Computer-Assisted Quality Assessment of Aortic CT Angiographies for Patient-Individual Dose Adjustment

Marja Fleitmann, Kira Soika, Andreas Stroth, Jan Gerlach, Alexander Fürschke, Peter Hunold, Jörg Barkhausen, Arpad Bischof, Heinz Handels

In: Studies in health technology and informatics 270 Pages 123-127 IOS Press 6/2020.


Iodine-containing contrast agents (CA) are important for enhanced image contrast in CT imaging especially in CT angiography (CTA). CA however poses a risk to the patient since it can e.g. harm the kidneys. In clinical routine often a standard dose is applied that does not take differences between individual patients into account. We propose a method that as a preliminary stage determines excessive image contrast and CA overdosing by assessing the image contrast in CTA images obtained with the ulrich medical CT motion contrast media injector with RIS/PACS interface. A resulting CA dose recommendation is linked to a set of clinical parameters collected for each assessed patient. We used the established data set to implement an automatic classification for individual CA dose adjustment. The classification determines similar cases of new patients to take on the associated CA dose adjustment recommendation. The computation of similar patient data is based on the previously collected patient-individual parameters. The study shows that as basis for a recommendations the largest proportion of patients receive too much CA. A first evaluation of the automatic classification showed an overall error rate of 22% to recognize the correct class for CA dose adjustments using a k-NN-Classifier and a leave-one-out method. The classification's positive predictive value for correctly assigning a CA overdosing was 85.71%.

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German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz