Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods.
Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods.
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DOI:
10.1002/hbm.26497
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发表时间:
2023-12-01
影响因子:
4.8
通讯作者:
O'Donnell LJ
中科院分区:
文献类型:
--
作者:
He J;Zhang F;Pan Y;Feng Y;Rushmore J;Torio E;Rathi Y;Makris N;Kikinis R;Golby AJ;O'Donnell LJ
The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. The CST exhibits a somatotopic organization, which means that the motor neurons that control specific body parts are arranged in order within the CST. Diffusion magnetic resonance imaging (MRI) tractography is increasingly used to study the anatomy of the CST. However, despite many advances in tractography algorithms over the past decade, modern, state‐of‐the‐art methods still face challenges. In this study, we compare the performance of six widely used tractography methods for reconstructing the CST and its somatotopic organization. These methods include constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD‐Stream) methods, unscented Kalman filter (UKF) tractography methods including multi‐fiber (UKF2T) and single‐fiber (UKF1T) models, the generalized q‐sampling imaging (GQI) based deterministic tractography method, and the TractSeg method. We investigate CST somatotopy by dividing the CST into four subdivisions per hemisphere that originate in the leg, trunk, hand, and face areas of the primary motor cortex. A quantitative and visual comparison is performed using diffusion MRI data (N = 100 subjects) from the Human Connectome Project. Quantitative evaluations include the reconstruction rate of the eight anatomical subdivisions, the percentage of streamlines in each subdivision, and the coverage of the white matter–gray matter (WM–GM) interface. CST somatotopy is further evaluated by comparing the percentage of streamlines in each subdivision to the cortical volumes for the leg, trunk, hand, and face areas. Overall, UKF2T has the highest reconstruction rate and cortical coverage. It is the only method with a significant positive correlation between the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex. However, our experimental results show that all compared tractography methods are biased toward generating many trunk streamlines (ranging from 35.10% to 71.66% of total streamlines across methods). Furthermore, the coverage of the WM–GM interface in the largest motor area (face) is generally low (under 40%) for all compared tractography methods. Different tractography methods give conflicting results regarding the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex, indicating that there is generally no clear relationship, and that reconstruction of CST somatotopy is still a large challenge. Overall, we conclude that while current tractography methods have made progress toward the well‐known challenge of improving the reconstruction of the lateral projections of the CST, the overall problem of performing a comprehensive CST reconstruction, including clinically important projections in the lateral (hand and face areas) and medial portions (leg area), remains an important challenge for diffusion MRI tractography. In this study, we compare the performance of six tractography methods for reconstructing the corticospinal tract (CST) and its somatotopic organization. Based on anatomical measurement results, we conclude that the overall problem of performing a comprehensive CST reconstruction, including both lateral and medial portions, remains an important challenge for tractography.
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影响因子:
5.7
作者:
Barakovic M;Tax CMW;Rudrapatna U;Chamberland M;Rafael-Patino J;Granziera C;Thiran JP;Daducci A;Canales-Rodríguez EJ;Jones DK
通讯作者:
Jones DK
影响因子:
4.8
作者:
Bryant L;McKinnon ET;Taylor JA;Jensen JH;Bonilha L;de Bezenac C;Kreilkamp BAK;Adan G;Wieshmann UC;Biswas S;Marson AG;Keller SS
通讯作者:
Keller SS
影响因子:
4.2
作者:
Bucci, Monica;Mandelli, Maria Luisa;Berman, Jeffrey I.;Amirbekian, Bagrat;Nguyen, Christopher;Berger, Mitchel S.;Henry, Roland G.
通讯作者:
Henry, Roland G.
DOI:
10.1016/j.nicl.2017.07.020
发表时间:
2017
期刊:
NeuroImage. Clinical
影响因子:
--
作者:
Cousineau M;Jodoin PM;Morency FC;Rozanski V;Grand'Maison M;Bedell BJ;Descoteaux M
通讯作者:
Descoteaux M
影响因子:
4.8
作者:
Park JK;Kim BS;Choi G;Kim SH;Choi JC;Khang H
通讯作者:
Khang H