数据采集方案对神经扩散模型影响的评估

Evaluation of the Influence of Data Sampling Schemes on Neural Diffusion Models

基于单次数据采集的多种扩散模型联合应用已逐渐成为临床研究的热点,本研究比较了三种采集方案对于神经扩散模型定量计算的影响,包括Q空间笛卡尔网格(QGrid)、多壳层异向(Free)和多壳层同向(MDDW)采集方案,涉及的扩散模型包含扩散张量成像(DTI);扩散峰度成像(DKI);神经突方向分散度和密度成像(NODDI);平均表观传播(MAP)模型.结果表明DTI和DKI模型对采集方案相对不敏感,而NODDI和MAP对采集方案和最大b值的设置相对较敏感,并且QGrid和Free方案一致性较高,因此在大样本和多中心研究中需要考虑采集方案的选择.此外,考虑到QGrid和Free方案分别在结合更多扩散模型和神经纤维束成像应用上更具优势,因此推荐使用.

The joint application of multiple diffusion models on single sampled dataset is becoming a hot topic in clinical research.This study investigated the influence of the three data sampling schemes on the quantification of neural diffusion models.The three sampling schemes compared were QGrid,Free and MDDW on the Siemens scanners.The diffusion models involved were diffusion tensor imaging(DTI),diffusion kurtosis imaging(DKI),neurite orientation dispersion and density imaging(NODDI)and mean apparent propagator(MAP)models.It was demonstrated that the results of NODDI and MAP were sensitive to the sampling schemes and the set of maximum b-value,while that of DTI and DKI were comparatively not sensitive to varying configurations.It was also shown that QGrid and Free schemes provided more consistent results.Thus the sampling scheme should be carefully selected in multi-center studies and studies with large sample size.QGrid and Free schemes are recommended for their advantages demonstrated in this study.