Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Siemens Healthcare, Siemens Medical Solutions USA Inc, Pittsburgh, Pennsylvania, USA.
Magn Reson Med. 2018 May;79(5):2470-2480. doi: 10.1002/mrm.26901. Epub 2017 Sep 14.
To use a fast 3D rosette spectroscopic imaging acquisition to quantitatively evaluate how spectral quality influences detection of the endogenous variation of gray and white matter metabolite differences in controls, and demonstrate how rosette spectroscopic imaging can detect metabolic dysfunction in patients with neocortical abnormalities.
Data were acquired on a 3T MR scanner and 32-channel head coil, with rosette spectroscopic imaging covering a 4-cm slab of fronto-parietal-temporal lobes. The influence of acquisition parameters and filtering on spectral quality and sensitivity to tissue composition was assessed by LCModel analysis, the Cramer-Rao lower bound, and the standard errors from regression analyses. The optimized protocol was used to generate normative white and gray matter regressions and evaluate three patients with neocortical abnormalities.
As a measure of the sensitivity to detect abnormalities, the standard errors of regression for Cr/NAA and Ch/NAA were significantly correlated with the Cramer-Rao lower bound values (R = 0.89 and 0.92, respectively, both with P < 0.001). The rosette acquisition with a duration of 9.6 min, produces a mean Cramer-Rao lower bound (%) over the entire slab of 4.6 ± 2.6 and 5.8 ± 2.3 for NAA and Cr, respectively. This enables a Cr/NAA standard error of 0.08 (i.e., detection sensitivity of 25% for a 50/50 mixed gray and white matter voxel). In healthy controls, the regression of Cr/NAA versus fraction gray matter in the cingulate differs from frontal and parietal regions.
Fast rosette spectroscopic imaging acquisitions with regression analyses are able to identify metabolic differences across 4-cm slabs of the brain centrally and over the cortical periphery with high efficiency, generating results that are consistent with clinical findings. Magn Reson Med 79:2470-2480, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
利用快速 3D 玫瑰花形光谱成像采集技术定量评估光谱质量如何影响对正常对照者灰质和白质代谢差异的内源性变化的检测,并展示玫瑰花形光谱成像如何检测皮质异常患者的代谢功能障碍。
在 3T MR 扫描仪和 32 通道头部线圈上采集数据,玫瑰花形光谱成像覆盖额顶颞叶的 4cm 厚切片。通过 LCModel 分析、克拉默-劳下限和回归分析的标准误差评估采集参数和滤波对光谱质量和组织成分灵敏度的影响。优化方案用于生成正常的白质和灰质回归,并评估 3 例皮质异常患者。
作为检测异常的灵敏度指标,Cr/NAA 和 Ch/NAA 回归的标准误差与克拉默-劳下限值显著相关(R 分别为 0.89 和 0.92,均 P<0.001)。持续时间为 9.6 分钟的玫瑰花形采集在整个切片上产生 4.6±2.6%的平均克拉默-劳下限(%),分别用于 NAA 和 Cr。这使得 Cr/NAA 的标准误差为 0.08(即,对于 50/50 混合灰质和白质体素,检测灵敏度为 25%)。在健康对照者中,扣带回的 Cr/NAA 与灰质分数的回归与额区和顶区不同。
使用回归分析的快速玫瑰花形光谱成像采集能够以高效率识别大脑中央和皮质外围 4cm 厚切片的代谢差异,产生与临床发现一致的结果。磁共振医学 79:2470-2480, 2018。© 2017 国际磁共振学会。