The Use of AI to Safely Reduce the Workload in Breast Cancer Screening With Mammography in Region Östergötland

NCT06187350 | Completed FDA Device

• 1 other identifier: AIM-RÖ
• Study Type: observational
• Target: 60,000
• Locations: 1 country
• Sites: 1

Brief Summary

The overall aim of the project is to investigate how artificial intelligence (AI) can be used to streamline and at the same time increase diagnostic safety in breast cancer screening with mammography. AI has been shown in a number of studies to have great potential for both increasing diagnostic certainty (e.g. reduced occurrence of interval cancers) and at the same time reducing the workload for doctors. However, much research remains to clinically validate these new tools and to increase the understanding of how they affect the work of doctors. The specific goal of the project is to investigate whether the implementation of AI in breast cancer screening in Östergötland, Sweden, can increase the sensitivity (the mammography examination's ability to find breast cancer) and the specificity (that is, the right case is selected for further investigation: a minimum of healthy women are recalled but so many breast cancer cases that are possible are selected for further investigation) and at the same time make screening more efficient through reduced workload. AI will be implemented in the clinical routine and performance metrics such as cancer detection rate etc will be closely monitored. The study do not assign specific interventions to the study participants.

Conditions

Artificial Intelligence; Breast Diseases; Neoplasms; Breast Neoplasms

Outcome Measures

Primary Outcomes (2)

• Cancer Detection rate

  Proportion of women diagnosed with breast cancer among those recalled after consensus

  4 Years

• Positive predictive value of Transpara® scores

  Proportion of breast cancers diagnosed among women with a given AI score

  4 Years

Study Arms (1)

Screened women in Region Östergötland, Sweden

All screened women in Region Östergötland, Sweden.

Device: AI cancer detection system

Interventions

AI cancer detection system DEVICE

The AI system Transpara (Screenpoint Medical, The Netherlands) will be implemented for triaging two-image mammography examinations based on the probability of malignancy. Transpara assigns a score from 1 to 10 to each examination, indicating the risk of malignancy. A score between 1 and 7 indicates a low risk of cancer, 8-9 indicates an intermediate and 10 an elevated risk of cancer. Examinations with an AI score between 1 and 7 will be reviewed by only one radiologist, while examinations with an AI score \> 7 will be double-reviewed as normal.

Also known as: Screenpoint Transpara

Screened women in Region Östergötland, Sweden

Eligibility Criteria

• Age: 40 Years - 74 Years
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Women eligible for population-based mammography screening

You may qualify if:

• Women participating in the regular Breast Cancer Screening Program in Region Östergötland

You may not qualify if:

• Women with breast implants or other foreign implants in the mammogram Women with symptoms or signs of suspected breast cancer

Sponsors & Collaborators

• Ostergotland County Council, Sweden: lead

Study Sites (1)

Region Östergötland

Linköping, Östergötland County, Sweden

Location

MeSH Terms

Conditions

Breast Diseases; Neoplasms; Breast Neoplasms

Condition Hierarchy (Ancestors)

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

Study Officials

• Håkan Gustafsson, Ph.D.

  Region Östergötland

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 4 Years
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: July 10, 2023
• First Posted: January 2, 2024
• Study Start: August 1, 2023
• Primary Completion: March 20, 2025
• Study Completion: March 20, 2025
• Last Updated: June 6, 2025

Record last verified: 2025-06

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)