Clinical trial NCT04838756: Mammography Screening With Artificial Intelligence (MASAI)
Official title: A Randomized, Single-blinded, Controlled Trial on the Efficacy of Mammography Screening With Artificial Intelligence - the MASAI Study
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Breast Cancer
Keywords: Mammography Screening
Artificial Intelligence
Lead sponsor: Region Skane
Sponsor class: OTHER
Collaborators: name: Unilabs
name: Norwegian Institute of Public Health
First posted: 2021-04-09
Enrollment: 100000
Sex: FEMALE
Minimum age (years): 40
Maximum age (years): 74
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: SCREENING

Brief summary: The purpose of this randomized controlled trial is to assess whether AI can improve the efficacy of mammography screening, by adapting single and double reading based on AI derived cancer-risk scores and to use AI as a decision support in the screen reading, compared with conventional mammography screening (double reading without AI).

Detailed description: European guidelines recommend that mammography exams in breast cancer screening are read by two breast radiologists to ensure a high sensitivity. Double reading is, however, resource demanding and still results in missed cancers. Computer-aided detection based on AI has been shown to have similar accuracy as an average breast radiologist. AI can be used as decision support by highlighting suspicious findings in the image as well as a means to triage screen exams according to risk of malignancy.

Eligible women will be randomized (1:1) to the intervention (AI-integrated mammography screening) or control arm (conventional mammography screening). In the intervention arm, exams will be analysed with AI and triaged into two groups based on risk of malignancy. Low risk exams will be single read and high risk exams will be double read. The high risk group will contain appx. 10% of the screening population. Within the high-risk group, exams with the highest 1% risk will by default be recalled by the readers with the exception of obvious false positives. AI risk scores and Computer-Aided Detection (CAD)-marks of suspicious calcifications and masses are provided to the reader(s). In the control arm, screen exams are double read without AI (standard of care). Considering the interplay of number of interval cancers and workload, the study will be considered successful if the interval-cancer rate in the intervention arm is not more than 20% larger than in the control arm. If the interval-cancer rate is statistically and clinically significantly lower in the intervention arm than in the control arm, AI-integrated mammography screening will be considered superior to conventional mammography screening.

Eligibility criteria: Inclusion Criteria:

Women eligible for population-based mammography screening.

Exclusion Criteria:

None.

Primary outcomes:
measure: Interval-cancer rate
timeFrame: 43 months
Secondary outcomes:
measure: Cancer-detection rate
timeFrame: 15 months
measure: Recall rate
timeFrame: 15 months
measure: False-positive rate
timeFrame: 15 months
measure: Positive Predictive Value-1
timeFrame: 15 months
measure: Sensitivity and specificity
timeFrame: 43 months
measure: Cancer detection per cancer type
timeFrame: 19 months
measure: Tumour biology of interval cancers
timeFrame: 43 months
measure: Screen-reading workload
timeFrame: 19 months
measure: Incremental cost-effectiveness ratio
timeFrame: 43 months
Other outcomes:
Locations:
city: Malmö
country: Sweden
facility: Mammography Unit, Unilabs/Skane University Hospital
state: Skane
Study officials:
affiliation: Region Skåne
name: Kristina Lång, MD PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Lang K, Josefsson V, Larsson AM, Larsson S, Hogberg C, Sartor H, Hofvind S, Andersson I, Rosso A. Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study. Lancet Oncol. 2023 Aug;24(8):936-944. doi: 10.1016/S1470-2045(23)00298-X.
citation: Hernstrom V, Josefsson V, Sartor H, Schmidt D, Larsson AM, Hofvind S, Andersson I, Rosso A, Hagberg O, Lang K. Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study. Lancet Digit Health. 2025 Mar;7(3):e175-e183. doi: 10.1016/S2589-7500(24)00267-X. Epub 2025 Feb 3.