Four dimensional magnetic resonance imaging with retrospective k-space reordering: A feasibility study
Four dimensional magnetic resonance imaging with retrospective k-space reordering: A feasibility study
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DOI：
10.1118/1.4905044
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发表时间：
2015-02-01
期刊：
影响因子：
3.8
通讯作者：
Cai, Jing
中科院分区：
文献类型：
--
作者：
Liu, Yilin;Yin, Fang-Fang;Cai, Jing
目的：当前的四维磁共振成像（4D-MRI）技术缺乏足够的时间/空间分辨率和一致的肿瘤对比度。为了克服这些限制，本研究提出了基于回顾性 k 空间重新排序的 4D-MRI 新策略的开发和初步评估。方法：我们在 4D 数字扩展心脏躯干 (XCAT) 人体模型上模拟了 k 空间重新排序的 4D-MRI。二维回波平面成像 MRI 序列 [帧速率 (F) = 0.448 Hz；图像分辨率（R）= 256x256；模拟中假定采用顺序图像采集模式的 k 空间段数 (N-KS) = 4。对从 XCAT 体模获取的模拟“4D-MRI”的图像质量进行定性评估，并将肿瘤运动轨迹与输入信号进行比较。特别是，计算了平均绝对幅度差（D）和互相关系数（CC）。此外，为了评估新的4D-MRI技术的数据充足条件，利用30名癌症患者的呼吸概况进行了全面的模拟研究，以研究数据完整性（C-p）与多个影响因素之间的关系：重复扫描次数（N-R）、切片数量（N-S）、呼吸相箱数（N-P）、NKS、F、R以及图像采集时的初始呼吸相（P-0）。作为概念验证，我们在 T2 加权快速自旋回波 MR 序列上实施了所提出的 k 空间重排序 4D-MRI 技术，并在健康志愿者身上进行了测试。结果：从 XCAT 体模获取的模拟 4D-MRI 与原始 XCAT 图像非常匹配。从模拟 4D-MRI 测量的肿瘤运动轨迹与输入信号匹配良好（上下方向和前后方向的 D = 0.83 和 0.83 mm，CC = 0.998 和 0.992）。发现 C-p 和 NR 之间的关系最好用指数函数表示（当 N-S = 30、N-P = 6 时，C-P = 100 1-e(-0.18NR) ）。在C-P值为95%时，肿瘤体积的相对误差为0.66%，表明C-P值为95%时的N-R（N-R，N-95%）就足够了。结果发现，N-R, 95% 与 N-P 近似线性正比 (r = 0.99)，并且几乎独立于所有其他因素。健康志愿者的 4D-MRI 图像清楚地显示了膈肌区域的呼吸运动，运动引起的噪声或混叠最小。结论：通过基于呼吸相位回顾性重新排序 k 空间来生成呼吸相关的 4D-MRI 是可行的。这项新技术可能会带来具有高时空分辨率和最佳肿瘤对比度的下一代 4D-MRI，有望改善移动癌症放射治疗的运动管理。 (C) 2015 年美国医学物理学家协会。
Purpose: Current four dimensional magnetic resonance imaging (4D-MRI) techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of a new strategy for 4D-MRI which is based on retrospective k-space reordering.Methods: We simulated a k-space reordered 4D-MRI on a 4D digital extended cardiac-torso (XCAT) human phantom. A 2D echo planar imaging MRI sequence [frame rate (F) = 0.448 Hz; image resolution (R) = 256x256; number of k-space segments (N-KS) = 4] with sequential image acquisition mode was assumed for the simulation. Image quality of the simulated "4D-MRI" acquired from the XCAT phantom was qualitatively evaluated, and tumor motion trajectories were compared to input signals. In particular, mean absolute amplitude differences (D) and cross correlation coefficients (CC) were calculated. Furthermore, to evaluate the data sufficient condition for the new 4D-MRI technique, a comprehensive simulation study was performed using 30 cancer patients' respiratory profiles to study the relationships between data completeness (C-p) and a number of impacting factors: the number of repeated scans (N-R), number of slices (N-S), number of respiratory phase bins (N-P), NKS, F, R, and initial respiratory phase at image acquisition (P-0). As a proof-of-concept, we implemented the proposed k-space reordering 4D-MRI technique on a T2-weighted fast spin echo MR sequence and tested it on a healthy volunteer.Results: The simulated 4D-MRI acquired from the XCAT phantom matched closely to the original XCAT images. Tumor motion trajectories measured from the simulated 4D-MRI matched well with input signals (D = 0.83 and 0.83 mm, and CC = 0.998 and 0.992 in superior-inferior and anterior-posterior directions, respectively). The relationship between C-p and NR was found best represented by an exponential function (C-P = 100 1-e(-0.18NR) ), when N-S = 30, N-P = 6). At a C-P value of 95%, the relative error in tumor volume was 0.66%, indicating that N-R at a C-P value of 95% (N-R,N- 95%) is sufficient. It was found that N-R, 95% is approximately linearly proportional to N-P (r = 0.99), and nearly independent of all other factors. The 4D-MRI images of the healthy volunteer clearly demonstrated respiratory motion in the diaphragm region with minimal motion induced noise or aliasing.Conclusions: It is feasible to generate respiratory correlated 4D-MRI by retrospectively reordering k-space based on respiratory phase. This new technology may lead to the next generation 4D-MRI with high spatiotemporal resolution and optimal tumor contrast, holding great promises to improve the motion management in radiotherapy of mobile cancers. (C) 2015 American Association of Physicists in Medicine.