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Clinical feasibility of diffusion microstructure imaging (DMI) in acute ischemic stroke

BACKGROUND: Diffusion microstructure imaging (DMI) is a fast approach to higher-order diffusion-weighted magnetic resonance imaging that allows robust decomposition and characterization of diffusion properties of brain tissue into intra-axonal, extra-axonal, and a free water-compartment. We now repo...

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Detalles Bibliográficos
Autores principales: Kellner, E., Reisert, M., Rau, A., Hosp, J., Demerath, T., Weiller, C., Urbach, H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9486659/
https://www.ncbi.nlm.nih.gov/pubmed/36126516
http://dx.doi.org/10.1016/j.nicl.2022.103189
Descripción
Sumario:BACKGROUND: Diffusion microstructure imaging (DMI) is a fast approach to higher-order diffusion-weighted magnetic resonance imaging that allows robust decomposition and characterization of diffusion properties of brain tissue into intra-axonal, extra-axonal, and a free water-compartment. We now report the application of this technique to acute ischemic stroke and demonstrate its potential applicability to the daily clinical routine. METHODS: Thirty-eight patients diagnosed with acute ischemic stroke were scanned using an accelerated multi-shell diffusion-weighted imaging protocol (median delay between onset and MRI scan of 113 min). DMI metrics were calculated and the apparent diffusion coefficient (ADC) derived from conventional diffusion-weighted imaging was used for comparison. The resulting DMI parameter maps were analysed for their potential to improve infarct core delineation, and a receiver-operating characteristic (ROC) analysis was subsequently performed for automated infarct segmentation. RESULTS: Robust parameter maps for diffusion microstructure properties were obtained in all cases. Within the ischemic tissue, an increase in the volume fraction of the intra-axonal compartment was accompanied by a volume fraction reduction in the other two compartments. Moreover, diffusivity was reduced in all three compartments, with intra-axonal diffusivity showing the highest degree of contrast. The intra-axonal diffusion coefficient maps were subsequently found to perform better than single-shell ADC-derived segmentation in terms of automatic segmentation of the infarct core (area under the curve = 0.98 vs 0.92). CONCLUSIONS: The alterations to the ischemic core detected by DMI are in line with the “beading-model” of non-uniform neurite swelling under ischemic conditions. When compared to conventional single-shell diffusion-weighted imaging, DMI metrics are associated with improved discriminative power for delineating and characterizing ischemic changes. This might allow a more detailed assessment of infarct age, severity of damage, the degree of reversibility, and outcome.