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Q-space trajectory imaging for multidimensional diffusion MRI of the human brain

Westin, Carl-Fredrik ; Knutsson, Hans ; Pasternak, Ofer ; Szczepankiewicz, Filip ; Özarslan, Evren ; van Westen, Danielle ; Mattisson, Cecilia ; Bogren, Mats ; O'Donnell, Lauren J. ; Kubicki, Marek ; Topgaard, Daniel ; Nilsson, Markus

NeuroImage (Orlando, Fla.), 2016-07, Vol.135, p.345-362 [Periódico revisado por pares]

United States: Elsevier Inc

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Título:
Q-space trajectory imaging for multidimensional diffusion MRI of the human brain
Autor: Westin, Carl-Fredrik ; Knutsson, Hans ; Pasternak, Ofer ; Szczepankiewicz, Filip ; Özarslan, Evren ; van Westen, Danielle ; Mattisson, Cecilia ; Bogren, Mats ; O'Donnell, Lauren J. ; Kubicki, Marek ; Topgaard, Daniel ; Nilsson, Markus
Assuntos: Algorithms ; Anisotropy ; Annan fysik ; Brain ; Brain - diagnostic imaging ; Brain - pathology ; Clinical Medicine ; DDE ; Diffusion ; Diffusion MRI ; Diffusion tensor distribution ; Diffusion Tensor Imaging - methods ; DTI ; Feasibility Studies ; Fysik ; Humans ; Image Interpretation, Computer-Assisted - methods ; Klinisk medicin ; Medical and Health Sciences ; Medicin och hälsovetenskap ; Methods ; Microscopic anisotropy ; Microscopic fractional anisotropy μFA ; Natural Sciences ; Naturvetenskap ; NMR ; Nuclear magnetic resonance ; Other Physics Topics ; Physical Sciences ; q-space ; q-space trajectory ; QTI ; Radiologi och bildbehandling ; Radiology, Nuclear Medicine and Medical Imaging ; Reproducibility of Results ; Schizophrenia - diagnostic imaging ; Schizophrenia - pathology ; SDE ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Spectrum analysis ; TDE ; White Matter - diagnostic imaging ; White Matter - pathology
É parte de: NeuroImage (Orlando, Fla.), 2016-07, Vol.135, p.345-362
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SourceType-Scholarly Journals-1
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Descrição: This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture. •We have described a new diffusion MR framework for imaging of microstructure that we call q-space trajectory imaging.•Performing diffusion encoding with a wide range of q-space trajectories is feasible on a clinical system.•The cumulant expansion of the MR signal yields the mean diffusion tensor and a fourth-order covariance tensor.•QTI can disentangle variation in size from variation in shape and direction.•QTI does not require macroscopic anisotropy and could be useful not only in white matter but also in gray matter.
Editor: United States: Elsevier Inc
Idioma: Inglês

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Q-space trajectory imaging for multidimensional diffusion MRI of the human brain

Westin, Carl-Fredrik ; Knutsson, Hans ; Pasternak, Ofer ; Szczepankiewicz, Filip ; Özarslan, Evren ; van Westen, Danielle ; Mattisson, Cecilia ; Bogren, Mats ; O'Donnell, Lauren J. ; Kubicki, Marek ; Topgaard, Daniel ; Nilsson, Markus

United States: Elsevier Inc

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