Multicolour imaging with spectral photon-counting CT: a phantom study

Abstract Background To evaluate the feasibility of multicolour quantitative imaging with spectral photon-counting computed tomography (SPCCT) of different mixed contrast agents. Methods Phantoms containing eleven tubes with mixtures of varying proportions of two contrast agents (i.e. two selected fr...

Full description

Bibliographic Details
Main Authors: Salim Si-Mohamed, Daniel Bar-Ness, Monica Sigovan, Valérie Tatard-Leitman, David P. Cormode, Pratap C. Naha, Philippe Coulon, Lucie Rascle, Ewald Roessl, Michal Rokni, Ami Altman, Yoad Yagil, Loic Boussel, Philippe Douek
Format: Article
Language:English
Published: SpringerOpen 2018-10-01
Series:European Radiology Experimental
Subjects:
Online Access:http://link.springer.com/article/10.1186/s41747-018-0063-4
_version_ 1818217590920577024
author Salim Si-Mohamed
Daniel Bar-Ness
Monica Sigovan
Valérie Tatard-Leitman
David P. Cormode
Pratap C. Naha
Philippe Coulon
Lucie Rascle
Ewald Roessl
Michal Rokni
Ami Altman
Yoad Yagil
Loic Boussel
Philippe Douek
author_facet Salim Si-Mohamed
Daniel Bar-Ness
Monica Sigovan
Valérie Tatard-Leitman
David P. Cormode
Pratap C. Naha
Philippe Coulon
Lucie Rascle
Ewald Roessl
Michal Rokni
Ami Altman
Yoad Yagil
Loic Boussel
Philippe Douek
author_sort Salim Si-Mohamed
collection DOAJ
description Abstract Background To evaluate the feasibility of multicolour quantitative imaging with spectral photon-counting computed tomography (SPCCT) of different mixed contrast agents. Methods Phantoms containing eleven tubes with mixtures of varying proportions of two contrast agents (i.e. two selected from gadolinium, iodine or gold nanoparticles) were prepared so that the attenuation of each tube was about 280 HU. Scans were acquired at 120 kVp and 100 mAs using a five-bin preclinical SPCCT prototype, generating conventional, water, iodine, gadolinium and gold images. The correlation between prepared and measured concentrations was assessed using linear regression. The cross-contamination was measured for each material as the root mean square error (RMSE) of its concentration in the other material images, where no signal was expected. The contrast-to-noise ratio (CNR) relative to a phosphate buffered saline tube was calculated for each contrast agent. Results The solutions had similar attenuations (279 ± 10 HU, mean ± standard deviation) and could not be differentiated on conventional images. However, a distinction was observed in the material images within the same samples, and the measured and prepared concentrations were strongly correlated (R2 ≥ 0.97, 0.81 ≤ slope ≤ 0.95, -0.68 ≤ offset ≤ 0.89 mg/mL). Cross-contamination in the iodine images for the mixture of gold and gadolinium contrast agents (RMSE = 0.34 mg/mL) was observed. CNR for 1 mg/mL of contrast agent was better for the mixture of iodine and gadolinium (CNRiodine = 3.20, CNRgadolinium = 2.80) than gold and gadolinium (CNRgadolinium = 1.67, CNRgold = 1.37). Conclusions SPCCT enables multicolour quantitative imaging. As a result, it should be possible to perform imaging of multiple uptake phases of a given tissue/organ within a single scan by injecting different contrast agents sequentially.
first_indexed 2024-12-12T07:10:18Z
format Article
id doaj.art-a35c8afc639a40aead2cae487ed9b92c
institution Directory Open Access Journal
issn 2509-9280
language English
last_indexed 2024-12-12T07:10:18Z
publishDate 2018-10-01
publisher SpringerOpen
record_format Article
series European Radiology Experimental
spelling doaj.art-a35c8afc639a40aead2cae487ed9b92c2022-12-22T00:33:39ZengSpringerOpenEuropean Radiology Experimental2509-92802018-10-012111010.1186/s41747-018-0063-4Multicolour imaging with spectral photon-counting CT: a phantom studySalim Si-Mohamed0Daniel Bar-Ness1Monica Sigovan2Valérie Tatard-Leitman3David P. Cormode4Pratap C. Naha5Philippe Coulon6Lucie Rascle7Ewald Roessl8Michal Rokni9Ami Altman10Yoad Yagil11Loic Boussel12Philippe Douek13University Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonUniversity Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonUniversity Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonUniversity Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonDepartment of Radiology, University of PennsylvaniaDepartment of Radiology, University of PennsylvaniaCT Clinical Science, PhilipsUniversity Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonPhilips GmbH Innovative Technologies, Research LaboratoriesGlobal Advanced Technologies, CT, PhilipsGlobal Advanced Technologies, CT, PhilipsGlobal Advanced Technologies, CT, PhilipsUniversity Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonUniversity Claude Bernard Lyon1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-LyonAbstract Background To evaluate the feasibility of multicolour quantitative imaging with spectral photon-counting computed tomography (SPCCT) of different mixed contrast agents. Methods Phantoms containing eleven tubes with mixtures of varying proportions of two contrast agents (i.e. two selected from gadolinium, iodine or gold nanoparticles) were prepared so that the attenuation of each tube was about 280 HU. Scans were acquired at 120 kVp and 100 mAs using a five-bin preclinical SPCCT prototype, generating conventional, water, iodine, gadolinium and gold images. The correlation between prepared and measured concentrations was assessed using linear regression. The cross-contamination was measured for each material as the root mean square error (RMSE) of its concentration in the other material images, where no signal was expected. The contrast-to-noise ratio (CNR) relative to a phosphate buffered saline tube was calculated for each contrast agent. Results The solutions had similar attenuations (279 ± 10 HU, mean ± standard deviation) and could not be differentiated on conventional images. However, a distinction was observed in the material images within the same samples, and the measured and prepared concentrations were strongly correlated (R2 ≥ 0.97, 0.81 ≤ slope ≤ 0.95, -0.68 ≤ offset ≤ 0.89 mg/mL). Cross-contamination in the iodine images for the mixture of gold and gadolinium contrast agents (RMSE = 0.34 mg/mL) was observed. CNR for 1 mg/mL of contrast agent was better for the mixture of iodine and gadolinium (CNRiodine = 3.20, CNRgadolinium = 2.80) than gold and gadolinium (CNRgadolinium = 1.67, CNRgold = 1.37). Conclusions SPCCT enables multicolour quantitative imaging. As a result, it should be possible to perform imaging of multiple uptake phases of a given tissue/organ within a single scan by injecting different contrast agents sequentially.http://link.springer.com/article/10.1186/s41747-018-0063-4GadoliniumGoldIodinePhantoms (imaging)Tomography (x-ray computed)
spellingShingle Salim Si-Mohamed
Daniel Bar-Ness
Monica Sigovan
Valérie Tatard-Leitman
David P. Cormode
Pratap C. Naha
Philippe Coulon
Lucie Rascle
Ewald Roessl
Michal Rokni
Ami Altman
Yoad Yagil
Loic Boussel
Philippe Douek
Multicolour imaging with spectral photon-counting CT: a phantom study
European Radiology Experimental
Gadolinium
Gold
Iodine
Phantoms (imaging)
Tomography (x-ray computed)
title Multicolour imaging with spectral photon-counting CT: a phantom study
title_full Multicolour imaging with spectral photon-counting CT: a phantom study
title_fullStr Multicolour imaging with spectral photon-counting CT: a phantom study
title_full_unstemmed Multicolour imaging with spectral photon-counting CT: a phantom study
title_short Multicolour imaging with spectral photon-counting CT: a phantom study
title_sort multicolour imaging with spectral photon counting ct a phantom study
topic Gadolinium
Gold
Iodine
Phantoms (imaging)
Tomography (x-ray computed)
url http://link.springer.com/article/10.1186/s41747-018-0063-4
work_keys_str_mv AT salimsimohamed multicolourimagingwithspectralphotoncountingctaphantomstudy
AT danielbarness multicolourimagingwithspectralphotoncountingctaphantomstudy
AT monicasigovan multicolourimagingwithspectralphotoncountingctaphantomstudy
AT valerietatardleitman multicolourimagingwithspectralphotoncountingctaphantomstudy
AT davidpcormode multicolourimagingwithspectralphotoncountingctaphantomstudy
AT pratapcnaha multicolourimagingwithspectralphotoncountingctaphantomstudy
AT philippecoulon multicolourimagingwithspectralphotoncountingctaphantomstudy
AT lucierascle multicolourimagingwithspectralphotoncountingctaphantomstudy
AT ewaldroessl multicolourimagingwithspectralphotoncountingctaphantomstudy
AT michalrokni multicolourimagingwithspectralphotoncountingctaphantomstudy
AT amialtman multicolourimagingwithspectralphotoncountingctaphantomstudy
AT yoadyagil multicolourimagingwithspectralphotoncountingctaphantomstudy
AT loicboussel multicolourimagingwithspectralphotoncountingctaphantomstudy
AT philippedouek multicolourimagingwithspectralphotoncountingctaphantomstudy