|Publication type:||Article in scientific journal|
|Type of review:||Peer review (publication)|
|Title:||Influence of SENSE on image properties in high-resolution single-shot echo-planar DTI|
|Published in:||Magnetic Resonance in Medicine|
|Publisher / Ed. Institution:||Wiley|
|Subjects:||Arteriovenous malformations; Artifacts; Brain mapping; Computer Simulation; Diffusion Magnetic Resonance Imaging; Humans; Computer-assisted image processing; Echo-planar imaging|
|Subject (DDC):||616: Internal medicine and diseases|
|Abstract:||Limited spatial resolution is a key obstacle to the study of brain white matter structure with diffusion tensor imaging (DTI). In its frequent implementation with single-excitation spin-echo echo-planar sequences, DTI's ability to resolve small structures is strongly restricted by T2 and T2* decay, B0 inhomogeneity, and limited signal-to-noise ratio (SNR). In this work the influence of sensitivity encoding (SENSE) on diffusion-weighted (DW) image properties is investigated. Computer simulations showed that the PSF becomes narrower with increasing SENSE reduction factors, R, enhancing the intrinsic resolution. After a brief theoretical discussion, we describe the estimation of SNR on a pixel-by-pixel basis as a function of R. The mean image SNR behavior is manifold: SENSE is capable of increasing SNR efficiency by reducing the echo time (TE). Each SNR(R) curve reveals a maximum that depends on the amount of partial Fourier encoding used. The overall best SNR efficiency for an eight-element head coil array and a b-factor of 1000 s/mm2 is achieved at R = 2.1 and partial Fourier encoding of 60%. In vivo tensor maps of volunteers and a patient, with an in-plane resolution of 0.78 x 0.78 mm2, are also presented to demonstrate the practical implementation of the parallel approach.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Engineering|
|Appears in Collections:||Publikationen School of Engineering|
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