MIDI (MR Imaging Abnormality Deep Learning Identification)
NCT ID: NCT04368481
Last Updated: 2024-04-10
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
30000 participants
OBSERVATIONAL
2019-04-01
2025-03-31
Brief Summary
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Detailed Description
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Furthermore, there is a wide variation in the management of incidental findings (IFs) discovered in 'healthy volunteers.' The routine reporting of 'healthy volunteer' scans by a radiologist poses logistical and financial challenges. It would be valuable to devise automated strategies to reliably and accurately identify IFs, potentially reducing the number of scans requiring routine radiological review by up to 90%, thus increasing the feasibility of implementing a routine reporting strategy.
Deep learning is a novel technique in computer science that automatically learns hierarchies of relevant features directly from the raw inputs (such as MRI or CT) using multi-layered neural networks. A deep learning algorithm will be trained on a large database of head MRI scans to recognize scans with abnormalities. This algorithm will be trained to classify a subset of these scans as normal or abnormal and then tested on an independent subset to determine its validity.
If the tested neural network demonstrates high diagnostic accuracy, future research participants and patients may benefit, as not all institutions currently review their research scans for incidental findings and clinical scans may not be reported for weeks in some cases. In both research and clinical scenarios, an algorithm could rapidly identify abnormal pathology and prioritize scans for reporting.
In summary, the aim is to develop a deep learning abnormality detection algorithm for use in both research and clinical settings.
Conditions
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Study Design
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OTHER
OTHER
Eligibility Criteria
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Inclusion Criteria
* \> 18 years old
Exclusion Criteria
* No consent for future use of the research images held within the historic database stored at The Centre for Neuroimaging Sciences (Kings College London).
* Poor image quality
18 Years
ALL
No
Sponsors
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King's College London
OTHER
King's College Hospital NHS Trust
OTHER
Responsible Party
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Principal Investigators
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Thomas Booth
Role: PRINCIPAL_INVESTIGATOR
King's College Hospital NHS Trust
Locations
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Princess Royal University Hospital, King's College Hospital NHS Foundation Trust
Orpington, Kent, United Kingdom
Buckinghamshire Healthcare Nhs Trust (Stoke Mandeville)
Aylesbury, , United Kingdom
Mid and South Essex NHS Foundation Trust
Basildon, , United Kingdom
Bedfordshire Hospitals Nhs Foundation Trust
Bedford, , United Kingdom
Betsi Cadwaladr University Health Board
Bodelwyddan, , United Kingdom
East Kent Hospitals University Nhs Foundation Trust
Canterbury, , United Kingdom
South Eastern Health & Social Care Trust
Dundonald, , United Kingdom
Queen Victoria Hospital Nhs Foundation Trust
East Grinstead, , United Kingdom
Medway Nhs Foundation Trust
Gillingham, , United Kingdom
Northern Lincolnshire and Goole Nhs Foundation Trust
Grimsby, , United Kingdom
Calderdale and Huddersfield NHS Foundation Trust
Huddersfield, , United Kingdom
The Queen Elizabeth Hospital King'S Lynn Nhs Trust
Kings Lynn, , United Kingdom
Kingston Hospital Nhs Foundation Trust
Kingston, , United Kingdom
NHS FIFE
Kirkcaldy, , United Kingdom
Forth Valley Royal Hospital
Larbert, , United Kingdom
Leeds Teaching Hospital NHS Trust
Leeds, , United Kingdom
University Hospitals of Leicester Nhs Trust
Leicester, , United Kingdom
Kings' College Hospital
London, , United Kingdom
CNS, Maudsley Hospital, South London and Maudsley NHS Foundation Trust
London, , United Kingdom
Croydon University Hospital, Croydon Health Services NHS Trust
London, , United Kingdom
Guy's Hospital, Guy's and St Thomas's NHS Foundation Trust
London, , United Kingdom
St George's Hospital, St George's University Hospital NHS Foundation Trust
London, , United Kingdom
St Thomas' Hospital, Guy's and St Thomas's NHS Foundation Trust
London, , United Kingdom
Norfolk and Norwich University Hospitals Nhs Foundation Trust
Norwich, , United Kingdom
Queen's Medical Centre University Hospital, Nottingham University Hospitals NHS Foundation Trust
Nottingham, , United Kingdom
Surrey and Sussex Healthcare Nhs Trust
Redhill, , United Kingdom
East Sussex Healthcare Nhs Trust
Saint Leonards-on-Sea, , United Kingdom
Northern Lincolnshire and Goole Nhs Foundation Trust
Scunthorpe, , United Kingdom
Mid and South Essex Nhs Foundation Trust
Southend, , United Kingdom
St George'S University Hospitals Nhs Foundation Trust
Tooting, , United Kingdom
Torbay and South Devon Nhs Foundation Trust
Torquay, , United Kingdom
Royal Cornwall Hospitals Nhs Trust
Truro, , United Kingdom
West Hertfordshire Hospitals Nhs Trust
Watford, , United Kingdom
Countries
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Central Contacts
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Facility Contacts
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Role: primary
Victoria Adell
Role: primary
Role: backup
Other Identifiers
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KCH18-197
Identifier Type: -
Identifier Source: org_study_id
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