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


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
16 Jun 2020
Historique:
entrez: 24 6 2020
pubmed: 24 6 2020
medline: 26 8 2020
Statut: ppublish

Résumé

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%.

Identifiants

pubmed: 32570359
pii: SHTI200135
doi: 10.3233/SHTI200135
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article

Langues

eng

Pagination

123-127

Auteurs

Marja Fleitmann (M)

Institute of Medical Informatics, University of Lübeck.

Kira Soika (K)

Institute of Medical Informatics, University of Lübeck.

Andreas Martin Stroth (AM)

Department of Radiology and Nuclear Medicine, UKSH Lübeck.

Jan Gerlach (J)

Department of Radiology and Nuclear Medicine, UKSH Lübeck.

Alexander Fürschke (A)

Department of Radiology and Nuclear Medicine, UKSH Lübeck.

Peter Hunold (P)

Department of Radiology and Nuclear Medicine, UKSH Lübeck.

Jörg Barkhausen (J)

Department of Radiology and Nuclear Medicine, UKSH Lübeck.

Arpad Bischof (A)

Department of Radiology and Nuclear Medicine, UKSH Lübeck.
IMAGE Information Systems Europe, Rostock.

Heinz Handels (H)

Institute of Medical Informatics, University of Lübeck.

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