Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China (Y.Z., X.W., Z.L., Q.F., R.C., E.G., Y.R., Y.Z., J.B., J.C.).
Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, 361000, China (M.Y., Q.Y., S.C., Z.C., C.C.).
Acad Radiol. 2024 Jun;31(6):2488-2500. doi: 10.1016/j.acra.2023.11.036. Epub 2023 Dec 22.
Stroke patients commonly face challenges during magnetic resonance imaging (MRI) examinations due to involuntary movements. This study aims to overcome these challenges by utilizing multiple overlapping-echo detachment (MOLED) quantitative technology. Through this technology, we also seek to detect microstructural changes of the normal-appearing corticospinal tract (NA-CST) in subacute-chronic stroke patients.
79 patients underwent 3.0 T MRI scans, including routine scans and MOLED technique. A deep learning network was utilized for image reconstruction, and the accuracy, reliability, and resistance to motion of the MOLED technique were validated on phantoms and volunteers. Subsequently, we assessed motor dysfunction severity, ischemic lesion volume, T values of the bilateral NA-CST, and the T ratio (rT) between the ipsilesional and contralesional NA-CST in patients.
The MOLED technique showed high accuracy (P < 0.001) and excellent repeatability, with a mean coefficient of variation (CoV) of 1.11%. It provided reliable quantitative results even under head movement, with a mean difference (Mean)= 0.28% and a standard deviation difference (SD)= 1.34%. Additionally, the T value of the ipsilesional NA-CST was significantly higher than contralesional side (P < 0.001), and a positive correlation was observed between rT and the severity of motor dysfunction (r =0.575, P < 0.001). Furthermore, rT successfully predicted post-stroke motor impairment, with an area under the curve (AUC) was 0.883.
The MOLED technique offers significant advantages for quantitatively imaging stroke patients with involuntary movements. Additionally, T mapping from MOLED can detect microstructural changes in the NA-CST, potentially aiding in monitoring stroke-induced motor impairment.
由于运动不受控制，中风患者在磁共振成像（MRI）检查中经常面临挑战。本研究旨在通过利用多重重叠回波分离（MOLED）定量技术来克服这些挑战。通过这项技术，我们还旨在检测亚急性慢性中风患者正常表现的皮质脊髓束（NA-CST）的微观结构变化。
79 名患者接受了 3.0T MRI 扫描，包括常规扫描和 MOLED 技术。利用深度学习网络进行图像重建，并在体模和志愿者上验证 MOLED 技术的准确性、可靠性和抗运动能力。随后，我们评估了患者的运动功能障碍严重程度、缺血性病变体积、双侧 NA-CST 的 T 值以及同侧和对侧 NA-CST 之间的 T 比值（rT）。
MOLED 技术表现出高精度（P<0.001）和极好的可重复性，平均变异系数（CoV）为 1.11%。即使在头部运动下，它也能提供可靠的定量结果，平均差异（Mean）为 0.28%，标准偏差差异（SD）为 1.34%。此外，同侧 NA-CST 的 T 值明显高于对侧（P<0.001），rT 与运动功能障碍严重程度呈正相关（r=0.575，P<0.001）。此外，rT 成功预测了中风后的运动障碍，曲线下面积（AUC）为 0.883。
MOLED 技术为定量成像运动不受控制的中风患者提供了显著优势。此外，MOLED 的 T 映射可以检测到 NA-CST 的微观结构变化，可能有助于监测中风引起的运动障碍。
