Open AccessEvaluation of an integrated 3D‐printed phantom for coronary CT angiography using iterative reconstruction algorithm
Author(s) -
Abdullah Kamarul A.,
McEntee Mark F.,
Reed Warren,
Kench Peter L.
Publication year - 2020
Publication title -
journal of medical radiation sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 18
eISSN - 2051-3909
pISSN - 2051-3895
DOI - 10.1002/jmrs.387
Subject(s) - imaging phantom , image quality , image noise , iterative reconstruction , noise (video) , scanner , contrast to noise ratio , radon transform , nuclear medicine , algorithm , signal to noise ratio (imaging) , tomography , computer science , medicine , radiology , image (mathematics) , artificial intelligence , telecommunications
3D‐printed imaging phantoms are now increasingly available and used for computed tomography (CT) dose optimisation study and image quality analysis. The aim of this study was to evaluate the integrated 3D‐printed cardiac insert phantom when evaluating iterative reconstruction (IR) algorithm in coronary CT angiography (CCTA) protocols. Methods The 3D‐printed cardiac insert phantom was positioned into a chest phantom and scanned with a 16‐slice CT scanner. Acquisitions were performed with CCTA protocols using 120 kVp at four different tube currents, 300, 200, 100 and 50 mA (protocols A, B, C and D, respectively). The image data sets were reconstructed with a filtered back projection (FBP) and three different IR algorithm strengths. The image quality metrics of image noise, signal–noise ratio (SNR) and contrast–noise ratio (CNR) were calculated for each protocol. Results Decrease in dose levels has significantly increased the image noise, compared to FBP of protocol A ( P < 0.001). As a result, the SNR and CNR were significantly decreased ( P < 0.001). For FBP, the highest noise with poor SNR and CNR was protocol D with 19.0 ± 1.6 HU, 18.9 ± 2.5 and 25.1 ± 3.6, respectively. For IR algorithm, the highest strength (AIDR3D strong ) yielded the lowest noise with excellent SNR and CNR. Conclusions The use of IR algorithm and increasing its strengths have reduced noise significantly and thus increased the SNR and CNR when compared to FBP. Therefore, this integrated 3D‐printed phantom approach could be used for dose optimisation study and image quality analysis in CCTA protocols.