Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques.
Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques.
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DOI：
10.1038/s41598-021-93558-1
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发表时间：
2021-07-12
影响因子：
4.6
通讯作者：
Jones DK
中科院分区：
文献类型：
--
作者：
Afzali M;Knutsson H;Özarslan E;Jones DK
弥散MRI的许多应用都涉及到方向平均弥散加权信号的计算。对于给定的b值，大多数方法隐含地假设梯度采样向量均匀分布在球体（或“壳”）上，通过简单的算术平均计算方向平均信号。这种方法的一个挑战是，并非所有的采集方案都具有分布在完美球体上的梯度采样向量。为了改善这一挑战，可选的平均方法包括：加权信号平均；各壳层信号的球谐表示；并使用平均表观传播子MRI （MAP-MRI）来推导三维信号表示并估计其“各向同性部分”。本文对这些方法在不同信噪比实现下进行了仿真和比较。有了足够密集的采样点（每个壳体61个方向）和各向同性分布的采样向量，所有的平均方法都能给出可比较的结果（基于map - mri的估计精度略高，尽管随着b值的增加，偏差会略微升高）。由于每个壳层的信噪比和数据点数降低，基于map - mri的方法比其他方法具有更高的精度。我们还将这些方法应用于体内数据，其结果与我们的模拟大致一致。对模拟数据的统计分析表明，各b值处的方向平均信号基本为高斯分布。
Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches implicitly assume, for a given b-value, that the gradient sampling vectors are uniformly distributed on a sphere (or ‘shell’), computing the orientationally-averaged signal through simple arithmetic averaging. One challenge with this approach is that not all acquisition schemes have gradient sampling vectors distributed over perfect spheres. To ameliorate this challenge, alternative averaging methods include: weighted signal averaging; spherical harmonic representation of the signal in each shell; and using Mean Apparent Propagator MRI (MAP-MRI) to derive a three-dimensional signal representation and estimate its ‘isotropic part’. Here, these different methods are simulated and compared under different signal-to-noise (SNR) realizations. With sufficiently dense sampling points (61 orientations per shell), and isotropically-distributed sampling vectors, all averaging methods give comparable results, (MAP-MRI-based estimates give slightly higher accuracy, albeit with slightly elevated bias as b-value increases). As the SNR and number of data points per shell are reduced, MAP-MRI-based approaches give significantly higher accuracy compared with the other methods. We also apply these approaches to in vivo data where the results are broadly consistent with our simulations. A statistical analysis of the simulated data shows that the orientationally-averaged signals at each b-value are largely Gaussian distributed.
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