Dual-Energy Spectral Computed Tomography: Comparing True and
Virtual Non Contrast Enhanced Images

J 2022

Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images

SIRUCKOVA, Katerina, Petr MARCON, Marek DOSTÁL, Anna SIRUCKOVA, Premysl DOHNAL et. al.

Základní údaje

Originální název

Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images

Autoři

SIRUCKOVA, Katerina (203 Česká republika), Petr MARCON (203 Česká republika), Marek DOSTÁL (203 Česká republika, domácí), Anna SIRUCKOVA (203 Česká republika) a Premysl DOHNAL (203 Česká republika)

Vydání

Measurement Science Review, WARSAW, SCIENDO, 2022, 1335-8871

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30224 Radiology, nuclear medicine and medical imaging

Stát vydavatele

Polsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 0.900

Kód RIV

RIV/00216224:14110/22:00128483

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.2478/msr-2022-0033

UT WoS

000867916800003

Klíčová slova anglicky

Biomedical data analysis; CNR; dual-layer; SNR; spectral computed tomography; statistical analysis

Štítky

14110216, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 1. 2. 2023 13:31, Mgr. Tereza Miškechová

Anotace

V originále

Spectral computed tomography (CT) imaging is one of several image reconstruction techniques based on the use of dual-layer CT. The intensity and attenuation of the radiation are measured in relation to different wavelengths, and such a procedure results in complex three-dimensional (3D) imaging and (pseudo) color adjustment of the soft tissue. This paper compares true non-contrast (TNC) enhanced images with virtual non-contrast (VNC) enhanced ones. Virtual native images are acquired by means of spectral computed tomography, and it has been suggested that VNCs could potentially substitute real native images to reduce significantly the total radiation dose from multiphase spectral CT. A comparison was performed by defining certain parameters that represent the difference between the measured and the calculated values in the images. The parameters included the mean value and standard deviation of the computed tomography number, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). All of these items were analyzed via statistical tests using p-value. The results are interpreted and correlated with those presented by other authors, who, however, did not make an examination on a comprehensive basis - five tissues simultaneously by using a single device. Prospectively, if analogies were found between the two types of images, it would be possible to skip the TNC image, thus markedly reducing the radiation dose for the patient.

Citovat

SIRUCKOVA, Katerina, Petr MARCON, Marek DOSTÁL, Anna SIRUCKOVA a Premysl DOHNAL. Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images. Measurement Science Review. WARSAW: SCIENDO, 2022, roč. 22, č. 6, s. 261-268. ISSN 1335-8871. Dostupné z: https://dx.doi.org/10.2478/msr-2022-0033.

@article{2251947,
   author = {Siruckova, Katerina and Marcon, Petr and Dostál, Marek and Siruckova, Anna and Dohnal, Premysl},
   article_location = {WARSAW},
   article_number = {6},
   doi = {http://dx.doi.org/10.2478/msr-2022-0033},
   keywords = {Biomedical data analysis; CNR; dual-layer; SNR; spectral computed tomography; statistical analysis},
   language = {eng},
   issn = {1335-8871},
   journal = {Measurement Science Review},
   title = {Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images},
   url = {https://sciendo.com/es/article/10.2478/msr-2022-0033},
   volume = {22},
   year = {2022}
}

TY  - JOUR
ID  - 2251947
AU  - Siruckova, Katerina - Marcon, Petr - Dostál, Marek - Siruckova, Anna - Dohnal, Premysl
PY  - 2022
TI  - Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images
JF  - Measurement Science Review
VL  - 22
IS  - 6
SP  - 261-268
EP  - 261-268
PB  - SCIENDO
SN  - 13358871
KW  - Biomedical data analysis
KW  - CNR
KW  - dual-layer
KW  - SNR
KW  - spectral computed tomography
KW  - statistical analysis
UR  - https://sciendo.com/es/article/10.2478/msr-2022-0033
N2  - Spectral computed tomography (CT) imaging is one of several image reconstruction techniques based on the use of dual-layer CT. The intensity and attenuation of the radiation are measured in relation to different wavelengths, and such a procedure results in complex three-dimensional (3D) imaging and (pseudo) color adjustment of the soft tissue. This paper compares true non-contrast (TNC) enhanced images with virtual non-contrast (VNC) enhanced ones. Virtual native images are acquired by means of spectral computed tomography, and it has been suggested that VNCs could potentially substitute real native images to reduce significantly the total radiation dose from multiphase spectral CT. A comparison was performed by defining certain parameters that represent the difference between the measured and the calculated values in the images. The parameters included the mean value and standard deviation of the computed tomography number, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). All of these items were analyzed via statistical tests using p-value. The results are interpreted and correlated with those presented by other authors, who, however, did not make an examination on a comprehensive basis - five tissues simultaneously by using a single device. Prospectively, if analogies were found between the two types of images, it would be possible to skip the TNC image, thus markedly reducing the radiation dose for the patient.
ER  -

SIRUCKOVA, Katerina, Petr MARCON, Marek DOSTÁL, Anna SIRUCKOVA a Premysl DOHNAL. Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images. \textit{Measurement Science Review}. WARSAW: SCIENDO, 2022, roč.~22, č.~6, s.~261-268. ISSN~1335-8871. Dostupné z: https://dx.doi.org/10.2478/msr-2022-0033.

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