Rational and Objectives
This study aims to investigate the performance of a whole-body, photon-counting detector (PCD) computed tomography (CT) system in differentiating urinary stone composition.
Materials and Methods
Eighty-seven human urinary stones with pure mineral composition were placed in four anthropomorphic water phantoms (35–50 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 CTDI vol (volume CT dose index) 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 a receiver operating characteristic (ROC) analysis. A comparison with second- and third-generation dual-source, dual-energy CT scanners with conventional energy integrating detectors (EIDs) was performed under matching conditions.
Results
For all investigated settings and smaller phantoms, perfect separation between uric acid and non–uric acid stones was achieved (area under the ROC curve [AUC] = 1). For smaller phantoms, performance in differentiation of calcium oxalate and apatite stones was also similar between the three 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 uric acid/non–uric acid differentiating task, AUC values of 0.63, 0.95, and 0.99 were recorded for the second- and third-generation 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.
Introduction
Conventional x-ray computed tomography (CT) systems rely on energy integrating detectors (EIDs), which generate an output signal that is proportional to the amount of energy deposited by the detected x-ray. Therefore, EID-CT systems inherently penalize the contribution of low-energy x-ray photons, which are the photons that carry the most contrast information for biological tissues and contrast media.
In recent years, a number of preclinical photon-counting detector (PCD) CT systems were introduced . Unlike EID-CT, PCD-CT systems directly convert each detected x-ray photon into individual pulses with amplitudes proportional to the energy of the incoming photon. Each individual pulse is counted separately through the use of fast electronics. The equal contribution of each detected photon regardless of their energy , combined with a reduced influence of electronic noise, results in improved contrast-to-noise ratio for PCD-CT when compared to EID-CT techniques . Additionally, PCD-CT can provide acquisitions with full field-of-view (FOV), fully registered data, stability against motion artifacts, no cross scatter from a second x-ray tube, and the ability to configure more than two energy thresholds. Finally, all measurements provide multienergy information, enabling the application of dual-energy or multienergy postprocessing algorithms for every scan.
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Materials and Methods
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Stone Samples
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PCD-CT Data Acquisition and Reconstruction
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TABLE 1
Acquisition Parameters for Photon-counting Detector Computed Tomography Scans
Tube Potential (kVp) 100 120 140 Phantom sizes scanned (cm) 35, 40 35, 40, 45 35, 40, 45, 50 Energy thresholds (keV) 25, 65 25, 70 25, 75 Detector collimation (mm) 32 × 0.5 Rotation time (s) 0.5 Helical pitch 0.6
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Image Processing and Classification Analysis
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Comparison with State-of-the-art dual-source, dual-energy CT
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Results
Dose and Image Quality for PCD-CT System
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TABLE 2
CTDI vol for Each of the Phantom Sizes Investigated
LAT Phantom Size (cm) CTDI vol (mGy) 35 13.5 40 19.9 45 33.4 50 45.0
CT, computed tomography; CTDI vol , volume CT dose index.
CTDI vol was matched among all three CT systems investigated.
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Differentiation of Kidney Stones
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TABLE 3
Absolute Difference (ΔCTR) Between Mean CTR for Uric Acid ( n = 17) vs Non–Uric Acid ( n = 70) Stones
CT System Tube Potential (kV) Phantom Size (cm) 35 40 45 50 EID-CT1 80/Sn140 0.69 0.62 100/Sn140 0.42 0.30 0.23 0.05 EID-CT2 70/Sn150 1.03 80/Sn150 0.83 0.78 90/Sn150 0.70 0.64 0.62 100/Sn150 0.58 0.50 0.52 0.43 PCD-CT 100 0.30 0.30 120 0.39 0.35 0.35 140 0.44 0.41 0.37 0.35
As phantom size increased, not all tube potential pairs could be used.
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TABLE 4
Absolute Difference (ΔCTR) Between Mean CTR for Calcium Oxalate ( n = 35) vs Apatite ( n = 30) Stones
CT System Tube Potential (kV) Phantom Size (cm) 35 40 45 50 EID-CT1 80/Sn140 0.05 0.03 \* \* 100/Sn140 0.04 0.03 0.01 0.01 EID-CT2 70/Sn150 0.11 \* \* \* 80/Sn150 0.08 0.10 \* \* 90/Sn150 0.08 0.09 0.07 \* 100/Sn150 0.04 0.08 0.08 0.08 PCD-CT 100 0.02 0.03 \* \* 120 0.04 0.03 0.04 \* 140 0.03 0.05 0.05 0.03
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Discussion
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