Accuracy and reliability of diffusion imaging models.
Accuracy and reliability of diffusion imaging models.
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扩散成像模型的准确性和可靠性。
DOI：
10.1016/j.neuroimage.2022.119138
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发表时间：
2022-07-01
期刊：
影响因子：
5.7
通讯作者：
Dosenbach, Nico U. F.
中科院分区：
文献类型：
--
作者：
Seider, Nicole A.;Adeyemo, Babatunde;Miller, Ryland;Newbold, Dillan J.;Hampton, Jacqueline M.;Scheidter, Kristen M.;Rutlin, Jerrel;Laumann, Timothy O.;Roland, Jarod L.;Montez, David F.;Van, Andrew N.;Zheng, Annie;Marek, Scott;Kay, Benjamin P.;Bretthorst, G. Larry;Schlaggar, Bradley L.;Greene, Deanna J.;Wang, Yong;Petersen, Steven E.;Barch, Deanna M.;Gordon, Evan M.;Snyder, Abraham Z.;Shimony, Joshua S.;Dosenbach, Nico U. F.
扩散成像旨在非侵入性地表征大脑白色物质纤维的解剖结构和完整性。我们使用模拟和高度采样的个体特异性数据（每个个体927-1442张弥散加权图像[DWI]），评估了常用弥散成像方法的准确性和可靠性，作为数据量和分析方法的函数。当数据不足和/或数据与模型先验不匹配时，允许交叉纤维的扩散成像方法（FSL的BedpostX [BPX]、DSI Studio的恒定立体角Q球成像[CSA-QBI]、MRtrix 3的约束球面去卷积[CSD]）估计了多余的纤维。为了减少这种过拟合，我们开发了一种新的贝叶斯多张量模型选择（BaMM）方法，并将其应用于FSL软件包中BedpostX中使用的流行的球杆模型。BaMM是强大的过拟合，并表现出较高的可靠性和相对最好的交叉纤维的准确性，随着扩散数据量的增加。因此，足够的数据和抗过拟合分析方法增强了扩散成像的精度。对于弥散成像的潜在临床应用，如神经外科计划和脑深部电刺激（DBS），实现弥散成像可靠性所需的数据量低于功能MRI所需的数据量
Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain’s white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927–1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL’s BedpostX [BPX], DSI Studio’s Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3’s Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI
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影响因子：
16.2
作者：
Corbetta M;Ramsey L;Callejas A;Baldassarre A;Hacker CD;Siegel JS;Astafiev SV;Rengachary J;Zinn K;Lang CE;Connor LT;Fucetola R;Strube M;Carter AR;Shulman GL
通讯作者：
Shulman GL
DOI：
10.1006/jmrb.1994.1037
发表时间：
1994-03-01
期刊：
JOURNAL OF MAGNETIC RESONANCE SERIES B
影响因子：
--
作者：
BASSER, PJ;MATTIELLO, J;LEBIHAN, D
通讯作者：
LEBIHAN, D
影响因子：
4.7
作者：
Casey BJ;Cannonier T;Conley MI;Cohen AO;Barch DM;Heitzeg MM;Soules ME;Teslovich T;Dellarco DV;Garavan H;Orr CA;Wager TD;Banich MT;Speer NK;Sutherland MT;Riedel MC;Dick AS;Bjork JM;Thomas KM;Chaarani B;Mejia MH;Hagler DJ Jr;Daniela Cornejo M;Sicat CS;Harms MP;Dosenbach NUF;Rosenberg M;Earl E;Bartsch H;Watts R;Polimeni JR;Kuperman JM;Fair DA;Dale AM;ABCD Imaging Acquisition Workgroup
通讯作者：
ABCD Imaging Acquisition Workgroup
影响因子：
3.3
作者：
Jbabdi, Saad;Sotiropoulos, Stamatios N.;Savio, Alexander M.;Grana, Manuel;Behrens, Timothy E. J.
通讯作者：
Behrens, Timothy E. J.
影响因子：
3.3
作者：
Alexander, AL;Hasan, KM;Parker, DL
通讯作者：
Parker, DL