Dual energy CT reconstruction using the constrained one step spectral image reconstruction algorithm

Abstract

AbstractBackgroundThe constrained one‐step spectral CT Image Reconstruction method (cOSSCIR) has been developed to estimate basis material maps directly from spectral CT data using a model of the polyenergetic x‐ray transmissions and incorporating convex constraints into the inversion problem. This ‘one‐step’ approach has been shown to stabilize the inversion in the case of photon‐counting CT, and may provide similar benefits to dual‐kV systems that utilize integrating detectors. Since the approach does not require the same rays be acquired for every spectral measurement, cOSSCIR can apply to dual energy protocols and systems used clinically, such as fast and slow kV switching systems and dual source scanning.PurposeThe purpose of this study is to investigate the use of cOSSCIR applied to dual‐kV data, using both registered and unregistered spectral acquisitions, specifically slow and fast kV switching imaging protocols. For this application, cOSSCIR is investigated using inverse crime simulations and dual‐kV experiments. This study is the first demonstration of cOSSCIR on the dual‐kV reconstruction problem.MethodsAn integrating detector model was developed for the purpose of reconstructing dual‐kV data, and an inverse crime study was used to validate the detector model within the cOSSCIR framework using a simulated pelvic phantom. Experiments were also used to evaluate cOSSCIR on the dual energy problem. Dual‐kV data was obtained from a physical phantom containing analogs of adipose, bone, and liver tissues, with the aim of recovering the material coefficients in the bone and adipose basis material maps. cOSSCIR was applied to acquisitions where all rays performed both spectral measurements (registered) and fast and slow kV switching acquisitions (unregistered). cOSSCIR was also compared to two image‐domain decomposition approaches, where image‐domain methods are the conventional approach for decomposing unregistered spectral data.ResultsSimulations demonstrate the application of cOSSCIR to the dual‐kV inversion problem by successfully recovering the material basis maps on ideal data, while further showing that unregistered data presents a more challenging inversion problem. In our experimental reconstructions, the recovered basis material coefficient errors were found to be less than 6.5% in the bone, adipose, and liver regions for both registered and unregistered protocols. Similarly, the errors were less than 4% in the 50 keV virtual mono‐energetic images, and the recovered material decomposition vectors nearly overlap their corresponding ground‐truth vectors. Additionally, a preliminary two material decomposition study of iodine quantification recovered an average concentration of 9.2 mg/mL from a 10 mg/mL experimental iodine analog.ConclusionsUsing our integrating detector and spectral models, cOSCCIR is capable of accurately recovering material basis maps from dual‐kV data for both registered and unregistered data. The material decomposition quantification compare favorably to the image domain approaches, and our results were not affected by the imaging protocol. Our results also suggest the extension of cOSSCIR to iodine quantification using two material decomposition.