Continuous monitoring method of cerebral subdural hematoma based on MRI guided DOT
Continuous monitoring method of cerebral subdural hematoma based on MRI guided DOT
复制标题
基于MRI引导DOT的脑硬膜下血肿连续监测方法
DOI：
10.1364/boe.388059
复制
发表时间：
2020-06-01
影响因子：
3.4
通讯作者：
Wang, Jinhai
中科院分区：
文献类型：
--
作者：
Wang, Huiquan;Wu, Nian;Wang, Jinhai
外伤引起的脑硬膜下血肿，病情稳定后，很容易因脑部血管破裂而突然恶化。因此，持续监测脑硬膜下血肿的大小具有重要的临床意义。为了实现硬膜下血肿的快速、实时、无创、准确监测，本文提出了一种结合脑磁共振成像（MRI）图像引导、扩散光学断层扫描技术和深度学习的脑硬膜下血肿监测方法。首先，对MRI大脑图像进行分割，获得结构和参数与真实大脑匹配的三维多层大脑模型。然后，将近红外光源和探测器（源-探测器间距范围为0.5至6.5 cm）放置在模型上，实现颅内血肿信息的快速、实时、无创采集。最后，采用深度学习方法获得准确的脑硬膜下血肿重建图像。实验结果表明，平均体积误差为0.1 ml的堆叠式自编码器的重建效果优于平均体积误差为0.9 ml的代数重建技术的重建结果。不同信噪比下，模拟血肿实际血容量与重建血肿的曲线拟合R-2均大于0.95。结论：所提出的监测方法能够实现硬膜下血肿的快速、无创、实时、准确监测，可为连续穿戴式硬膜下血肿监测设备提供技术基础。 (C) 2020 年美国光学学会根据 OSA 开放获取出版协议的条款
Cerebral subdural hematomas due to trauma can easily worsen suddenly due to the rupture of blood vessels in the brain after the condition is stabilized. Therefore, continuous monitoring of the size of cerebral subdural hematomas has important clinical significance. To achieve fast, real-time, noninvasive, and accurate monitoring of subdural hematomas, a cerebral subdural hematoma monitoring method combining brain magnetic resonance imaging (MRI) image guidance, diffusion optical tomography technology, and deep learning is proposed in this manuscript. First, an MRI brain image is segmented to obtain a three-dimensional multi-layer brain model with structures and parameters matching a real brain. Then, a near-infrared light source and detectors (source-detector separations ranging from 0.5 to 6.5 cm) were placed on the model to achieve fast, real-time and noninvasive acquisition of intracranial hematoma information. Finally, a deep learning method is used to obtain accurate reconstructed images of cerebral subdural hematomas. The experimental results show that the reconstruction effect of stacked auto-encoder with the mean volume error of 0.1 ml is better than the result reconstructed by algebraic reconstruction techniques with the mean volume error of 0.9 ml. Under different signal-to-noise ratios, the curve fitting R-2 between the actual blood volume of a simulated hematoma and a reconstructed hematoma is more than 0.95. We conclude that the proposed monitoring method can realize fast, noninvasive, real-time, and accurate monitoring of subdural hematomas, and can provide a technical basis for continuous wearable subdural hematoma monitoring equipment. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement