MOIVRE Center, Université de Sherbrooke, 2500 Boul. Université, J1K 2R1, Sherbrooke, Canada.
Med Image Anal. 2011 Aug;15(4):603-21. doi: 10.1016/j.media.2010.07.001. Epub 2010 Jul 14.
Many recent high angular resolution diffusion imaging (HARDI) reconstruction techniques have been introduced to infer an orientation distribution function (ODF) of the underlying tissue structure. These methods are more often based on a single-shell (one b-value) acquisition and can only recover angular structure information contained in the ensemble average propagator (EAP) describing the three-dimensional (3D) average diffusion process of water molecules. The EAP can thus provide richer information about complex tissue microstructure properties than the ODF by also considering the radial part of the diffusion signal. In this paper, we present a novel technique for analytical EAP reconstruction from multiple q-shell acquisitions. The solution is based on a Laplace equation by part estimation between the diffusion signal for each shell acquisition. This simplifies greatly the Fourier integral relating diffusion signal and EAP, which leads to an analytical, linear and compact EAP reconstruction. An important part of the paper is dedicated to validate the diffusion signal estimation and EAP reconstruction on real datasets from ex vivo phantoms. We also illustrate multiple q-shell diffusion propagator imaging (mq-DPI) on a real in vivo human brain and perform a qualitative comparison against state-of-the-art diffusion spectrum imaging (DSI) on the same subject. mq-DPI is shown to reconstruct robust EAP from only several different b-value shells and less diffusion measurements than DSI. This opens interesting perspectives for new q-space sampling schemes and tissue microstructure investigation.
许多最近的高角度分辨率扩散成像(HARDI)重建技术被引入来推断基础组织结构的方向分布函数(ODF)。这些方法更经常基于单壳(一个 b 值)采集,只能恢复描述水分子三维(3D)平均扩散过程的整体平均扩散算子(EAP)中包含的角度结构信息。EAP 因此可以通过考虑扩散信号的径向部分,提供比 ODF 更丰富的关于复杂组织微观结构特性的信息。在本文中,我们提出了一种从多 q 壳采集进行解析 EAP 重建的新技术。该解决方案基于对每个壳采集的扩散信号进行部分估计的拉普拉斯方程。这极大地简化了将扩散信号与 EAP 相关联的傅里叶积分,从而导致了一种解析、线性和紧凑的 EAP 重建。本文的一个重要部分致力于验证从离体体模的真实数据集上的扩散信号估计和 EAP 重建。我们还在真实的人体大脑上进行了多 q 壳扩散传播成像(mq-DPI),并与同一主题上的最新扩散光谱成像(DSI)进行了定性比较。mq-DPI 被证明可以仅从几个不同的 b 值壳和比 DSI 更少的扩散测量中重建稳健的 EAP。这为新的 q 空间采样方案和组织微观结构研究开辟了有趣的前景。