A geometrically adjustable receive array for imaging marmoset cohorts.
Neuroimage
; 156: 78-86, 2017 08 01.
Article
en En
| MEDLINE
| ID: mdl-28499849
The common marmoset (Callithrix jacchus) is an increasingly popular animal model for translational neuroscience studies, during which anatomical and functional MRI can be useful investigative tools. To attain the requisite SNR for high-resolution acquisitions, the radiofrequency coil must be optimized for the marmoset; however, relatively few custom coils have been developed that maximize SNR and are compatible with accelerated acquisitions. For the study of large populations of animals, the heterogeneity in animal size reduces the effectiveness of a "one size fits all" approach to coil sizing and makes coils tailored to individual animals cost and time prohibitive. The approach taken in this study was to create an 8-channel phased-array receive coil that was adjustable to the width of the marmoset head, thereby negating the need for tailored coils while still maintaining high SNR. Two marmosets of different size were imaged on a 9.4-T small-animal scanner. Consistent SNR was achieved in the periphery of the brain between head sizes. When compared to a 15-channel, "one size fits all" receive coil, the adjustable coil achieved 57% higher SNR in the superior frontal and parietal cortices and 29% higher SNR in the centre of the brain. The mean geometry factor of the adjustable coil was less than 1.2 for a 2-fold reduction factor in the left-right and anterior-posterior directions. Geometry factors were compared to the 15-channel coil to guide future designs. The adjustable coil was shown to be a practical means for anatomical and echo-planar imaging of marmoset cohorts.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Callithrix
/
Imagen por Resonancia Magnética
/
Neuroimagen
Tipo de estudio:
Etiology_studies
/
Incidence_studies
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Observational_studies
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Prognostic_studies
/
Risk_factors_studies
Límite:
Animals
Idioma:
En
Revista:
Neuroimage
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2017
Tipo del documento:
Article