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Tissue optimization strategies for high-quality ex vivo diffusion imaging.
Barrett, Rachel L C; Cash, Diana; Simmons, Camilla; Kim, Eugene; Wood, Tobias C; Stones, Richard; Vernon, Anthony C; Catani, Marco; Dell'Acqua, Flavio.
Afiliación
  • Barrett RLC; NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Cash D; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Simmons C; Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Kim E; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Wood TC; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Stones R; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Vernon AC; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Catani M; NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Dell'Acqua F; Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
NMR Biomed ; 36(3): e4866, 2023 03.
Article en En | MEDLINE | ID: mdl-36321360
ABSTRACT
Ex vivo diffusion imaging can be used to study healthy and pathological tissue microstructure in the rodent brain with high resolution, providing a link between in vivo MRI and ex vivo microscopy techniques. Major challenges for the successful acquisition of ex vivo diffusion imaging data however are changes in the relaxivity and diffusivity of brain tissue following perfusion fixation. In this study we address this question by examining the combined effects of tissue preparation factors that influence signal-to-noise ratio (SNR) and consequently image quality, including fixative concentration, contrast agent concentration and tissue rehydration time. We present an optimization strategy combining these factors to manipulate the T 1 and T 2 of fixed tissue and maximize SNR efficiency. We apply this strategy in the rat brain, for a diffusion-weighted spin echo protocol with TE = 27 ms on a 9.4 T scanner with a 39 mm volume coil and 660 mT/m 114 mm gradient insert. We used a reduced fixative concentration of 2% paraformaldehyde (PFA), rehydration time more than 20 days, 15 mM Gd-DTPA in perfusate and TR 250 ms. This resulted in a doubling of SNR and an increase in SNR per unit time of 135% in cortical grey matter and 88% in white matter compared with 4% PFA and no contrast agent. This improved SNR efficiency enabled the acquisition of excellent-quality high-resolution (78 µ m isotropic voxel size) diffusion data with b = 4000 s/mm 2 , 30 diffusion directions and a field of view of 40 × 13 × 18 mm3 in less than 4 days. It was also possible to achieve comparable data quality for a standard resolution (150 µ m) diffusion dataset in 2 1 4 h. In conclusion, the tissue optimization strategy presented here may be used to improve SNR, increase spatial resolution and/or allow faster acquisitions in preclinical ex vivo diffusion MRI experiments.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Imagen de Difusión por Resonancia Magnética Idioma: En Revista: NMR Biomed Asunto de la revista: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Imagen de Difusión por Resonancia Magnética Idioma: En Revista: NMR Biomed Asunto de la revista: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM