数据采集方案对神经扩散模型影响的评估

doi:10.11938/cjmr20202870

波谱学杂志 ›› 2022, Vol. 39 ›› Issue (2): 220-229.doi: 10.11938/cjmr20202870

数据采集方案对神经扩散模型影响的评估

周敏雄¹,张会婷²,王一达³,杨光³,姚旭峰¹,高安康⁴,程敬亮⁴,白洁⁴,严序^2,*()

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 201318
2. 西门子医疗磁共振科研市场部，上海 201318
3. 华东师范大学上海市磁共振重点实验室，上海 200062
4. 郑州大学第一附属医院磁共振科，河南郑州 450052

收稿日期:2020-11-05 出版日期:2022-06-05 发布日期:2022-05-28
通讯作者: 严序 E-mail:maxwell4444@hotmail.com
基金资助:
上海健康医学院师资人才百人库;上海健康医学院校级科研基金资助项目;上海高校教师产学研践习计划;国家自然科学基金资助项目(81830052);国家自然科学基金资助项目(61971257);分子影像学重点实验室建设资助项目(18DZ2260400)

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

Min-xiong ZHOU¹,Hui-ting ZHANG²,Yi-da WANG³,Guang YANG³,Xu-feng YAO¹,An-kang GAO⁴,Jing-liang CHENG⁴,Jie BAI⁴,Xu YAN^2,*()

1. College of Medical Imaging & Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
2. MR Scientific Marketing, Siemens Healthcare, Shanghai 201318, China
3. Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai 200062, China
4. Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China

Received:2020-11-05 Online:2022-06-05 Published:2022-05-28
Contact: Xu YAN E-mail:maxwell4444@hotmail.com

摘要/Abstract

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.

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）

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.

Key words: 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)

中图分类号:

O482.53

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.

Min-xiong ZHOU, Hui-ting ZHANG, Yi-da WANG, Guang YANG, Xu-feng YAO, An-kang GAO, Jing-liang CHENG, Jie BAI, Xu YAN. Evaluation of the Influence of Data Sampling Schemes on Neural Diffusion Models[J]. Chinese Journal of Magnetic Resonance, 2022, 39(2): 220-229.

图/表 6

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模型	参数	全名（英文/中文）	物理含义
DTI	FA	fractional anisotropy各向异性分数	反映扩散系数在空间上分布不均匀的程度.
DTI	MD\AD\RD	mean\axial\radial diffusivity平均\轴向\径向扩散系数	反映平均、轴向（神经纤维方向）和垂直于轴向平面的扩散速率.

DKI	MD\AD\RD	mean\axial\radial diffusivity 平均\轴向\径向扩散系数	与DTI的MD\AD\RD参数类似，但为校正后的扩散速率.
DKI	MK\AK\RK	mean\axial\radial kurtosis 平均\轴向\径向扩散峰度	反映平均、轴向（神经纤维方向）和垂直于轴向平面的扩散偏离正态分布的程度，与扩散受限和多组织成分混杂有关.

NODDI	ICVF	intra-cellular volume fraction 细胞内容积比	为细胞内信号占总扩散信号的比例，与神经突密度相关.
	ISOVF	isotropic volume fraction 各向同性容积比	为各向同性信号占总扩散信号的比例，通常反映脑脊液信号
	ODI	orientation dispersion index 方向分散指数	量化神经轴突方向角度的不一致性，其值在单方向的神经组织中趋近于0，在各向同性组织趋近于1.

MAP	RTOP	return-to-the-origin probability 返回原点概率	水分子在扩散过程中不发生净位移的概率，反映扩散受限程度.
	MSD	mean squared displacement 平均平方位移	单位时间内水分子的均方位移，反映扩散速率，与DTI/DKI的MD参数接近.
	QIV	Q space inverse variance Q空间逆方差	Q空间信号几何平均值的逆方差
	NG	no-Gaussianity 非高斯性	含义与DKI中的MK接近，反映扩散偏离正态分布的程度.

	DTI		DKI		MAP				NODDI
	FA	MD	MD	MK	MSD	NG	QIV	RTOP	ICVF	ISOVF	ODI
灰质	0.06	0.04	0.01	0.05	0.09	0.04	0.08	0.11	0.07	0.47	0.01
白质	0.02	0.01	0.03	0.04	0.06	0.08	0.09	0.03	0.01	0.11	0.04

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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

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