AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study Article Swipe
Howell Fu
,
Alex Novak
,
Dennis Robert
,
Shamie Kumar
,
Swetha Tanamala
,
Jason Oke
,
Kanika Bhatia
,
Ruchir Shah
,
Andrea Romsauerova
,
Tilak Das
,
Abdalá Espinosa
,
Mariusz Grzeda
,
Mariapaola Narbone
,
Rahul Dharmadhikari
,
Mark Harrison
,
Kavitha Vimalesvaran
,
Jane Gooch
,
Nicholas Woznitza
,
Nabeeha Salik
,
Alan Campbell
,
Farhaan Khan
,
David J. Lowe
,
Haris Shuaib
,
Sarim Ather
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1136/bmjopen-2023-079824
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1136/bmjopen-2023-079824
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 .
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1136/bmjopen-2023-079824
- https://bmjopen.bmj.com/content/bmjopen/14/2/e079824.full.pdf
- OA Status
- gold
- Cited By
- 4
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392730069
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392730069Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1136/bmjopen-2023-079824Digital Object Identifier
- Title
-
AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase studyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-01Full publication date if available
- Authors
-
Howell Fu, Alex Novak, Dennis Robert, Shamie Kumar, Swetha Tanamala, Jason Oke, Kanika Bhatia, Ruchir Shah, Andrea Romsauerova, Tilak Das, Abdalá Espinosa, Mariusz Grzeda, Mariapaola Narbone, Rahul Dharmadhikari, Mark Harrison, Kavitha Vimalesvaran, Jane Gooch, Nicholas Woznitza, Nabeeha Salik, Alan Campbell, Farhaan Khan, David J. Lowe, Haris Shuaib, Sarim AtherList of authors in order
- Landing page
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https://doi.org/10.1136/bmjopen-2023-079824Publisher landing page
- PDF URL
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https://bmjopen.bmj.com/content/bmjopen/14/2/e079824.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://bmjopen.bmj.com/content/bmjopen/14/2/e079824.full.pdfDirect OA link when available
- Concepts
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Medicine, Neuroradiologist, Protocol (science), Radiology, Second opinion, Subarachnoid haemorrhage, Medical physics, Magnetic resonance imaging, Alternative medicine, Aneurysm, PathologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
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2025: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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