关键词: MRI Pilot-Tone Time-of-Flight low-field motion sensors therapy ultrasound

Mesh : Humans Magnetic Resonance Imaging / methods Respiration Liver / diagnostic imaging physiology Movement / physiology Urinary Bladder / diagnostic imaging physiology Algorithms Deep Learning Motion Ultrasonography / methods

来  源:   DOI:10.3390/s24123710   PDF(Pubmed)

Abstract:
Due to limitations in current motion tracking technologies and increasing interest in alternative sensors for motion tracking both inside and outside the MRI system, in this study we share our preliminary experience with three alternative sensors utilizing diverse technologies and interactions with tissue to monitor motion of the body surface, respiratory-related motion of major organs, and non-respiratory motion of deep-seated organs. These consist of (1) a Pilot-Tone RF transmitter combined with deep learning algorithms for tracking liver motion, (2) a single-channel ultrasound transducer with deep learning for monitoring bladder motion, and (3) a 3D Time-of-Flight camera for observing the motion of the anterior torso surface. Additionally, we demonstrate the capability of these sensors to simultaneously capture motion data outside the MRI environment, which is particularly relevant for procedures like radiation therapy, where motion status could be related to previously characterized cyclical anatomical data. Our findings indicate that the ultrasound sensor can track motion in deep-seated organs (bladder) as well as respiratory-related motion. The Time-of-Flight camera offers ease of interpretation and performs well in detecting surface motion (respiration). The Pilot-Tone demonstrates efficacy in tracking bulk respiratory motion and motion of major organs (liver). Simultaneous use of all three sensors could provide complementary motion information outside the MRI bore, providing potential value for motion tracking during position-sensitive treatments such as radiation therapy.
摘要:
由于当前运动跟踪技术的局限性以及对用于MRI系统内部和外部运动跟踪的替代传感器的兴趣日益增加,在这项研究中,我们分享了我们的初步经验,三个替代传感器利用不同的技术和与组织的相互作用来监测身体表面的运动,主要器官的呼吸相关运动,和深层器官的非呼吸运动。这些包括(1)一个Pilot-ToneRF发射器与深度学习算法相结合,用于跟踪肝脏运动,(2)采用深度学习的单通道超声换能器监测膀胱运动,和(3)用于观察前躯干表面的运动的3D飞行时间相机。此外,我们展示了这些传感器同时捕获MRI环境之外的运动数据的能力,这与放射治疗等程序特别相关,其中运动状态可能与先前表征的周期性解剖数据有关。我们的发现表明,超声传感器可以跟踪深层器官(膀胱)的运动以及与呼吸有关的运动。飞行时间相机易于解释,并在检测表面运动(呼吸)方面表现出色。Pilot-Tone展示了跟踪大量呼吸运动和主要器官(肝脏)运动的功效。同时使用所有三个传感器可以在MRI孔外提供互补的运动信息,在诸如放射治疗的位置敏感治疗期间为运动跟踪提供潜在价值。
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