Clinicians' perspectives on the use of artificial intelligence to triage MRI brain scans.

Journal: European journal of radiology
Published Date:

Abstract

Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and also relieve clinician workload. Validated AI tools can mitigate the delays in reporting scans by flagging time-sensitive and actionable findings. In this study, we aim to investigate current stakeholder perspectives and identify obstacles to integrating AI in clinical pathways. We created a survey to ascertain the perspectives of 133 clinicians across the United Kingdom regarding the acceptability of an AI tool that triages MRI brain scans into 'normal' and 'abnormal'. As part of this survey, we supplied clinicians with information on training and validation case numbers, model performance, validation using unseen data, and explainability saliency maps. With regards to the specific use case of AI in MRI brain scans, 71% of respondents preferred the use of an AI-assisted triage compared to the current system without triage, typically chronologically. Notably, information that explained and helped visualise the AI model's decision making was found to improve clinician confidence. When shown a heatmap, 60% of participants felt more confident in the AI's decision. The results of this short communication demonstrate a positive support for the implementation of AI-assistive tools in triage.

Authors

  • Munaib Din
    School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Karan Daga
    School of Biomedical Engineering & Imaging Sciences, King's College London, BMEIS, King's College London. 1 Lambeth Palace Road, UK SE1 7EU, London, UK.
  • Jihad Saoud
    School of Biomedical Engineering & Imaging Sciences, King's College London, London, the United Kingdom of Great Britain and Northern Ireland.
  • David Wood
    School of Biomedical Engineering & Imaging Sciences, King's College London, Rayne Institute, 4th Floor, Lambeth Wing, SE1 7EH, London, UK.
  • Patrick Kierkegaard
    CRUK Convergence Science Centre, Institute for Cancer Research & Imperial College London, London, the United Kingdom of Great Britain and Northern Ireland.
  • Peter Brex
    Department of Neurology, King's College Hospital NHS Foundation Trust, London, the United Kingdom of Great Britain and Northern Ireland.
  • Thomas C Booth
    School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, United Kingdom.