Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data
To evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two a...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-06-01
|
| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/12/6/1467 |
| _version_ | 1797488242687213568 |
|---|---|
| author | Ronald Booij Niels R. van der Werf Marcel L. Dijkshoorn Aad van der Lugt Marcel van Straten |
| author_facet | Ronald Booij Niels R. van der Werf Marcel L. Dijkshoorn Aad van der Lugt Marcel van Straten |
| author_sort | Ronald Booij |
| collection | DOAJ |
| description | To evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two anthropomorphic phantoms in three different sizes (thorax and abdomen, QRM GmbH), in combination with a custom-built insert containing cavities filled with water, and water with 15 mg iodine/mL, were scanned on an EID-based scanner (Siemens SOMATOM Force) and on a PCD-based scanner (Siemens, NAEOTOM Alpha). VMI (range 40–100 keV) were reconstructed without an iterative reconstruction (IR) technique and with an IR strength of 60% for the EID technique (ADMIRE) and closest matching IR strengths of 50% and 75% for the PCD technique (QIR). CNR was defined as the difference in mean CT numbers of water, and water with iodine, divided by the root mean square value of the measured noise in water, and water with iodine. A two-sample t-test was performed to evaluate differences in CNR between images. A <i>p</i>-value < 0.05 was considered statistically significant. For VMI without IR and below 60 keV, the CNR of the PCD-based images at 120 and 90 kVp was up to 55% and 75% higher than the CNR of the EID-based images, respectively (<i>p</i> < 0.05). For VMI above 60 keV, CNRs of PCD-based images at both 120 and 90 kVp were up to 20% lower than the CNRs of EID-based images. Similar or improved performance of PCD-based images in comparison with EID-based images were observed for VMIs reconstructed with IR techniques. In conclusion, with PCD-CT, iodine CNR on low energy VMI (<60 keV) is better than with EID-CT. |
| first_indexed | 2024-03-09T23:59:15Z |
| format | Article |
| id | doaj.art-61c03bafe49f4b23abbd3ab4943cda09 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T23:59:15Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-61c03bafe49f4b23abbd3ab4943cda092023-11-23T16:18:39ZengMDPI AGDiagnostics2075-44182022-06-01126146710.3390/diagnostics12061467Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT DataRonald Booij0Niels R. van der Werf1Marcel L. Dijkshoorn2Aad van der Lugt3Marcel van Straten4Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsDepartment of Radiology & Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsDepartment of Radiology & Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsDepartment of Radiology & Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsDepartment of Radiology & Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The NetherlandsTo evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two anthropomorphic phantoms in three different sizes (thorax and abdomen, QRM GmbH), in combination with a custom-built insert containing cavities filled with water, and water with 15 mg iodine/mL, were scanned on an EID-based scanner (Siemens SOMATOM Force) and on a PCD-based scanner (Siemens, NAEOTOM Alpha). VMI (range 40–100 keV) were reconstructed without an iterative reconstruction (IR) technique and with an IR strength of 60% for the EID technique (ADMIRE) and closest matching IR strengths of 50% and 75% for the PCD technique (QIR). CNR was defined as the difference in mean CT numbers of water, and water with iodine, divided by the root mean square value of the measured noise in water, and water with iodine. A two-sample t-test was performed to evaluate differences in CNR between images. A <i>p</i>-value < 0.05 was considered statistically significant. For VMI without IR and below 60 keV, the CNR of the PCD-based images at 120 and 90 kVp was up to 55% and 75% higher than the CNR of the EID-based images, respectively (<i>p</i> < 0.05). For VMI above 60 keV, CNRs of PCD-based images at both 120 and 90 kVp were up to 20% lower than the CNRs of EID-based images. Similar or improved performance of PCD-based images in comparison with EID-based images were observed for VMIs reconstructed with IR techniques. In conclusion, with PCD-CT, iodine CNR on low energy VMI (<60 keV) is better than with EID-CT.https://www.mdpi.com/2075-4418/12/6/1467X-ray computed tomographyiodinedual-energyphoton-counting CTimage quality |
| spellingShingle | Ronald Booij Niels R. van der Werf Marcel L. Dijkshoorn Aad van der Lugt Marcel van Straten Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data Diagnostics X-ray computed tomography iodine dual-energy photon-counting CT image quality |
| title | Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data |
| title_full | Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data |
| title_fullStr | Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data |
| title_full_unstemmed | Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data |
| title_short | Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data |
| title_sort | assessment of iodine contrast to noise ratio in virtual monoenergetic images reconstructed from dual source energy integrating ct and photon counting ct data |
| topic | X-ray computed tomography iodine dual-energy photon-counting CT image quality |
| url | https://www.mdpi.com/2075-4418/12/6/1467 |
| work_keys_str_mv | AT ronaldbooij assessmentofiodinecontrasttonoiseratioinvirtualmonoenergeticimagesreconstructedfromdualsourceenergyintegratingctandphotoncountingctdata AT nielsrvanderwerf assessmentofiodinecontrasttonoiseratioinvirtualmonoenergeticimagesreconstructedfromdualsourceenergyintegratingctandphotoncountingctdata AT marcelldijkshoorn assessmentofiodinecontrasttonoiseratioinvirtualmonoenergeticimagesreconstructedfromdualsourceenergyintegratingctandphotoncountingctdata AT aadvanderlugt assessmentofiodinecontrasttonoiseratioinvirtualmonoenergeticimagesreconstructedfromdualsourceenergyintegratingctandphotoncountingctdata AT marcelvanstraten assessmentofiodinecontrasttonoiseratioinvirtualmonoenergeticimagesreconstructedfromdualsourceenergyintegratingctandphotoncountingctdata |