Mammography Screening With Artificial Intelligence (MASAI)

NCT04838756 | Completed

• 1 other identifier: 2020-04936
• Study Type: interventional
• Target: 100,000
• Locations: 1 country
• Sites: 1

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).

Conditions

Breast Cancer

Keywords

Mammography Screening; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• Interval-cancer rate

  Women with interval cancer per 1000 screens

  43 months

Secondary Outcomes (9)

• Cancer-detection rate

  15 months

• Recall rate

  15 months

• False-positive rate

  15 months

• Positive Predictive Value-1

  15 months

• Sensitivity and specificity

  43 months

Study Arms (2)

Intervention arm

EXPERIMENTAL

AI-integrated mammography screening

Other: AI screening modality

Control arm

EXPERIMENTAL

Conventional mammography screening (standard of care)

Other: Conventional screening modality

Interventions

AI screening modality OTHER

Screen exam will be analysed with an AI system (Transpara, ScreenPoint, Nijmegen, The Netherlands) that assigns exams with a cancer-risk score from 1 to 10, as well as presenting CAD-marks at suspicious findings. Exams with risk score 1-9 will be single read and exam with score 10 will be double read. Risk scores and CAD-marks are provided to the reader(s). The reader(s) will decide whether to recall the woman for work-up or not (as per standard of care). In addition, exams with the highest 1% risk will by default be recalled with the exception of obvious false positives.

Intervention arm

Conventional screening modality OTHER

Screen exams will be read by two radiologists without the support of AI.

Control arm

Eligibility Criteria

• Age: 40 Years - 74 Years
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Women eligible for population-based mammography screening.

You may not qualify if:

• None.

Sponsors & Collaborators

• Region Skane: lead
• Unilabs: collaborator
• Norwegian Institute of Public Health: collaborator

Study Sites (1)

Mammography Unit, Unilabs/Skane University Hospital

Malmo, Skåne County, 20550, Sweden

Location

Related Publications (3)

• 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.

  PMID: 37541274 RESULT

• 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.

  PMID: 39904652 RESULT

• Gommers J, Hernstrom V, Josefsson V, Sartor H, Schmidt D, Hjelmgren A, Larsson AM, Hofvind S, Andersson I, Rosso A, Hagberg O, Lang K. Interval cancer, sensitivity, and specificity comparing AI-supported mammography screening with standard double reading without AI in the MASAI study: a randomised, controlled, non-inferiority, single-blinded, population-based, screening-accuracy trial. Lancet. 2026 Jan 31;407(10527):505-514. doi: 10.1016/S0140-6736(25)02464-X.

  PMID: 41620232 DERIVED

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Study Officials

• Kristina Lång, MD PhD

  Region Skåne

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: Participants have the possibility to opt-out. If they do not opt-out, neither the participant nor the nurse performing the screen exam will know to what study arm the participant was allocated. The radiologist reading the screen exam will however not be blinded to allocation information.
• Purpose: SCREENING
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 6, 2021
• First Posted: April 9, 2021
• Study Start: April 12, 2021
• Primary Completion: December 7, 2024
• Study Completion: August 12, 2025
• Last Updated: April 2, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)