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A preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial 무뎌교는
DC Field | Value | Language |
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dc.contributor.author | 심학준 | - |
dc.date.accessioned | 2025-07-09T08:40:35Z | - |
dc.date.available | 2025-07-09T08:40:35Z | - |
dc.date.issued | 2024-06 | - |
dc.identifier.issn | 0007-1285 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/206564 | - |
dc.description.abstract | Objectives: To investigate the usefulness of super-resolution deep learning reconstruction (SR-DLR) with cardiac option in the assessment of image quality in patients with stent-assisted coil embolization, coil embolization, and flow-diverting stent placement compared with other image reconstructions. Methods: This single-centre retrospective study included 50 patients (mean age, 59 years; range, 44-81 years; 13 men) who were treated with stent-assisted coil embolization, coil embolization, and flow-diverting stent placement between January and July 2023. The images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (IR), and SR-DLR. The objective image analysis included image noise in the Hounsfield unit (HU), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and full width at half maximum (FWHM). Subjectively, two radiologists evaluated the overall image quality for the visualization of the flow-diverting stent, coil, and stent. Results: The image noise in HU in SR-DLR was 6.99 ± 1.49, which was significantly lower than that in images reconstructed with FBP (12.32 ± 3.01) and hybrid IR (8.63 ± 2.12) (P < .001). Both the mean SNR and CNR were significantly higher in SR-DLR than in FBP and hybrid IR (P < .001 and P < .001). The FWHMs for the stent (P < .004), flow-diverting stent (P < .001), and coil (P < .001) were significantly lower in SR-DLR than in FBP and hybrid IR. The subjective visual scores were significantly higher in SR-DLR than in other image reconstructions (P < .001). Conclusions: SR-DLR with cardiac option is useful for follow-up imaging in stent-assisted coil embolization and flow-diverting stent placement in terms of lower image noise, higher SNR and CNR, superior subjective image analysis, and less blooming artifact than other image reconstructions. Advances in knowledge: SR-DLR with cardiac option allows better visualization of the peripheral and smaller cerebral arteries. SR-DLR with cardiac option can be beneficial for CT imaging of stent-assisted coil embolization and flow-diverting stent. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | British Institute of Radiology | - |
dc.relation.isPartOf | BRITISH JOURNAL OF RADIOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Adult | - |
dc.subject.MESH | Aged | - |
dc.subject.MESH | Aged, 80 and over | - |
dc.subject.MESH | Deep Learning* | - |
dc.subject.MESH | Embolization, Therapeutic / methods | - |
dc.subject.MESH | Endovascular Procedures* / methods | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Intracranial Aneurysm* / diagnostic imaging | - |
dc.subject.MESH | Intracranial Aneurysm* / surgery | - |
dc.subject.MESH | Intracranial Aneurysm* / therapy | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Retrospective Studies | - |
dc.subject.MESH | Signal-To-Noise Ratio | - |
dc.subject.MESH | Stents* | - |
dc.title | A preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial 무뎌교는 | - |
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 | Hyunjung Kim | - |
dc.contributor.googleauthor | Pil-Hyun Jeon | - |
dc.contributor.googleauthor | Sang-Hyun Jeon | - |
dc.contributor.googleauthor | Sung-Jin Cha | - |
dc.contributor.googleauthor | Jae-Kyun Ryu | - |
dc.contributor.googleauthor | Won Beom Jung | - |
dc.contributor.googleauthor | Hackjoon Shim | - |
dc.contributor.googleauthor | Sung Min Ko | - |
dc.contributor.googleauthor | Jin Woo Kim | - |
dc.identifier.doi | 10.1093/bjr/tqae117 | - |
dc.contributor.localId | A02215 | - |
dc.relation.journalcode | J00417 | - |
dc.identifier.eissn | 1748-880X | - |
dc.identifier.pmid | 38917414 | - |
dc.subject.keyword | CT angiography | - |
dc.subject.keyword | blooming artifact | - |
dc.subject.keyword | image reconstruction | - |
dc.subject.keyword | intracranial aneurysm | - |
dc.subject.keyword | super-resolution deep learning reconstruction | - |
dc.contributor.alternativeName | Shim, Hack Joon | - |
dc.contributor.affiliatedAuthor | 심학준 | - |
dc.citation.volume | 97 | - |
dc.citation.number | 1160 | - |
dc.citation.startPage | 1492 | - |
dc.citation.endPage | 1500 | - |
dc.identifier.bibliographicCitation | BRITISH JOURNAL OF RADIOLOGY, Vol.97(1160) : 1492-1500, 2024-06 | - |
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