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

Authors
 Chae Jung Park  ;  Ki Wook Kim  ;  Ho-Joon Lee  ;  Myeong-Jin Kim  ;  Jinna Kim 
Citation
 Korean Journal of Radiology, Vol.19(5) : 957-964, 2018 
Journal Title
 Korean Journal of Radiology 
ISSN
 1229-6929 
Issue Date
2018
Keywords
Computed tomography ; Filtered back projection ; Image quality ; Image reconstruction ; Knowledge-based iterative reconstruction ; Parotid gland ; Parotid tumor ; Radiation dosage
Abstract
Objective: 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.
Files in This Item:
T201802572.pdf Download
DOI
10.3348/kjr.2018.19.5.957
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Ki Wook(김기욱)
Kim, Myeong Jin(김명진) ORCID logo https://orcid.org/0000-0001-7949-5402
Kim, Jinna(김진아) ORCID logo https://orcid.org/0000-0002-9978-4356
Park, Chae Jung(박채정) ORCID logo https://orcid.org/0000-0002-5567-8658
Lee, Ho Joon(이호준)
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URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/163661
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