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Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study
Korean Journal of Radiology ; : 957-964, 2018.
Article in English | WPRIM | ID: wpr-717626
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.
Subject(s)

Full text: Available Index: WPRIM (Western Pacific) Main subject: Parotid Gland / Radiation Dosage / Weights and Measures / Image Processing, Computer-Assisted / Tomography, X-Ray Computed / Feasibility Studies / Prospective Studies / Signal-To-Noise Ratio / Noise Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Korean Journal of Radiology Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Parotid Gland / Radiation Dosage / Weights and Measures / Image Processing, Computer-Assisted / Tomography, X-Ray Computed / Feasibility Studies / Prospective Studies / Signal-To-Noise Ratio / Noise Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Korean Journal of Radiology Year: 2018 Type: Article