Breast CancerIntelliScanNCT03829423
An Enhanced Artificial Intelligence Breast MRI Interpretation System
A study testing Breast MRI interpretation in people with Breast Cancer, run by Jamil Kanfoud.
Trial summary
Interpretation of breast MR images is a very time-consuming process and places a great burden on breast radiologists. This project aims to develop a technical solution that addresses this healthcare challenge by developing a system that is able to automatically interpret breast MR images in order to aid the… Read more about this study
- Who is it for?
- Ages 20 years and older, women only
- Conditions the study is for
- Breast Cancer
- What is being tested?
- Breast MRI interpretation
- How many people
- 1,526 participants
- Where
- No sites listed yet
- Study dates
- Apr 2019to Jul 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Breast MRI scans
- MRI examinations undertaken at partner NHS Trust in the UK
- MRI examinations undertaken on the MRI system currently installed at partner NHS Trust site (since 2008)
Who cannot join
- Incomplete breast MRI datasets
- Breast MRI without lesions
- Breast lesion on MRI not biopsied
Trial locations and contacts
No sites are listed yet.
About this study
Official title: A Comparative Single-centre Study to Evaluate an Enhanced Artificial Intelligence Breast MRI Interpretation System in Women Over 20 With Breast Lesions
Interpretation of breast MR images is a very time-consuming process and places a great burden on breast radiologists. This project aims to develop a technical solution that addresses this healthcare challenge by developing a system that is able to automatically interpret breast MR images in order to aid the radiologist in their diagnosis.
Read the detailed description
Breast cancer is the most common type of cancer in women worldwide, with nearly 1.7 million new cases diagnosed in 2015. In the UK, one in five cases of breast cancer results in a fatality. The IntelliScan project aims to develop a technological solution that addresses a significant healthcare challenge. IntelliScan will develop a software system that will be able to interpret breast MR images automatically in order to identify potential breast cancers.
Regular MRI screening of the breast is offered to women from the age of 20, who are at higher risk of developing breast cancer. MR image sequences provide a large amount of information to the radiologist and the interpretation of images is a manual process, which is very time consuming. The high number of women eligible for MRI screening combined with the amount of data provided by MRI scans places a great burden on healthcare systems. Therefore, automatisation of this process would greatly relieve this burden and also has the potential to provide more accurate diagnoses.
In this first study, the system's user interface as well as the algorithm will be developed using existing MRI scans. Existing MRI scans with known breast anomalies will be used to develop the decision-making basis for the algorithm. The system will then be tested using existing MRI scans without information about possible anomalies and results will be compared to results from the software system currently in use. In addition, the user-friendliness of the system's user interface will also be evaluated.
- Conditions
- Breast Cancer
- Being tested
- Breast MRI interpretation
- Keywords
- artificial intelligence, magnetic resonance imaging, breast cancer
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Breast MRI interpretationDiagnostic test
Analysis and interpretation of breast MRI sequences by a specially developed breast MRI interpretation algorithm
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity/specificity of breast interpretation algorithm
Sensitivity and specificity of the information provided by the breast interpretation algorithm to be above 90% and 70%, respectively
Measured: 1 year
Secondary outcomes (2)
Time required for diagnosis
The time required to arrive at a diagnosis using IntelliScan should be less than using manual procedures
Measured: 1 year
User-friendliness of IntelliScan system
Obviousness score for categorisation of beast lesions (0 [not obvious] to 100 [extremely obvious]); ease-of-use score for IntelliScan system (0 [not easy to use] to 10 [extremely easy to use])
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Feb 2019
- Study startApr 2019 (estimated)
- Primary completionJan 2020 (estimated)
- Study completionJul 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- Single blind
- Who is masked
- Care provider
- Enrolment
- 1,526 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Jamil Kanfoud
- Sponsor type
- University, hospital or other
- Collaborators
- Brunel University London, First Option Software Ltd.
- Responsible party
- Sponsor-investigator, Jamil Kanfoud, Teesside University
- Investigators
- Steve Dennis, B.Sc., Study director, First Option Software
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03829423
- Sponsor's protocol ID
- 4901
- Acronym
- IntelliScan
- Status last verified
- Feb 2019
- First submitted
- 30 Jan 2019
- Last updated
- 6 Feb 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 Feb 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Comparative Single-centre Study to Evaluate an Enhanced Artificial Intelligence Breast MRI Interpretation System in Women Over 20 With Breast Lesions
- ClinicalTrials.gov ID
- NCT03829423
- Acronym / sponsor ID
- IntelliScan / 4901
- Conditions
- Breast Cancer
- Keywords
- artificial intelligence, magnetic resonance imaging, breast cancer
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 1,526 participants (estimated)
- Lead sponsor
- Jamil KanfoudUniversity, hospital or other
- Collaborators
- Brunel University London, First Option Software Ltd.
- Study start
- Apr 2019 (estimated)
- Primary completion
- Jan 2020 (estimated)
- Study completion
- Jul 2020 (estimated)
- First posted
- 4 Feb 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Interpretation of breast MR images is a very time-consuming process and places a great burden on breast radiologists. This project aims to develop a technical solution that addresses this healthcare challenge by developing a system that is able to automatically interpret breast MR images in order to aid the radiologist in their diagnosis.
Detailed description
Breast cancer is the most common type of cancer in women worldwide, with nearly 1.7 million new cases diagnosed in 2015. In the UK, one in five cases of breast cancer results in a fatality. The IntelliScan project aims to develop a technological solution that addresses a significant healthcare challenge. IntelliScan will develop a software system that will be able to interpret breast MR images automatically in order to identify potential breast cancers.
Regular MRI screening of the breast is offered to women from the age of 20, who are at higher risk of developing breast cancer. MR image sequences provide a large amount of information to the radiologist and the interpretation of images is a manual process, which is very time consuming. The high number of women eligible for MRI screening combined with the amount of data provided by MRI scans places a great burden on healthcare systems. Therefore, automatisation of this process would greatly relieve this burden and also has the potential to provide more accurate diagnoses.
In this first study, the system's user interface as well as the algorithm will be developed using existing MRI scans. Existing MRI scans with known breast anomalies will be used to develop the decision-making basis for the algorithm. The system will then be tested using existing MRI scans without information about possible anomalies and results will be compared to results from the software system currently in use. In addition, the user-friendliness of the system's user interface will also be evaluated.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- Single blind (care provider)
Who may qualify
- Ages
- 20 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Breast MRI scans
- MRI examinations undertaken at partner NHS Trust in the UK
- MRI examinations undertaken on the MRI system currently installed at partner NHS Trust site (since 2008)
Key exclusion criteria (3 listed)
- Incomplete breast MRI datasets
- Breast MRI without lesions
- Breast lesion on MRI not biopsied
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Breast MRI interpretationAnalysis and interpretation of breast MRI sequences by a specially developed breast MRI interpretation algorithm | Diagnostic test | – |
Primary outcome
Sensitivity/specificity of breast interpretation algorithm
Time frame: 1 year
Sensitivity and specificity of the information provided by the breast interpretation algorithm to be above 90% and 70%, respectively
2 secondary outcomes
Time required for diagnosis
Time frame: 1 year
User-friendliness of IntelliScan system
Time frame: 1 year
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Feb 2019.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Steve Dennis, B.Sc. study director
First Option Software
Questions about this trial
What is this clinical trial studying?
A study testing Breast MRI interpretation in people with Breast Cancer, run by Jamil Kanfoud.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 6 Feb 2019. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Jamil Kanfoud, M.Eng. (+44(0)01223940 ext. 310, jamil.kanfoud@brunel.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity/specificity of breast interpretation algorithm (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Feb 2019.