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1.
J Magn Reson Imaging ; 54(2): 372-390, 2021 08.
Artículo en Inglés | MEDLINE | ID: mdl-32827173

RESUMEN

Stroke is a leading cause of death and disability worldwide. The reasons for increased stroke burden in developing countries are inadequately controlled risk factors resulting from poor public awareness and inadequate infrastructure. Computed tomography and MRI are common neuroimaging modalities used to assess stroke with diffusion-weighted MRI, in particular, being the recommended choice for acute stroke imaging. However, access to these imaging modalities is primarily restricted to major cities and high-income groups. In the case of stroke, the time-window of treatment to limit the damage is of a few hours and needs a point-of-care diagnosis. A low-cost MR system typically achieved at the ultra-low- and very-low-field would meet the need for a geographically accessible and portable solution. We review studies focused on accessible stroke imaging and recent developments in MR methodologies, including hardware, to image at low fields. We hypothesize that in the absence of a formal, rapid stroke triaging system, the value of timely on-site delivery of the scanner to the stroke patient can be significant. To this end, we discuss multiple recent hardware and methods developments in the low-field regime. Our review suggests a compelling need to explore further the trade-offs between high signal, contrast, and accessibility at low fields in low-income communities. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 6.


Asunto(s)
Imagen por Resonancia Magnética , Accidente Cerebrovascular , Imagen de Difusión por Resonancia Magnética , Humanos , Neuroimagen , Accidente Cerebrovascular/diagnóstico por imagen , Tomografía Computarizada por Rayos X
2.
Magn Reson Imaging ; 99: 81-90, 2023 06.
Artículo en Inglés | MEDLINE | ID: mdl-36764630

RESUMEN

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).


Asunto(s)
Encéfalo , Imagen por Resonancia Magnética , Humanos , Niño , Anciano , Imagen por Resonancia Magnética/métodos , Neuroimagen , Fantasmas de Imagen , Espectroscopía de Resonancia Magnética , Procesamiento de Imagen Asistido por Computador/métodos
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