| Literature DB >> 26202159 |
Takuya Matsuda1, Teruhito Kido2, Toshihide Itoh3, Hideyuki Saeki4, Susumu Shigemi4, Kouki Watanabe4, Tomoyuki Kido5, Shoji Aono5, Masaya Yamamoto5, Takeshi Matsuda6, Teruhito Mochizuki2.
Abstract
We evaluated the image quality and diagnostic performance of late iodine enhancement (LIE) in dual-source computed tomography (DSCT) with low kilo-voltage peak (kVp) images and a denoise filter for the detection of acute myocardial infarction (AMI) in comparison with late gadolinium enhancement (LGE) magnetic resonance imaging (MRI). The Hospital Ethics Committee approved the study protocol. Before discharge, 19 patients who received percutaneous coronary intervention after AMI underwent DSCT and 1.5 T MRI. Immediately after coronary computed tomography (CT) angiography, contrast medium was administered at a slow injection rate. LIE-CT scans were acquired via dual-energy CT and reconstructed as 100-, 140-kVp, and mixed images. An iterative three-dimensional edge-preserved smoothing filter was applied to the 100-kVp images to obtain denoised 100-kVp images. The mixed, 140-kVp, 100-kVp, and denoised 100-kVp images were assessed using contrast-to-noise ratio (CNR), and their diagnostic performance in comparison with MRI and infarcted volumes were evaluated. Three hundred four segments of 19 patients were evaluated. Fifty-three segments showed LGE in MRI. The median CNR of the mixed, 140-, 100-kVp and denoised 100-kVp images was 3.49, 1.21, 3.57, and 6.08, respectively. The median CNR was significantly higher in the denoised 100-kVp images than in the other three images (P < 0.05). The denoised 100-kVp images showed the highest diagnostic accuracy and sensitivity. The percentage of myocardium in the four CT image types was significantly correlated with the respective MRI findings. The use of a denoise filter with a low-kVp image can improve CNR, sensitivity, and accuracy in LIE-CT.Entities:
Keywords: Acute myocardial infarction; Cardiac computed tomography; Image postprocessing; Late iodine enhancement
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Year: 2015 PMID: 26202159 DOI: 10.1007/s10554-015-0716-9
Source DB: PubMed Journal: Int J Cardiovasc Imaging ISSN: 1569-5794 Impact factor: 2.357