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A preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial 무뎌교는

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dc.contributor.author심학준-
dc.date.accessioned2025-07-09T08:40:35Z-
dc.date.available2025-07-09T08:40:35Z-
dc.date.issued2024-06-
dc.identifier.issn0007-1285-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/206564-
dc.description.abstractObjectives: 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.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherBritish Institute of Radiology-
dc.relation.isPartOfBRITISH JOURNAL OF RADIOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAdult-
dc.subject.MESHAged-
dc.subject.MESHAged, 80 and over-
dc.subject.MESHDeep Learning*-
dc.subject.MESHEmbolization, Therapeutic / methods-
dc.subject.MESHEndovascular Procedures* / methods-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHIntracranial Aneurysm* / diagnostic imaging-
dc.subject.MESHIntracranial Aneurysm* / surgery-
dc.subject.MESHIntracranial Aneurysm* / therapy-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHRetrospective Studies-
dc.subject.MESHSignal-To-Noise Ratio-
dc.subject.MESHStents*-
dc.titleA preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial 무뎌교는-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentYonsei Biomedical Research Center (연세의생명연구원)-
dc.contributor.googleauthorChuluunbaatar Otgonbaatar-
dc.contributor.googleauthorHyunjung Kim-
dc.contributor.googleauthorPil-Hyun Jeon-
dc.contributor.googleauthorSang-Hyun Jeon-
dc.contributor.googleauthorSung-Jin Cha-
dc.contributor.googleauthorJae-Kyun Ryu-
dc.contributor.googleauthorWon Beom Jung-
dc.contributor.googleauthorHackjoon Shim-
dc.contributor.googleauthorSung Min Ko-
dc.contributor.googleauthorJin Woo Kim-
dc.identifier.doi10.1093/bjr/tqae117-
dc.contributor.localIdA02215-
dc.relation.journalcodeJ00417-
dc.identifier.eissn1748-880X-
dc.identifier.pmid38917414-
dc.subject.keywordCT angiography-
dc.subject.keywordblooming artifact-
dc.subject.keywordimage reconstruction-
dc.subject.keywordintracranial aneurysm-
dc.subject.keywordsuper-resolution deep learning reconstruction-
dc.contributor.alternativeNameShim, Hack Joon-
dc.contributor.affiliatedAuthor심학준-
dc.citation.volume97-
dc.citation.number1160-
dc.citation.startPage1492-
dc.citation.endPage1500-
dc.identifier.bibliographicCitationBRITISH JOURNAL OF RADIOLOGY, Vol.97(1160) : 1492-1500, 2024-06-
Appears in Collections:
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers

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