Highlights
- •Cluster analysis (CA) can be used to summarize data of CT patient dose registries.
- •Different CA methods were tested, obtaining the best results with the Ward method.
- •CA highlights the combinations of exposure parameters most used in practice.
- •Outliers analysis associated with CA allows to investigate anomalous high dose values.
Abstract
Purpose
This study investigated the benefits of implementing a cluster analysis technique
to extract relevant information from a computed tomography (CT) dose registry archive.
Methods
A CT patient dose database consisting of about 12,000 examinations and 29,000 single
scans collected from three CT systems was interrogated. The database was divided into
six subsets according to the equipment and the reference phantoms in the definition
of the dose indicators. Hierarchical (single, average, and complete linkage, Ward)
and not hierarchical (K-means) clustering methods were implemented using R software.
The suitable number of clusters for each CT system was determined by analysing the
dendrogram, the within clusters sum of squares, and the cluster content. Summary statistics
were produced for each cluster, and the outliers of the dose indicator distribution
were investigated.
Results
Ward clustering identified the most common combinations of scanning parameters for
each group. The optimal number of clusters for each CT equipment system ranged from
5 to 15. The main diagnostic applications were then extracted from each cluster. Outlier
analysis of the dose indicator distribution of each cluster revealed potential improper
settings that resulted in increased patient dose.
Conclusions
Clustering methods applied to CT patient dose archives provide a quick and effective
overview of the main combinations of currently used exposure parameters and the consequences
for dose indicator distributions, also when protocol labels and/or study descriptions
are not homogeneous.
Graphical abstract

Graphical Abstract
Keywords
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Article info
Publication history
Published online: March 29, 2019
Accepted:
March 17,
2019
Received in revised form:
February 19,
2019
Received:
November 30,
2018
Identification
Copyright
© 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.