A Pourmorteza1,2, R Symons1,3, D S Reich1,4, M Bagheri1, T E Cork1,5, S Kappler6, S Ulzheimer6, D A Bluemke7. 1. From the Department of Radiology and Imaging Sciences (A.P., R.S., D.S.R., M.B., T.E.C., D.A.B.), National Institutes of Health Clinical Center, Bethesda, Maryland. 2. Department of Radiology and Imaging Sciences (A.P.), Emory University School of Medicine, Atlanta, Georgia. 3. Department of Imaging and Pathology (R.S.), Medical Imaging Research Centre, University Hospitals, Leuven, Belgium. 4. Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, Maryland. 5. Departments of Radiological Sciences and Bioengineering (T.E.C.), University of California, Los Angeles, Los Angeles, California. 6. Siemens (S.K., S.U.), Erlangen, Germany. 7. From the Department of Radiology and Imaging Sciences (A.P., R.S., D.S.R., M.B., T.E.C., D.A.B.), National Institutes of Health Clinical Center, Bethesda, Maryland david.bluemke@nih.gov DBluemke@rsna.org.
Abstract
BACKGROUND AND PURPOSE: Photon-counting detectors offer the potential for improved image quality for brain CT but have not yet been evaluated in vivo. The purpose of this study was to compare photon-counting detector CT with conventional energy-integrating detector CT for human brains. MATERIALS AND METHODS: Radiation dose-matched energy-integrating detector and photon-counting detector head CT scans were acquired with standardized protocols (tube voltage/current, 120 kV(peak)/370 mAs) in both an anthropomorphic head phantom and 21 human asymptomatic volunteers (mean age, 58.9 ± 8.5 years). Photon-counting detector thresholds were 22 and 52 keV (low-energy bin, 22-52 keV; high-energy bin, 52-120 keV). Image noise, gray matter, and white matter signal-to-noise ratios and GM-WM contrast and contrast-to-noise ratios were measured. Image quality was scored by 2 neuroradiologists blinded to the CT detector type. Reproducibility was assessed with the intraclass correlation coefficient. Energy-integrating detector and photon-counting detector CT images were compared using a paired t test and the Wilcoxon signed rank test. RESULTS: Photon-counting detector CT images received higher reader scores for GM-WM differentiation with lower image noise (all P < .001). Intrareader and interreader reproducibility was excellent (intraclass correlation coefficient, ≥0.86 and 0.79, respectively). Quantitative analysis showed 12.8%-20.6% less image noise for photon-counting detector CT. The SNR of photon-counting detector CT was 19.0%-20.0% higher than of energy-integrating detector CT for GM and WM. The contrast-to-noise ratio of photon-counting detector CT was 15.7% higher for GM-WM contrast and 33.3% higher for GM-WM contrast-to-noise ratio. CONCLUSIONS: Photon-counting detector brain CT scans demonstrated greater gray-white matter contrast compared with conventional CT. This was due to both higher soft-tissue contrast and lower image noise for photon-counting CT.
BACKGROUND AND PURPOSE: Photon-counting detectors offer the potential for improved image quality for brain CT but have not yet been evaluated in vivo. The purpose of this study was to compare photon-counting detector CT with conventional energy-integrating detector CT for human brains. MATERIALS AND METHODS: Radiation dose-matched energy-integrating detector and photon-counting detector head CT scans were acquired with standardized protocols (tube voltage/current, 120 kV(peak)/370 mAs) in both an anthropomorphic head phantom and 21 human asymptomatic volunteers (mean age, 58.9 ± 8.5 years). Photon-counting detector thresholds were 22 and 52 keV (low-energy bin, 22-52 keV; high-energy bin, 52-120 keV). Image noise, gray matter, and white matter signal-to-noise ratios and GM-WM contrast and contrast-to-noise ratios were measured. Image quality was scored by 2 neuroradiologists blinded to the CT detector type. Reproducibility was assessed with the intraclass correlation coefficient. Energy-integrating detector and photon-counting detector CT images were compared using a paired t test and the Wilcoxon signed rank test. RESULTS: Photon-counting detector CT images received higher reader scores for GM-WM differentiation with lower image noise (all P < .001). Intrareader and interreader reproducibility was excellent (intraclass correlation coefficient, ≥0.86 and 0.79, respectively). Quantitative analysis showed 12.8%-20.6% less image noise for photon-counting detector CT. The SNR of photon-counting detector CT was 19.0%-20.0% higher than of energy-integrating detector CT for GM and WM. The contrast-to-noise ratio of photon-counting detector CT was 15.7% higher for GM-WM contrast and 33.3% higher for GM-WM contrast-to-noise ratio. CONCLUSIONS: Photon-counting detector brain CT scans demonstrated greater gray-white matter contrast compared with conventional CT. This was due to both higher soft-tissue contrast and lower image noise for photon-counting CT.
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