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Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Song, Seunghyun | - |
| dc.contributor.author | Cho, Eun-Suk | - |
| dc.contributor.author | Kim, YuSik | - |
| dc.contributor.author | Ahn, Chulkyun | - |
| dc.contributor.author | Suh, Sang Hyun | - |
| dc.contributor.author | Chung, Jae-Joon | - |
| dc.contributor.author | Kim, Jong Hyo | - |
| dc.contributor.author | 정재준 | - |
| dc.date.accessioned | 2026-06-10T05:55:31Z | - |
| dc.date.available | 2026-06-10T05:55:31Z | - |
| dc.date.created | 2026-06-01 | - |
| dc.date.issued | 2026-05 | - |
| dc.identifier.issn | 1229-6929 | - |
| dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/212480 | - |
| dc.description.abstract | Objective: To evaluate the feasibility of cerebral computed tomography angiography (CTA) obtained with reduced iodine and low radiation at 70 kVp and the effect of deep learning-based augmented contrast enhancement (DL-ACE) and denoising (DL-DN) algorithms on the CTA quality. Materials and Methods: In this prospective study, 47 healthy volunteers (male:female, 31:16; mean age +/- standard deviation, 57.8 +/- 10.9 years) were randomly assigned to one of three CTA protocols: Group A (n = 16; 100 kVp, 40 mL of 350 mgI/mL), Group B (n = 16; 70 kVp, 40 mL of 270 mgI/mL), and Group C (n = 15; 70 kVp, 28 mL of 270 mgI/mL [ultralow iodine]), with an injection rate of 2.5 mL/s for all. Images were reconstructed using filtered back projection (FBP), and images in Groups B and C were additionally reconstructed using DL-ACE and DL-DN. Arterial attenuation, image noise, contrast-to-noise ratio (CNR), and subjective image quality were compared among five image sets. Results: Compared with Group A, Groups B and C received 23.7% lower radiation doses. With FBP, arterial attenuation was significantly higher in Groups B (435.8 +/- 50.2 Hounsfield units [HU]) and C (391.8 +/- 52.1 HU) than in Group A (321.1 +/- 47.4 HU) (P < 0.001), while CNR did not differ significantly (Group A, 19.9 +/- 4.7; Group B, 20.3 +/- 3.8; and Group C, 18.4 +/- 4.6) due to higher image noise in Groups B and C. After applying DL-ACE and DL-DN in Groups B and C, arterial attenuation increased by 45.4% and image noise decreased by 34.5%, resulting in significantly higher arterial attenuation, CNR, and subjective image quality compared with Group A (P < 0.001). Conclusion: Cerebral CTA at 70-kVp using ultralow iodine enhanced arterial attenuation but increased image noise compared with the 100-kVp CTA protocol. DL-ACE and DL-DN significantly increased arterial attenuation and reduced image noise, resulting in higher CNR and better subjective image quality. | - |
| dc.format | application/pdf | - |
| dc.language | English | - |
| dc.publisher | Korean Society of Radiology | - |
| dc.relation.isPartOf | KOREAN JOURNAL OF RADIOLOGY | - |
| dc.relation.isPartOf | KOREAN JOURNAL OF RADIOLOGY | - |
| dc.subject.MESH | Adult | - |
| dc.subject.MESH | Aged, 80 and over | - |
| dc.subject.MESH | Cerebral Angiography / methods | - |
| dc.subject.MESH | Computed Tomography Angiography* / methods | - |
| dc.subject.MESH | Contrast Media / administration & dosage | - |
| dc.subject.MESH | Deep Learning | - |
| dc.subject.MESH | Female | - |
| dc.subject.MESH | Humans | - |
| dc.subject.MESH | Iodine / administration & dosage | - |
| dc.subject.MESH | Male | - |
| dc.subject.MESH | Radiation Dosage | - |
| dc.subject.MESH | Radiographic Image Interpretation, Computer-Assisted* / methods | - |
| dc.title | Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study | - |
| dc.type | Article | - |
| dc.contributor.googleauthor | Song, Seunghyun | - |
| dc.contributor.googleauthor | Cho, Eun-Suk | - |
| dc.contributor.googleauthor | Kim, YuSik | - |
| dc.contributor.googleauthor | Ahn, Chulkyun | - |
| dc.contributor.googleauthor | Suh, Sang Hyun | - |
| dc.contributor.googleauthor | Chung, Jae-Joon | - |
| dc.contributor.googleauthor | Kim, Jong Hyo | - |
| dc.identifier.doi | 10.3348/kjr.2025.1520 | - |
| dc.relation.journalcode | J02884 | - |
| dc.identifier.eissn | 2005-8330 | - |
| dc.identifier.pmid | 42062228 | - |
| dc.subject.keyword | Cerebral artery | - |
| dc.subject.keyword | Computed tomography angiography | - |
| dc.subject.keyword | Contrast media | - |
| dc.subject.keyword | Radiation | - |
| dc.subject.keyword | Deep learning | - |
| dc.contributor.affiliatedAuthor | Song, Seunghyun | - |
| dc.contributor.affiliatedAuthor | Cho, Eun-Suk | - |
| dc.contributor.affiliatedAuthor | Kim, YuSik | - |
| dc.contributor.affiliatedAuthor | Suh, Sang Hyun | - |
| dc.contributor.affiliatedAuthor | Chung, Jae-Joon | - |
| dc.identifier.scopusid | 2-s2.0-105037175972 | - |
| dc.identifier.wosid | 001753439400009 | - |
| dc.citation.volume | 27 | - |
| dc.citation.number | 5 | - |
| dc.citation.startPage | 461 | - |
| dc.citation.endPage | 470 | - |
| dc.identifier.bibliographicCitation | KOREAN JOURNAL OF RADIOLOGY, Vol.27(5) : 461-470, 2026-05 | - |
| dc.identifier.rimsid | 93087 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 1 | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordAuthor | Cerebral artery | - |
| dc.subject.keywordAuthor | Computed tomography angiography | - |
| dc.subject.keywordAuthor | Contrast media | - |
| dc.subject.keywordAuthor | Radiation | - |
| dc.subject.keywordAuthor | Deep learning | - |
| dc.subject.keywordPlus | LOW TUBE VOLTAGE | - |
| dc.subject.keywordPlus | IMAGE-QUALITY | - |
| dc.subject.keywordPlus | KVP | - |
| dc.subject.keywordPlus | REDUCTION | - |
| dc.subject.keywordPlus | VOLUME | - |
| dc.type.docType | Article | - |
| dc.identifier.kciid | ART003328446 | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.relation.journalWebOfScienceCategory | Radiology, Nuclear Medicine & Medical Imaging | - |
| dc.relation.journalResearchArea | Radiology, Nuclear Medicine & Medical Imaging | - |
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