In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)‐R1‐R2 distributions MRI DOI Creative Commons
Maxime Yon, Omar Narvaez, Daniel Topgaard

и другие.

NMR in Biomedicine, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 24, 2024

Abstract Massively multidimensional diffusion magnetic resonance imaging combines tensor‐valued encoding, oscillating gradients, and diffusion‐relaxation correlation to provide multicomponent subvoxel parameters depicting some tissue microstructural features. This method was successfully implemented ex vivo in microimaging systems clinical conditions with gradient waveform of variable duration giving access a narrow frequency ( ω ) range. We demonstrate here its preclinical implementation protocol 389 contrast images probing wide range 18 92 Hz at b ‐values up 2.1 ms/μm 2 enabled by the use modulated waveforms combined multislice high‐resolution low‐distortion echo planar acquisition segmented full reversed phase‐encode acquisition. framework allows identification ‐dependence rat cerebellum olfactory bulb gray matter (GM), parameter distributions are shown resolve two water pools GM different coefficients, shapes, ‐dependence, relaxation rates, spatial repartition whose attribution specific microstructure could modify current understanding origin restriction GM.

Язык: Английский

Cerebellar Pathology in Forensic and Clinical Neuroscience DOI
Azhagu Madhavan Sivalingam,

Darshitha D Sureshkumar

Ageing Research Reviews, Год журнала: 2025, Номер unknown, С. 102697 - 102697

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI DOI Creative Commons
Maxime Yon, Omar Narvaez, Daniel Topgaard

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июнь 9, 2024

Abstract Massively Multidimensional Diffusion MRI combines tensor-valued encoding, oscillating gradients, and diffusion-relaxation correlation to provide multicomponent sub-voxel parameters depicting the tissue microstructure. This method was successfully implemented ex vivo in micro-imaging systems clinical conditions but with a reduced diffusion frequency ( ω ) range due use of classical encoding. We demonstrate here its preclinical implementation protocol 389 contrast images probing wide 18 92 Hz at b -values up 2.1 ms/µm 2 enabled by modulated gradient waveforms combined multislice high-resolution low-distortion EPI acquisition segmented full reversed phase-encode acquisition. framework allows identification -dependence rat cerebellum olfactory bulb gray matter (GM) parameter distributions are shown resolve two water pools GM different coefficients, shapes, -dependence, relaxation rates, spatial repartition whose attribution specific microstructure could modify current understanding origin restriction GM.

Язык: Английский

Процитировано

0
In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)‐R1‐R2 distributions MRI DOI Creative Commons
Maxime Yon, Omar Narvaez, Daniel Topgaard

и другие.

NMR in Biomedicine, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 24, 2024

Abstract Massively multidimensional diffusion magnetic resonance imaging combines tensor‐valued encoding, oscillating gradients, and diffusion‐relaxation correlation to provide multicomponent subvoxel parameters depicting some tissue microstructural features. This method was successfully implemented ex vivo in microimaging systems clinical conditions with gradient waveform of variable duration giving access a narrow frequency ( ω ) range. We demonstrate here its preclinical implementation protocol 389 contrast images probing wide range 18 92 Hz at b ‐values up 2.1 ms/μm 2 enabled by the use modulated waveforms combined multislice high‐resolution low‐distortion echo planar acquisition segmented full reversed phase‐encode acquisition. framework allows identification ‐dependence rat cerebellum olfactory bulb gray matter (GM), parameter distributions are shown resolve two water pools GM different coefficients, shapes, ‐dependence, relaxation rates, spatial repartition whose attribution specific microstructure could modify current understanding origin restriction GM.

Язык: Английский

Процитировано

0