Meng Ziyu, Guo Rong, Wang Tianyao, Bo Bin, Lin Zengping, Li Yudu, Zhao Yibo, Yu Xin, Lin David J, Nachev Parashkev, Liang Zhi-Pei, Li Yao
IEEE Trans Biomed Eng. 2023 Nov;70(11):3147-3155. doi: 10.1109/TBME.2023.3277546. Epub 2023 Oct 19.
The purpose of this work is to develop a multispectral imaging approach that combines fast high-resolution 3D magnetic resonance spectroscopic imaging (MRSI) and fast quantitative T mapping to capture the multifactorial biochemical changes within stroke lesions and evaluate its potentials for stroke onset time prediction.
Special imaging sequences combining fast trajectories and sparse sampling were used to obtain whole-brain maps of both neurometabolites (2.0 × 3.0 × 3.0 mm) and quantitative T values (1.9 × 1.9 × 3.0 mm) within a 9-minute scan. Participants with ischemic stroke at hyperacute (0-24 h, n = 23) or acute (24 h-7d, n = 33) phase were recruited in this study. Lesion N-acetylaspartate (NAA), lactate, choline, creatine, and T signals were compared between groups and correlated with patient symptomatic duration. Bayesian regression analyses were employed to compare the predictive models of symptomatic duration using multispectral signals.
In both groups, increased T and lactate levels, as well as decreased NAA and choline levels were detected within the lesion (all p < 0.001). Changes in T, NAA, choline, and creatine signals were correlated with symptomatic duration for all patients (all p < 0.005). Predictive models of stroke onset time combining signals from MRSI and T mapping achieved the best performance (hyperacute: R = 0.438; all: R = 0.548).
The proposed multispectral imaging approach provides a combination of biomarkers that index early pathological changes after stroke in a clinical-feasible time and improves the assessment of the duration of cerebral infarction.
Developing accurate and efficient neuroimaging techniques to provide sensitive biomarkers for prediction of stroke onset time is of great importance for maximizing the proportion of patients eligible for therapeutic intervention. The proposed method provides a clinically feasible tool for the assessment of symptom onset time post ischemic stroke, which will help guide time-sensitive clinical management.
本研究旨在开发一种多光谱成像方法，该方法结合快速高分辨率三维磁共振波谱成像（MRSI）和快速定量T值映射，以捕捉中风病灶内的多因素生化变化，并评估其在预测中风发病时间方面的潜力。
采用结合快速轨迹和稀疏采样的特殊成像序列，在9分钟扫描内获取全脑的神经代谢物（2.0×3.0×3.0毫米）和定量T值（1.9×1.9×3.0毫米）图谱。本研究招募了超急性期（0 - 24小时，n = 23）或急性期（24小时 - 7天，n = 33）的缺血性中风患者。比较两组之间病灶的N - 乙酰天门冬氨酸（NAA）、乳酸、胆碱、肌酸和T信号，并与患者症状持续时间相关联。采用贝叶斯回归分析比较使用多光谱信号的症状持续时间预测模型。
在两组中，均检测到病灶内T和乳酸水平升高，以及NAA和胆碱水平降低（所有p < 0.001）。所有患者的T、NAA、胆碱和肌酸信号变化与症状持续时间相关（所有p < 0.005）。结合MRSI和T值映射信号的中风发病时间预测模型表现最佳（超急性期：R = 0.438；所有患者：R = 0.548）。
所提出的多光谱成像方法提供了一组生物标志物组合，可在临床可行的时间内指示中风后的早期病理变化，并改善对脑梗死持续时间的评估。
开发准确高效的神经成像技术以提供敏感的生物标志物用于预测中风发病时间，对于最大化符合治疗干预条件的患者比例非常重要。所提出的方法为评估缺血性中风后的症状发作时间提供了一种临床可行的工具，这将有助于指导对时间敏感的临床管理。
