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基于 GAN 的颅穿透聚焦超声声模拟的合成 CT

Acoustic Simulation for Transcranial Focused Ultrasound Using GAN-Based Synthetic CT.

出版信息

IEEE J Biomed Health Inform. 2022 Jan;26(1):161-171. doi: 10.1109/JBHI.2021.3103387. Epub 2022 Jan 17.

Abstract

Transcranial focused ultrasound (tFUS) is a promising non-invasive technique for treating neurological and psychiatric disorders. One of the challenges for tFUS is the disruption of wave propagation through the skull. Consequently, despite the risks associated with exposure to ionizing radiation, computed tomography (CT) is required to estimate the acoustic transmission through the skull. This study aims to generate synthetic CT (sCT) from T1-weighted magnetic resonance imaging (MRI) and investigate its applicability to tFUS acoustic simulation. We trained a 3D conditional generative adversarial network (3D-cGAN) with 15 subjects. We then assessed image quality with 15 test subjects: mean absolute error (MAE) = 85.72±9.50 HU (head) and 280.25±24.02 HU (skull), dice coefficient similarity (DSC) = 0.88±0.02 (skull). In terms of skull density ratio (SDR) and skull thickness (ST), no significant difference was found between sCT and real CT (rCT). When the acoustic simulation results of rCT and sCT were compared, the intracranial peak acoustic pressure ratio was found to be less than 4%, and the distance between focal points less than 1 mm.

摘要

经颅聚焦超声(tFUS)是一种有前途的治疗神经和精神疾病的非侵入性技术。tFUS 的一个挑战是颅骨对波传播的干扰。因此,尽管与电离辐射暴露相关的风险很高,但仍需要计算机断层扫描(CT)来估计颅骨的声传输。本研究旨在从 T1 加权磁共振成像(MRI)生成合成 CT(sCT),并研究其在 tFUS 声模拟中的适用性。我们使用 15 个受试者对 3D 条件生成对抗网络(3D-cGAN)进行了训练。然后,我们使用 15 个测试受试者评估了图像质量:平均绝对误差(MAE)=85.72±9.50 HU(头部)和 280.25±24.02 HU(颅骨),骰子系数相似性(DSC)=0.88±0.02(颅骨)。在颅骨密度比(SDR)和颅骨厚度(ST)方面,sCT 与真实 CT(rCT)之间没有发现显著差异。当比较 rCT 和 sCT 的声模拟结果时,发现颅内峰值声压比小于 4%,焦点之间的距离小于 1 毫米。

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