Workflow optimisation for multimodal imaging procedures: a case of combined X-ray and MRI-guided TACE

Abstract

This study presents a framework for workflow optimisation of multimodal image-guided procedures (MIGP) based on discrete event simulation (DES). A case of a combined X-Ray and magnetic resonance image-guided transarterial chemoembolisation (TACE) is presented to illustrate the application of this method. We used a ranking and selection optimisation algorithm to measure the performance of a number of proposed alternatives to improve a current scenario. A DES model was implemented with detail data collected from 59 TACE procedures and durations of magnetic resonance imaging (MRI) diagnostic procedures usually performed in a common MRI suite. Fourteen alternatives were proposed and assessed to minimise the waiting times and improve workflow. Data analysis observed an average of 20.68 (7.68) min of waiting between angiography and MRI for TACE patients in 71.19% of the cases. Following the optimisation analysis, an alternative was identified to reduce waiting times in angiography suite up to 48.74%. The model helped to understand and detect ‘bottlenecks’ during multimodal TACE procedures, identifying a better alternative to the current workflow and reducing waiting times. Simulation-based workflow analysis provides a cost-effective way to face some of the challenges of introducing MIGP in clinical radiology, highligthed in this study.

Keywords:

• Workflow
• discrete event simulation
• optimisation
• MRI
• TACE

Acknowledgements

The authors would like to thank the staff members of the Clinic of Diagnostic and Interventional Radiology, Saarland University, Medical Centre (Homburg, Germany) for their collaboration during this study.

Disclosure statement

Fabiola Fernández-Gutiérrez, Malgorzata Wolska-Krawczyk, Arno Buecker, J. Graeme Houston and Andreas Melzer declare that they have no conflict of interest.