Mammography Screening With Artificial Intelligence (MASAI) (MASAI)

• ClinicalTrials.gov Identifier: NCT04838756
• Recruitment Status: Active, not recruiting
• First Posted: April 9, 2021
• Last Update Posted: March 12, 2024
• Sponsor: Region Skane
• Collaborators: Unilabs; Cancer Registry of Norway
• Information provided by (Responsible Party): Region Skane

Tracking Information

• First Submitted Date: April 6, 2021
• First Posted Date: April 9, 2021
• Last Update Posted Date: March 12, 2024
• Actual Study Start Date: April 12, 2021
• Estimated Primary Completion Date: November 12, 2024 (Final data collection date for primary outcome measure)

Current Primary Outcome Measures (submitted: April 8, 2021)

Interval-cancer rate [ Time Frame: 43 months ]

Women with interval cancer per 1000 screens

• Original Primary Outcome Measures: Same as current

Current Secondary Outcome Measures (submitted: April 8, 2021)

• Cancer-detection rate [ Time Frame: 15 months ]
  Women with screen-detected cancer per 1000 screens
• Recall rate [ Time Frame: 15 months ]
  Number of recalls per 1000 screens
• False-positive rate [ Time Frame: 15 months ]
  Women with false positive per 1000 screens
• Positive Predictive Value-1 [ Time Frame: 15 months ]
  Women with cancer for all recalls
• Sensitivity and specificity [ Time Frame: 43 months ]
  True and false-positive rate
• Cancer detection per cancer type [ Time Frame: 19 months ]
  Screen detection of cancer in relation to cancer type, size and stage
• Tumour biology of interval cancers [ Time Frame: 43 months ]
  Characterization of interval cancers per type, size and stage
• Screen-reading workload [ Time Frame: 19 months ]
  Number of screen-readings and number of consensus meetings
• Incremental cost-effectiveness ratio [ Time Frame: 43 months ]
  The incremental cost-effectiveness ratio for AI-integrated mammography screening versus standard of care

• 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: 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
• 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.

• Study Type: Interventional
• Study Phase: Not Applicable

Study Design

Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single (Participant)
Masking Description:

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.

Primary Purpose: Screening

• Condition: Breast Cancer

Intervention

• Other: AI screening modality
  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.
• Other: Conventional screening modality
  Screen exams will be read by two radiologists without the support of AI.

Study Arms

• Experimental: Intervention arm
  AI-integrated mammography screening
  Intervention: Other: AI screening modality
• Experimental: Control arm
  Conventional mammography screening (standard of care)
  Intervention: Other: Conventional screening modality

• Publications *: Not Provided

Recruitment Information

• Recruitment Status: Active, not recruiting
• Actual Enrollment (submitted: April 8, 2021): 100000
• Original Estimated Enrollment: Same as current
• Estimated Study Completion Date: April 12, 2025
• Estimated Primary Completion Date: November 12, 2024 (Final data collection date for primary outcome measure)

Eligibility Criteria

Inclusion Criteria:

Women eligible for population-based mammography screening.

Exclusion Criteria:

None.

Sex/Gender

• Sexes Eligible for Study: Female

• Ages: 40 Years to 74 Years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Contacts: Contact information is only displayed when the study is recruiting subjects
• Listed Location Countries: Sweden

Administrative Information

• NCT Number: NCT04838756
• Other Study ID Numbers: 2020-04936
• 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: No
• Plan Description: IPD could be considered to be shared in future collaborations.

• Current Responsible Party: Region Skane
• Original Responsible Party: Same as current
• Current Study Sponsor: Region Skane
• Original Study Sponsor: Same as current

Collaborators

• Unilabs
• Cancer Registry of Norway

Investigators

• Principal Investigator: Kristina Lång, MD PhD; Region Skåne

• PRS Account: Region Skane
• Verification Date: March 2024