Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Eur J Neurosci. 2024 Sep;60(5):4987-4999. doi: 10.1111/ejn.16490. Epub 2024 Jul 31.
Diffusion-based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert-placed, high-resolution T1-weighted ROI-data transfer onto lower spatial resolution diffusion-weighted images. Slab volumes from 20 volunteers were acquired and preprocessed including distortion bias correction and artifact reduction. Constrained spherical deconvolution was used to generate a directional diffusion information grid (fibre orientation distribution-model [FOD]). Three neuroradiologists marked landmarks on both diffusion imaging variants and structural datasets. Structural ROI information (volumetric interpolated breath-hold sequence [VIBE]) was respectively registered (linear with 6/12 degrees of freedom [DOF]) onto single-shot EPI (ss-EPI) and readout-segmented EPI (rs-EPI) volumes, respectively. All eight ROI/FOD-combinations were compared in a targeted tractography task of the optic nerve pathway. Inter-rater reliability for placed ROIs among experts was highest in VIBE images (lower confidence interval 0.84 to 0.97, mean 0.91) and lower in both ss-EPI (0.61 to 0.95, mean 0.79) and rs-EPI (0.59 to 0.86, mean 0.70). Tractography success rate based on streamline selection performance was highest in VIBE-drawn ROIs registered (6-DOF) onto rs-EPI FOD (70.0% over 5%-threshold, capped to failed ratio 39/16) followed by both 12-DOF-registered (67.5%; 41/16) and nonregistered VIBE (67.5%; 40/23). On ss-EPI FOD, VIBE-ROI-datasets obtained fewer streamlines overall with each at 55.0% above 5%-threshold and with lower capped to failed ratio (6-DOF: 35/36; 12-DOF: 34/34, nonregistered 33/36). The combination of VIBE-placed ROIs (highest inter-rater reliability) with 6-DOF registration onto rs-EPI targets (best streamline selection performance) is most suitable for white matter template generation required in group studies.
基于扩散的视神经束追踪需要采样策略辅助解剖学地标信息（感兴趣区域 [ROI]）。我们旨在研究将专家放置的高分辨率 T1 加权 ROI 数据转移到较低空间分辨率扩散加权图像上的可行性。从 20 名志愿者中采集并预处理了板层体积，包括失真偏置校正和伪影减少。受约束的球解卷积用于生成方向扩散信息网格（纤维方向分布模型 [FOD]）。三位神经放射科医生在扩散成像变体和结构数据集上标记了地标。结构 ROI 信息（容积内插屏气序列 [VIBE]）分别（线性 6/12 个自由度 [DOF]）注册到单次激发 EPI（ss-EPI）和读出分段 EPI（rs-EPI）体积上。在视神经通路的靶向追踪任务中比较了所有 8 个 ROI/FOD 组合。专家之间放置 ROI 的组内可靠性在 VIBE 图像中最高（置信区间下限为 0.84 至 0.97，平均值为 0.91），在 ss-EPI 中较低（置信区间下限为 0.61 至 0.95，平均值为 0.79），在 rs-EPI 中较低（置信区间下限为 0.59 至 0.86，平均值为 0.70）。基于流线选择性能的追踪成功率在基于 VIBE 绘制的 ROI （6-DOF）注册到 rs-EPI FOD 时最高（60%的流线超过 5%的阈值，上限为失败比例 39/16），其次是 12-DOF 注册（67.5%；41/16）和未注册的 VIBE（67.5%；40/23）。在 ss-EPI FOD 上，VIBE-ROI 数据集总体上获得的流线较少，每条线的 5%阈值以上均为 55.0%，且失败上限比例较低（6-DOF：35/36；12-DOF：34/34，未注册 33/36）。VIBE 放置 ROI（最高组内可靠性）与 rs-EPI 目标的 6-DOF 注册相结合（最佳流线选择性能）最适合于群组研究所需的白质模板生成。
