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Spots Global Cancer Trial Database for Mammography Screening With Artificial Intelligence (MASAI)

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Trial Identification

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

Study ID: NCT04838756

Conditions

Breast Cancer

Study Description

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

Minimum Age: 40 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: FEMALE

Healthy Volunteers: Yes

Locations

Mammography Unit, Unilabs/Skane University Hospital, Malmö, Skane, Sweden

Contact Details

Name: Kristina Lång, MD PhD

Affiliation: Region Skåne

Role: PRINCIPAL_INVESTIGATOR

Useful links and downloads for this trial

Clinicaltrials.gov

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