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

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 me...

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Detalles Bibliográficos
Publicado en:Minimally Invasive Therapy & Allied Technologies Vol. 26; no. 1; pp. 31 - 39
Autores principales: Fernández-Gutiérrez, Fabiola, Wolska-Krawczyk, Malgorzata, Buecker, Arno, Houston, J. Graeme, Melzer, Andreas
Formato: algorithm equations & formulas pictorial research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Feb2017
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.