Diffusion Tensor Tractography of the Brainstem Pyramidal Tract: A Study on the Optimal Reduction Factor in Parallel Imaging

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Parallel magnetic resonance imaging (MRI) techniques have been widely utilized to shorten scan times or improve spatial resolution (1, 2). Parallel imaging reduces the number of phase-encoding steps by a reduction (R) factor, which refers to the ratio of original phase-encoding steps to reduced phase-encoding steps. The R factor ranges from 1.5 to 4 in most commercially available applications (1, 2). Although applications with much higher R factors are possible, they are currently limited by poor signalto-noise ratio (SNR) and image reconstruction artifacts (1-3). The use of diffusion tensor tractography (DTT) of the cerebral white matter has become widespread in research into a broad spectrum of diseases (4-6). DTT is an imaging method based on diffusion weighted imaging data, which is usually obtained by single-shot echo-planar imaging (EPI). Single-shot EPI has several inherent drawbacks, including low SNR and vulnerability to susceptibility artifacts (1, 2). These drawbacks can be partially overcome by parallel imaging; the reduction in phase-encoding steps increases the SNR via a reduction in the echo time Diffusion Tensor Tractography of the Brainstem Pyramidal Tract: A Study on the Optimal Reduction Factor in Parallel Imaging 뇌간 추체로의 확산텐서 신경다발 영상: 병렬 영상에서의 적정 감소 인자에 대한 연구