IEEE J Biomed Health Inform. 2024 Jul;28(7):4024-4035. doi: 10.1109/JBHI.2024.3389708. Epub 2024 Jul 2.
Transcranial focused ultrasound (tFUS) has emerged as a new mode of non-invasive brain stimulation (NIBS), with its exquisite spatial precision and capacity to reach the deep regions of the brain. The placement of the acoustic focus onto the desired part of the brain is critical for successful tFUS procedures; however, acoustic wave propagation is severely affected by the skull, distorting the focal location/shape and the pressure level. High-resolution (HR) numerical simulation allows for monitoring of acoustic pressure within the skull but with a considerable computational burden. To address this challenge, we employed a 4× super-resolution (SR) Swin Transformer method to improve the precision of estimating tFUS acoustic pressure field, targeting operator-defined brain areas. The training datasets were obtained through numerical simulations at both ultra-low (2.0 [Formula: see text]) and high (0.5 [Formula: see text]) resolutions, conducted on in vivo CT images of 12 human skulls. Our multivariable datasets, which incorporate physical properties of the acoustic pressure field, wave velocity, and skull CT images, were utilized to train three-dimensional SR models. We found that our method yielded 87.99 ± 4.28% accuracy in terms of focal volume conformity under foreseen skull data, and accuracy of 82.32 ± 5.83% for unforeseen skulls, respectively. Moreover, a significant improvement of 99.4% in computational efficiency compared to the traditional 0.5 [Formula: see text] HR numerical simulation was shown. The presented technique, when adopted in guiding the placement of the FUS transducer to engage specific brain targets, holds great potential in enhancing the safety and effectiveness of tFUS therapy.
经颅聚焦超声(tFUS)作为一种新的非侵入性脑刺激(NIBS)模式出现,其具有精细的空间精度和到达大脑深部区域的能力。将声焦点放置在大脑的期望部位对于成功的 tFUS 程序至关重要;然而,声波传播受到颅骨的严重影响,导致焦点位置/形状和压力水平发生扭曲。高分辨率(HR)数值模拟允许监测颅骨内的声压,但计算负担相当大。为了解决这一挑战,我们采用了 4×超分辨率(SR)Swin Transformer 方法来提高估计 tFUS 声压场的精度,以针对操作员定义的大脑区域。训练数据集是通过在 12 个人类颅骨的体内 CT 图像上进行的超低(2.0 [公式:见文本])和高(0.5 [公式:见文本])分辨率的数值模拟获得的。我们的多变量数据集包含声压场、波速和颅骨 CT 图像的物理特性,用于训练三维 SR 模型。我们发现,我们的方法在预见颅骨数据下,焦点体积一致性的准确率为 87.99 ± 4.28%,在未预见颅骨下的准确率为 82.32 ± 5.83%。此外,与传统的 0.5 [公式:见文本] HR 数值模拟相比,计算效率显著提高了 99.4%。该技术在指导 FUS 换能器放置以接触特定的大脑目标时,如果采用,有可能提高 tFUS 治疗的安全性和有效性。