利用 QSM 和定量 BOLD 进行氧摄取分数图绘制的时间聚类、组织成分和全变差
Temporal clustering, tissue composition, and total variation for mapping oxygen extraction fraction using QSM and quantitative BOLD.
机构信息
Department of Radiology, Weill Cornell Medical College, New York, New York, USA.
Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA.
出版信息
Magn Reson Med. 2021 Nov;86(5):2635-2646. doi: 10.1002/mrm.28875. Epub 2021 Jun 10.
PURPOSE
To improve the accuracy of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) based mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO ) using temporal clustering, tissue composition, and total variation (CCTV).
METHODS
Three-dimensional multi-echo gradient echo and arterial spin labeling images were acquired from 11 healthy subjects and 33 ischemic stroke patients. Diffusion-weighted imaging (DWI) was also obtained from patients. The CCTV mapping was developed for incorporating tissue-type information into clustering of the previous cluster analysis of time evolution (CAT) and applying total variation (TV). The QQ-based OEF and CMRO were reconstructed with CAT, CAT+TV (CATV), and the proposed CCTV, and results were compared using region-of-interest analysis, Kruskal-Wallis test, and post hoc Wilcoxson rank sum test.
RESULTS
In simulation, CCTV provided more accurate and precise OEF than CAT or CATV. In healthy subjects, QQ-based OEF was less noisy and more uniform with CCTV than CAT. In subacute stroke patients, OEF with CCTV had a greater contrast-to-noise ratio between DWI-defined lesions and the unaffected contralateral side than with CAT or CATV: 1.9 ± 1.3 versus 1.1 ± 0.7 (P = .01) versus 0.7 ± 0.5 (P < .001).
CONCLUSION
The CCTV mapping significantly improves the robustness of QQ-based OEF against noise.
目的
通过时间聚类、组织成分和全变差（CTV）来提高定量磁化率映射加定量血氧水平依赖幅度（QSM+qBOLD 或 QQ）氧提取分数（OEF）和脑氧代谢率（CMRO）的定量图的准确性。
方法
从 11 名健康受试者和 33 名缺血性脑卒中患者中采集三维多回波梯度回波和动脉自旋标记图像。还从患者中获得了弥散加权成像（DWI）。CTV 映射是为了将组织类型信息纳入先前时间演化聚类分析（CAT）的聚类中，并应用全变差（TV）而开发的。使用感兴趣区域分析、Kruskal-Wallis 检验和事后 Wilcoxson 秩和检验，比较 CAT、CAT+TV（CATV）和提出的 CTV 重建的 QQ 基于 OEF 和 CMRO 的结果。
结果
在模拟中，CTV 比 CAT 或 CATV 提供了更准确和更精确的 OEF。在健康受试者中，CTV 比 CAT 具有更低噪声和更均匀的 QQ 基于 OEF。在亚急性脑卒中患者中，CTV 与 CAT 或 CATV 相比，DWI 定义的病变与未受影响的对侧之间的 OEF 对比度噪声比更高：1.9±1.3 比 1.1±0.7（P=0.01）比 0.7±0.5（P<.001）。
结论
CTV 映射显著提高了 QQ 基于 OEF 对噪声的稳健性。
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