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A Unified Image Reconstruction Framework for Quantitative Dual- and Triple-Energy CT Imaging of Material Decomposition

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W Zhao

W Zhao1*, B Han2 , D Vernekohl3 , H Liu4 , J Min5 , G Xiong6 , L Xing7 , (1) Stanford University, Palo Alto, CA, (2) Stanford Univ School of Medicine, Stanford, CA, (3) University of Stanford, Palo Alto, CA, (4) Stanford University, Palo Alto, CA,(5) Dalio Institute of Cardiovascular Imaging NewYork-Presbyterian Hospital and, New York, NY, (6) Dalio Institute of Cardiovascular Imaging NewYork-Presbyterian Hospital and, New York, NY, (7) Stanford Univ School of Medicine, Stanford, CA


SU-K-FS4-17 (Sunday, July 30, 2017) 4:00 PM - 6:00 PM Room: Four Seasons 4

Purpose: Many clinical applications depend critically on the accurate differentiation and classification of different types of materials in patient anatomy. This work introduces, for the first time, the concept of triple-energy CT for enhanced capability of material differentiation and classification and establishes a unified framework for accurate non-linear material decomposition of both dual-and triple-energy CT.

Methods: We express a polychromatic CT projection into linear combination of two (dual-energy) or three (triple-energy) line integrals of material-selective images. The problem of material decomposition is then solved by using an optimization technique which minimizes the quadratic error between measured and estimated CT projections. The optimization problem is then solved iteratively by updating the line integrals. The proposed technique is evaluated by using various phantom measurements under different scanning protocols. Specifically, the triple-energy data acquisition is implemented at the scales of micro-CT and clinical CT imaging using the commercial “TwinBeam” dual-source DECT configuration and the fast kV switching DECT configuration. Material decomposition and quantitative comparison with a photon counting detector are also performed with the presence of a bow-tie filter. Finally, the corresponding monochromatic images are calculated for each of the nominal energies and compared to the polychromatic kV images.

Results: The results show that the proposed method provides quantitative material- and energy-selective images at realistic configurations for both dual- and triple-energy CT measurements. The decomposed virtual non-contrast image and contrast map showed quantitative accuracies comparable to that obtained using photon counting detector. Superior images are also generated using the proposed method in the presence of bow-tie filter.

Conclusion: With the use of the currently available commercial DECT configurations, a unified framework for both dual- and triple-energy CT imaging has been established for accurate extraction of material compositions. The novel technique may provide an urgently needed solution for various CT-based diagnosis and therapy applications.

Funding Support, Disclosures, and Conflict of Interest: This work was supported in part by NIH/NIBIB (No. 1R01- EB016777). The contents of this article are solely the responsibility of the authors and do not necessarily represent the official NIH views.

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