TY - JOUR
T1 - Systematic assessment of coronary calcium detectability and quantification on four generations of CT reconstruction techniques
T2 - a patient and phantom study
AU - Dobrolinska, M. M.
AU - van Praagh, G. D.
AU - Oostveen, L. J.
AU - Poelhekken, K.
AU - Greuter, M. J. W.
AU - Fleischmann, D.
AU - Willemink, M. J.
AU - de Lange, F.
AU - Slart, R. H. J. A.
AU - Leiner, T.
AU - van der Werf, N. R.
N1 - Funding Information:
M.M.D. received the “EACVI Research Grant 2020” and “Specialised Research Fellowship 2019 Grant from “Club 30” and Polish Cardiac Society”.
Publisher Copyright:
© 2022, The Author(s).
PY - 2023/1
Y1 - 2023/1
N2 - In computed tomography, coronary artery calcium (CAC) scores are influenced by image reconstruction. The effect of a newly introduced deep learning-based reconstruction (DLR) on CAC scoring in relation to other algorithms is unknown. The aim of this study was to evaluate the effect of four generations of image reconstruction techniques (filtered back projection (FBP), hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), and DLR) on CAC detectability, quantification, and risk classification. First, CAC detectability was assessed with a dedicated static phantom containing 100 small calcifications varying in size and density. Second, CAC quantification was assessed with a dynamic coronary phantom with velocities equivalent to heart rates of 60–75 bpm. Both phantoms were scanned and reconstructed with four techniques. Last, scans of fifty patients were included and the Agatston calcium score was calculated for all four reconstruction techniques. FBP was used as a reference. In the phantom studies, all reconstruction techniques resulted in less detected small calcifications, up to 22%. No clinically relevant quantification changes occurred with different reconstruction techniques (less than 10%). In the patient study, the cardiovascular risk classification resulted, for all reconstruction techniques, in excellent agreement with the reference (κ = 0.96–0.97). However, MBIR resulted in significantly higher Agatston scores (61 (5.5–435.0) vs. 81.5 (9.25–435.0); p < 0.001) and 6% reclassification rate. In conclusion, HIR and DLR reconstructed scans resulted in similar Agatston scores with excellent agreement and low-risk reclassification rate compared with routine reconstructed scans (FBP). However, caution should be taken with low Agatston scores, as based on phantom study, detectability of small calcifications varies with the used reconstruction algorithm, especially with MBIR and DLR.
AB - In computed tomography, coronary artery calcium (CAC) scores are influenced by image reconstruction. The effect of a newly introduced deep learning-based reconstruction (DLR) on CAC scoring in relation to other algorithms is unknown. The aim of this study was to evaluate the effect of four generations of image reconstruction techniques (filtered back projection (FBP), hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), and DLR) on CAC detectability, quantification, and risk classification. First, CAC detectability was assessed with a dedicated static phantom containing 100 small calcifications varying in size and density. Second, CAC quantification was assessed with a dynamic coronary phantom with velocities equivalent to heart rates of 60–75 bpm. Both phantoms were scanned and reconstructed with four techniques. Last, scans of fifty patients were included and the Agatston calcium score was calculated for all four reconstruction techniques. FBP was used as a reference. In the phantom studies, all reconstruction techniques resulted in less detected small calcifications, up to 22%. No clinically relevant quantification changes occurred with different reconstruction techniques (less than 10%). In the patient study, the cardiovascular risk classification resulted, for all reconstruction techniques, in excellent agreement with the reference (κ = 0.96–0.97). However, MBIR resulted in significantly higher Agatston scores (61 (5.5–435.0) vs. 81.5 (9.25–435.0); p < 0.001) and 6% reclassification rate. In conclusion, HIR and DLR reconstructed scans resulted in similar Agatston scores with excellent agreement and low-risk reclassification rate compared with routine reconstructed scans (FBP). However, caution should be taken with low Agatston scores, as based on phantom study, detectability of small calcifications varies with the used reconstruction algorithm, especially with MBIR and DLR.
UR - http://www.scopus.com/inward/record.url?scp=85135847661&partnerID=8YFLogxK
U2 - 10.1007/s10554-022-02703-y
DO - 10.1007/s10554-022-02703-y
M3 - Article
C2 - 36598691
SN - 1569-5794
VL - 39
SP - 221
EP - 231
JO - International Journal of Cardiovascular Imaging
JF - International Journal of Cardiovascular Imaging
IS - 1
ER -