Optimization of CT protocols using cause-and-effect analysis of outliers

  • Alfredo Serna /
  • David Ramos /
  • Enrique Garcia-Angosto /
  • Antonio Javier Garcia-Sanchez /
  • Maria A. Chans /
  • Jose M. Benedicto-Orovitg /
  • Vicente Puchades-Puchades /
  • Juan F. Mata-Colodro
Journal ar
Physica Medica
  • Volumen: 55
  • Fecha: 01 November 2018
  • Páginas: 1-7
  • ISSN: 1724191X 11201797
  • Source Type: Journal
  • DOI: 10.1016/j.ejmp.2018.10.010
  • Document Type: Article
  • Publisher: Associazione Italiana di Fisica Medica
© 2018 Associazione Italiana di Fisica Medica The aim of this study was to implement an outlier marking and analysis methodology to optimize CT examination protocols. CT Head examination data, including dose metrics along with technical parameters, were stored in an automatic dose registry system. Reference dose metrics distribution was obtained throughout a 1-year period. Outlier thresholds were calculated taking into account the specific shape of the distribution, by using a robust measure of the skewness; the medcouple parameter. Subsequently, outliers from a 4-month period were marked and Cause-and-Effect analysis was carried out by a multidisciplinary dose committee. Reference Dose metrics distributions were obtained from 3690 CT Head examinations. Both CTDIvol and DLP showed a certain degree of skewness, with a medcouple value of 0.05 and 0.11, respectively. All of the upper-outliers fell within 3 identifiable groups of causes, ordered by relative importance: i) inadequate protocol selection, ii) arms or objects in the field-of-view, and iii) abnormal scanning region diameter. Regarding the lower-outliers, 90% were attributable to the inclusion of additional series in the original head protocol and the remaining 10% to unknown causes. Also, a general Cause-and-Effect diagram for outliers was elaborated. While the Dose Reference Level method applies to the general performance of a CT protocol and allows comparison with other centers, the outlier method represents a step further in the optimization process. The proposed method focuses on detecting incorrect utilization of the CT, which mainly arises from inadequate knowledge of CT technology.

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