| 数据采集方案对神经扩散模型影响的评估 |
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| 引用本文： | 周敏雄,张会婷,王一达,杨光,姚旭峰,高安康,程敬亮,白洁,严序. 数据采集方案对神经扩散模型影响的评估[J]. 波谱学杂志, 2022, 39(2): 220-229. DOI: 10.11938/cjmr20202870 |
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| 作者姓名： | 周敏雄 张会婷 王一达 杨光 姚旭峰 高安康 程敬亮 白洁 严序 |
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| 作者单位： | 1. 上海健康医学院 医学影像学院，上海市分子影像学重点实验室，上海 2013182. 西门子医疗 磁共振科研市场部，上海 2013183. 华东师范大学 上海市磁共振重点实验室，上海 2000624. 郑州大学第一附属医院 磁共振科，河南 郑州 450052 |
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| 基金项目： | 上海健康医学院师资人才百人库;国家自然科学基金;上海健康医学院校级科研基金资助项目;分子影像学重点实验室建设资助项目;上海高校教师产学研践习计划 |
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| 摘 要： | 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.
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| 关 键 词： | 磁共振成像 数据采集方案 扩散模型 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） |
| 收稿时间： | 2020-11-05 |
Evaluation of the Influence of Data Sampling Schemes on Neural Diffusion Models |
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| ZHOU Min-xiong,ZHANG Hui-ting,WANG Yi-da,YANG Guang,YAO Xu-feng,GAO An-kang,CHENG Jing-liang,BAI Jie,YAN Xu. Evaluation of the Influence of Data Sampling Schemes on Neural Diffusion Models[J]. Chinese Journal of Magnetic Resonance, 2022, 39(2): 220-229. DOI: 10.11938/cjmr20202870 |
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| Authors: | ZHOU Min-xiong ZHANG Hui-ting WANG Yi-da YANG Guang YAO Xu-feng GAO An-kang CHENG Jing-liang BAI Jie YAN Xu |
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| Affiliation: | 1. College of Medical Imaging & Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China2. MR Scientific Marketing, Siemens Healthcare, Shanghai 201318, China3. Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai 200062, China4. Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China |
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| Abstract: | 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. |
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| Keywords: | magnetic resonance imaging data sampling scheme diffusion model diffusion tensor imaging (DTI) diffusion kurtosis imaging (DKI) neurite orientation dispersion and density imaging (NODDI) mean apparent propagator (MAP) |
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