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WE-G-217BCD-01:物理学(成像)最佳实践 - 使用光谱系统模型和植入设备知识在手术器械存在的情况下进行高质量CT成像。

WE-G-217BCD-01: BEST IN PHYSICS (IMAGING) - High-Quality CT Imaging in the Presence of Surgical Instrumentation Using Spectral System Models and Knowledge of Implanted Devices.

作者信息

Zbijewski W, Stayman J, Otake Y, Carrino J, Khanna A, Siewerdsen J

机构信息

Johns Hopkins University, Baltimore, MD.

出版信息

Med Phys. 2012 Jun;39(6Part28):3972-3973. doi: 10.1118/1.4736211.

Abstract

PURPOSE

Imaging in the presence of implants (instrumentation and prostheses) presents a notoriously difficult challenge to CT because of photon starvation and beam hardening. To alleviate these limitations, a statistical reconstruction approach that includes knowledge of implant shape and composition was previously reported. This work extends the approach to modeling of photon transport, including polychromatic x-ray beams and scatter, and evaluates the method in simulated and real data.

METHODS

Previous work on Known-Component Reconstruction (KCR) is first extended to include a polyenergetic beam (KCR-POLY). The method simultaneously estimates the unknown background volume and the position of implants with known attenuation and shape. Simulations included an anthropomorphic knee with a Co-Cr-Mo implant and system model for an extremities CT system (110 kVp+0.2 mm Cu). Experimental validation was performed on an imaging bench in which a Titanium spine fixation rod (65 mm long, 5.5 mm diameter) was imaged within a 20.5 cm diameter water cylinder (120 kVp+0.2 mm Cu) in geometry simulating an interventional C- arm.

RESULTS

The polyenergetic system model was essential to high image quality in KCR reconstructions of large, highly attenuating implants such as knee prostheses and spine instrumentation, where standard penalized- likelihood and monoenergetic variants of KCR fail. The first application of KCR-POLY in real data demonstrates the potential of the algorithm in practice, reducing or eliminating artifacts and restoring image uniformity.

CONCLUSIONS

The KCR-POLY algorithm yielded major reduction in metal artifacts, owing both to a priori component knowledge (the implant) and account of the polyenergetic beam, object attenuation, and x-ray scatter. Ongoing research focuses on improvements to the registration algorithm, scatter, and experimental studies with complex, deformable implants. The work supports application of CT to a range of applications conventionally prohibited by metal implants - e.g. surgical guidance or diagnostic imaging of joints with prostheses. This work was supported in part by NIH 2R01-CA-112163.

摘要

目的

由于光子饥饿和束硬化,在存在植入物(器械和假体)的情况下进行成像对CT来说是一个极其困难的挑战。为了缓解这些限制,先前报道了一种包含植入物形状和成分知识的统计重建方法。这项工作将该方法扩展到光子传输建模,包括多色X射线束和散射,并在模拟数据和真实数据中评估了该方法。

方法

先前关于已知成分重建(KCR)的工作首先扩展到包括多能束(KCR-POLY)。该方法同时估计未知的背景体积以及具有已知衰减和形状的植入物的位置。模拟包括一个带有钴铬钼植入物的人体膝关节和一个四肢CT系统(110 kVp + 0.2 mm铜)的系统模型。在一个成像工作台上进行了实验验证,其中在一个直径20.5 cm的水缸(120 kVp + 0.2 mm铜)内对一根钛制脊柱固定棒(长65 mm,直径5.5 mm)进行成像,其几何形状模拟介入式C形臂。

结果

多能系统模型对于大型、高衰减植入物(如膝关节假体和脊柱器械)的KCR重建中的高图像质量至关重要,在这些情况下,KCR的标准惩罚似然法和单能变体均失败。KCR-POLY在真实数据中的首次应用证明了该算法在实际中的潜力,减少或消除了伪影并恢复了图像均匀性。

结论

KCR-POLY算法使金属伪影大幅减少,这既归功于先验成分知识(植入物),也归功于对多能束、物体衰减和X射线散射的考虑。正在进行的研究重点是改进配准算法、散射以及对复杂、可变形植入物的实验研究。这项工作支持将CT应用于一系列传统上因金属植入物而被禁止的应用,例如手术导航或假体关节的诊断成像。本研究部分得到了美国国立卫生研究院2R01-CA-112163的资助。

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