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.
Studieoversikt
Status
Intervensjon / Behandling
Studietype
Registrering (Antatt)
Kontakter og plasseringer
Studiekontakt
- Navn: Edozie Iweka, MSc (Dist)
- Telefonnummer: +441225386989
- E-post: eoi29@bath.ac.uk
Deltakelseskriterier
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
- Barn
- Voksen
- Eldre voksen
Tar imot friske frivillige
Kjønn som er kvalifisert for studier
Prøvetakingsmetode
Studiepopulasjon
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 studiet utformet?
Designdetaljer
- Observasjonsmodeller: COHORT
- Tidsperspektiver: RETROSPECTIVE
Kohorter og intervensjoner
Gruppe / Kohort |
Intervensjon / Behandling |
|---|---|
|
Group
Adult Patients undergoing MRI examinations |
No Intervention as this is an experiment on retrospective collected referral data |
Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
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 |
Tiltaksbeskrivelse |
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
|
Samarbeidspartnere og etterforskere
Sponsor
Samarbeidspartnere
Studierekorddatoer
Studer hoveddatoer
Studiestart (Antatt)
Primær fullføring (Antatt)
Studiet fullført (Antatt)
Datoer for studieregistrering
Først innsendt
Først innsendt som oppfylte QC-kriteriene
Først lagt ut (Faktiske)
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
Siste oppdatering sendt inn som oppfylte QC-kriteriene
Sist bekreftet
Mer informasjon
Begreper knyttet til denne studien
Andre studie-ID-numre
- 18376
Plan for individuelle deltakerdata (IPD)
Planlegger du å dele individuelle deltakerdata (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.
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