Korean Journal of Radiology

  • 제19권5호
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  • Pages.957-964
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  • 2018
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  • 1229-6929(pISSN)
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  • 2005-8330(eISSN)
대한영상의학회 (The Korean Society of Radiology)
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Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study

  • Park, Chae Jung (Department of Radiology, Yonsei University College of Medicine) ;
  • Kim, Ki Wook (Department of Radiology, Yonsei University College of Medicine) ;
  • Lee, Ho-Joon (Department of Radiology, Yonsei University College of Medicine) ;
  • Kim, Myeong-Jin (Department of Radiology, Yonsei University College of Medicine) ;
  • Kim, Jinna (Department of Radiology, Yonsei University College of Medicine)
  • 투고 : 2017.09.09
  • 심사 : 2018.02.10
  • 발행 : 2018.10.01
⟨ 이전 논문 다음 논문 ⟩

초록

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 ($iDose^4$; 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, $4.24{\pm}3.77$; $iDose^4$, $8.77{\pm}3.85$; FBP, $11.73{\pm}4.06$; p = 0.037 [IMR vs. $iDose^4$] and p < 0.001 [IMR vs. FBP]) was significantly lower and SNR (IMR, $23.93{\pm}7.49$; $iDose^4$, $10.20{\pm}3.29$; FBP, $7.33{\pm}2.03$; p = 0.011 [IMR vs. $iDose^4$] 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 ($25.76{\pm}11.88$ vs. $9.02{\pm}3.18$, 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.

키워드

과제정보

연구 과제 주관 기관 : Yonsei University College of Medicine

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