Automated Vetting and Protocolling of MRI Examinations (AutoProMpt)
Automated Vetting and Protocoling of MRI Examination Referrals Using Explainable Large Language Models (LLM) With Retrieval Augmented Generation (RAG) (XLLM) Techniques- A Multi-stage Study
Background Vetting and assigning of protocols to MRI scan requests are usually carried out by radiologists and radiographers. This way is both time-consuming and prone to error. Recent improvements in Artificial Intelligence (Al) like Large Language Models (LLMs) are better at processing human language. It could be used to improve tasks like image reporting and assigning protocols in radiology.
Approach Firstly, I will find out about the delays in the way this is currently done. I will use a survey to find out the perceptions of radiologists to both the current process and the proposed Al intervention.
I will then use an LLM to undertake referral and protocol tasks. I will compare its performance to the performance of clinical specialists and established guidelines.
I will present the explanation reports to radiologists and ask them if they can be understood and whether they can be trusted as clinically reliable.
Impact My research could help reduce the workload and time radiologists spend dealing with scan requests. The findings will help design future research to consider application in real clinical settings.
Studieoversigt
Status
Intervention / Behandling
Undersøgelsestype
Tilmelding (Anslået)
Kontakter og lokationer
Studiekontakt
- Navn: Edozie Iweka, MSc (Dist)
- Telefonnummer: +441225386989
- E-mail: eoi29@bath.ac.uk
Deltagelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
- Barn
- Voksen
- Ældre voksen
Tager imod sunde frivillige
Køn, der er berettiget til at studere
Prøveudtagningsmetode
Studiebefolkning
This study is multi-stage multi-center research involving retrospective MRI referral data of patients and collected across three NHS Foundation Trusts in the United Kingdom.
Beskrivelse
Inclusion Criteria:
- Patients who have had MRI examinations in the study sites
- Patients with MRI referrals submitted through electronic referral systems
- Patients whose MRI referrals were vetted and protocolled prior to examination
Exclusion Criteria:
- Patients who have had other imaging examination outside the MRI
- Patients with paper referrals scanned in electronic referral systems
- Patients for MRI examinations without vetting and protocolling
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
- Observationsmodeller: COHORT
- Tidsperspektiver: RETROSPECTIVE
Kohorter og interventioner
Gruppe / kohorte |
Intervention / Behandling |
|---|---|
|
Group
Adult Patients undergoing MRI examinations |
No Intervention as this is an experiment on retrospective collected referral data |
Hvad måler undersøgelsen?
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Accuracy
Tidsramme: Through study completion, an average of 2 years
|
Accuracy of pretrained LLMs+RAG in automating vetting and protocolling of MRI examination referrals. |
Through study completion, an average of 2 years
|
Sekundære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Clinical Usefulness
Tidsramme: Through study completion, an average of 2 years
|
Clinical usefulness of explainability reports on the performance of pretrained LLMs+RAG in automating vetting and protocolling of MRI examination referrals. |
Through study completion, an average of 2 years
|
Samarbejdspartnere og efterforskere
Sponsor
Samarbejdspartnere
Datoer for undersøgelser
Studer store datoer
Studiestart (Anslået)
Primær færdiggørelse (Anslået)
Studieafslutning (Anslået)
Datoer for studieregistrering
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først opslået (Faktiske)
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Andre undersøgelses-id-numre
- 18376
Plan for individuelle deltagerdata (IPD)
Planlægger du at dele individuelle deltagerdata (IPD)?
IPD-planbeskrivelse
No patient identifiable data will be collected from this study. All collected data will be held by the sponsor institution, University of Bath as per local research data policy.
Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter
Studerer et amerikansk FDA-reguleret lægemiddelprodukt
Studerer et amerikansk FDA-reguleret enhedsprodukt
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