AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study.

Fu, H. et al. (2024) AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study. BMJ Open, 14(2), e079824. (doi: 10.1136/bmjopen-2023-079824) (PMID:38346874) (PMCID:PMC10862304)

Abstract

Introduction: A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice. Methods and analysis: A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers’ performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty. Ethics and dissemination: The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal. Trial registration number NCT06018545.

• Item Type: Articles
• Additional Information: This work was supported by the NHSX AI in Health and Care Award grant number AI_AWARD02354 via Qure AI.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lowe, Dr David
• Authors: Fu, H., Novak, A., Robert, D., Kumar, S., Tanamala, S., Oke, J., Bhatia, K., Shah, R., Romsauerova, A., Das, T., Espinosa, A., Grzeda, M. T., Narbone, M., Dharmadhikari, R., Harrison, M., Vimalesvaran, K., Gooch, J., Woznitza, N., Salik, N., Campbell, A., Khan, F., Lowe, D. J., Shuaib, H., and Ather, S.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > General Practice and Primary Care
• Journal Name: BMJ Open
• Publisher: BMJ Publishing Group
• ISSN: 2044-6055
• ISSN (Online): 2044-6055
• Published Online: 12 February 2024
• Copyright Holders: Copyright © 2024 The Authors
• First Published: First published in BMJ Open 14(2):e079824
• Publisher Policy: Reproduced under a Creative Commons License