Lu Huanxiang, Li Junbo, Lu Qiang, Bharat Shyam, Erkamp Ramon, Chen Bin, Drysdale Jeremy, Vignon Francois, Jain Ameet
Med Image Comput Comput Assist Interv. 2014;17(Pt 2):389-96. doi: 10.1007/978-3-319-10470-6_49.
2D Ultrasound (US) is becoming the preferred modality for image-guided interventions due to its low cost and portability. However, the main limitation is the limited visibility of surgical tools. We present a new sensor technology that can easily be embedded on needles that are used for US-guided interventions. Two different types of materials are proposed to be used as sensor--co-polymer and PZT. The co-polymer technology is particularly attractive due to its plasticity, allowing very thin depositions (10-20 μm) on a variety of needle shapes. Both sensors receive acoustic energy and convert it to an electrical signal. The precise location of the needle can then be estimated from this signal, to provide real-time feedback to the clinician. We evaluated the feasibility of this new technology using (i) a 4DOF robot in a water tank; (ii) extensive ex vivo experiments; and (iii) in vivo studies. Quantitative robotic studies indicated that the co-polymer is more robust and stable when compared to PZT. In quantitative experiments, the technology achieved a tracking accuracy of 0.14 ± 0.03mm, significantly superior to competing technologies. The technology also proved success in near-real clinical studies on tissue data. This sensor technology is non-disruptive of existing clinical workflows, highly accurate, and is cost-effective. Initial clinician feedback shows great potential for large scale clinical impact.
二维超声(US)因其低成本和便携性正成为图像引导介入手术的首选方式。然而,其主要局限性在于手术工具的可视性有限。我们提出了一种新的传感器技术,它可以轻松地嵌入用于超声引导介入手术的针上。提出了两种不同类型的材料用作传感器——共聚物和锆钛酸铅(PZT)。共聚物技术因其可塑性特别有吸引力,能够在各种形状的针上进行非常薄的沉积(10 - 20微米)。两种传感器都接收声能并将其转换为电信号。然后可以从该信号估计针的精确位置,为临床医生提供实时反馈。我们使用(i)水箱中的四自由度机器人;(ii)广泛的离体实验;以及(iii)体内研究评估了这项新技术的可行性。定量机器人研究表明,与锆钛酸铅相比,共聚物更坚固且稳定。在定量实验中,该技术实现了0.14±0.03毫米的跟踪精度,明显优于竞争技术。该技术在关于组织数据的近真实临床研究中也证明是成功的。这种传感器技术不会干扰现有的临床工作流程,高度准确且具有成本效益。临床医生的初步反馈显示出对大规模临床影响的巨大潜力。