Clinical Trials Logo

Clinical Trial 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.


Clinical Trial Description

The overall aim of the project is to study whether the use of artificial intelligence can improve breast cancer screening with mammography. 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. The specific objective is to investigate whether the use of AI leads to increased diagnostic safety in mammography in Östergötland (measured as a reduced incidence of interval cancer) and at the same time leads to a reduced workload for the breast radiologists. Furthermore, the intention is to investigate how the use of AI affects the breast radiologists´ work in terms of reading time per examination and whether the radiologists' specificity and sensitivity are affected when they have access to the decision support based on AI during the review compared to if they do not have this support. The hypotheses are that: 1. The use of AI in breast cancer screening in Östergötland Sweden improves the diagnostic quality. As a result, more breast cancer cases are detected early and the incidence of interval cancer decreases. 2. The reduced workload for the radiologists in Östergötland that could be demonstrated through the data collected in Östergötland 2021-2022 [NCT05048095 - Artificial Intelligence in Breast Cancer Screening in Region Östergötland Linkoping (AI-ROL)] can also be demonstrated in a large-scale prospective study. 3. Through the use of an AI-based decision support, not only can double review be eliminated for those cases where the AI assesses the cancer risk as low, but also each examination can be reviewed more quickly while maintaining or improving diagnostic certainty. 4. It is the least experienced radiologists who are most helped by the decision support, both for increased diagnostic certainty and increased efficiency. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT06187350
Study type Observational [Patient Registry]
Source Ostergotland County Council, Sweden
Contact Håkan Gustafsson, Ph.D.
Phone +46101043023
Email hakan.l.gustafsson@liu.se
Status Recruiting
Phase
Start date August 1, 2023
Completion date December 31, 2027

See also
  Status Clinical Trial Phase
Completed NCT03826043 - THrombo-Embolic Event in Onco-hematology N/A
Terminated NCT03166631 - A Trial to Find the Safe Dose for BI 891065 Alone and in Combination With BI 754091 in Patients With Incurable Tumours or Tumours That Have Spread Phase 1
Completed NCT01938846 - BI 860585 Dose Escalation Single Agent and in Combination With Exemestane or With Paclitaxel in Patients With Various Advanced and/or Metastatic Solid Tumors Phase 1
Recruiting NCT06058312 - Individual Food Preferences for the Mediterranean Diet in Cancer Patients N/A
Completed NCT03308942 - Effects of Single Agent Niraparib and Niraparib Plus Programmed Cell Death-1 (PD-1) Inhibitors in Non-Small Cell Lung Cancer Participants Phase 2
Recruiting NCT06018311 - Exercising Together for Hispanic Prostate Cancer Survivor-Caregiver Dyads N/A
Withdrawn NCT05431439 - Omics of Cancer: OncoGenomics
Completed NCT01343043 - A Pilot Study of Genetically Engineered NY-ESO-1 Specific NY-ESO-1ᶜ²⁵⁹T in HLA-A2+ Patients With Synovial Sarcoma Phase 1
Completed NCT01938638 - Open Label Phase I Dose Escalation Study With BAY1143572 in Patients With Advanced Cancer Phase 1
Recruiting NCT05514444 - Study of MK-4464 as Monotherapy and in Combination With Pembrolizumab in Participants With Advanced/Metastatic Solid Tumors (MK-4464-001) Phase 1
Recruiting NCT02292641 - Beyond TME Origins N/A
Terminated NCT00954512 - Study of Robatumumab (SCH 717454, MK-7454) in Combination With Different Treatment Regimens in Participants With Advanced Solid Tumors (P04722, MK-7454-004) Phase 1/Phase 2
Recruiting NCT04958239 - A Study to Test Different Doses of BI 765179 Alone and in Combination With Ezabenlimab in Patients With Advanced Cancer (Solid Tumors) Phase 1
Recruiting NCT04627376 - Multimodal Program for Cancer Related Cachexia Prevention N/A
Completed NCT01222728 - Using Positron Emission Tomography to Predict Intracranial Tumor Growth in Neurofibromatosis Type II Patients
Recruiting NCT06004440 - Real World Registry for Use of the Ion Endoluminal System
Active, not recruiting NCT05636696 - COMPANION: A Couple Intervention Targeting Cancer-related Fatigue N/A
Not yet recruiting NCT06035549 - Resilience in East Asian Immigrants for Advance Care Planning Discussions N/A
Recruiting NCT06004466 - Noninvasive Internal Jugular Venous Oximetry
Completed NCT02909348 - Immunophenotyping of Melanoma Patients on Treatment With Pembrolizumab