From the Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, 3740 McClintock Ave, EEB 400, Los Angeles, CA 90089-2564 (Y.B., K.S.N.); GE Healthcare, Calgary, Canada (R.M.L.); Department of Radiology, University of Calgary, Calgary, Canada (R.M.L.); Seaman Family MR Research Centre, Foothills Hospital, Calgary, Canada (R.M.L., R.F.); Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, Calif (J.A., K.S.N.); and Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada (R.F.).
Radiology. 2021 Aug;300(2):410-420. doi: 10.1148/radiol.2021203628. Epub 2021 Jun 8.
Background Advances in sub-Nyquist-sampled dynamic contrast-enhanced (DCE) MRI enable monitoring of brain tumors with millimeter resolution and whole-brain coverage. Such undersampled quantitative methods need careful characterization regarding achievable test-retest reproducibility. Purpose To demonstrate a fully automated high-resolution whole-brain DCE MRI pipeline with 30-fold sparse undersampling and estimate its reproducibility on the basis of reference regions of stable tissue types during multiple posttreatment time points by using longitudinal clinical images of high-grade glioma. Materials and Methods Two methods for sub-Nyquist-sampled DCE MRI were extended with automatic estimation of vascular input functions. Continuously acquired three-dimensional k-space data with ramped-up flip angles were partitioned to yield high-resolution, whole-brain tracer kinetic parameter maps with matched precontrast-agent T1 and M maps. Reproducibility was estimated in a retrospective study in participants with high-grade glioma, who underwent three consecutive standard-of-care examinations between December 2016 and April 2019. Coefficients of variation and reproducibility coefficients were reported for histogram statistics of the tracer kinetic parameters plasma volume fraction and volume transfer constant (K) on five healthy tissue types. Results The images from 13 participants (mean age ± standard deviation, 61 years ± 10; nine women) with high-grade glioma were evaluated. In healthy tissues, the protocol achieved a coefficient of variation less than 57% for median K, if K was estimated consecutively. The maximum reproducibility coefficient for median K was estimated to be at 0.06 min for large or low-enhancing tissues and to be as high as 0.48 min in smaller or strongly enhancing tissues. Conclusion A fully automated, sparsely sampled DCE MRI reconstruction with patient-specific vascular input function offered high spatial and temporal resolution and whole-brain coverage; in healthy tissues, the protocol estimated median volume transfer constant with maximum reproducibility coefficient of 0.06 min in large, low-enhancing tissue regions and maximum reproducibility coefficient of less than 0.48 min in smaller or more strongly enhancing tissue regions. Published under a CC BY 4.0 license. See also the editorial by Lenkinski in this issue.
背景 亚奈奎斯特采样动态对比增强(DCE)MRI 的进步使毫米分辨率和全脑覆盖的脑肿瘤监测成为可能。这种欠采样的定量方法需要仔细描述其在多次治疗后时间点的稳定组织类型参考区域的可实现测试-重测可重复性。
目的 展示一种全自动高分辨率全脑 DCE MRI 流水线,采用 30 倍稀疏欠采样,并使用高级别神经胶质瘤的纵向临床图像,基于稳定组织类型的参考区域,估计其在多个治疗后时间点的可重复性。
材料与方法 扩展了两种亚奈奎斯特采样 DCE MRI 方法,自动估计血管输入功能。使用 ramped-up 翻转角连续采集三维 k 空间数据,以生成具有匹配的预造影剂 T1 和 M 图的高分辨率全脑示踪剂动力学参数图。在 2016 年 12 月至 2019 年 4 月期间连续进行的三项标准护理检查的参与者中进行了回顾性研究,以估计重复性。报告了五种健康组织类型的示踪剂动力学参数血浆容积分数和容积转移常数(K)直方图统计的变异系数和再现系数。
结果 对 13 名高级别神经胶质瘤患者(平均年龄±标准差,61 岁±10;9 名女性)的图像进行了评估。在健康组织中,如果连续估计 K,则该方案的中位数 K 变异系数小于 57%。最大的中位数 K 再现系数估计值为 0.06 min,适用于大或低增强组织,而在较小或强增强组织中高达 0.48 min。
结论 具有患者特异性血管输入函数的全自动稀疏采样 DCE MRI 重建提供了高空间和时间分辨率以及全脑覆盖;在健康组织中,该方案以 0.06 min 的最大再现系数估计中位数体积转移常数,在较大、低增强组织区域和较小或更强增强组织区域的最大再现系数小于 0.48 min。根据 CC BY 4.0 许可发布。 请参阅本期 Lenkinski 的社论。