Ignite Creation Date:
2024-10-26 @ 3:39 PM
Last Modification Date:
2024-10-26 @ 3:39 PM
Study NCT ID:
NCT06578988
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
None
First Post:
2023-12-19
Brief Title:
Use of Artificial Intelligence in the Symptomatic BReAst Clinic SEtting
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Use of Artificial Intelligence in the Symptomatic BReAst Clinic SEtting - A Retrospective Study AI-BRACE
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2023-12
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Artificial Intelligence AI systems for the classification of mammography images have been developed and are beginning to be trialled and deployed in a breast cancer screening setting with encouraging results
It is reasonable to think that these systems could be useful in the context of symptomatic breast clinic However these systems developed in the screening setting have unknown performance in the context of symptomatic breast clinic
It is therefore important to test the performance of these systems in this alternative context
This study will use retrospective data from where it is possible to determine ground truth outcomes with greater confidence accessing relatively large volumes of data with less patient burden when compared to prospective studies This important cohort of patients has been less investigated to date mainly because symptomatic data is typically more difficult to curate than screening data where key data is methodically prospectively collected
The proposed work will be carried out in collaboration with a selected AI vendor and local clinical teams to define optimal use case scenarios for the symptomatic breast clinic
It is reasonable to think that these systems could be useful in the context of symptomatic breast clinic However these systems developed in the screening setting have unknown performance in the context of symptomatic breast clinic
It is therefore important to test the performance of these systems in this alternative context
This study will use retrospective data from where it is possible to determine ground truth outcomes with greater confidence accessing relatively large volumes of data with less patient burden when compared to prospective studies This important cohort of patients has been less investigated to date mainly because symptomatic data is typically more difficult to curate than screening data where key data is methodically prospectively collected
The proposed work will be carried out in collaboration with a selected AI vendor and local clinical teams to define optimal use case scenarios for the symptomatic breast clinic
Detailed Description:
Patients with breast symptoms are referred from primary care to symptomatic breast clinics often under the two-week-wait cancer pathway Clinicians assess the patients breast symptoms by looking at the patients personal and family history of cancer conducting a physical examination and referring the patient for imaging as required
Ultrasound and or mammography are typically performed and reported by the imaging team at the same visit with biopsy performed when indicated This service is an important part of cancer care provision with approximately half of the breast cancers diagnosed presenting via the symptomatic service rather than identified at screening
It is important to note that cancers diagnosed symptomatically tend to be larger and more aggressive with worse outcome than those diagnosed via screening The volume of referrals to the National Health Service NHS symptomatic service has risen over the last decade placing increased pressure on service delivery in breast imaging
Artificial Intelligence AI systems for the classification of mammography images have been developed and are beginning to be trialled and deployed in a breast cancer screening setting with encouraging results It is reasonable to think that these systems could be useful in the context of symptomatic breast clinic However these systems developed in the screening setting have unknown performance in the context of symptomatic breast clinic It is therefore important to test the performance of these systems in this alternative context
Ultrasound and or mammography are typically performed and reported by the imaging team at the same visit with biopsy performed when indicated This service is an important part of cancer care provision with approximately half of the breast cancers diagnosed presenting via the symptomatic service rather than identified at screening
It is important to note that cancers diagnosed symptomatically tend to be larger and more aggressive with worse outcome than those diagnosed via screening The volume of referrals to the National Health Service NHS symptomatic service has risen over the last decade placing increased pressure on service delivery in breast imaging
Artificial Intelligence AI systems for the classification of mammography images have been developed and are beginning to be trialled and deployed in a breast cancer screening setting with encouraging results It is reasonable to think that these systems could be useful in the context of symptomatic breast clinic However these systems developed in the screening setting have unknown performance in the context of symptomatic breast clinic It is therefore important to test the performance of these systems in this alternative context
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None