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通过脑氧代谢和血流动力学的多模态无创功能神经监测进行模型预测的脑温计算成像:基于MRI的研究及临床验证

Model-predicted brain temperature computational imaging by multimodal noninvasive functional neuromonitoring of cerebral oxygen metabolism and hemodynamics: MRI-derived and clinical validation.

作者信息

Jiang Miaowen, Cao Fuzhi, Zhang Qihan, Qi Zhengfei, Gao Yuan, Zhang Yang, Song Baoyin, Wu Chuanjie, Li Ming, Xu Yongbo, Zhang Xin, Wang Yuan, Wei Ming, Ji Xunming

机构信息

Beijing Institute for Brain Disorders, Capital Medical University, Beijing, 100069, China.

School of Engineering Medicine, Beihang University, Beijing 100083, China.

出版信息

J Cereb Blood Flow Metab. 2025 Feb;45(2):275-291. doi: 10.1177/0271678X241270485. Epub 2024 Aug 11.

Abstract

Brain temperature, a crucial yet under-researched neurophysiological parameter, is governed by the equilibrium between cerebral oxygen metabolism and hemodynamics. Therapeutic hypothermia has been demonstrated as an effective intervention for acute brain injuries, enhancing survival rates and prognosis. The success of this treatment hinges on the precise regulation of brain temperature. However, the absence of comprehensive brain temperature monitoring methods during therapy, combined with a limited understanding of human brain heat transmission mechanisms, significantly hampers the advancement of hypothermia-based neuroprotective therapies. Leveraging the principles of bioheat transfer and MRI technology, this study conducted quantitative analyses of brain heat transfer during mild hypothermia therapy. Utilizing MRI, we reconstructed brain structures, estimated cerebral blood flow and oxygen consumption parameters, and developed a brain temperature calculation model founded on bioheat transfer theory. Employing computational cerebral hemodynamic simulation analysis, we established an intracranial arterial fluid dynamics model to predict brain temperature variations across different therapeutic hypothermia modalities. We introduce a noninvasive, spatially resolved, and optimized mathematical bio-heat model that synergizes model-predicted and MRI-derived data for brain temperature prediction and imaging. Our findings reveal that the brain temperature images generated by our model reflect distinct spatial variations across individual participants, aligning with experimentally observed temperatures.

摘要

脑温是一个关键但研究不足的神经生理参数,受脑氧代谢与血流动力学之间的平衡支配。治疗性低温已被证明是治疗急性脑损伤的有效干预措施,可提高生存率和改善预后。这种治疗的成功取决于对脑温的精确调节。然而,治疗期间缺乏全面的脑温监测方法,加上对人脑热传递机制的了解有限,严重阻碍了基于低温的神经保护疗法的发展。本研究利用生物热传递原理和磁共振成像(MRI)技术,对轻度低温治疗期间的脑热传递进行了定量分析。利用MRI,我们重建了脑结构,估计了脑血流量和氧消耗参数,并基于生物热传递理论建立了脑温计算模型。通过计算性脑血流动力学模拟分析,我们建立了颅内动脉流体动力学模型,以预测不同治疗性低温模式下的脑温变化。我们引入了一种无创、具有空间分辨率且经过优化的数学生物热模型,该模型将模型预测数据与MRI衍生数据相结合,用于脑温预测和成像。我们的研究结果表明,我们的模型生成的脑温图像反映了个体参与者之间不同的空间变化,与实验观察到的温度一致。

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本文引用的文献

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Non-invasive Brain Temperature Measurement in Acute Ischemic Stroke.急性缺血性卒中的无创脑温测量
Front Neurol. 2022 Aug 5;13:889214. doi: 10.3389/fneur.2022.889214. eCollection 2022.

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