Key result
Automated raw-data reconstruction matches visually optimal cardiac phases in ~52% of cases.
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For coronary computed tomography (CT) angiography, the reconstruction phase finally used has to be iteratively adapted to the patient-specific heart motion to provide optimal image quality and therewith to improve the diagnostic value. The purpose was to provide an automatically raw data-based identification of the patient-specific optimal reconstruction phase for cardiac computed tomography imaging. We validated our method by a visual assessment of 65 patient data sets. In 52% of all cases, the highest correlation of the computed and the visually identified optimal reconstruction phase was ensured. In 30% of the cases, our method provided a higher image quality compared with the results obtained in routine clinical work. Our identification of the optimal reconstruction phase is a reliable method and can improve the medical workflow by providing optimal image quality with the initial image reconstruction, making multiple time-consuming image reconstructions obsolete.
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Ertel et al. (2009) studied coronary computed tomography (CT) angiography (n=65). Automatically raw data-based identification of the optimal reconstruction phase vs. Visual assessment / routine clinical work was evaluated on Highest correlation of the computed and the visually identified optimal reconstruction phase. An automated raw data-based method matched visually identified optimal reconstruction phases in 52% of cases and provided higher image quality than routine clinical work in 30% of cases.
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