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Proceedings Paper

Dual energy CT kidney stone differentiation in photon counting computed tomography
Author(s): R. Gutjahr; C. Polster; A. Henning; S. Kappler; S. Leng; C. H. McCollough; M. U. Sedlmair; B. Schmidt; B. Krauss; T. G. Flohr
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Paper Abstract

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.

Paper Details

Date Published: 9 March 2017
PDF: 7 pages
Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 1013237 (9 March 2017); doi: 10.1117/12.2252021
Show Author Affiliations
R. Gutjahr, Technische Univ. München (Germany)
Siemens Healthcare GmbH (Germany)
C. Polster, Siemens Healthcare GmbH (Germany)
Ludwig-Maximilians-Univ. Hospital (Germany)
A. Henning, Siemens Healthcare GmbH (Germany)
S. Kappler, Siemens Healthcare GmbH (Germany)
S. Leng, Mayo Clinic (United States)
C. H. McCollough, Mayo Clinic (United States)
M. U. Sedlmair, Siemens Healthcare GmbH (Germany)
B. Schmidt, Siemens Healthcare GmbH (Germany)
B. Krauss, Siemens Healthcare GmbH (Germany)
T. G. Flohr, Siemens Healthcare GmbH (Germany)

Published in SPIE Proceedings Vol. 10132:
Medical Imaging 2017: Physics of Medical Imaging
Thomas G. Flohr; Joseph Y. Lo; Taly Gilat Schmidt, Editor(s)

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