A Novel Computed Tomography Image Reconstruction for Improving Visualization of Pulmonary Vasculature: Comparison Between Preprocessing and Postprocessing Images Using a Contrast Enhancement Boost Technique Article Swipe
Chuluunbaatar Otgonbaatar
,
Jae‐Kyun Ryu
,
Hackjoon Shim
,
Pil-Hyun Jeon
,
Sang-Hyun Jeon
,
Jin Woo Kim
,
Sung Min Ko
,
Hyunjung Kim
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1097/rct.0000000000001347
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1097/rct.0000000000001347
Objective This study aimed to evaluate chest computed tomography (CT) angiography image quality using the contrast enhancement (CE)–boost technique compared with conventional images. Methods Forty patients who underwent contrast-enhanced chest CT were included. Combined CT angiography images of the iodinated image obtained from the subtraction of nonenhanced CT images and CT angiography images were used to generate CE-boost images. Computed tomography attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for the right and left pulmonary arteries as the central and subsegmental arteries as peripheral vessels were assessed. Subjective image quality was rated on a 5-point scale by 2 radiologists. Image quality was assessed using a paired t test. Results Computed tomography attenuation in the main pulmonary artery was significantly higher for the CE-boost images (311.05 ± 91.94) than for the conventional images (221.25 ± 61.21, P < 0.001). Similarly, the CE-boost images resulted in significantly higher CT attenuation in the subsegmental arteries (right, 305.34 ± 90.13; left, 313.05 ± 97.21) than in the conventional images (right, 218.45 ± 63.16; left, 223.89 ± 74.27). The CE-boost technique demonstrated marked improvement in the visualization of the peripheral pulmonary artery without the administration of a higher iodine delivery rate. The mean SNR and CNR were also significantly higher in the central and peripheral vessels in the CE-boost images than in the conventional images ( P < 0.001). In the subjective analysis, the image contrast and vascular contrast edge were significantly higher for the CE-boost images than for conventional images ( P < 0.001). Conclusions The CE-boost technique increases not only the visualization of peripheral arteries by improving vascular attenuation but also the SNR and CNR.
Related Topics
Concepts
Medicine
Image quality
Radiology
Contrast (vision)
Nuclear medicine
Angiography
Subtraction
Iodinated contrast
Digital subtraction angiography
Computed tomography angiography
Image noise
Tomography
Computed tomography
Artificial intelligence
Image (mathematics)
Computer science
Mathematics
Arithmetic
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1097/rct.0000000000001347
- OA Status
- green
- Cited By
- 13
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4295778788
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4295778788Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1097/rct.0000000000001347Digital Object Identifier
- Title
-
A Novel Computed Tomography Image Reconstruction for Improving Visualization of Pulmonary Vasculature: Comparison Between Preprocessing and Postprocessing Images Using a Contrast Enhancement Boost TechniqueWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-09-01Full publication date if available
- Authors
-
Chuluunbaatar Otgonbaatar, Jae‐Kyun Ryu, Hackjoon Shim, Pil-Hyun Jeon, Sang-Hyun Jeon, Jin Woo Kim, Sung Min Ko, Hyunjung KimList of authors in order
- Landing page
-
https://doi.org/10.1097/rct.0000000000001347Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://ir.ymlib.yonsei.ac.kr/handle/22282913/193404Direct OA link when available
- Concepts
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Medicine, Image quality, Radiology, Contrast (vision), Nuclear medicine, Angiography, Subtraction, Iodinated contrast, Digital subtraction angiography, Computed tomography angiography, Image noise, Tomography, Computed tomography, Artificial intelligence, Image (mathematics), Computer science, Mathematics, ArithmeticTop concepts (fields/topics) attached by OpenAlex
- Cited by
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13Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 8Per-year citation counts (last 5 years)
- References (count)
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24Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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