Room: AAPM ePoster Library
Purpose:
Contemporary small animal radiation platforms are equipped with cone beam CT (CBCT) for image-guided radiation experiments. The CBCT images are used for treatment planning, which requires accurate quantitative voxel information. In this work, we implemented multi-energy (ME) CBCT using multiple scans and a simultaneous image reconstruction and material decomposition algorithm on a preclinical CBCT platform to derive voxel density and material composition for dose calculation and other advanced applications.
Methods:
X-ray CBCT projection images of a microCT calibration phantom and a cadaver mouse were acquired with 50, 60 and 70 kVp in multiple scans on a Precision Smart platform. The simultaneous CBCT reconstruction and material decomposition method solved an optimization problem to determine x-ray attenuation coefficients in each kVp, electron density relative to water (rED), and elemental composition (EC). The objective function contained a tight-frame regularization term for image quality, a data fidelity term to ensure consistency between the attenuation coefficients and the projection images, and a self-consistency term to ensure agreement between attenuation coefficients, and rED and EC. The EC was further subject to the constraint of a sparse representation of the material’s ECs in a dictionary. The optimization problem was solved by an alternating-direction minimization scheme.
Results:
In the microCT phantom, mean relative error of rED and EC were 2.19% and 4.40% comparing to the ground truth values. Average decomposition errors of H, O, Ca elements were 5.31%, 6.61%, and 1.30%, respectively. The algorithm were able to derive rED and EC images for the cadaver mouse case.
Conclusion:
Our work demonstrated feasibility to implement ME-CBCT on a preclinical CBCT system and to quantitatively derive information useful for dose calculation and other applications in pre-clinical radiation experiments.
Not Applicable / None Entered.
Not Applicable / None Entered.