Li Hongwei, Ji Yang, Wang He, Chen Zhensen, Qian Tiansheng, Liao Yujun, Wang Jian, Woods Joseph G, Suzuki Yuriko, Okell Thomas W
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, People's Republic of China.
Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Magn Reson Med. 2025 Oct;94(4):1415-1431. doi: 10.1002/mrm.30542. Epub 2025 Jul 1.
To improve the robustness of noninvasive vessel-selective perfusion imaging and angiography using vessel-encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain.
Our proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR-efficient encodings than previous approaches. Pseudo-continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients.
In simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients.
Combining IOES with optimized PCASL parameters, the vessel-decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.
当将血管编码动脉自旋标记(VEASL)应用于复杂血管几何结构(如脑底 Willis 环(CoW)上方)时,提高无创血管选择性灌注成像和血管造影的稳健性。
我们提出的改进优化编码方案(IOES)更好地考虑了血管几何结构和 VEASL 编码过程,比以前的方法产生了更高信噪比效率的编码。伪连续动脉自旋标记(PCASL)参数针对更薄的标记区域进行了优化,使曲折的血管在标记平面内更准确地被视为单个点。我们将优化后的方法与健康志愿者脑底 Willis 环上方的原始 OES 方法进行了比较,并在两名烟雾病患者中进行了初步应用。
在模拟中,IOES 将信噪比效率提高了约 10%,并使用了对受试者运动不太敏感的更长波长编码。使用优化的 PCASL 参数降低了有效标记厚度,同时保持了高标记效率。在健康志愿者中,这些改进使得至少九条动脉及其下游组织得以分离,血管解码更准确,测量的 VEASL 信号调制与编码设计之间的对齐更紧密。在烟雾病患者中发现了与血管造影一致的血管区域。
将 IOES 与优化的 PCASL 参数相结合,提高了脑底 Willis 环上方具有复杂血管几何结构区域的血管解码效能。自动化编码设计过程和 6 分钟以内的扫描时间使得在临床环境中观察脑底 Willis 环上方的血流模式成为可能,特别是对于侧支循环的研究。