Dual-energy (DE) decomposition has been adopted in orthopedic imaging to measure bone composition and visualize intraarticular contrast enhancement. One of the potential applications involves monitoring of callus mineralization for longitudinal assessment of fracture healing. However, fracture repair usually involves internal fixation hardware that can generate significant artifacts in reconstructed images. To address this challenge, we develop a novel algorithm that combines simultaneous reconstruction-decomposition using a previously reported method for model-based material decomposition (MBMD) augmented by the known-component (KC) reconstruction framework to mitigate metal artifacts. We apply the proposed algorithm to simulated DE data representative of a dedicated extremity cone-beam CT (CBCT) employing an x-ray unit with three vertically arranged sources. The scanner generates DE data with non-coinciding high- and low-energy projection rays when the central source is operated at high tube potential and the peripheral sources at low potential. The proposed algorithm was validated using a digital extremity phantom containing varying concentrations of Ca-water mixtures and Ti implants. Decomposition accuracy was compared to MBMD without the KC model. The proposed method suppressed metal artifacts and yielded estimated Ca concentrations that approached the reconstructions of an implant-free phantom for most mixture regions. In the vicinity of simple components, the errors of Ca density estimates obtained by incorporating KC in MBMD were ∼1.5–5 lower than the errors of conventional MBMD; for cases with complex implants, the errors were ∼3–5 lower. In conclusion, the proposed method can achieve accurate bone mineral density measurements in the presence of metal implants using non-coinciding DE projections acquired on a multisource CBCT system.

双能（DE）分解已在骨科成像中用于测量骨成分和可视化关节内对比度增强。潜在的应用之一涉及监测愈伤组织矿化，以纵向评估骨折愈合。然而，骨折修复通常涉及内固定硬件，可能会在重建图像中产生明显的伪影。为了应对这一挑战，我们开发了一种新颖的算法，该算法结合了同步重建-分解，使用先前报道的基于模型的材料分解（MBMD）方法，并通过已知组件（KC）重建框架进行增强，以减轻金属伪影。我们将所提出的算法应用于代表专用四肢锥束 CT (CBCT) 的模拟 DE 数据，该数据采用具有三个垂直排列源的 X 射线装置。当中心源在高管电势下工作而外围源在低电势下工作时，扫描仪生成具有不重合的高能和低能投影射线的DE数据。使用包含不同浓度的钙水混合物和钛植入物的数字肢体模型对所提出的算法进行了验证。将分解精度与没有 KC 模型的 MBMD 进行了比较。所提出的方法抑制了金属伪影，并产生了估计的 Ca 浓度，该浓度接近大多数混合区域的无植入体模型的重建。在简单成分附近，通过将 KC 纳入 MBMD 获得的 Ca 密度估计误差比传统 MBMD 的误差低约 1.5-5；对于复杂种植体的情况，误差要低约 3-5 倍。 总之，所提出的方法可以使用在多源 CBCT 系统上获取的非重合 DE 投影在金属植入物存在的情况下实现准确的骨矿物质密度测量。