Quantitative dual-energy imaging in the presence of metal implants using locally constrained model-based decomposition

Purpose: To mitigate effects of metal artifacts in Dual-Energy (DE) CT imaging, we introduce a constrained optimization algorithm to enable simultaneous reconstruction-decomposition of three materials: two tissues-of-interest and the metal. Methods: The volume conservation principle and nonnegativity of volume fractions were incorporated as a pair of linear constraints into the Model-Based Material Decomposition (MBMD) algorithm. This enabled solving for three unknown material concentrations from DE projection data. A primal-dual Ordered Subsets Predictor-Corrector Interior-Point (OSPCIP) algorithm was derived to perform the optimization in the proposed constrained-MBMD (CMBMD). To improve computational efficiency and monotonicity of CMBMD, we investigated an approach where the constraint was applied locally onto a small region containing the metal (identified from a preliminary reconstruction) during initial iterations, followed by final iterations with the constraint applied globally. Validation studies involved simulations and test bench experiments to assess the quantitative accuracy of bone concentration measurements in the presence of fracture fixation hardware. In all studies, DE data was acquired using a kVp-switching protocol with the 60 kVp low-energy beam and the 140 kVp high-energy beam. The system geometry emulated the extremity Cone-Beam CT (CBCT). Simulation studies included: i) a cylindrical phantom (80 mm diameter) with a 30 mm long Ti screw and an insert of varying cortical bone concentrations (3 - 13%), and ii) a realistic tibia phantom created from patient CBCT data with Ti fixation hardware of increasing complexity. The test bench experiment involved a 100 mm diameter water bath containing four Ca inserts (6.5 - 39.1% bone concentration) and a Ti plate. Results: CMBMD substantially reduced artifacts in DE decompositions in the presence of metal. The sequentially localglobal constraint strategy resulted in more monotonic convergence than using a global constraint for all iterations. In the simulation studies, CMBMD achieved quantitative accuracy within ∼12% of nominal bone concentration in areas adjacent to metal, and within ∼5% in areas further away from the metal, compared to ∼80% error for the two-material MBMD. In the test bench study, CMBMD generated ∼40% reduction in the error of bone concentration estimates compared to MBMD for nominal insert concentrations of <250 mg/mL, and ∼12% reduction for concentrations <250 mg/mL. Conclusion: Proposed CMBMD enables accurate DE decomposition in the presence of metal implants by incorporating the metal as an additional base material. Proposed method will be particularly useful in quantitative orthopedic imaging, which is often challenged by metal fracture fixation and joint replacement hardware.