Cited 7 times in
A Novel Computed Tomography Image Reconstruction for Improving Visualization of Pulmonary Vasculature: Comparison Between Preprocessing and Postprocessing Images Using a Contrast Enhancement Boost Technique
DC Field | Value | Language |
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dc.contributor.author | 심학준 | - |
dc.date.accessioned | 2023-03-21T07:29:53Z | - |
dc.date.available | 2023-03-21T07:29:53Z | - |
dc.date.issued | 2022-09 | - |
dc.identifier.issn | 0363-8715 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/193404 | - |
dc.description.abstract | 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. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Lippincott Williams & Wilkins | - |
dc.relation.isPartOf | JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Angiography | - |
dc.subject.MESH | Contrast Media* | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Image Processing, Computer-Assisted / methods | - |
dc.subject.MESH | Signal-To-Noise Ratio | - |
dc.subject.MESH | Tomography, X-Ray Computed* / methods | - |
dc.title | A Novel Computed Tomography Image Reconstruction for Improving Visualization of Pulmonary Vasculature: Comparison Between Preprocessing and Postprocessing Images Using a Contrast Enhancement Boost Technique | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Yonsei Biomedical Research Center (연세의생명연구원) | - |
dc.contributor.googleauthor | Chuluunbaatar Otgonbaatar | - |
dc.contributor.googleauthor | Jae-Kyun Ryu | - |
dc.contributor.googleauthor | Hackjoon Shim | - |
dc.contributor.googleauthor | Pil-Hyun Jeon | - |
dc.contributor.googleauthor | Sang-Hyun Jeon | - |
dc.contributor.googleauthor | Jin Woo Kim | - |
dc.contributor.googleauthor | Sung Min Ko | - |
dc.contributor.googleauthor | Hyunjung Kim | - |
dc.identifier.doi | 10.1097/RCT.0000000000001347 | - |
dc.contributor.localId | A02215 | - |
dc.relation.journalcode | J01350 | - |
dc.identifier.eissn | 1532-3145 | - |
dc.identifier.pmid | 36103677 | - |
dc.identifier.url | https://journals.lww.com/jcat/Fulltext/2022/09000/A_Novel_Computed_Tomography_Image_Reconstruction.10.aspx | - |
dc.contributor.alternativeName | Shim, Hack Joon | - |
dc.contributor.affiliatedAuthor | 심학준 | - |
dc.citation.volume | 46 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 729 | - |
dc.citation.endPage | 734 | - |
dc.identifier.bibliographicCitation | JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, Vol.46(5) : 729-734, 2022-09 | - |
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