Lee HJ, Kim J, Kim KW, Lee SK, Yoon JS. Feasibility of a low-dose orbital CT protocol with a knowledge-based iterative model reconstruction algorithm for evaluating Graves' orbitopathy.
Clin Imaging 2018;
51:327-331. [PMID:
29960265 DOI:
10.1016/j.clinimag.2018.06.018]
[Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 04/17/2018] [Accepted: 06/20/2018] [Indexed: 10/28/2022]
Abstract
PURPOSE
To evaluate the clinical feasibility of low-dose orbital CT with a knowledge-based iterative model reconstruction (IMR) algorithm for evaluating Graves' orbitopathy.
METHODS
Low-dose orbital CT was performed with a CTDIvol of 4.4 mGy. In 12 patients for whom prior or subsequent non-low-dose orbital CT data obtained within 12 months were available, background noise, SNR, and CNR were compared for images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose4), and IMR and non-low-dose CT images. Comparison of clinically relevant measurements for Graves' orbitopathy, such as rectus muscle thickness and retrobulbar fat area, was performed in a subset of 6 patients who underwent CT for causes other than Graves' orbitopathy, by using the Wilcoxon signed-rank test.
RESULTS
The lens dose estimated from skin dosimetry on a phantom was 4.13 mGy, which was on average 59.34% lower than that of the non-low-dose protocols. Image quality in terms of background noise, SNR, and CNR was the best for IMR, followed by non-low-dose CT, iDose4, and FBP, in descending order. A comparison of clinically relevant measurements revealed no significant difference in the retrobulbar fat area and the inferior and medial rectus muscle thicknesses between the low-dose and non-low-dose CT images.
CONCLUSIONS
Low-dose CT with IMR may be performed without significantly affecting the measurement of prognostic parameters for Graves' orbitopathy while lowering the lens dose and image noise.
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