Dual Energy CT Kidney Stone Differentiation in Photon Counting Computed Tomography
2017
This study evaluates the capabilities of a whole-body photon counting CT system to differentiate between four
common kidney stone materials, namely uric acid (UA), calcium oxalate monohydrate (COM), cystine (CYS),
and apatite (APA) ex vivo . Two different x-ray spectra (120 kV and 140 kV) were applied and two acquisition
modes were investigated. The macro-mode generates two energy threshold based image-volumes and two energy
bin based image-volumes. In the chesspattern-mode four energy thresholds are applied. A virtual low energy
image, as well as a virtual high energy image are derived from initial threshold-based images, while considering
their statistically correlated nature. The energy bin based images of the macro-mode, as well as the virtual
low and high energy image of the chesspattern-mode serve as input for our dual energy evaluation. The dual
energy ratio of the individually segmented kidney stones were utilized to quantify the discriminability of the
different materials. The dual energy ratios of the two acquisition modes showed high correlation for both applied
spectra. Wilcoxon-rank sum tests and the evaluation of the area under the receiver operating characteristics
curves suggest that the UA kidney stones are best differentiable from all other materials (AUC = 1.0), followed
by CYS (AUC ≈ 0.9 compared against COM and APA). COM and APA, however, are hardly distinguishable
(AUC between 0.63 and 0.76). The results hold true for the measurements of both spectra and both acquisition
modes.
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