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使用已知组件三维-二维图像配准技术对脊柱手术中器械放置进行术中评估。

Intraoperative evaluation of device placement in spine surgery using known-component 3D-2D image registration.

作者信息

Uneri A, De Silva T, Goerres J, Jacobson M W, Ketcha M D, Reaungamornrat S, Kleinszig G, Vogt S, Khanna A J, Osgood G M, Wolinsky J-P, Siewerdsen J H

机构信息

Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, United States of America. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America.

出版信息

Phys Med Biol. 2017 Apr 21;62(8):3330-3351. doi: 10.1088/1361-6560/aa62c5. Epub 2017 Feb 24.

Abstract

Intraoperative x-ray radiography/fluoroscopy is commonly used to assess the placement of surgical devices in the operating room (e.g. spine pedicle screws), but qualitative interpretation can fail to reliably detect suboptimal delivery and/or breach of adjacent critical structures. We present a 3D-2D image registration method wherein intraoperative radiographs are leveraged in combination with prior knowledge of the patient and surgical components for quantitative assessment of device placement and more rigorous quality assurance (QA) of the surgical product. The algorithm is based on known-component registration (KC-Reg) in which patient-specific preoperative CT and parametric component models are used. The registration performs optimization of gradient similarity, removes the need for offline geometric calibration of the C-arm, and simultaneously solves for multiple component bodies, thereby allowing QA in a single step (e.g. spinal construct with 4-20 screws). Performance was tested in a spine phantom, and first clinical results are reported for QA of transpedicle screws delivered in a patient undergoing thoracolumbar spine surgery. Simultaneous registration of ten pedicle screws (five contralateral pairs) demonstrated mean target registration error (TRE) of 1.1  ±  0.1 mm at the screw tip and 0.7  ±  0.4° in angulation when a prior geometric calibration was used. The calibration-free formulation, with the aid of component collision constraints, achieved TRE of 1.4  ±  0.6 mm. In all cases, a statistically significant improvement (p  <  0.05) was observed for the simultaneous solutions in comparison to previously reported sequential solution of individual components. Initial application in clinical data in spine surgery demonstrated TRE of 2.7  ±  2.6 mm and 1.5  ±  0.8°. The KC-Reg algorithm offers an independent check and quantitative QA of the surgical product using radiographic/fluoroscopic views acquired within standard OR workflow. Such intraoperative assessment could improve quality and safety, provide the opportunity to revise suboptimal constructs in the OR, and reduce the frequency of revision surgery.

摘要

术中X射线摄影/荧光透视常用于在手术室评估手术器械的放置情况(如脊柱椎弓根螺钉),但定性解读可能无法可靠地检测到器械放置欠佳和/或对相邻关键结构的破坏。我们提出一种三维-二维图像配准方法,该方法利用术中X射线照片,并结合患者和手术部件的先验知识,对器械放置进行定量评估,并对手术产品进行更严格的质量保证(QA)。该算法基于已知部件配准(KC-Reg),其中使用了患者特定的术前CT和参数化部件模型。该配准进行梯度相似性优化,无需对C形臂进行离线几何校准,同时求解多个部件主体,从而实现一步质量保证(如带有4至20枚螺钉的脊柱结构)。在脊柱模型中测试了该算法的性能,并报告了在一名接受胸腰椎脊柱手术患者中对经椎弓根螺钉进行质量保证的首批临床结果。当使用先前的几何校准时,同时配准十枚椎弓根螺钉(五对双侧)显示螺钉尖端的平均目标配准误差(TRE)为1.1±0.1毫米,角度误差为0.7±0.4°。在部件碰撞约束的帮助下,免校准公式实现了1.4±0.6毫米的TRE。在所有情况下,与先前报道的单个部件的顺序求解相比,同时求解在统计学上有显著改善(p<0.05)。在脊柱手术临床数据中的初步应用显示TRE为2.7±2.6毫米和1.5±0.8°。KC-Reg算法通过使用在标准手术室工作流程中获取的射线照相/荧光透视视图,对手术产品提供独立检查和定量质量保证。这种术中评估可以提高质量和安全性,提供在手术室中修正欠佳结构的机会,并减少翻修手术的频率。

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