Artificial Intelligence in Large-scale Breast Cancer Screening (ScreenTrustCAD)

• ClinicalTrials.gov Identifier: NCT04778670
• Recruitment Status: Active, not recruiting
• First Posted: March 3, 2021
• Last Update Posted: March 14, 2023
• Sponsor: Karolinska University Hospital
• Collaborators: Capio Sankt Görans Hospital; Lunit Inc.; Karolinska Institutet
• Information provided by (Responsible Party): Fredrik Strand, Karolinska University Hospital

Tracking Information

• First Submitted Date: February 22, 2021
• First Posted Date: March 3, 2021
• Last Update Posted Date: March 14, 2023
• Actual Study Start Date: April 1, 2021
• Actual Primary Completion Date: June 9, 2022 (Final data collection date for primary outcome measure)

Current Primary Outcome Measures (submitted: February 26, 2021)

• Incident breast cancer [ Time Frame: At Screening ]
  Breast cancer diagnosis by pathologist
• Incident breast cancer [ Time Frame: Within 12 months after screening ]
  Breast cancer diagnosis by pathologist
• Incident breast cancer [ Time Frame: Within 23 months after screening ]
  Breast cancer diagnosis by pathologist

• Original Primary Outcome Measures: Same as current

Current Secondary Outcome Measures (submitted: February 26, 2021)

• Reader flagging [ Time Frame: At screening ]
  Radiologist or AICAD assessing the mammograms as suspicious or not suspicious for malignancy
• Consensus recall [ Time Frame: At screening ]
  A decision by the consensus discussion to recall the woman for further work-up
• Tissue sampling [ Time Frame: At screening ]
  Biopsy or fine needle aspiration performed
• Process failure [ Time Frame: At screening ]
  Failure of the AI CAD software to generate AI scores

• Original Secondary Outcome Measures: Same as current
• Current Other Pre-specified Outcome Measures: Not Provided
• Original Other Pre-specified Outcome Measures: Not Provided

Descriptive Information

• Brief Title: Artificial Intelligence in Large-scale Breast Cancer Screening
• Official Title: Artificial Intelligence in a Population-based Breast Cancer Screening - the Prospective Clinical Trial ScreenTrust CAD
• Brief Summary: This is a prospective clinical trial following a paired screen-positive design, with the aims to assess the performance of an artificial intelligence (AI) computer-aided detection (CAD) algorithm as an independent reader, in addition to two radiologists, of screening mammograms in a true screening population. Since all decisions by individual readers will be recorded, it is possible to determine what the outcome would have been had one or two of the readers not been allowed to assess images, and to determine what the outcome would have been had the recall decision been performed by consensus decision (actual) compared to single reader arbitration of discordant cases.
• Detailed Description: Not Provided
• Study Type: Interventional
• Study Phase: Not Applicable

Study Design

Allocation: Non-Randomized
Intervention Model: Single Group Assignment
Intervention Model Description:

This is a prospective clinical trial following a paired screen-positive design (Pepe, Alonzo; 2001), with the aims to assess the performance of an AI algorithm combined with radiologists(s) compared to standard-of-care being two radiologists assessing screening mammograms in a true screening population. Since all decisions by individual readers will be recorded, it is possible to determine what the outcome would have been had one or two of the readers not been allowed to assess images, and to determine what the outcome would have been had the recall decision been performed by consensus decision (actual) compared to single reader arbitration of discordant cases.

Masking: Triple (Participant, Care Provider, Investigator)
Masking Description:

Positive disease status is ascertained by pathology-verified breast cancer. Disease status is not known to any of the actors (except for the outcomes assessor by necessity). AI decision is not known by the care provider radiologists until they have made their decisions. In the subsequent consensus discussion where a decision is made to recall or not to recall a woman, the AI decision is known. After AI decision has been recorded and outcomes have been assessed, the investigators will have full information on outcomes and AI decisions.

Primary Purpose: Diagnostic

• Condition: Breast Neoplasm Female

Intervention

• Diagnostic Test: AI CAD
  The Lunit INSIGHT MMG will be used as the AI CAD in our study. Initially, version 1.6.1.1 will be installed. The software version will be continuously updated with subsequent software releases, after confirming in a historic calibration dataset that the performance is improved. The operating point will be set based on a historic calibration dataset to attain a joint sensitivity of breast cancer detection of AI and first reader which is 2% higher than for first and second reader.
  Other Name: Lunit INSIGHT MMG
• Diagnostic Test: Radiologist reading
  Standard of care, each radiologist will assess the mammography examination, making a binary flagging decision (flag the examination to continue to consensus discussion, or not)

Study Arms

• Active Comparator: Standard of Care
  Standard of Care means all examinations will receive a flagging decision by: first reader and second reader radiologist as usual. However, in this paired design all participants will belong to both arms.
  Intervention: Diagnostic Test: Radiologist reading
• Experimental: AI CAD combination
  AI CAD combination in the primary end-point means the combination of the flagging decision of the first reader and AI CAD; in the secondary end-points it means any combination of AI alone, or AI in combination with first, second and both readers.
  Interventions:

  • Diagnostic Test: AI CAD
  • Diagnostic Test: Radiologist reading

• Publications *: Not Provided

Recruitment Information

• Recruitment Status: Active, not recruiting
• Actual Enrollment (submitted: August 18, 2022): 55579
• Original Estimated Enrollment (submitted: February 26, 2021): 55000
• Estimated Study Completion Date: December 2024
• Actual Primary Completion Date: June 9, 2022 (Final data collection date for primary outcome measure)

Eligibility Criteria

Inclusion Criteria:

• Participants in regular population-based breast cancer screening at Capio St Göran Hospital

Exclusion Criteria:

• Incomplete exam (complete exam: mediolateral oblique and craniocaudal images of Left and Right breast)
• Breast implant
• Complete mastectomy (excluded from screening positive group)
• Participant in surveillance program for prior breast cancer

Sex/Gender

• Sexes Eligible for Study: Female

• Ages: 40 Years to 74 Years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Contacts: Contact information is only displayed when the study is recruiting subjects
• Listed Location Countries: Sweden

Administrative Information

• NCT Number: NCT04778670
• Other Study ID Numbers: STGKS001; EPM 2020-00487 ( Other Identifier: Ethical Review Authority (Sweden) ); K 2020-0807 ( Other Identifier: Karolinska University Hospital )
• Has Data Monitoring Committee: No

U.S. FDA-regulated Product

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

IPD Sharing Statement

• Plan to Share IPD: Yes
• Plan Description: To the extent allowed by source institution, legal agreements, and applicable laws and regulations
• Supporting Materials: Study Protocol
• Supporting Materials: Statistical Analysis Plan (SAP)
• Time Frame: At study start
• Access Criteria: Anyone can access study protocol and SAP.

• Current Responsible Party: Fredrik Strand, Karolinska University Hospital
• Original Responsible Party: Same as current
• Current Study Sponsor: Karolinska University Hospital
• Original Study Sponsor: Same as current

Collaborators

• Capio Sankt Görans Hospital
• Lunit Inc.
• Karolinska Institutet

Investigators

• Principal Investigator: Fredrik Strand, MD PhD; Karolinska University Hospital

• PRS Account: Karolinska University Hospital
• Verification Date: March 2023