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Characterization of Urinary Stone Composition Using a Photon Counting Detector CT System with Optimized Energy Thresholds

G Michalak*, L Ren , A Ferrero , S Leng , C McCollough , Mayo Clinic, Rochester, MN

Presentations

(Thursday, 8/2/2018) 7:30 AM - 9:30 AM

Room: Room 202

Purpose: Multi-energy CT can be used to characterize urinary stone composition. In this study, we investigated the ability to characterize urinary stones with optimized energy thresholds on a photon-counting-detector CT (PCD-CT) system relative to a clinical dual-energy CT system.

Methods: Four energy thresholds for the PCD-CT system were optimized to maximize the separation of uric acid (UA) from non-UA stones and calcium oxalate (COX) from apatite (APA) stones, while taking into account noise levels in each energy bin. Eighty-eight urinary stones from humans were then scanned in 25, 35, and 45cm anthropomorphic water phantoms. Receiver operating characteristic curves were generated for each phantom size and classification task, and the area under the curve (AUC) was used as a figure of merit for performance.

Results: Simulation of the CT scan using a tube potential of 140 kV resulted in optimized energy thresholds of 25, 48, 69, and 85keV, resulting in a low energy bin of 25-48keV and a high energy bin of 85-140keV. In the 25cm phantom, the AUC’s for UA/non-UA and COX/APA classifications were 1 and 0.744 respectively. When compared with a clinical dual-energy (DE) scanner evaluated in a previous study (Siemens FLASH; 80/140Sn for 35cm and 100/140Sn for 45cm), PCD-CT performed equally in the 35cm phantom (AUC = 1 for both) but superior in the 45 cm phantom (AUC = 0.997 vs. 0.923). PCD-CT was worse at differentiating COX and APA stones in the 35cm phantom (AUC = 0.595 vs. 0.687), but better in the 45 cm phantom (AUC = 0.72 vs. 0.597).

Conclusion: In medium sized patients, either system can be used to differentiate UA/non-UA stones, with the clinical system somewhat better for COX/APA differentiation. In large patients, PCD-CT is better for both classification tasks.

Funding Support, Disclosures, and Conflict of Interest: Research reported in this report was supported by the National Institutes of Health under Award Nos. C06 RR018898 and R01 EB016966. The CT scanner used is not commercially available.

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