Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/12/2/522 |
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| author | Thomas Sartoretti Damien Racine Victor Mergen Lisa Jungblut Pascal Monnin Thomas G. Flohr Katharina Martini Thomas Frauenfelder Hatem Alkadhi André Euler |
| author_facet | Thomas Sartoretti Damien Racine Victor Mergen Lisa Jungblut Pascal Monnin Thomas G. Flohr Katharina Martini Thomas Frauenfelder Hatem Alkadhi André Euler |
| author_sort | Thomas Sartoretti |
| collection | DOAJ |
| description | 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 (CTDI<sub>vol</sub>: 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) (<i>p</i> < 0.001) by 48%. GSNRI increased from QIR-off (4.4 ± 0.8) to QIR-4 (8.2 ± 1.6) (<i>p</i> < 0.001) by 87%. Attenuation of lung parenchyma was highly comparable among reconstructions (QIR-off: −849 ± 53 HU to QIR-4: −853 ± 52 HU, <i>p</i> < 0.001). Subjective noise was best in QIR-4 (<i>p</i> < 0.001), while QIR-3 was best for sharpness and overall image quality (<i>p</i> < 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. |
| first_indexed | 2024-03-09T22:10:11Z |
| format | Article |
| id | doaj.art-2e430e83669b49c0b532c53e3620313b |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T22:10:11Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-2e430e83669b49c0b532c53e3620313b2023-11-23T19:33:34ZengMDPI AGDiagnostics2075-44182022-02-0112252210.3390/diagnostics12020522Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the LungThomas Sartoretti0Damien Racine1Victor Mergen2Lisa Jungblut3Pascal Monnin4Thomas G. Flohr5Katharina Martini6Thomas Frauenfelder7Hatem Alkadhi8André Euler9Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandInstitute of Radiation Physics (IRA), Lausanne University Hospital (CHUV), University of Lausanne (UNIL), CH-1010 Lausanne, SwitzerlandInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandInstitute of Radiation Physics (IRA), Lausanne University Hospital (CHUV), University of Lausanne (UNIL), CH-1010 Lausanne, SwitzerlandSiemens Healthcare GmbH, 91052 Forchheim, GermanyInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, CH-8091 Zurich, SwitzerlandThe 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 (CTDI<sub>vol</sub>: 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) (<i>p</i> < 0.001) by 48%. GSNRI increased from QIR-off (4.4 ± 0.8) to QIR-4 (8.2 ± 1.6) (<i>p</i> < 0.001) by 87%. Attenuation of lung parenchyma was highly comparable among reconstructions (QIR-off: −849 ± 53 HU to QIR-4: −853 ± 52 HU, <i>p</i> < 0.001). Subjective noise was best in QIR-4 (<i>p</i> < 0.001), while QIR-3 was best for sharpness and overall image quality (<i>p</i> < 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.https://www.mdpi.com/2075-4418/12/2/522phantomsimagingtomographyX-ray computedlung |
| spellingShingle | Thomas Sartoretti Damien Racine Victor Mergen Lisa Jungblut Pascal Monnin Thomas G. Flohr Katharina Martini Thomas Frauenfelder Hatem Alkadhi André Euler Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung Diagnostics phantoms imaging tomography X-ray computed lung |
| title | Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung |
| title_full | Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung |
| title_fullStr | Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung |
| title_full_unstemmed | Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung |
| title_short | Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung |
| title_sort | quantum iterative reconstruction for low dose ultra high resolution photon counting detector ct of the lung |
| topic | phantoms imaging tomography X-ray computed lung |
| url | https://www.mdpi.com/2075-4418/12/2/522 |
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