Evidence map›Paper›PMID 38346874›Full record

ArticleBMJ open2024

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

Howell Fu, Alex Novak, Dennis Robert, Shamie Kumar, Swetha Tanamala, Jason Oke, Kanika Bhatia, Ruchir Shah, Andrea Romsauerova, Tilak Das and 14 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06018545 (AI Assisted Reader Evaluation in Acute CT Head Interpretation), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06018545 completednot on this map

AI Assisted Reader Evaluation in Acute CT Head Interpretation

TypeobservationalSponsorOxford University Hospitals NHS TrustRan2023 to 2025Enrolled33ConditionsIntracranial Hemorrhages, Acute Ischemic Stroke, Hydrocephalus, Cerebral InfarctionArmsGround truthing, Reading
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors at 14 institutions in 4 countries.

Howell FuOxford University Hospitals NHS Foundation Trust, Oxford, UK.ORCID 0000-0002-0582-9518
Alex NovakEmergency Medicine Research Oxford, Oxford University Hospitals NHS Foundation Trust, Oxford, UK Alex.Novak@ouh.nhs.uk.
Dennis RobertQure.AI, Bangalore, India.
Shamie KumarQure.AI, Bangalore, India.
Swetha TanamalaQure.AI, Bangalore, India.
Jason OkeDepartment of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Kanika BhatiaOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Ruchir ShahOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Andrea RomsauerovaOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Tilak DasDepartment of Clinical Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Abdalá EspinosaEmergency Medicine Research Oxford, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Mariusz Tadeusz GrzedaSchool of Biomedical Science, King's College London, London, UK.
Mariapaola NarboneGuy's and St Thomas' Hospitals NHS Trust, London, UK.
Rahul DharmadhikariNorthumbria Healthcare NHS Foundation Trust, Northumberland, UK.
Mark HarrisonEmergency Department, Northumbria Specialist Emergency Care Hospital, Cramlington, UK.
Kavitha VimalesvaranClinical Scientific Computing, Guy's and St Thomas' NHS Foundation Trust, London, UK.ORCID 0000-0003-2236-7279
Jane GoochCollege of Health, Psychology & Social Care, University of Derby, Derby, UK.
Nicholas WoznitzaRadiology Department, University College London Hospitals NHS Foundation Trust, London, UK.ORCID 0000-0001-9598-189X
Nabeeha SalikRAIQC Ltd, Oxford, UK.
Alan CampbellRadiology Department, University College London Hospitals NHS Foundation Trust, London, UK.
Farhaan KhanOxford University Hospitals NHS Foundation Trust, Oxford, UK.
David J LoweNHS Greater Glasgow and Clyde, Glasgow, UK.ORCID 0000-0003-4866-2049
Haris ShuaibClinical Scientific Computing, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Sarim AtherOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Oxford University Hospitals NHS Trust · GBQarshi University · PKGuy's and St Thomas' NHS Foundation Trust · GBCambridge University Hospitals NHS Foundation Trust · GBCanterbury Christ Church University · GBKing's College London · GBNHS Greater Glasgow and Clyde · GBNorthumbria Healthcare NHS Foundation Trust · GBNorthumbria Specialist Emergency Care Hospital · GBScience Oxford · GBSt Thomas' Hospital · GBUniversity College London Hospitals NHS Foundation Trust · GBUniversity of Derby · GBUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA 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.

Indexed as

Artificial IntelligenceState MedicineAllied Health PersonnelHumansIntracranial HemorrhagesRetrospective StudiesClinical Decision-MakingComputed tomographyHead & neck imagingIntracerebral Hemorrhage

Identifiers

PMID38346874
PMCPMC10862304
OpenAlexW4392730069

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.