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Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Yongcheol | - |
| dc.contributor.author | Yoon, Hyuck-Jun | - |
| dc.contributor.author | Suh, Jon | - |
| dc.contributor.author | Kang, Si-Hyuck | - |
| dc.contributor.author | Lim, Young-Hyo | - |
| dc.contributor.author | Jang, Duck Hyun | - |
| dc.contributor.author | Park, Jae Hyoung | - |
| dc.contributor.author | Shin, Eun-Seok | - |
| dc.contributor.author | Park, Hanbit | - |
| dc.contributor.author | Ahn, Jung-Min | - |
| dc.contributor.author | Bae, Jang-Whan | - |
| dc.contributor.author | Lee, Jang Hoon | - |
| dc.contributor.author | Oh, Jun-Hyok | - |
| dc.contributor.author | Kang, Do-Yoon | - |
| dc.contributor.author | Kweon, Jihoon | - |
| dc.contributor.author | Jo, Min-Woo | - |
| dc.contributor.author | Yun, Sung-Cheol | - |
| dc.contributor.author | Park, Duk-Woo | - |
| dc.contributor.author | Kim, Young-Hak | - |
| dc.contributor.author | Park, Seung-Jung | - |
| dc.date.accessioned | 2025-03-13T05:30:19Z | - |
| dc.date.available | 2025-03-13T05:30:19Z | - |
| dc.date.issued | 2025-01 | - |
| dc.identifier.issn | 1936-8798 | - |
| dc.identifier.issn | 1876-7605 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/206769 | - |
| dc.description.abstract | Background: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully automated) provides real-time, objective, and reproducible quantitative analysis of coronary angiography without requiring additional time or labor. Objectives: This study aimed to evaluate the efficacy of AI-QCA-assisted percutaneous coronary intervention (PCI) compared to optical coherence tomography (OCT)-guided PCI in terms of post-PCI results. Methods: This trial enrolled 400 patients with significant coronary artery disease undergoing PCI from 13 participating centers in South Korea. Patients were randomized in a 1:1 ratio to either AI-QCA-assisted or OCT-guided PCI. The primary endpoint was the post-PCI minimal stent area (MSA) assessed by OCT. The noninferiority of AI-QCA-assisted PCI to OCT-guided PCI regarding the post-PCI MSA was tested with a noninferiority margin of 0.8 mm(2). Results: </bold>A total of 395 patients (199 in the AI-QCA group and 196 in the OCT group) were included in the primary endpoint analysis. The post-PCI MSA was 6.3 +/- 2.2 mm(2) in the AI-QCA group and 6.2 +/- 2.2 mm(2) in the OCT group (difference, -0.16; 95% CI: -0.59 to 0.28; P for noninferiority < 0.001). Other OCT-defined endpoints, such as stent underexpansion (50.8% [101/199] vs 54.6% [107/196]; P = 0.48), dissection (15.6% [31/199] vs 12.8% [25/196]; P = 0.42), and untreated reference segment disease (15.1% [30/199] vs 13.3% [26/196]; P = 0.61), were not significantly different between groups, except for a higher incidence of stent malapposition in the AI-QCA group (13.6% [27/199] vs 5.6 [11/196]; P = 0.007). Conclusions: This study demonstrated the noninferiority of AI-QCA-assisted PCI to OCT-guided PCI in achieving MSA with comparable OCT-defined endpoints. (Fully Automated Quantitative Coronary Angiography Versus Optical Coherence Tomography Guidance for Coronary Stent Implantation [FLASH]; NCT05388357). | - |
| dc.format.extent | 11 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Elsevier BV | - |
| dc.title | Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1016/j.jcin.2024.10.025 | - |
| dc.identifier.scopusid | 2-s2.0-85209749979 | - |
| dc.identifier.wosid | 001418030500001 | - |
| dc.identifier.bibliographicCitation | JACC: Cardiovascular Interventions, v.18, no.2, pp 187 - 197 | - |
| dc.citation.title | JACC: Cardiovascular Interventions | - |
| dc.citation.volume | 18 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 187 | - |
| dc.citation.endPage | 197 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Cardiovascular System & Cardiology | - |
| dc.relation.journalWebOfScienceCategory | Cardiac & Cardiovascular Systems | - |
| dc.subject.keywordPlus | ELUTING STENT IMPLANTATION | - |
| dc.subject.keywordPlus | INTRAVASCULAR ULTRASOUND | - |
| dc.subject.keywordPlus | IMPACT | - |
| dc.subject.keywordPlus | IVUS | - |
| dc.subject.keywordPlus | INTERVENTION | - |
| dc.subject.keywordPlus | MULTICENTER | - |
| dc.subject.keywordPlus | LESION | - |
| dc.subject.keywordPlus | AREA | - |
| dc.subject.keywordAuthor | artificial intelligence | - |
| dc.subject.keywordAuthor | coronary imaging | - |
| dc.subject.keywordAuthor | coronary intervention | - |
| dc.subject.keywordAuthor | quantitative coronary angiography | - |
| dc.subject.keywordAuthor | stent(s) | - |
| dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S1936879824014225?via%3Dihub | - |
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