| Title |
Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance
|
|---|---|
| Published in |
The International Journal of Cardiovascular Imaging, April 2017
|
| DOI | 10.1007/s10554-017-1137-8 |
| Pubmed ID | |
| Authors |
Yuki Tanabe, Teruhito Kido, Akira Kurata, Naoki Fukuyama, Takahiro Yokoi, Tomoyuki Kido, Teruyoshi Uetani, Mani Vembar, Amar Dhanantwari, Shinichi Tokuyasu, Natsumi Yamashita, Teruhito Mochizuki |
| Abstract |
We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The study investigated 35 patients who underwent a comprehensive cardiac CT protocol and LGE-MRI for the assessment of coronary artery disease. The CT protocol consisted of stress dynamic myocardial CT perfusion, coronary CT angiography (CTA) and LIE-CT using 256-slice CT. LIE-CT scans were acquired 5 min after CTA without additional contrast medium and reconstructed with filtered back projection (FBP), a hybrid iterative reconstruction (HIR), and IMR. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed. Sensitivity and specificity of LIE-CT for detecting MI were assessed according to the 16-segment model. Image quality scores, and diagnostic performance were compared among LIE-CT with FBP, HIR and IMR. Among the 35 patients, 139 of 560 segments showed MI in LGE-MRI. On LIE-CT with FBP, HIR, and IMR, the median SNRs were 2.1, 2.9, and 6.1; and the median CNRs were 1.7, 2.2, and 4.7, respectively. Sensitivity and specificity were 56 and 93% for FBP, 62 and 91% for HIR, and 80 and 91% for IMR. LIE-CT with IMR showed the highest image quality and sensitivity (p < 0.05). The use of IMR enables significant improvement of image quality and diagnostic performance of LIE-CT for detecting MI in comparison with FBP and HIR. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 6 | 16% |
| Researcher | 5 | 13% |
| Student > Master | 5 | 13% |
| Student > Bachelor | 4 | 11% |
| Student > Ph. D. Student | 3 | 8% |
| Other | 7 | 18% |
| Unknown | 8 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 37% |
| Computer Science | 2 | 5% |
| Engineering | 2 | 5% |
| Nursing and Health Professions | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 14 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 May 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from The International Journal of Cardiovascular Imaging
#1,116
of 2,012 outputs
Outputs of similar age
#235,006
of 324,612 outputs
Outputs of similar age from The International Journal of Cardiovascular Imaging
#29
of 60 outputs
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