标题： 基于快速MRI的合成CT模拟用于精确的tFUS定位 显示英文标题

标题： Rapid MRI-Based Synthetic CT Simulations for Precise tFUS Targeting

摘要： 精确的靶向对于经颅聚焦超声（tFUS）神经调节的有效性至关重要。 虽然CT能提供准确的颅骨声学特性，但其电离辐射和软组织对比度差限制了其临床应用。 相比之下，MRI能无辐射地提供优越的神经解剖可视化，但缺乏颅骨特性映射。 本研究提出了一种全新的、完全无需CT的仿真框架，该框架结合了从MRI生成的合成CT（sCT）与高效的建模技术，以实现快速且精确的tFUS靶向。 我们训练了一个深度学习模型，从T1加权MRI生成sCT，并将其与全波（k-Wave）以及加速仿真方法相结合，包括混合角谱（kWASM）和瑞利-索末菲ASM（RSASM）。 在五个颅骨模型中，使用sCT的全波和混合流程均表现出亚毫米级的靶向偏差、焦斑形状一致性（FWHM ~3.3-3.8 mm），以及与基于CT的黄金标准相比小于0.2的归一化压力误差。 值得注意的是，kW-ASM和RS-ASM流程将仿真时间分别从约3320秒减少到187秒和34秒，实现了约94%和约90%的时间节省。 这些结果证实，结合MRI生成的sCT和创新的快速仿真技术，可以实现快速、准确且无辐射的tFUS规划，支持其在可扩展临床应用中的可行性。 显示英文摘要

摘要： Accurate targeting is critical for the effectiveness of transcranial focused ultrasound (tFUS) neuromodulation. While CT provides accurate skull acoustic properties, its ionizing radiation and poor soft tissue contrast limit clinical applicability. In contrast, MRI offers superior neuroanatomical visualization without radiation exposure but lacks skull property mapping. This study proposes a novel, fully CT free simulation framework that integrates MRI-derived synthetic CT (sCT) with efficient modeling techniques for rapid and precise tFUS targeting. We trained a deep-learning model to generate sCT from T1-weighted MRI and integrated it with both full-wave (k-Wave) and accelerated simulation methods, hybrid angular spectrum (kWASM) and Rayleigh-Sommerfeld ASM (RSASM). Across five skull models, both full-wave and hybrid pipelines using sCT demonstrated sub-millimeter targeting deviation, focal shape consistency (FWHM ~3.3-3.8 mm), and <0.2 normalized pressure error compared to CT-based gold standard. Notably, the kW-ASM and RS-ASM pipelines reduced simulation time from ~3320 s to 187 s and 34 s respectively, achieving ~94% and ~90% time savings. These results confirm that MRI-derived sCT combined with innovative rapid simulation techniques enables fast, accurate, and radiation-free tFUS planning, supporting its feasibility for scalable clinical applications.