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Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study

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dc.contributor.author김기욱-
dc.contributor.author김명진-
dc.contributor.author김진아-
dc.contributor.author박채정-
dc.contributor.author이호준-
dc.date.accessioned2018-10-22T13:14:57Z-
dc.date.available2018-10-22T13:14:57Z-
dc.date.issued2018-
dc.identifier.issn1229-6929-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/163661-
dc.description.abstractObjective: The purpose of this study was to determine the diagnostic utility of low-dose CT with knowledge-based iterative model reconstruction (IMR) for the evaluation of parotid gland tumors. Materials and Methods: This prospective study included 42 consecutive patients who had undergone low-dose contrast-enhanced CT for the evaluation of suspected parotid gland tumors. Prior or subsequent non-low-dose CT scans within 12 months were available in 10 of the participants. Background noise (BN), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between non-low-dose CT images and images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose4; Philips Healthcare), and knowledge-based IMR. Subjective image quality was rated by two radiologists using five-point grading scales to assess the overall image quality, delineation of lesion contour, image sharpness, and noise. Results: With the IMR algorithm, background noise (IMR, 4.24 ± 3.77; iDose4, 8.77 ± 3.85; FBP, 11.73 ± 4.06; p = 0.037 [IMR vs. iDose4] and p < 0.001 [IMR vs. FBP]) was significantly lower and SNR (IMR, 23.93 ± 7.49; iDose4, 10.20 ± 3.29; FBP, 7.33 ± 2.03; p = 0.011 [IMR vs. iDose4] and p < 0.001 [IMR vs. FBP]) was significantly higher compared with the other two algorithms. The CNR was also significantly higher with the IMR compared with the FBP (25.76 ± 11.88 vs. 9.02 ± 3.18, p < 0.001). There was no significant difference in BN, SNR, and CNR between low-dose CT with the IMR algorithm and non-low-dose CT. Subjective image analysis revealed that IMR-generated low-dose CT images showed significantly better overall image quality and delineation of lesion contour with lesser noise, compared with those generated using FBP by both reviewers 1 and 2 (4 vs. 3; 4 vs. 3; and 3-4 vs. 2; p < 0.05 for all pairs), although there was no significant difference in subjective image quality scores between IMR-generated low-dose CT and non-low-dose CT images. Conclusion: Iterative model reconstruction-generated low-dose CT is an alternative to standard non-low-dose CT without significantly affecting image quality for the evaluation of parotid gland tumors.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherKorean Society of Radiology-
dc.relation.isPartOfKOREAN JOURNAL OF RADIOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.titleContrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine-
dc.contributor.departmentDept. of Radiology-
dc.contributor.googleauthorChae Jung Park-
dc.contributor.googleauthorKi Wook Kim-
dc.contributor.googleauthorHo-Joon Lee-
dc.contributor.googleauthorMyeong-Jin Kim-
dc.contributor.googleauthorJinna Kim-
dc.identifier.doi10.3348/kjr.2018.19.5.957-
dc.contributor.localIdA05089-
dc.contributor.localIdA00426-
dc.contributor.localIdA01022-
dc.contributor.localIdA04942-
dc.contributor.localIdA03329-
dc.relation.journalcodeJ02884-
dc.identifier.eissn2005-8330-
dc.identifier.pmid30174486-
dc.subject.keywordComputed tomography-
dc.subject.keywordFiltered back projection-
dc.subject.keywordImage quality-
dc.subject.keywordImage reconstruction-
dc.subject.keywordKnowledge-based iterative reconstruction-
dc.subject.keywordParotid gland-
dc.subject.keywordParotid tumor-
dc.subject.keywordRadiation dosage-
dc.contributor.alternativeNameKim, Ki Wook-
dc.contributor.alternativeNameKim, Myeong Jin-
dc.contributor.alternativeNameKim, Jinna-
dc.contributor.alternativeNamePark, Chae Jung-
dc.contributor.alternativeNameLee, Ho Joon-
dc.contributor.affiliatedAuthorKim, Ki Wook-
dc.contributor.affiliatedAuthorKim, Myeong Jin-
dc.contributor.affiliatedAuthorKim, Jinna-
dc.contributor.affiliatedAuthorPark, Chae Jung-
dc.contributor.affiliatedAuthorLee, Ho Joon-
dc.citation.volume19-
dc.citation.number5-
dc.citation.startPage957-
dc.citation.endPage964-
dc.identifier.bibliographicCitationKOREAN JOURNAL OF RADIOLOGY, Vol.19(5) : 957-964, 2018-
dc.identifier.rimsid58962-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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