QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.
QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.
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DOI：
10.1002/mrm.29057
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发表时间：
2022-03
影响因子：
3.3
通讯作者：
Wang, Yi
中科院分区：
文献类型：
--
作者：
Cho, Junghun;Zhang, Jinwei;Spincemaille, Pascal;Zhang, Hang;Hubertus, Simon;Wen, Yan;Jafari, Ramin;Zhang, Shun;Nguyen, Thanh D.;Dimov, Alexey, V;Gupta, Ajay;Wang, Yi
关键词：
使用深度神经网络 (QQ-NET) 提高定量磁敏度绘图以及基于定量血氧水平依赖幅度（QSM+qBOLD 或 QQ）的氧提取分数 (OEF) 绘图的准确性和速度。 34 名缺血性中风患者和 4 名健康受试者获得了 3D 多回波梯度回波图像。还对患者进行了动脉自旋标记和弥散加权成像（DWI）。 NET是为了解决基于Unet的QQ模型反演问题而开发的。基于 QQ 的 OEF 图利用先前引入的时间聚类、组织成分和总变异 (CCTV) 和 NET 进行重建。使用两样本柯尔莫哥洛夫-斯米尔诺夫检验对模拟、缺血性中风患者和健康受试者的结果进行比较。在模拟中，QQ-NET提供了比QQ-CCTV更准确、更精确的OEF地图，重建速度快了150倍。在亚急性卒中患者中，QQ-NET 的 OEF 在 DWI 定义的病变与其未受影响的对侧正常组织之间具有比 QQ-CCTV 更大的对比噪声比 (CNR)：1.9 ± 1.3 vs 6.6 ± 10.7 (p = 0.03)。在健康受试者中，QQ-CCTV 和 QQ-NET 均提供统一的 OEF 图。 QQ-NET 提高了基于 QQ 的 OEF 的准确性，重建速度更快。
To improve accuracy and speed of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) -based oxygen extraction fraction (OEF) mapping using a deep neural network (QQ-NET). The 3D multi-echo gradient echo images were acquired in 34 ischemic stroke patients and 4 healthy subjects. Arterial spin labeling and diffusion weighted imaging (DWI) were also performed in the patients. NET was developed to solve the QQ model inversion problem based on Unet. QQ-based OEF maps were reconstructed with previously introduced temporal clustering, tissue composition, and total variation (CCTV) and NET. The results were compared in simulation, ischemic stroke patients, and healthy subjects using a two-sample Kolmogorov-Smirnov test. In the simulation, QQ-NET provided more accurate and precise OEF maps than QQ-CCTV with 150 times faster reconstruction speed. In the subacute stroke patients, OEF from QQ-NET had greater contrast-to-noise ratio (CNR) between DWI-defined lesions and their unaffected contralateral normal tissue than with QQ-CCTV: 1.9 ± 1.3 vs 6.6 ± 10.7 (p = 0.03). In healthy subjects, both QQ-CCTV and QQ-NET provided uniform OEF maps. QQ-NET improves the accuracy of QQ-based OEF with faster reconstruction.
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影响因子：
3.7
作者：
Acosta-Cabronero J;Williams GB;Cardenas-Blanco A;Arnold RJ;Lupson V;Nestor PJ
通讯作者：
Nestor PJ
影响因子：
3.3
作者：
Cho J;Kee Y;Spincemaille P;Nguyen TD;Zhang J;Gupta A;Zhang S;Wang Y
通讯作者：
Wang Y
影响因子：
3.3
作者：
An, HY;Lin, WL
通讯作者：
Lin, WL
使用QSM和定量BOLD的时间聚类，组织组成和映射氧气萃取分数的总变化。
影响因子：
3.3
作者：
Cho, Junghun;Spincemaille, Pascal;Nguyen, Thanh D.;Gupta, Ajay;Wang, Yi
通讯作者：
Wang, Yi
影响因子：
3.3
作者：
Cho J;Ma Y;Spincemaille P;Pike GB;Wang Y
通讯作者：
Wang Y