Characterization of Urinary Stone Composition by Use of Whole-body, Photon-counting Detector CT

Abstract

Rational and Objectives To investigate the performance of a whole-body, photon-counting-detector (PCD) CT system in differentiating urinary stone composition. Materials and Methods Eighty-seven human urinary stones with pure mineral composition were placed in 4 anthropomorphic water phantoms (35 to 50 cm lateral dimension) and scanned on a PCD-CT system at 100, 120 and 140 kV. For each phantom size, tube current was selected to match CTDIvol to our clinical practice. Energy thresholds at [25, 65], [25, 70] and[25,75] keV for 100, 120 and 140 kV, respectively, were used to generate dual energy images. Each stone was automatically segmented using in-house software; CT number ratios were calculated and used to differentiate stone types in an ROC analysis. A comparison with second and third generation dual-source, dual-energy CT scanners with conventional energy integrating detectors (EID) was performed under matching conditions. Results For all investigated settings and smaller phantoms, perfect separation between uric acid (UA) and non-uric acid (NUA) stones was achieved (AUC = 1). For smaller phantoms, performance in differentiation of calcium oxalate (CaOx) and apatite (APA) stones was also similar between the 3 scanners: for the 35 cm phantom size, AUC values of 0.76, 0.79 and 0.80 were recorded for the second and third generation EID-CT and for the PCD-CT, respectively. For larger phantoms, PCD-CT and the third generation EID-CT outperformed the second generation EID-CT for both differentiation tasks: for a 50 cm phantom size and a UA/NUA differentiating task, AUC values of 0.63, 0.95 and 0.99 were recorded for the second and third generations EID-CT and for the PCD-CT, respectively. Conclusion PCD-CT provides comparable performance to state-of-the art EID-CT in differentiating urinary stone composition.

Detection and Characterization of Renal Stones by Using Photon-Counting–based CT

“…An ex vivo characterization of PCD CT performance to differentiate stone composition reported that PCD CT outperformed second-generation dual-source dual-energy CT for larger patients (18). Because the same tube potential and energy bins are used for all patient sizes with the multienergy PCD CT system, patient size does not affect characterization performance.…”

“…Unenhanced spiral scanning was performed by using the same parameters as the EID dual-energy CT examination, with the exception of the following: 140-kV tube potential, 25- and 75-keV energy thresholds, and 32 × 0.5 mm collimation with no automatic exposure control. The two energy thresholds were selected to give approximately equal numbers of photons in the two energy bins (bin 1 and bin 2) for patients with 35–40 cm lateral width (17,18). Tube current was adjusted so that the volumetric CT dose index before acquisition of the image matched that used for the EID examination.…”

“…PCD images were reconstructed by using data corresponding to the low-energy threshold (T L ; 25–140 keV), bin 1 (25–75 keV), and bin 2 (75–140 keV) with identical thicknesses, reconstruction intervals, and kernels (18). …”

Basic principles and clinical potential of photon-counting detector CT

“…Several authors assessed the performance of spectral photon-counting CT for detection and characterization of kidney stones, which is another established dual-energy CT application [9,15,30]. They found comparable overall performance to state-of-the art energy-integrating detector CT in differentiating stone composition, while photon-counting Fig.…”

Task-driven optimization of the non-spectral mode of photon counting CT for intracranial hemorrhage assessment

“…In this case, polychromatic x-ray photons make equal contributions to the PCD outputs, as long as their energies are above the threshold energy. Based on the x-ray detection mechanism used in PCD, PCCT has three attractive features that could potentially benefit ICH imaging: first, the equal energy weighting scheme in PCD could lead to super ior CNR compared with EID (Tapiovaara andWagner 1985, Pourmorteza et al 2017); second, the direct x-ray conversion mechanism in PCD could lead to improved spatial resolution compared with EID (Leng et al 2016, Yu et al 2016, Leng et al 2017; third, the energy resolving capability of PCD could potentially be utilized to implement the optimal photon weighting scheme described in Tapiovaara and Wagner (1985), Cahn et al (1999), Giersch et al (2004), Shikhaliev (2008), Schmidt (2009), to reduce beam hardening artifacts (Yu et al 2016, Symons et al 2018, or to obtain quantitative tissue information (Roessl and Proksa 2007, Roessl et al 2011, Shikhaliev and Fritz 2011, Wang et al 2011, Schmidt et al 2017, Ferrero et al 2018.…”