be used to minimize artifacts and even lead to resolution enhancement. In spite of the short data acquisition times, the signal amplitudes of structures with long T2 are nearly the same as those in a conventional 2D FT experiment. Our method, therefore, is an ideal screening technique for lesions with long T2.
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                Author and article information

                Journal
                101696896
                45929
                Nat Biomed Eng
                Nat Biomed Eng
                Nature biomedical engineering
                2157-846X
                25 October 2020
                23 November 2020
                March 2021
                17 November 2021
                : 5
                : 3
                : 229-239
                Affiliations
                [1 ]Athinoula A. Martinos Center for Biomedical Imaging, Department. of Radiology, Massachusetts General Hospital, 149 13 th St, Charlestown, MA 02129, USA.
                [2 ]Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
                [3 ]Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
                [4 ]Department of Physics, Harvard University, 17 Oxford St, Cambridge, MA 02138, USA
                [5 ]Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA
                [6 ]Harvard-MIT Division of Health Science and Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
                Author notes

                Author contributions

                C.Z.C., P.C.M, J.P.S., S.A.S., C.R.S., C.F.V., M.S., M.S.R. and L.L.W. contributed to or advised on the system design, implementation, and validation experiments. C.Z.C., J.P.S., S.F.C., and B.G. contributed to the development of the image reconstruction method. MHL provided guidance for clinical application and subsequent design choices. C.Z.C. wrote the manuscript and all authors contributed to reviewing and editing.

                [* ] Correspondence and requests for materials should be addressed to C.Z.C or L.L.W, czcooley@ 123456mgh.harvard.edu
                Article
                NIHMS1634808
                10.1038/s41551-020-00641-5
                8597947
                33230306
                cdcc134f-3f03-4e48-8d8d-5028b9c4b511

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