Renal stone characterization using high resolution imaging mode on a photon counting detector CT system

A. Ferrero; R. Gutjahr; A. Henning; S. Kappler; A. Halaweish; D. Abdurakhimova; Z. Peterson; J. Montoya; S. Leng; C. McCollough

doi:10.1117/12.2255651

9 March 2017 Renal stone characterization using high resolution imaging mode on a photon counting detector CT system

A. Ferrero, R. Gutjahr, A. Henning, S. Kappler, A. Halaweish, D. Abdurakhimova, Z. Peterson, J. Montoya, S. Leng, C. McCollough

Author Affiliations +

Proceedings Volume 10132, Medical Imaging 2017: Physics of Medical Imaging; 101323J (2017) https://doi.org/10.1117/12.2255651
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

In addition to the standard-resolution (SR) acquisition mode, a high-resolution (HR) mode is available on a research photon-counting-detector (PCD) whole-body CT system. In the HR mode each detector consists of a 2x2 array of 0.225 mm x 0.225 mm subpixel elements. This is in contrast to the SR mode that consists of a 4x4 array of the same subelements, and results in 0.25 mm isotropic resolution at iso-center for the HR mode. In this study, we quantified ex vivo the capabilities of the HR mode to characterize renal stones in terms of morphology and mineral composition. Forty pure stones - 10 uric acid (UA), 10 cystine (CYS), 10 calcium oxalate monohydrate (COM) and 10 apatite (APA) - and 14 mixed stones were placed in a 20 cm water phantom and scanned in HR mode, at radiation dose matched to that of routine dual-energy stone exams. Data from micro CT provided a reference for the quantification of morphology and mineral composition of the mixed stones. The area under the ROC curve was 1.0 for discriminating UA from CYS, 0.89 for CYS vs COM and 0.84 for COM vs APA. The root mean square error (RMSE) of the percent UA in mixed stones was 11.0% with a medium-sharp kernel and 15.6% with the sharpest kernel. The HR showed qualitatively accurate characterization of stone morphology relative to micro CT.

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A. Ferrero, R. Gutjahr, A. Henning, S. Kappler, A. Halaweish, D. Abdurakhimova, Z. Peterson, J. Montoya, S. Leng, and C. McCollough "Renal stone characterization using high resolution imaging mode on a photon counting detector CT system", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101323J (9 March 2017); https://doi.org/10.1117/12.2255651

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