Comparison of Low Dose Performance of Photon-Counting and Energy Integrating CT

Rajagopal, Jayasai R.; Farhadi, Faraz; Solomon, Justin; Sahbaee, Pooyan; Saboury, Babak; Pritchard, William F.; Samei, Ehsan

doi:10.1016/j.acra.2020.07.033

Cited by 53 publications

(36 citation statements)

References 21 publications

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“…Third, the detectability index d' served as a metric for overall image quality because it aims to measure how well a certain material can be detected in the presence of noise (31,33). In this phantom setup, d' represents the task of detecting a uniform circular contrast object of a certain size on a uniform background.…”

Section: Image Quality Assessmentmentioning

confidence: 99%

Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance

Cester¹,

Eberhard²,

Alkadhi³

et al. 2022

Quant Imaging Med Surg

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Background: To compare task-based image quality (TB-IQ) among virtual monoenergetic images (VMI) and linear-blended images (LBI) from dual-energy CT as a function of contrast task, radiation dose, size, and lesion diameter.Methods: A TB-IQ phantom (Mercury Phantom 4.0, Sun Nuclear Corporation) was imaged on a thirdgeneration dual-source dual-energy CT with 100/Sn150 kVp at three volume CT dose levels (5, 10, 15 mGy).Three size sections (diameters 16, 26, 36 cm) with subsections for image noise and spatial resolution analysis were used. High-contrast tasks (e.g., calcium-containing stone and vascular lesion) were emulated using bone and iodine inserts. A low-contrast task (e.g., low-contrast lesion or hematoma) was emulated using a polystyrene insert. VMI at 40-190 keV and LBI were reconstructed. Noise power spectrum (NPS) determined the noise magnitude and texture. Spatial resolution was assessed using the task-transfer function (TTF) of the three inserts. The detectability index (d') served as TB-IQ metric.Results: Noise magnitude increased with increasing phantom size, decreasing dose, and decreasing VMIenergy. Overall, noise magnitude was higher for VMI at 40-60 keV compared to LBI (range of noise increase, 3-124%). Blotchier noise texture was found for low and high VMIs (40-60 keV, 130-190 keV) compared to LBI. No difference in spatial resolution was observed for high contrast tasks. d' increased with increasing dose level or lesion diameter and decreasing size. For high-contrast tasks, d' was higher at 40-80 keV and lower at high VMIs. For the low-contrast task, d' was higher for VMI at 70-90 keV and lower at 40-60 keV.Conclusions: Task-based image quality differed among VMI-energy and LBI dependent on the contrast task, dose level, phantom size, and lesion diameter. Image quality could be optimized by tailoring VMIenergy to the contrast task. Considering the clinical relevance of iodine, VMIs at 50-60 keV could be proposed as an alternative to LBI.

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Section: Image Quality Assessmentmentioning

confidence: 99%

Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance

Cester¹,

Eberhard²,

Alkadhi³

et al. 2022

Quant Imaging Med Surg

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“…Photon-counting detector computed tomography (PCD-CT) is an emerging technology that enables the direct conversion of incident x-ray photons into an electrical signal. As compared to conventional energy-integrating detector (EID)-CT systems, PCD-CT has shown improved spatial resolution, lower image noise, and higher contrast-to-noise ratio (CNR) [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. Previous studies on preclinical prototype PCD-CT suggest that these benefits can be translated to an improved diagnosis of pulmonary nodules [ 10 ] and to improvements in shape and texture image information due to the higher spatial resolution of PCD-CT as compared to EID-CT [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung

et al. 2022

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The aim of this study was to characterize image quality and to determine the optimal strength levels of a novel iterative reconstruction algorithm (quantum iterative reconstruction, QIR) for low-dose, ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) of the lung. Images were acquired on a clinical dual-source PCD-CT in the UHR mode and reconstructed with a sharp lung reconstruction kernel at different strength levels of QIR (QIR-1 to QIR-4) and without QIR (QIR-off). Noise power spectrum (NPS) and target transfer function (TTF) were analyzed in a cylindrical phantom. 52 consecutive patients referred for low-dose UHR chest PCD-CT were included (CTDIvol: 1 ± 0.6 mGy). Quantitative image quality analysis was performed computationally which included the calculation of the global noise index (GNI) and the global signal-to-noise ratio index (GSNRI). The mean attenuation of the lung parenchyma was measured. Two readers graded images qualitatively in terms of overall image quality, image sharpness, and subjective image noise using 5-point Likert scales. In the phantom, an increase in the QIR level slightly decreased spatial resolution and considerably decreased noise amplitude without affecting the frequency content. In patients, GNI decreased from QIR-off (202 ± 34 HU) to QIR-4 (106 ± 18 HU) (p < 0.001) by 48%. GSNRI increased from QIR-off (4.4 ± 0.8) to QIR-4 (8.2 ± 1.6) (p < 0.001) by 87%. Attenuation of lung parenchyma was highly comparable among reconstructions (QIR-off: −849 ± 53 HU to QIR-4: −853 ± 52 HU, p < 0.001). Subjective noise was best in QIR-4 (p < 0.001), while QIR-3 was best for sharpness and overall image quality (p < 0.001). Thus, our phantom and patient study indicates that QIR-3 provides the optimal iterative reconstruction level for low-dose, UHR PCD-CT of the lungs.

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“…Compared with previous energy-integrating detector CT systems, this first-generation dual-source full fieldof-view PCD CT can detect and weigh single photons on the basis of their energies, enabling spectral separation and multi-material decomposition (1)(2)(3). Prototype PCD CT systems have been shown to provide improved spatial resolution, dose efficiency, contrast-to-noise ratio (CNR), and lower image noise (4)(5)(6)(7)(8)(9)(10)(11)(12).…”

mentioning

confidence: 99%

Quantum Iterative Reconstruction for Abdominal Photon-counting Detector CT Improves Image Quality

et al. 2022

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Background: An iterative reconstruction (IR) algorithm was introduced for clinical photon-counting detector (PCD) CT.Purpose: To investigate the image quality and the optimal strength level of a quantum IR algorithm (QIR; Siemens Healthcare) for virtual monoenergetic images and polychromatic images (T3D) in a phantom and in patients undergoing portal venous abdominal PCD CT. Materials and Methods:In this retrospective study, noise power spectrum (NPS) was measured in a water-filled phantom. Consecutive oncologic patients who underwent portal venous abdominal PCD CT between March and April 2021 were included. Virtual monoenergetic images at 60 keV and T3D were reconstructed without QIR (QIR-off; reference standard) and with QIR at four levels (QIR 1-4; index tests). Global noise index, contrast-to-noise ratio (CNR), and voxel-wise CT attenuation differences were measured. Noise and texture, artifacts, diagnostic confidence, and overall quality were assessed qualitatively. Conspicuity of hypodense liver lesions was rated by four readers. Parametric (analyses of variance, paired t tests) and nonparametric tests (Friedman, post hoc Wilcoxon signed-rank tests) were used to compare quantitative and qualitative image quality among reconstructions. Results:In the phantom, NPS showed unchanged noise texture across reconstructions with maximum spatial frequency differences of 0.01 per millimeter. Fifty patients (mean age, 59 years 6 16 [standard deviation]; 31 women) were included. Global noise index was reduced from QIR-off to QIR-4 by 45% for 60 keV and by 44% for T3D (both, P , .001). CNR of the liver improved from QIR-off to QIR-4 by 74% for 60 keV and by 69% for T3D (both, P , .001). No evidence of difference was found in mean attenuation of fat and liver (P = .79-.84) and on a voxel-wise basis among reconstructions. Qualitatively, QIR-4 outperformed all reconstructions in every category for 60 keV and T3D (P value range, ,.001 to .01). All four readers rated QIR-4 superior to other strengths for lesion conspicuity (P value range, ,.001 to .04). Conclusion:In portal venous abdominal photon-counting detector CT, an iterative reconstruction algorithm (QIR; Siemens Healthcare) at high strength levels improved image quality by reducing noise and improving contrast-to-noise ratio and lesion conspicuity without compromising image texture or CT attenuation values.

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Comparison of Low Dose Performance of Photon-Counting and Energy Integrating CT

Cited by 53 publications

References 21 publications

Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance

Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance

Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung

Quantum Iterative Reconstruction for Abdominal Photon-counting Detector CT Improves Image Quality

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