Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study.
10.3348/kjr.2018.19.5.957
- Author:
Chae Jung PARK
1
;
Ki Wook KIM
;
Ho Joon LEE
;
Myeong Jin KIM
;
Jinna KIM
Author Information
1. Department of Radiology, Yonsei University College of Medicine, Seoul 03722, Korea. jinna@yuhs.ac
- Publication Type:Original Article
- Keywords:
Knowledge-based iterative reconstruction;
Filtered back projection;
Computed tomography;
Parotid tumor;
Parotid gland;
Radiation dosage;
Image reconstruction;
Image quality
- MeSH:
Feasibility Studies*;
Humans;
Image Processing, Computer-Assisted;
Noise;
Parotid Gland*;
Prospective Studies;
Radiation Dosage;
Signal-To-Noise Ratio;
Tomography, X-Ray Computed*;
Weights and Measures
- From:Korean Journal of Radiology
2018;19(5):957-964
- CountryRepublic of Korea
- Language:English
-
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.
