Systematic assessment of coronary calcium detectability and quantification on four generations of CT reconstruction techniques: a patient and phantom study.
Calcification
Deep learning
Image reconstruction
Imaging
Phantoms
Radiation dosage
Tomography
X-ray computed
Journal
The international journal of cardiovascular imaging
ISSN: 1875-8312
Titre abrégé: Int J Cardiovasc Imaging
Pays: United States
ID NLM: 100969716
Informations de publication
Date de publication:
Jan 2023
Jan 2023
Historique:
received:
03
06
2022
accepted:
24
07
2022
entrez:
4
1
2023
pubmed:
5
1
2023
medline:
7
1
2023
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 36598691
doi: 10.1007/s10554-022-02703-y
pii: 10.1007/s10554-022-02703-y
doi:
Substances chimiques
Calcium
SY7Q814VUP
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
221-231Informations de copyright
© 2022. The Author(s).
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