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基于CT衍生虚拟生物力学模型和荧光基准点的实体器官肿瘤定位稳健增强现实配准方法

Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.

作者信息

Kong Seong-Ho, Haouchine Nazim, Soares Renato, Klymchenko Andrey, Andreiuk Bohdan, Marques Bruno, Shabat Galyna, Piechaud Thierry, Diana Michele, Cotin Stéphane, Marescaux Jacques

机构信息

IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.

Department of Surgery, Seoul National University Hospital, Seoul, Korea.

出版信息

Surg Endosc. 2017 Jul;31(7):2863-2871. doi: 10.1007/s00464-016-5297-8. Epub 2016 Oct 27.


DOI:10.1007/s00464-016-5297-8
PMID:27796600
Abstract

BACKGROUND: Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials. METHODS: Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials. RESULTS: Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images. CONCLUSIONS: Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking.

摘要

背景:增强现实(AR)是计算机生成图像与实时图像的融合。通过对DICOM成像(如CT扫描)进行3D软件操作创建患者特异性虚拟模型,AR可作为手术中的导航工具。虚拟模型可叠加到实时图像上,实现内部解剖结构的透明可视化以及肿瘤的精确定位。然而,3D模型是刚性的,未考虑内部结构的变形。我们提出了一种自动AR配准的概念,即在手术操作过程中器官发生变形时,基于有限元建模(FEM)并结合荧光表面基准点的光学成像来实现。 方法:将两根10×1mm的金属丝(假肿瘤)和六个10×0.9mm的荧光基准点放置在离体猪肾(n = 10)中。基于生物力学的FEM模型由CT扫描生成。使肾脏变形,并使用近红外光学系统通过跟踪基准点来识别形状变化。这些变化会自动与虚拟模型配准,虚拟模型也相应变形。在变形状态下通过CT扫描(真实情况)评估假肿瘤位置预测的准确性。体内实验:在超声引导下将荧光基准点插入一头猪的肾脏,随后进行CT扫描。通过基准点的自动配准,将基于FEM的虚拟模型叠加到腹腔镜图像上。 结果:成功生成生物力学模型并将其准确叠加到光学图像上。通过生物力学传播估计的肿瘤与扫描肿瘤(真实情况)之间的平均测量距离为0.84±0.42mm。所有基准点均成功放置在体内肾脏中,并在近红外模式下清晰可见,从而能够在腹腔镜图像上对虚拟模型进行准确的自动配准。 结论:我们的初步实验表明,带有荧光基准点的生物力学模型有潜力将实体器官表面的变形准确地传递到其内部结构,包括肿瘤,并实现自动化的稳健跟踪。

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