Clinical trial NCT05024591: Artificial Intelligence for breaST canceR scrEening in mAMmography (AI-STREAM)
Official title: Artificial Intelligence for breaST canceR scrEening in mAMmography (AI-STREAM): A Prospective, Multicenter Cohort Study
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Breast Cancer
Keywords: breast cancer
screening
AI-based CADe/x
Lead sponsor: Kyung Hee University Hospital at Gangdong
Sponsor class: OTHER
Collaborators: name: Korea Health Industry Development Institute
First posted: 2021-08-27
Enrollment: 25008
Sex: FEMALE
Minimum age (years): 40
Maximum age (years): 100
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Participants of breast cancer screening in Korean women aged 40 years or older with average risk of breast cancer.

Brief summary: This prospective study aims to generate real-world evidence on the overall benefits and disadvantages of using Lunit INSIGHT MMG AI based CADe/x for breast cancer detection in a population-based breast cancer screening program in Korea.

Detailed description: 1. Several challenges have been identified in breast cancer screening: 1) Some breast cancer cases not identified through screening; 2) Excessive recalls for further testing; 3) Low sensitivity in dense breasts; 4) Inter-reader variability. AI-based CADe/x has been shown to improve radiologist performance and provides results equivalent or superior to those from radiologists alone.
2. This multicenter, prospective study involves women who visit sites for breast cancer screening in Korea. Women eligible for national cancer screening in the relevant year who read the study participant recruitment brochure and read and sign the Participant Information Sheet and Informed Consent Form will be recruited into this study. Approximately 32,714 participants will be enrolled from February 2021 through December 2022 at five study sites in Korea.
3. In Korea, a single radiologist performs mammogram readings. If recall is required (per usual care), further diagnostic work-up will be conducted to confirm cancer detected at screening. The national cancer registry databases will be reviewed in 2026 and 2027. Available findings will be recorded for all participants regardless of their screening status to identify study participants with breast cancer diagnosis within one year and within two years from screening.
4. In primary outcome measurement, as part of the standard screening procedure, mammograms will be read and recorded by a breast radiologist without AI-CADe/x, and then with AI-based CADe/x. \[Set1\]
5. In secondary outcome measurement, mammograms from the same participants as Set 1 will be read and recorded by a general radiologist without AI-based CADe/x, and then with AI-based CADe/x. \[Set 2\] In additional secondary outcome measurement, arbitration reading will be conducted by another breast radiologist without AI-based CADe/x for cases in which the reading results of the two radiologists without AI-based CADe/x in Set 1 and Set 2 are inconsistent. \[Set 3\]
6. After completing the standard screening procedure in Set 1, several situational comparison groups \[Set2 and Set3\] for comparison the diagnostic accuracy will be performed independently and retrospectively The results from Set 2 and Set 3 will not impact the clinical decision(s) associated with the care of the study participants.

Eligibility criteria: Inclusion Criteria:

* Participants must meet all of the following inclusion criteria in order to be enrolled in the study:
* Be eligible for national cancer screening in the relevant year and visit the site for breast cancer screening
* Provide consent for study participation using the Informed Consent Form and complete a Participant information Sheet

Exclusion Criteria:

* Participants who meet any of the following criteria will be excluded from the study:
* Has a history of or current breast cancer
* Is currently pregnant or plans to become pregnant in the next 12 months
* Has a history of breast surgery (mammoplasty or insertion of a foreign substance, such as paraffin or silicon)
* Has mammography for diagnostic purposes

Primary outcomes:
measure: • Diagnostic accuracy with difference between breast radiologists with and without AI-based CADe/x
timeFrame: 12months after screening, 24months after screening
Secondary outcomes:
measure: • Diagnostic accuracy and difference of the following comparison groups with or without AI
timeFrame: 12months after screening, 24 months after screening
Other outcomes:
Locations:
city: Seongnam-si
country: Korea, Republic of
facility: Department of Radiology, CHA bundang Medical Center
city: Seoul
country: Korea, Republic of
facility: Department of Radiology, Soonchunhyang University Hospital
city: Seoul
country: Korea, Republic of
facility: Department of Radiology, Konkuk University Medical Center
city: Seoul
country: Korea, Republic of
facility: Department of Radiology, Kyung Hee University Hospital at Gangdong
city: Seoul
country: Korea, Republic of
facility: Department of Radiology, Nowon Eulgi Medical center
Study officials:
affiliation: Soonchunhyang University Hospital, Seoul
name: Yun-Woo Chang, MD, PhD
role: STUDY_DIRECTOR
References:
citation: Kim HE, Kim HH, Han BK, Kim KH, Han K, Nam H, Lee EH, Kim EK. Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study. Lancet Digit Health. 2020 Mar;2(3):e138-e148. doi: 10.1016/S2589-7500(20)30003-0. Epub 2020 Feb 6.
citation: Salim M, Wahlin E, Dembrower K, Azavedo E, Foukakis T, Liu Y, Smith K, Eklund M, Strand F. External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms. JAMA Oncol. 2020 Oct 1;6(10):1581-1588. doi: 10.1001/jamaoncol.2020.3321.
citation: Chang YW, An JK, Choi N, Ko KH, Kim KH, Han K, Ryu JK. Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM): A Prospective Multicenter Study Design in Korea Using AI-Based CADe/x. J Breast Cancer. 2022 Feb;25(1):57-68. doi: 10.4048/jbc.2022.25.e4. Epub 2022 Jan 6.